GEFS-reforecast-dt.ipynb

GEFS-reforecast-dt.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3819dbc7-1990-4310-a939-f452635a985f",
   "metadata": {},
   "source": [
    "# Kerchunk the GEFS reforecast \n",
    "Data contained in these grib2 files described here: https://www.nco.ncep.noaa.gov/pmb/products/gens/\n",
    "\n",
    "Approach:\n",
    "* create a list of grib files to process\n",
    "* use scan_grib to create JSON references for each message in each grib file. \n",
    "* combine JSONs along the `step` dimension (the forecast hour, or \"tau\" dimension)\n",
    "* combine JSONs along the `ensemble` or \"number\" dimension\n",
    "* combine along the `time` dimension (the daily forecast date)\n",
    "* combine JSONs for all variables (messages) with similar vertical coordinates into groups\n",
    "* load variable groups into xarray DataTree\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2d430bab-d0e4-467d-aa87-e67ce18029db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exception reporting mode: Minimal\n"
     ]
    }
   ],
   "source": [
    "%xmode minimal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "dec8b9af-3777-4118-876d-27264a286838",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import fsspec\n",
    "from datetime import datetime, timedelta\n",
    "import xarray as xr\n",
    "\n",
    "import ujson\n",
    "import kerchunk\n",
    "from kerchunk.grib2 import scan_grib\n",
    "from kerchunk.combine import MultiZarrToZarr\n",
    "from pathlib import Path\n",
    "\n",
    "import dask\n",
    "from dask.distributed import LocalCluster, Client, performance_report\n",
    "import dask.bag as db\n",
    "\n",
    "from datatree import DataTree\n",
    "\n",
    "import panel as pn\n",
    "import pandas as pd\n",
    "import hvplot.xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7df67e0d-4b92-4c5e-ba34-0b36ce4852e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2023.3.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c717c209-b08f-4161-902e-0c52e6e4d461",
   "metadata": {},
   "source": [
    "Create a set of fsspec file systems to read the latest GEFS forecast and write the reference files locally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e2776e85-df07-4282-94d5-17af6ca02269",
   "metadata": {},
   "outputs": [],
   "source": [
    "fs_local = fsspec.filesystem('', skip_instance_cache = True, use_listings_cache=False)\n",
    "fs_s3 = fsspec.filesystem('s3', anon = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76339156-abcf-4d9f-b798-9ca5676bd80a",
   "metadata": {},
   "source": [
    "**s3://noaa-gefs-pds/gefs.{date}/{cycle}/atmos/pgrb2ap5/gep{ensemble_member}.t{cycle}.pgrb2a.0p50.f{forecast_hour}**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b9923e97-cde8-48dc-9b33-6a5d9699d7d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['noaa-gefs-retrospective/Description_of_reforecast_data.pdf',\n",
       " 'noaa-gefs-retrospective/GEFSv12',\n",
       " 'noaa-gefs-retrospective/index.html',\n",
       " 'noaa-gefs-retrospective/landsfc.pgrb2.0p25',\n",
       " 'noaa-gefs-retrospective/landsfc.pgrb2.0p50']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bucket = 's3://noaa-gefs-retrospective'\n",
    "flist = fs_s3.ls(bucket)\n",
    "flist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4df8ce54-0419-421b-968b-78af1a66394d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "365\n",
      "noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019010100\n",
      "noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019123100\n"
     ]
    }
   ],
   "source": [
    "dates = fs_s3.glob(f'{bucket}/GEFSv12/reforecast/2019/??????????')\n",
    "print(len(dates))\n",
    "print(dates[0])\n",
    "print(dates[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a421985e-1406-40d4-847d-4630bbeb3461",
   "metadata": {},
   "source": [
    "## Select a range of dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "49b11937-4805-42f1-ab0a-347421cf3d83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2019122900', '2019123000', '2019123100']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = [Path(date).name for date in dates[-3:]]\n",
    "dates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9dcbffa-f3be-41a4-9948-6405f47b8094",
   "metadata": {},
   "source": [
    "## Determine number of ensemble members\n",
    "by searching all gribs for a specific date and variable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "24855007-42e5-484b-a081-7f8620642e0a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019122900/c00/Days:1-10/weasd_sfc_2019122900_c00.grib2',\n",
       " 'noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019122900/p01/Days:1-10/weasd_sfc_2019122900_p01.grib2',\n",
       " 'noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019122900/p02/Days:1-10/weasd_sfc_2019122900_p02.grib2',\n",
       " 'noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019122900/p03/Days:1-10/weasd_sfc_2019122900_p03.grib2',\n",
       " 'noaa-gefs-retrospective/GEFSv12/reforecast/2019/2019122900/p04/Days:1-10/weasd_sfc_2019122900_p04.grib2']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date = dates[0]\n",
    "year = date[:4]\n",
    "variable = 'weasd_sfc'\n",
    "f = fs_s3.glob(f's3://noaa-gefs-retrospective/GEFSv12/reforecast/{year}/{date}/???/Days:1-10/{variable}_{date}_???.grib2')\n",
    "np_ensembles = len(f)\n",
    "print(np_ensembles)\n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a1a9d5e3-e46d-40a3-ad60-0c3daa41bfc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "ensembles = ['c00', 'p01', 'p02', 'p03', 'p04']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fee100a-f450-4cd3-b6d3-066d058f7ac5",
   "metadata": {},
   "source": [
    "## Determine number of variables for each forecast\n",
    "by searching for a ensemble member and date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "152a08b8-f625-4976-b5eb-11dde3eae027",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flist = sorted(fs_s3.glob(f's3://noaa-gefs-retrospective/GEFSv12/reforecast/{year}/{date}/c00/Days:1-10/*.grib2'))\n",
    "flist = [f's3://{f}' for f in flist]\n",
    "len(flist)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cdc2a42-6183-480c-8b15-748140672dbf",
   "metadata": {},
   "source": [
    "Make a list of variable names (extracting them from the grib file names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3e4a3aa1-00b5-47df-9373-00c84f6306dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "varnames = []\n",
    "for f in flist:\n",
    "    file = Path(f).parts[8]\n",
    "    p = file.split('_')\n",
    "    pp = p[:-2]\n",
    "    var = '_'.join(pp)\n",
    "    varnames.append(var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "704783e9-797b-4c7d-8b2f-ef24ebc193dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['acpcp_sfc',\n",
       " 'apcp_sfc',\n",
       " 'cape_sfc',\n",
       " 'cin_sfc',\n",
       " 'dlwrf_sfc',\n",
       " 'dswrf_sfc',\n",
       " 'gflux_sfc',\n",
       " 'gust_sfc',\n",
       " 'hgt_ceiling',\n",
       " 'hgt_hybr',\n",
       " 'hgt_pres',\n",
       " 'hgt_pres_abv700mb',\n",
       " 'hgt_sfc',\n",
       " 'hlcy_hgt',\n",
       " 'lhtfl_sfc',\n",
       " 'ncpcp_sfc',\n",
       " 'pbl_hgt',\n",
       " 'pres_hybr',\n",
       " 'pres_msl',\n",
       " 'pres_pvor',\n",
       " 'pres_sfc',\n",
       " 'pvort_isen',\n",
       " 'pwat_eatm',\n",
       " 'rh_hybr',\n",
       " 'sfcr_sfc',\n",
       " 'shtfl_sfc',\n",
       " 'soilw_bgrnd',\n",
       " 'spfh_2m',\n",
       " 'spfh_pres',\n",
       " 'spfh_pres_abv700mb',\n",
       " 'tcdc_eatm',\n",
       " 'tmax_2m',\n",
       " 'tmin_2m',\n",
       " 'tmp_2m',\n",
       " 'tmp_hybr',\n",
       " 'tmp_pres',\n",
       " 'tmp_pres_abv700mb',\n",
       " 'tmp_pvor',\n",
       " 'tmp_sfc',\n",
       " 'tozne_eatm',\n",
       " 'tsoil_bgrnd',\n",
       " 'uflx_sfc',\n",
       " 'ugrd_hgt',\n",
       " 'ugrd_hybr',\n",
       " 'ugrd_pres',\n",
       " 'ugrd_pres_abv700mb',\n",
       " 'ugrd_pvor',\n",
       " 'ulwrf_sfc',\n",
       " 'ulwrf_tatm',\n",
       " 'uswrf_sfc',\n",
       " 'vflx_sfc',\n",
       " 'vgrd_hgt',\n",
       " 'vgrd_hybr',\n",
       " 'vgrd_pres',\n",
       " 'vgrd_pres_abv700mb',\n",
       " 'vgrd_pvor',\n",
       " 'vvel_pres',\n",
       " 'vvel_pres_abv700mb',\n",
       " 'watr_sfc',\n",
       " 'weasd_sfc']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "varnames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "59c2e510-80da-4260-a78c-a1c3093ef757",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_ensembles = len(ensembles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7c3272a3-e590-4bb2-af9f-48e6c5a15c76",
   "metadata": {},
   "outputs": [],
   "source": [
    "s3_so = {\n",
    "    'anon': True, \n",
    "    'skip_instance_cache': True\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf0af1f6-09ca-467d-bb25-a2e72b29b16f",
   "metadata": {},
   "source": [
    "Try scan_grib on one grib file to deterine the number of messages \n",
    "\n",
    "Scanning one file works if they all have the same number, but not all of the reforecast files do.  It turns out that in these grib files, each file is for a specific variable, and the messages contain not only all the tau values but also the different levels.   So for surface vars, there are 80 messages, but for variables with 4 levels there are 320 messages, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "bce94308-6323-414b-85f9-b831ff577d6b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.07 s, sys: 1.55 s, total: 9.62 s\n",
      "Wall time: 13.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "out = scan_grib(flist[0], storage_options= s3_so)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "df1b77d4-23d7-46be-9ae5-8713111c162f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_messages = len(out)\n",
    "n_messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "54a096ab-906f-4736-b12b-ddd7ea524c52",
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = [f'{i:03d}' for i in range(n_messages)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fa5a1515-85da-4f71-abce-fe7fc9b28b2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#client.close(); cluster.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "70966f62-0c87-4140-98a6-6a4e07971886",
   "metadata": {},
   "outputs": [],
   "source": [
    "individual_dir = 'individual_retro'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4ba885b3-c4b6-4566-9677-2c8482a25a11",
   "metadata": {},
   "outputs": [],
   "source": [
    "try: \n",
    "    fs_local.rm(individual_dir, recursive = True)\n",
    "except:\n",
    "    pass\n",
    "fs_local.mkdirs(individual_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7303a753-249c-4335-8be2-0455e61489cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('s3:',\n",
       " 'noaa-gefs-retrospective',\n",
       " 'GEFSv12',\n",
       " 'reforecast',\n",
       " '2019',\n",
       " '2019122900',\n",
       " 'c00',\n",
       " 'Days:1-10',\n",
       " 'acpcp_sfc_2019122900_c00.grib2')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Path(flist[0]).parts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "13e528e2-4af6-4b6e-8d48-28f4a8fbdb2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_json_name(url, grib_message_number, json_dir):\n",
    "    p = Path(url).parts\n",
    "    return f'{json_dir}/{Path(p[8]).stem}_m{grib_message_number:03d}.json'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6331fa05-7d39-4dd2-87b3-29d32b5a52a6",
   "metadata": {},
   "source": [
    "test make_json_name on one grib file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4e0816b3-bdb7-4edc-9568-54f077726b73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'individual_retro/acpcp_sfc_2019122900_c00_m000.json'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "make_json_name(flist[0], 0, individual_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8228574-6148-48e7-921b-e3a0dc01a665",
   "metadata": {},
   "source": [
    "Define function to generate single JSONs "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0bbdeb5e-aa92-4a0b-aa5d-c8975c95cdd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_json(file_url, json_dir):\n",
    "    out = scan_grib(file_url, storage_options=s3_so)\n",
    "    for i, message in enumerate(out): # scan_grib outputs a list containing one reference file per grib message\n",
    "        out_file_name = make_json_name(file_url, i, json_dir)  #get name\n",
    "        with fs_local.open(out_file_name, \"w\") as f: \n",
    "            f.write(ujson.dumps(message)) #write to file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b82745d-6270-4eae-b37d-bca009d09aa2",
   "metadata": {},
   "source": [
    "Process all the messages in one grib file as a test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "1fb7c04f-f9db-40fa-ad45-722e5a6f60f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 7.95 s, sys: 2.12 s, total: 10.1 s\n",
      "Wall time: 12.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "flist[0]\n",
    "gen_json(flist[0], individual_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "864ddcde-2729-47ba-bf7e-20667370d3cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list = sorted(fs_local.ls(individual_dir))\n",
    "len(json_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "7d043345-ca4a-47bc-8991-ff24eb98a667",
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_ds(d):\n",
    "    fs_ = fsspec.filesystem(\"reference\", fo=d, remote_protocol='s3', remote_options={'anon':True})\n",
    "    m = fs_.get_mapper(\"\")\n",
    "    return xr.open_dataset(m, engine=\"zarr\", backend_kwargs=dict(consolidated=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1b60798-02e8-42a7-b8ea-7801f6f7b8a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "json_list[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f62fb82-3bd9-4dd0-9027-58d836aa13dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "return_ds(json_list[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adee4dbe-043a-4f4b-93e7-a27d3f36da36",
   "metadata": {},
   "source": [
    "Use dask.distributed to create Jsons in parallel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21cae403-f3a1-47fe-9e73-5842f99b7dcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#client.close(); cluster.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a1c4f9a7-67bb-4358-ac08-b8569ab2c7e3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n_workers = 31\n",
    "threads_per_worker = 2\n",
    "cluster = LocalCluster(n_workers=n_workers, threads_per_worker=threads_per_worker)\n",
    "client = Client(cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b520d5ae-77f2-44d5-b05e-a32b6785f2d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2019122900', '2019123000', '2019123100']"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ff3d09ec-9714-4abd-b345-94a3b1b2cad2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6.41 ms, sys: 2.16 ms, total: 8.57 ms\n",
      "Wall time: 7.59 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "900"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "flist = []\n",
    "for date in dates:\n",
    "    year = date[:4]\n",
    "    flist.extend(sorted(fs_s3.glob(f's3://noaa-gefs-retrospective/GEFSv12/reforecast/{year}/{date}/???/Days:1-10/*.grib2')))\n",
    "\n",
    "flist = [f's3://{f}' for f in flist]\n",
    "len(flist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b44aaab8-c804-499f-bc6f-4f0ba6ac3945",
   "metadata": {},
   "outputs": [],
   "source": [
    "b = db.from_sequence(flist, npartitions=n_workers*threads_per_worker)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "25874fe9-c419-431f-82ef-4bcc2ac3a043",
   "metadata": {},
   "outputs": [],
   "source": [
    "b1 = b.map(gen_json, individual_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "95026e0b-b552-4247-9e47-859e683b74f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3min 28s, sys: 1min 3s, total: 4min 31s\n",
      "Wall time: 20min 35s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "with performance_report(filename=\"dask-report.html\"):\n",
    "    _ = b1.compute(retries=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "bada5f32-dbb2-4282-a594-aa9f0f910e1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "260400\n",
      "/home/rsignell/EarthMap/Projects/notebooks/gefs/individual_retro/acpcp_sfc_2019122900_c00_m000.json\n",
      "/home/rsignell/EarthMap/Projects/notebooks/gefs/individual_retro/weasd_sfc_2019123100_p04_m079.json\n"
     ]
    }
   ],
   "source": [
    "json_list = sorted(fs_local.ls(individual_dir))\n",
    "print(len(json_list))\n",
    "print(json_list[0])\n",
    "print(json_list[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdc6eb0e-4171-4d71-b7d0-bd7a9b98a98a",
   "metadata": {},
   "source": [
    "## Determine which grib files only have 80 messages: grib files that only have valid_times at one level (e.g. don't have multiple levels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "a42d65f4-26f5-4202-851f-d3e607b96c33",
   "metadata": {},
   "outputs": [],
   "source": [
    "ensemble='c00'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "dde0e427-a5dd-49d6-9e7b-7743a87a2270",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "individual_retro/acpcp_sfc_2019123100_c00_m???.json\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pattern = f'{individual_dir}/{varnames[0]}_{date}_{ensemble}_m???.json'\n",
    "print(pattern)\n",
    "json_list = fs_local.glob(pattern)\n",
    "len(json_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "16229cd6-6d6f-495b-87dc-b7dbfc48c71c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def var80(var):\n",
    "    pattern = f'{individual_dir}/{var}_{date}_{ensemble}_m???.json'\n",
    "    json_list = fs_local.glob(pattern)\n",
    "    if len(json_list)==80:\n",
    "        v = var\n",
    "    else:\n",
    "        v = 'null'\n",
    "    return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "b476bdba-2a85-4388-86a6-eb60cc54ca6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9.88 s, sys: 2.15 s, total: 12 s\n",
      "Wall time: 54.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ensemble='c00'\n",
    "\n",
    "a = dask.compute(*[dask.delayed(var80)(v) for v in varnames], retries=10);\n",
    "\n",
    "v80 = [v for v in a if 'null' not in v]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "d49b1a29-7cc7-4b33-978d-422a1d00a785",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['acpcp_sfc',\n",
       " 'apcp_sfc',\n",
       " 'cape_sfc',\n",
       " 'cin_sfc',\n",
       " 'dlwrf_sfc',\n",
       " 'dswrf_sfc',\n",
       " 'gflux_sfc',\n",
       " 'gust_sfc',\n",
       " 'hgt_ceiling',\n",
       " 'hgt_sfc',\n",
       " 'hlcy_hgt',\n",
       " 'lhtfl_sfc',\n",
       " 'ncpcp_sfc',\n",
       " 'pbl_hgt',\n",
       " 'pres_msl',\n",
       " 'pres_pvor',\n",
       " 'pres_sfc',\n",
       " 'pwat_eatm',\n",
       " 'sfcr_sfc',\n",
       " 'shtfl_sfc',\n",
       " 'spfh_2m',\n",
       " 'tcdc_eatm',\n",
       " 'tmax_2m',\n",
       " 'tmin_2m',\n",
       " 'tmp_2m',\n",
       " 'tmp_pvor',\n",
       " 'tmp_sfc',\n",
       " 'tozne_eatm',\n",
       " 'uflx_sfc',\n",
       " 'ugrd_pvor',\n",
       " 'ulwrf_sfc',\n",
       " 'ulwrf_tatm',\n",
       " 'uswrf_sfc',\n",
       " 'vflx_sfc',\n",
       " 'vgrd_pvor',\n",
       " 'watr_sfc',\n",
       " 'weasd_sfc']"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v80"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc47bf92-9f72-4398-9f15-2e91ea1c7a87",
   "metadata": {},
   "source": [
    "## Combine along the forecast time (tau) \"step\" dimension \n",
    "join along `step` dimension for each message in each ensemble member for a specific date.   Each grib file has all the `step` fields as separate messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8e5ba5f6-a631-41c7-9878-c2bce57373b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "step_dir = 'step'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "89562de1-9d85-4611-878b-ec9db9b72da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "try: \n",
    "    fs_local.rm(step_dir, recursive=True)\n",
    "except:\n",
    "    pass\n",
    "fs_local.mkdirs(step_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "58232d11-d66d-422a-9427-9052b090c961",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/rsignell/EarthMap/Projects/notebooks/gefs/individual_retro/acpcp_sfc_2019122900_c00_m000.json'"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "4a810ff7-df52-4a42-9838-bf59e85bef73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/rsignell/EarthMap/Projects/notebooks/gefs/individual_retro/ugrd_pres_2019122900_p02_m253.json'"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs_local.ls(individual_dir)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "6c37989a-677b-40b4-b5a3-0ed0916c2ed6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_steps(date,  ensemble):\n",
    "    for var in v80:\n",
    "        json_list = fs_local.glob(f'{individual_dir}/{var}_{date}_{ensemble}_*.json')\n",
    "        mzz = MultiZarrToZarr(json_list,\n",
    "                              concat_dims = ['step'],  \n",
    "                              remote_protocol='s3',\n",
    "                              remote_options=dict(anon=True),\n",
    "                              identical_dims=['latitude', 'longitude'])  \n",
    "        name = f'{step_dir}/{Path(json_list[0]).parts[-1]}'\n",
    "        with fs_local.open(name, 'w') as f:\n",
    "            f.write(ujson.dumps(mzz.translate()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "1b83e82f-1770-405b-af81-1ad95b6e050a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/rsignell/EarthMap/Projects/notebooks/gefs/individual_retro/acpcp_sfc_2019123100_c00_m000.json'"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57c3754f-6d48-4b5a-a50d-9c2894b82f7b",
   "metadata": {},
   "source": [
    "## Do ensembles and dates in parallel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "12bd42e6-9b30-4006-9ffa-c82f018e696c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['c00', 'p01', 'p02', 'p03', 'p04']"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ensembles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "321ecc05-16c3-4843-b9a6-ede12244c6c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2019122900', '2019123000', '2019123100']"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "b9fd09c3-fd7a-4bb1-846e-ddb044317e78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 29s, sys: 19 s, total: 1min 48s\n",
      "Wall time: 8min 38s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "_ = dask.compute(*[dask.delayed(combine_steps)(date,ensemble) for ensemble in ensembles for date in dates], retries=10);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "7c032c83-49f5-4aaf-a7a2-c1c72bced1f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "555"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list = sorted(fs_local.ls(step_dir))\n",
    "len(json_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26cf6dc4-f5d4-4ffa-8786-a5cd24ed8b17",
   "metadata": {},
   "source": [
    "## Combine across ensemble members"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "a94811ca-edf3-4ee3-9d99-682cb00b0f64",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.55 ms, sys: 551 µs, total: 2.1 ms\n",
      "Wall time: 1.52 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ensemble_dir = 'ensemble'\n",
    "\n",
    "try:\n",
    "    fs_local.rm(ensemble_dir, recursive = True)\n",
    "except:\n",
    "    pass\n",
    "fs_local.mkdirs(ensemble_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "24cbe3e8-e70a-4fca-b268-0a6de417c483",
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_ensemble(date):\n",
    "    for var in v80:\n",
    "        json_list = fs_local.glob(f'{step_dir}/{var}_{date}_???_m000.json')\n",
    "        mzz = MultiZarrToZarr(json_list,\n",
    "                              concat_dims = ['number'],  \n",
    "                              remote_protocol='s3',\n",
    "                              remote_options=dict(anon=True),\n",
    "                              identical_dims=['latitude', 'longitude'])  \n",
    "        name = f'{ensemble_dir}/{Path(json_list[0]).parts[-1]}'\n",
    "        with fs_local.open(name, 'w') as f:\n",
    "            f.write(ujson.dumps(mzz.translate()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "1835819e-df8e-40b6-8774-b34db3a41c15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.06 s, sys: 1.44 s, total: 5.5 s\n",
      "Wall time: 4.99 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None, None]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "[combine_ensemble(date) for date in dates]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "098cb343-638e-4aa0-82b1-e44703430f76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "111"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list = fs_local.glob(f'{ensemble_dir}/*.json')\n",
    "len(json_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "f655675e-050b-4817-974d-f6512b7c4f50",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "  warnings.warn(f\"Engine {name!r} loading failed:\\n{ex}\", RuntimeWarning)\n"
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    },
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       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (number: 5, step: 80, latitude: 721, longitude: 1440,\n",
       "                 surface: 1, time: 1, valid_time: 1)\n",
       "Coordinates:\n",
       "  * latitude    (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude   (longitude) float64 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * number      (number) int64 0 1 2 3 4\n",
       "  * step        (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * surface     (surface) int64 0\n",
       "  * time        (time) datetime64[ns] 2019-12-29\n",
       "  * valid_time  (valid_time) datetime64[ns] 2019-12-29T03:00:00\n",
       "Data variables:\n",
       "    acpcp       (number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b6fc4203-b4b4-4bdc-94c6-0d4e1418d438' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b6fc4203-b4b4-4bdc-94c6-0d4e1418d438' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>number</span>: 5</li><li><span class='xr-has-index'>step</span>: 80</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>valid_time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9bca196e-260c-488a-8052-2652687f79d5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9bca196e-260c-488a-8052-2652687f79d5' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-bc64270e-c639-4d59-b2ee-a9f9bddce446' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc64270e-c639-4d59-b2ee-a9f9bddce446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e608f0-5f5d-4b17-a1d4-d64be0e95e59' class='xr-var-data-in' type='checkbox'><label for='data-a4e608f0-5f5d-4b17-a1d4-d64be0e95e59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-ca51e3b1-a0f9-4e2e-820c-022f222c47dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca51e3b1-a0f9-4e2e-820c-022f222c47dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edb3ed0c-7fb9-4599-a3d8-31f2ab1aee7e' class='xr-var-data-in' type='checkbox'><label for='data-edb3ed0c-7fb9-4599-a3d8-31f2ab1aee7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-bddeac00-bd1c-4a3e-b182-f812c419ff70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bddeac00-bd1c-4a3e-b182-f812c419ff70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-badc07af-62ee-4042-93fc-c7abb3b7bdda' class='xr-var-data-in' type='checkbox'><label for='data-badc07af-62ee-4042-93fc-c7abb3b7bdda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>standard_name :</span></dt><dd>realization</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 03:00:00 ... 10 days 00:0...</div><input id='attrs-c0482833-5c06-423a-92e4-a8e50c135625' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0482833-5c06-423a-92e4-a8e50c135625' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9977a00e-0207-4d05-ab32-6341f799e304' class='xr-var-data-in' type='checkbox'><label for='data-9977a00e-0207-4d05-ab32-6341f799e304' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 10800000000000,  21600000000000,  32400000000000,  43200000000000,\n",
       "        54000000000000,  64800000000000,  75600000000000,  86400000000000,\n",
       "        97200000000000, 108000000000000, 118800000000000, 129600000000000,\n",
       "       140400000000000, 151200000000000, 162000000000000, 172800000000000,\n",
       "       183600000000000, 194400000000000, 205200000000000, 216000000000000,\n",
       "       226800000000000, 237600000000000, 248400000000000, 259200000000000,\n",
       "       270000000000000, 280800000000000, 291600000000000, 302400000000000,\n",
       "       313200000000000, 324000000000000, 334800000000000, 345600000000000,\n",
       "       356400000000000, 367200000000000, 378000000000000, 388800000000000,\n",
       "       399600000000000, 410400000000000, 421200000000000, 432000000000000,\n",
       "       442800000000000, 453600000000000, 464400000000000, 475200000000000,\n",
       "       486000000000000, 496800000000000, 507600000000000, 518400000000000,\n",
       "       529200000000000, 540000000000000, 550800000000000, 561600000000000,\n",
       "       572400000000000, 583200000000000, 594000000000000, 604800000000000,\n",
       "       615600000000000, 626400000000000, 637200000000000, 648000000000000,\n",
       "       658800000000000, 669600000000000, 680400000000000, 691200000000000,\n",
       "       702000000000000, 712800000000000, 723600000000000, 734400000000000,\n",
       "       745200000000000, 756000000000000, 766800000000000, 777600000000000,\n",
       "       788400000000000, 799200000000000, 810000000000000, 820800000000000,\n",
       "       831600000000000, 842400000000000, 853200000000000, 864000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-b238b67d-a190-4ec7-91ee-47c533cbeea1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b238b67d-a190-4ec7-91ee-47c533cbeea1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a70e317c-e57f-4094-aa7b-6102121ffd45' class='xr-var-data-in' type='checkbox'><label for='data-a70e317c-e57f-4094-aa7b-6102121ffd45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29</div><input id='attrs-6cc83206-9ab0-4cc4-850b-e0828d10b02d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cc83206-9ab0-4cc4-850b-e0828d10b02d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfa107b0-04d3-4ad2-bf1f-cf6b8700c43a' class='xr-var-data-in' type='checkbox'><label for='data-dfa107b0-04d3-4ad2-bf1f-cf6b8700c43a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>valid_time</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29T03:00:00</div><input id='attrs-4c47079c-3ca9-431c-af98-86cf494a629f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c47079c-3ca9-431c-af98-86cf494a629f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37ced685-4474-4a10-a0aa-4d051c807759' class='xr-var-data-in' type='checkbox'><label for='data-37ced685-4474-4a10-a0aa-4d051c807759' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T03:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e5b71a98-8ff1-49f2-85e8-154faf54aac0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e5b71a98-8ff1-49f2-85e8-154faf54aac0' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acpcp</span></div><div class='xr-var-dims'>(number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73019db4-8632-4f1b-a225-2e52623bd559' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73019db4-8632-4f1b-a225-2e52623bd559' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-059c0b37-90a7-4a85-9f5d-641cfeb4eb98' class='xr-var-data-in' type='checkbox'><label for='data-059c0b37-90a7-4a85-9f5d-641cfeb4eb98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_convective_precipitation_amount</dd><dt><span>cfVarName :</span></dt><dd>acpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective precipitation (water)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>3063</dd><dt><span>shortName :</span></dt><dd>acpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[415296000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd0634e4-aa74-444c-ae12-673acaa6a5a4' class='xr-section-summary-in' type='checkbox'  ><label for='section-cd0634e4-aa74-444c-ae12-673acaa6a5a4' class='xr-section-summary' >Indexes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2e3fbe1e-abf0-44d9-9af9-6d104e04d49a' class='xr-index-data-in' type='checkbox'/><label for='index-2e3fbe1e-abf0-44d9-9af9-6d104e04d49a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  90.0,  89.75,   89.5,  89.25,   89.0,  88.75,   88.5,  88.25,\n",
       "                88.0,  87.75,\n",
       "              ...\n",
       "              -87.75,  -88.0, -88.25,  -88.5, -88.75,  -89.0, -89.25,  -89.5,\n",
       "              -89.75,  -90.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=721))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b208a014-b8d5-44cb-9b4a-420d202acb65' class='xr-index-data-in' type='checkbox'/><label for='index-b208a014-b8d5-44cb-9b4a-420d202acb65' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([   0.0,   0.25,    0.5,   0.75,    1.0,   1.25,    1.5,   1.75,\n",
       "                 2.0,   2.25,\n",
       "              ...\n",
       "               357.5, 357.75,  358.0, 358.25,  358.5, 358.75,  359.0, 359.25,\n",
       "               359.5, 359.75],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42b5fb38-7ca8-41b8-88b0-9e385ef283e9' class='xr-index-data-in' type='checkbox'/><label for='index-42b5fb38-7ca8-41b8-88b0-9e385ef283e9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c76e36fe-651a-4ea1-a39c-aa37fe5b5e0b' class='xr-index-data-in' type='checkbox'/><label for='index-c76e36fe-651a-4ea1-a39c-aa37fe5b5e0b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(TimedeltaIndex([ &#x27;0 days 03:00:00&#x27;,  &#x27;0 days 06:00:00&#x27;,  &#x27;0 days 09:00:00&#x27;,\n",
       "                 &#x27;0 days 12:00:00&#x27;,  &#x27;0 days 15:00:00&#x27;,  &#x27;0 days 18:00:00&#x27;,\n",
       "                 &#x27;0 days 21:00:00&#x27;,  &#x27;1 days 00:00:00&#x27;,  &#x27;1 days 03:00:00&#x27;,\n",
       "                 &#x27;1 days 06:00:00&#x27;,  &#x27;1 days 09:00:00&#x27;,  &#x27;1 days 12:00:00&#x27;,\n",
       "                 &#x27;1 days 15:00:00&#x27;,  &#x27;1 days 18:00:00&#x27;,  &#x27;1 days 21:00:00&#x27;,\n",
       "                 &#x27;2 days 00:00:00&#x27;,  &#x27;2 days 03:00:00&#x27;,  &#x27;2 days 06:00:00&#x27;,\n",
       "                 &#x27;2 days 09:00:00&#x27;,  &#x27;2 days 12:00:00&#x27;,  &#x27;2 days 15:00:00&#x27;,\n",
       "                 &#x27;2 days 18:00:00&#x27;,  &#x27;2 days 21:00:00&#x27;,  &#x27;3 days 00:00:00&#x27;,\n",
       "                 &#x27;3 days 03:00:00&#x27;,  &#x27;3 days 06:00:00&#x27;,  &#x27;3 days 09:00:00&#x27;,\n",
       "                 &#x27;3 days 12:00:00&#x27;,  &#x27;3 days 15:00:00&#x27;,  &#x27;3 days 18:00:00&#x27;,\n",
       "                 &#x27;3 days 21:00:00&#x27;,  &#x27;4 days 00:00:00&#x27;,  &#x27;4 days 03:00:00&#x27;,\n",
       "                 &#x27;4 days 06:00:00&#x27;,  &#x27;4 days 09:00:00&#x27;,  &#x27;4 days 12:00:00&#x27;,\n",
       "                 &#x27;4 days 15:00:00&#x27;,  &#x27;4 days 18:00:00&#x27;,  &#x27;4 days 21:00:00&#x27;,\n",
       "                 &#x27;5 days 00:00:00&#x27;,  &#x27;5 days 03:00:00&#x27;,  &#x27;5 days 06:00:00&#x27;,\n",
       "                 &#x27;5 days 09:00:00&#x27;,  &#x27;5 days 12:00:00&#x27;,  &#x27;5 days 15:00:00&#x27;,\n",
       "                 &#x27;5 days 18:00:00&#x27;,  &#x27;5 days 21:00:00&#x27;,  &#x27;6 days 00:00:00&#x27;,\n",
       "                 &#x27;6 days 03:00:00&#x27;,  &#x27;6 days 06:00:00&#x27;,  &#x27;6 days 09:00:00&#x27;,\n",
       "                 &#x27;6 days 12:00:00&#x27;,  &#x27;6 days 15:00:00&#x27;,  &#x27;6 days 18:00:00&#x27;,\n",
       "                 &#x27;6 days 21:00:00&#x27;,  &#x27;7 days 00:00:00&#x27;,  &#x27;7 days 03:00:00&#x27;,\n",
       "                 &#x27;7 days 06:00:00&#x27;,  &#x27;7 days 09:00:00&#x27;,  &#x27;7 days 12:00:00&#x27;,\n",
       "                 &#x27;7 days 15:00:00&#x27;,  &#x27;7 days 18:00:00&#x27;,  &#x27;7 days 21:00:00&#x27;,\n",
       "                 &#x27;8 days 00:00:00&#x27;,  &#x27;8 days 03:00:00&#x27;,  &#x27;8 days 06:00:00&#x27;,\n",
       "                 &#x27;8 days 09:00:00&#x27;,  &#x27;8 days 12:00:00&#x27;,  &#x27;8 days 15:00:00&#x27;,\n",
       "                 &#x27;8 days 18:00:00&#x27;,  &#x27;8 days 21:00:00&#x27;,  &#x27;9 days 00:00:00&#x27;,\n",
       "                 &#x27;9 days 03:00:00&#x27;,  &#x27;9 days 06:00:00&#x27;,  &#x27;9 days 09:00:00&#x27;,\n",
       "                 &#x27;9 days 12:00:00&#x27;,  &#x27;9 days 15:00:00&#x27;,  &#x27;9 days 18:00:00&#x27;,\n",
       "                 &#x27;9 days 21:00:00&#x27;, &#x27;10 days 00:00:00&#x27;],\n",
       "               dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a90124e3-3f5e-41b9-bd5f-25d469dd22dd' class='xr-index-data-in' type='checkbox'/><label for='index-a90124e3-3f5e-41b9-bd5f-25d469dd22dd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([0], dtype=&#x27;int64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-87c98178-e399-4eb0-831b-b755996af721' class='xr-index-data-in' type='checkbox'/><label for='index-87c98178-e399-4eb0-831b-b755996af721' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-12-29&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>valid_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ead4f56f-6b43-40a9-8244-04c968218bdf' class='xr-index-data-in' type='checkbox'/><label for='index-ead4f56f-6b43-40a9-8244-04c968218bdf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-12-29 03:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;valid_time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8d69866c-1c6e-40f3-8cae-3ab62d05f963' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d69866c-1c6e-40f3-8cae-3ab62d05f963' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>centre :</span></dt><dd>kwbc</dd><dt><span>centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>edition :</span></dt><dd>2</dd><dt><span>subCentre :</span></dt><dd>2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:     (number: 5, step: 80, latitude: 721, longitude: 1440,\n",
       "                 surface: 1, time: 1, valid_time: 1)\n",
       "Coordinates:\n",
       "  * latitude    (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude   (longitude) float64 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * number      (number) int64 0 1 2 3 4\n",
       "  * step        (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * surface     (surface) int64 0\n",
       "  * time        (time) datetime64[ns] 2019-12-29\n",
       "  * valid_time  (valid_time) datetime64[ns] 2019-12-29T03:00:00\n",
       "Data variables:\n",
       "    acpcp       (number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_ds(json_list[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "fe617180-d6ab-4c63-a8d0-bd8010b4d794",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/rsignell/EarthMap/Projects/notebooks/gefs/ensemble/acpcp_sfc_2019122900_c00_m000.json'"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8669b3ce-d8ba-4484-9df6-361170bb2851",
   "metadata": {},
   "source": [
    "## Combine each group along the date dimension (time dimension)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "8f3e0c3a-f277-402d-8187-ee9cc02c121c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dates_dir = 'dates'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "84695595-5969-4aed-8aff-910a23129eb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:   \n",
    "    fs_local.mkdirs(dates_dir)\n",
    "except:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "6784ee3b-1f6d-43a2-85e2-5cb5eff240af",
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_dates(json_list, var):\n",
    "        mzz = MultiZarrToZarr(json_list,\n",
    "                              concat_dims = 'time',  \n",
    "                              remote_protocol='s3',\n",
    "                              remote_options=dict(anon=True),\n",
    "                              identical_dims=['latitude', 'longitude', 'step'])  \n",
    "        name = f'{dates_dir}/{var}.json'\n",
    "        with fs_local.open(name, 'w') as f:\n",
    "            f.write(ujson.dumps(mzz.translate()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "c1e50fbc-fae5-4664-8b19-a5aa8350d566",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.47 s, sys: 412 ms, total: 1.88 s\n",
      "Wall time: 1.72 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "for var in v80:\n",
    "    json_list = sorted(fs_local.glob(f'{ensemble_dir}/{var}*.json'))\n",
    "    combine_dates(json_list, var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "b94effd6-7dc8-438c-8ea1-265d90bec4c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/acpcp_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/apcp_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/cape_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/cin_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/dlwrf_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/dswrf_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/gflux_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/gust_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/hgt_ceiling.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/hgt_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/hlcy_hgt.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/lhtfl_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/ncpcp_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/pbl_hgt.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/pres_msl.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/pres_pvor.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/pres_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/pwat_eatm.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/sfcr_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/shtfl_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/spfh_2m.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tcdc_eatm.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tmax_2m.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tmin_2m.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tmp_2m.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tmp_pvor.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tmp_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/tozne_eatm.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/uflx_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/ugrd_pvor.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/ulwrf_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/ulwrf_tatm.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/uswrf_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/vflx_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/vgrd_pvor.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/watr_sfc.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/dates/weasd_sfc.json']"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list = fs_local.glob(f'{dates_dir}/*.json')\n",
    "len(json_list)\n",
    "json_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "b35b10a6-580b-496b-9ac0-d68324f71d12",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 3, number: 5, step: 80, latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude  (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
       "  * number     (number) int64 0 1 2 3 4\n",
       "  * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "Data variables:\n",
       "    acpcp      (time, number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f45776ab-67fb-48e3-806b-a2bc398fd963' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f45776ab-67fb-48e3-806b-a2bc398fd963' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3</li><li><span class='xr-has-index'>number</span>: 5</li><li><span class='xr-has-index'>step</span>: 80</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a25ad157-9c1d-4653-a3aa-d6d65be01794' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a25ad157-9c1d-4653-a3aa-d6d65be01794' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-3c2d351d-3f1c-45c3-ab06-dd84fd338b38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c2d351d-3f1c-45c3-ab06-dd84fd338b38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e9bbf52-fd75-4eba-b89a-9917f2e0493a' class='xr-var-data-in' type='checkbox'><label for='data-7e9bbf52-fd75-4eba-b89a-9917f2e0493a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-47a93136-0490-47c9-91c2-5a4813a2d0f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47a93136-0490-47c9-91c2-5a4813a2d0f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7bdfb75-01d4-41b3-8184-8c5607c82acf' class='xr-var-data-in' type='checkbox'><label for='data-e7bdfb75-01d4-41b3-8184-8c5607c82acf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-72583bbc-bf2d-43e1-acd2-30293feb01cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72583bbc-bf2d-43e1-acd2-30293feb01cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24512a0b-c71e-4469-810e-293b74220934' class='xr-var-data-in' type='checkbox'><label for='data-24512a0b-c71e-4469-810e-293b74220934' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>standard_name :</span></dt><dd>realization</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 03:00:00 ... 10 days 00:0...</div><input id='attrs-d40d75d6-2b4c-4a65-9190-3d49e18cbfe3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d40d75d6-2b4c-4a65-9190-3d49e18cbfe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e0be623-34d0-48d4-b84f-358ab3e5ce50' class='xr-var-data-in' type='checkbox'><label for='data-0e0be623-34d0-48d4-b84f-358ab3e5ce50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 10800000000000,  21600000000000,  32400000000000,  43200000000000,\n",
       "        54000000000000,  64800000000000,  75600000000000,  86400000000000,\n",
       "        97200000000000, 108000000000000, 118800000000000, 129600000000000,\n",
       "       140400000000000, 151200000000000, 162000000000000, 172800000000000,\n",
       "       183600000000000, 194400000000000, 205200000000000, 216000000000000,\n",
       "       226800000000000, 237600000000000, 248400000000000, 259200000000000,\n",
       "       270000000000000, 280800000000000, 291600000000000, 302400000000000,\n",
       "       313200000000000, 324000000000000, 334800000000000, 345600000000000,\n",
       "       356400000000000, 367200000000000, 378000000000000, 388800000000000,\n",
       "       399600000000000, 410400000000000, 421200000000000, 432000000000000,\n",
       "       442800000000000, 453600000000000, 464400000000000, 475200000000000,\n",
       "       486000000000000, 496800000000000, 507600000000000, 518400000000000,\n",
       "       529200000000000, 540000000000000, 550800000000000, 561600000000000,\n",
       "       572400000000000, 583200000000000, 594000000000000, 604800000000000,\n",
       "       615600000000000, 626400000000000, 637200000000000, 648000000000000,\n",
       "       658800000000000, 669600000000000, 680400000000000, 691200000000000,\n",
       "       702000000000000, 712800000000000, 723600000000000, 734400000000000,\n",
       "       745200000000000, 756000000000000, 766800000000000, 777600000000000,\n",
       "       788400000000000, 799200000000000, 810000000000000, 820800000000000,\n",
       "       831600000000000, 842400000000000, 853200000000000, 864000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29 2019-12-30 2019-12-31</div><input id='attrs-68da4d2c-ee50-421b-920c-cc666afc9703' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68da4d2c-ee50-421b-920c-cc666afc9703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b274bd0-8f19-4f5d-bbd3-cf4ba046382b' class='xr-var-data-in' type='checkbox'><label for='data-6b274bd0-8f19-4f5d-bbd3-cf4ba046382b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T00:00:00.000000000&#x27;, &#x27;2019-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3d41e495-72f9-4fe3-8742-6d647b8c573f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3d41e495-72f9-4fe3-8742-6d647b8c573f' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acpcp</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c40ba9e2-2c8c-4806-9a3c-3ea24e1866e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c40ba9e2-2c8c-4806-9a3c-3ea24e1866e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b779fe94-fa0d-484c-90f4-40446666f621' class='xr-var-data-in' type='checkbox'><label for='data-b779fe94-fa0d-484c-90f4-40446666f621' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_convective_precipitation_amount</dd><dt><span>cfVarName :</span></dt><dd>acpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective precipitation (water)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>3063</dd><dt><span>shortName :</span></dt><dd>acpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c194991-5347-4c90-a7c9-3c1326dfe459' class='xr-section-summary-in' type='checkbox'  ><label for='section-4c194991-5347-4c90-a7c9-3c1326dfe459' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ff7fe220-2dc2-44c7-bc28-686930368b57' class='xr-index-data-in' type='checkbox'/><label for='index-ff7fe220-2dc2-44c7-bc28-686930368b57' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  90.0,  89.75,   89.5,  89.25,   89.0,  88.75,   88.5,  88.25,\n",
       "                88.0,  87.75,\n",
       "              ...\n",
       "              -87.75,  -88.0, -88.25,  -88.5, -88.75,  -89.0, -89.25,  -89.5,\n",
       "              -89.75,  -90.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=721))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b2834db2-b477-4a2e-a44a-a8d1aa803c48' class='xr-index-data-in' type='checkbox'/><label for='index-b2834db2-b477-4a2e-a44a-a8d1aa803c48' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([   0.0,   0.25,    0.5,   0.75,    1.0,   1.25,    1.5,   1.75,\n",
       "                 2.0,   2.25,\n",
       "              ...\n",
       "               357.5, 357.75,  358.0, 358.25,  358.5, 358.75,  359.0, 359.25,\n",
       "               359.5, 359.75],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d6386ea7-2cbc-4640-b677-8b78a7c7b9c9' class='xr-index-data-in' type='checkbox'/><label for='index-d6386ea7-2cbc-4640-b677-8b78a7c7b9c9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-faddd33a-0f68-4e85-bb04-0760ed0a6f6e' class='xr-index-data-in' type='checkbox'/><label for='index-faddd33a-0f68-4e85-bb04-0760ed0a6f6e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(TimedeltaIndex([ &#x27;0 days 03:00:00&#x27;,  &#x27;0 days 06:00:00&#x27;,  &#x27;0 days 09:00:00&#x27;,\n",
       "                 &#x27;0 days 12:00:00&#x27;,  &#x27;0 days 15:00:00&#x27;,  &#x27;0 days 18:00:00&#x27;,\n",
       "                 &#x27;0 days 21:00:00&#x27;,  &#x27;1 days 00:00:00&#x27;,  &#x27;1 days 03:00:00&#x27;,\n",
       "                 &#x27;1 days 06:00:00&#x27;,  &#x27;1 days 09:00:00&#x27;,  &#x27;1 days 12:00:00&#x27;,\n",
       "                 &#x27;1 days 15:00:00&#x27;,  &#x27;1 days 18:00:00&#x27;,  &#x27;1 days 21:00:00&#x27;,\n",
       "                 &#x27;2 days 00:00:00&#x27;,  &#x27;2 days 03:00:00&#x27;,  &#x27;2 days 06:00:00&#x27;,\n",
       "                 &#x27;2 days 09:00:00&#x27;,  &#x27;2 days 12:00:00&#x27;,  &#x27;2 days 15:00:00&#x27;,\n",
       "                 &#x27;2 days 18:00:00&#x27;,  &#x27;2 days 21:00:00&#x27;,  &#x27;3 days 00:00:00&#x27;,\n",
       "                 &#x27;3 days 03:00:00&#x27;,  &#x27;3 days 06:00:00&#x27;,  &#x27;3 days 09:00:00&#x27;,\n",
       "                 &#x27;3 days 12:00:00&#x27;,  &#x27;3 days 15:00:00&#x27;,  &#x27;3 days 18:00:00&#x27;,\n",
       "                 &#x27;3 days 21:00:00&#x27;,  &#x27;4 days 00:00:00&#x27;,  &#x27;4 days 03:00:00&#x27;,\n",
       "                 &#x27;4 days 06:00:00&#x27;,  &#x27;4 days 09:00:00&#x27;,  &#x27;4 days 12:00:00&#x27;,\n",
       "                 &#x27;4 days 15:00:00&#x27;,  &#x27;4 days 18:00:00&#x27;,  &#x27;4 days 21:00:00&#x27;,\n",
       "                 &#x27;5 days 00:00:00&#x27;,  &#x27;5 days 03:00:00&#x27;,  &#x27;5 days 06:00:00&#x27;,\n",
       "                 &#x27;5 days 09:00:00&#x27;,  &#x27;5 days 12:00:00&#x27;,  &#x27;5 days 15:00:00&#x27;,\n",
       "                 &#x27;5 days 18:00:00&#x27;,  &#x27;5 days 21:00:00&#x27;,  &#x27;6 days 00:00:00&#x27;,\n",
       "                 &#x27;6 days 03:00:00&#x27;,  &#x27;6 days 06:00:00&#x27;,  &#x27;6 days 09:00:00&#x27;,\n",
       "                 &#x27;6 days 12:00:00&#x27;,  &#x27;6 days 15:00:00&#x27;,  &#x27;6 days 18:00:00&#x27;,\n",
       "                 &#x27;6 days 21:00:00&#x27;,  &#x27;7 days 00:00:00&#x27;,  &#x27;7 days 03:00:00&#x27;,\n",
       "                 &#x27;7 days 06:00:00&#x27;,  &#x27;7 days 09:00:00&#x27;,  &#x27;7 days 12:00:00&#x27;,\n",
       "                 &#x27;7 days 15:00:00&#x27;,  &#x27;7 days 18:00:00&#x27;,  &#x27;7 days 21:00:00&#x27;,\n",
       "                 &#x27;8 days 00:00:00&#x27;,  &#x27;8 days 03:00:00&#x27;,  &#x27;8 days 06:00:00&#x27;,\n",
       "                 &#x27;8 days 09:00:00&#x27;,  &#x27;8 days 12:00:00&#x27;,  &#x27;8 days 15:00:00&#x27;,\n",
       "                 &#x27;8 days 18:00:00&#x27;,  &#x27;8 days 21:00:00&#x27;,  &#x27;9 days 00:00:00&#x27;,\n",
       "                 &#x27;9 days 03:00:00&#x27;,  &#x27;9 days 06:00:00&#x27;,  &#x27;9 days 09:00:00&#x27;,\n",
       "                 &#x27;9 days 12:00:00&#x27;,  &#x27;9 days 15:00:00&#x27;,  &#x27;9 days 18:00:00&#x27;,\n",
       "                 &#x27;9 days 21:00:00&#x27;, &#x27;10 days 00:00:00&#x27;],\n",
       "               dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb5da455-955a-4f7c-b5ff-68dc652bb8c5' class='xr-index-data-in' type='checkbox'/><label for='index-bb5da455-955a-4f7c-b5ff-68dc652bb8c5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-12-29&#x27;, &#x27;2019-12-30&#x27;, &#x27;2019-12-31&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8554878-5d85-484c-a547-e660910dafaa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8554878-5d85-484c-a547-e660910dafaa' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>centre :</span></dt><dd>kwbc</dd><dt><span>centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>edition :</span></dt><dd>2</dd><dt><span>subCentre :</span></dt><dd>2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 3, number: 5, step: 80, latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude  (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
       "  * number     (number) int64 0 1 2 3 4\n",
       "  * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "Data variables:\n",
       "    acpcp      (time, number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_ds(json_list[0]).squeeze(['surface', 'valid_time'],drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44a5446a-af9b-4786-83f1-6a5810e4e5ef",
   "metadata": {},
   "source": [
    "### Determine which variables can be combined into a single dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02f0bf0d-355b-44a1-bb5f-06fe50a95141",
   "metadata": {},
   "source": [
    "Here we open each reference message and determine what type of vertical level it contains. We will use this later to combine the messages alongs these levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ca090987-e71f-46c1-800d-ca71577fd32c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 854 ms, sys: 147 ms, total: 1 s\n",
      "Wall time: 880 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "typeoflevel = {}\n",
    "for i,ref in enumerate(json_list):\n",
    "    try:\n",
    "        ds = return_ds(ref)\n",
    "        dim = [dim for dim in list(ds.dims) if dim not in ['valid_time', 'x', 'y', 'step', 'time','latitude', 'longitude', 'number']] #I manually figure out which dims are common\n",
    "        typeoflevel[i] = dim[0]\n",
    "    except:\n",
    "        print(i, 'not included')\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "a4dcb0ad-96be-4b3e-8ccc-37f3240f4651",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 18 µs, sys: 0 ns, total: 18 µs\n",
      "Wall time: 21.9 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "groups = {}\n",
    "for key, value in sorted(typeoflevel.items()):\n",
    "    groups.setdefault(value, []).append(key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "36aa8473-1aa9-4ee0-8f4b-96b12642977a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'surface': [0,\n",
       "  1,\n",
       "  2,\n",
       "  3,\n",
       "  4,\n",
       "  5,\n",
       "  6,\n",
       "  7,\n",
       "  9,\n",
       "  11,\n",
       "  12,\n",
       "  13,\n",
       "  16,\n",
       "  18,\n",
       "  19,\n",
       "  26,\n",
       "  28,\n",
       "  30,\n",
       "  32,\n",
       "  33,\n",
       "  35,\n",
       "  36],\n",
       " 'cloudCeiling': [8],\n",
       " 'heightAboveGroundLayer': [10],\n",
       " 'meanSea': [14],\n",
       " 'potentialVorticity': [15, 25, 29, 34],\n",
       " 'atmosphereSingleLayer': [17, 27],\n",
       " 'heightAboveGround': [20, 22, 23, 24],\n",
       " 'atmosphere': [21],\n",
       " 'nominalTop': [31]}"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groups"
   ]
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  {
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   "id": "48c1886d-94e8-460f-a543-c91297dfcb49",
   "metadata": {},
   "source": [
    "We can now use this groups dictionary to combine the compatible messages "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "92bae4cf-cc49-41b4-a585-d2ddca2fac40",
   "metadata": {},
   "outputs": [],
   "source": [
    "groups_dir = 'groups'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "abb3a20c-6b5a-4afc-8ce8-cd4a5aa1ee9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    fs_local.mkdirs(groups_dir)\n",
    "except:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "5e06b9c3-8ce9-4593-80aa-e55330ef57d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine_groups(json_list, group):\n",
    "        mzz = MultiZarrToZarr(json_list,\n",
    "                              concat_dims = group,  \n",
    "                              remote_protocol='s3',\n",
    "                              remote_options=dict(anon=True),\n",
    "                              identical_dims=['latitude', 'longitude'])  \n",
    "        name = f'{groups_dir}/{group}.json'\n",
    "        with fs_local.open(name, 'w') as f:\n",
    "            f.write(ujson.dumps(mzz.translate()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f07625f2-378b-438e-b071-bc4979569e3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "for group,igroup in groups.items():\n",
    "    json_list=[]\n",
    "    print(group, len(igroup))\n",
    "    for i in igroup:\n",
    "        json_list.append(f'{dates_dir}/{v80[i]}.json')\n",
    "    combine_groups(json_list, group)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26c2f3c7-6b74-457a-934a-36e568a85b75",
   "metadata": {},
   "source": [
    "This leaves us with reference files which we can now use to open the GEFS data as an xarray-datatree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "11114360-2ce5-458f-8684-0eaaab4fbd1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/atmosphere.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/atmosphereSingleLayer.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/cloudCeiling.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/heightAboveGround.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/heightAboveGroundLayer.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/meanSea.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/nominalTop.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/potentialVorticity.json',\n",
       " '/home/rsignell/EarthMap/Projects/notebooks/gefs/groups/surface.json']"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_list = fs_local.glob(f\"{groups_dir}/*.json\")\n",
    "json_list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1246d2a-ff33-40f0-a47b-3b1cb41887cc",
   "metadata": {},
   "source": [
    "## Combine all groups in a DataTree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "3a938370-f008-4cd9-8ad5-8e4d51f41f6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "datasets = {}\n",
    "for group in groups:\n",
    "    datasets[group] = return_ds(f'{groups_dir}/{group}.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "01c6258b-0acf-4747-b52e-468412338af2",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = DataTree.from_dict(datasets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "a223d006-0fa1-4e5f-83d7-0844bb070ff1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('/',\n",
       " '/surface',\n",
       " '/cloudCeiling',\n",
       " '/heightAboveGroundLayer',\n",
       " '/meanSea',\n",
       " '/potentialVorticity',\n",
       " '/atmosphereSingleLayer',\n",
       " '/heightAboveGround',\n",
       " '/atmosphere',\n",
       " '/nominalTop')"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "60c50ae3-9f0c-4f78-a98a-0e34e48385dd",
   "metadata": {},
   "outputs": [
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       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt;\n",
       "Dimensions:     (surface: 1, time: 3, number: 5, step: 80, latitude: 721,\n",
       "                 longitude: 1440, valid_time: 1)\n",
       "Coordinates:\n",
       "  * latitude    (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude   (longitude) float64 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * number      (number) int64 0 1 2 3 4\n",
       "  * step        (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * surface     (surface) int64 0\n",
       "  * time        (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "  * valid_time  (valid_time) datetime64[ns] 2019-12-29T03:00:00\n",
       "Data variables: (12/22)\n",
       "    acpcp       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    cape        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    cin         (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    dlwrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    dswrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    gflux       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    ...          ...\n",
       "    tp          (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    uflx        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    ulwrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    uswrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    vflx        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    watr        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>datatree.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ef0418d6-cc34-4c3d-b9b3-98e2e1f8e22f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ef0418d6-cc34-4c3d-b9b3-98e2e1f8e22f' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%'></div></div></li><li class='xr-section-item'><input id='section-76faab17-8f0b-44ad-910a-f5af9f7eb8cb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-76faab17-8f0b-44ad-910a-f5af9f7eb8cb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>time</span>: 3</li><li><span class='xr-has-index'>number</span>: 5</li><li><span class='xr-has-index'>step</span>: 80</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li><li><span class='xr-has-index'>valid_time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-939821c5-bbdc-4681-8215-37eafe30493e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-939821c5-bbdc-4681-8215-37eafe30493e' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-cc579300-d89b-483a-989c-2e97552af2e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc579300-d89b-483a-989c-2e97552af2e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6619fbb2-4355-4a2b-9095-8e9876eb947f' class='xr-var-data-in' type='checkbox'><label for='data-6619fbb2-4355-4a2b-9095-8e9876eb947f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-abab6374-f76c-4c16-99ce-8a433661abe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abab6374-f76c-4c16-99ce-8a433661abe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1636d03-16b1-4ee4-b7ec-9143d45b489a' class='xr-var-data-in' type='checkbox'><label for='data-e1636d03-16b1-4ee4-b7ec-9143d45b489a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-eb225635-88b5-4abd-a951-698c48d45b08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb225635-88b5-4abd-a951-698c48d45b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7700ba1-aa85-4f10-adc5-7ac1aa8752a6' class='xr-var-data-in' type='checkbox'><label for='data-d7700ba1-aa85-4f10-adc5-7ac1aa8752a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>standard_name :</span></dt><dd>realization</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 03:00:00 ... 10 days 00:0...</div><input id='attrs-35a0f70a-3d9c-4697-9af8-d036adeb0db7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a0f70a-3d9c-4697-9af8-d036adeb0db7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe59fede-4bf1-4cd9-8f71-427c7453b1af' class='xr-var-data-in' type='checkbox'><label for='data-fe59fede-4bf1-4cd9-8f71-427c7453b1af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 10800000000000,  21600000000000,  32400000000000,  43200000000000,\n",
       "        54000000000000,  64800000000000,  75600000000000,  86400000000000,\n",
       "        97200000000000, 108000000000000, 118800000000000, 129600000000000,\n",
       "       140400000000000, 151200000000000, 162000000000000, 172800000000000,\n",
       "       183600000000000, 194400000000000, 205200000000000, 216000000000000,\n",
       "       226800000000000, 237600000000000, 248400000000000, 259200000000000,\n",
       "       270000000000000, 280800000000000, 291600000000000, 302400000000000,\n",
       "       313200000000000, 324000000000000, 334800000000000, 345600000000000,\n",
       "       356400000000000, 367200000000000, 378000000000000, 388800000000000,\n",
       "       399600000000000, 410400000000000, 421200000000000, 432000000000000,\n",
       "       442800000000000, 453600000000000, 464400000000000, 475200000000000,\n",
       "       486000000000000, 496800000000000, 507600000000000, 518400000000000,\n",
       "       529200000000000, 540000000000000, 550800000000000, 561600000000000,\n",
       "       572400000000000, 583200000000000, 594000000000000, 604800000000000,\n",
       "       615600000000000, 626400000000000, 637200000000000, 648000000000000,\n",
       "       658800000000000, 669600000000000, 680400000000000, 691200000000000,\n",
       "       702000000000000, 712800000000000, 723600000000000, 734400000000000,\n",
       "       745200000000000, 756000000000000, 766800000000000, 777600000000000,\n",
       "       788400000000000, 799200000000000, 810000000000000, 820800000000000,\n",
       "       831600000000000, 842400000000000, 853200000000000, 864000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-9fa51275-a552-4831-be58-526b07afe1f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9fa51275-a552-4831-be58-526b07afe1f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-034dad58-7230-4cba-a785-12f0261bc29c' class='xr-var-data-in' type='checkbox'><label for='data-034dad58-7230-4cba-a785-12f0261bc29c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29 2019-12-30 2019-12-31</div><input id='attrs-078eae0f-4b10-41ac-bffc-e2d3736793b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-078eae0f-4b10-41ac-bffc-e2d3736793b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b626cded-a5a6-4fbb-ab31-edf61c915f20' class='xr-var-data-in' type='checkbox'><label for='data-b626cded-a5a6-4fbb-ab31-edf61c915f20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T00:00:00.000000000&#x27;, &#x27;2019-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>valid_time</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29T03:00:00</div><input id='attrs-60add885-44e5-428c-ba76-af5108f8bcfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60add885-44e5-428c-ba76-af5108f8bcfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6b19aeb-de20-49f9-a388-df857519cef8' class='xr-var-data-in' type='checkbox'><label for='data-b6b19aeb-de20-49f9-a388-df857519cef8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T03:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb67ff24-3e62-471a-b936-6c6ad02334f2' class='xr-section-summary-in' type='checkbox'  ><label for='section-eb67ff24-3e62-471a-b936-6c6ad02334f2' class='xr-section-summary' >Data variables: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acpcp</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c3527262-6f5e-49b0-9075-366d9477630d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3527262-6f5e-49b0-9075-366d9477630d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f1de177-ef42-49ff-bd17-0f546184b147' class='xr-var-data-in' type='checkbox'><label for='data-8f1de177-ef42-49ff-bd17-0f546184b147' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_convective_precipitation_amount</dd><dt><span>cfVarName :</span></dt><dd>acpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective precipitation (water)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>3063</dd><dt><span>shortName :</span></dt><dd>acpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cape</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f18e5f95-a6e0-4e83-97b3-99ad9aef890d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f18e5f95-a6e0-4e83-97b3-99ad9aef890d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15019d00-99ca-4379-9ef8-6a3db8cf9cbf' class='xr-var-data-in' type='checkbox'><label for='data-15019d00-99ca-4379-9ef8-6a3db8cf9cbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective available potential energy</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>59</dd><dt><span>shortName :</span></dt><dd>cape</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>J kg**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cin</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb185aa5-1e85-4ee8-bacd-f2d92f028595' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb185aa5-1e85-4ee8-bacd-f2d92f028595' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-354c0bb7-9061-40b7-be7a-80ca1aba0f66' class='xr-var-data-in' type='checkbox'><label for='data-354c0bb7-9061-40b7-be7a-80ca1aba0f66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective inhibition</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228001</dd><dt><span>shortName :</span></dt><dd>cin</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>J kg**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dlwrf</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6114a8c3-1296-4558-8e7e-bf3cc2979925' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6114a8c3-1296-4558-8e7e-bf3cc2979925' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b3eafc5-5df4-4f51-9f17-1ab18c0fc4da' class='xr-var-data-in' type='checkbox'><label for='data-7b3eafc5-5df4-4f51-9f17-1ab18c0fc4da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Downward long-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260097</dd><dt><span>shortName :</span></dt><dd>dlwrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dswrf</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d2fb7375-dc63-4108-bd3c-08b33bf65cde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2fb7375-dc63-4108-bd3c-08b33bf65cde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a46def03-2117-46c5-8abf-ecfbb40ca805' class='xr-var-data-in' type='checkbox'><label for='data-a46def03-2117-46c5-8abf-ecfbb40ca805' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Downward short-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260087</dd><dt><span>shortName :</span></dt><dd>dswrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gflux</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5f710211-7523-4e44-9717-755ef75ddf6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f710211-7523-4e44-9717-755ef75ddf6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b03c4b87-3f5e-4d99-b94c-ae719298043f' class='xr-var-data-in' type='checkbox'><label for='data-b03c4b87-3f5e-4d99-b94c-ae719298043f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Ground heat flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260186</dd><dt><span>shortName :</span></dt><dd>gflux</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gust</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-201639e5-1e91-4879-9a10-7302caeed964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-201639e5-1e91-4879-9a10-7302caeed964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-114d26f1-46a0-4920-a11d-09d233f6549f' class='xr-var-data-in' type='checkbox'><label for='data-114d26f1-46a0-4920-a11d-09d233f6549f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>gust</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Wind speed (gust)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260065</dd><dt><span>shortName :</span></dt><dd>gust</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m s**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hpbl</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-24f96159-8467-4987-9a76-d1f05559036f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24f96159-8467-4987-9a76-d1f05559036f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a11b8cf6-6ec6-49f3-902c-62874a3815ec' class='xr-var-data-in' type='checkbox'><label for='data-a11b8cf6-6ec6-49f3-902c-62874a3815ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Planetary boundary layer height</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260083</dd><dt><span>shortName :</span></dt><dd>hpbl</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lhtfl</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2c93ff6c-3dc6-4929-886a-cf501b83d980' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c93ff6c-3dc6-4929-886a-cf501b83d980' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-752fb76a-c50a-42ec-a347-5011a5bf7fbe' class='xr-var-data-in' type='checkbox'><label for='data-752fb76a-c50a-42ec-a347-5011a5bf7fbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>lhtfl</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Latent heat net flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260002</dd><dt><span>shortName :</span></dt><dd>lhtfl</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ncpcp</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-809f0d04-637b-4d67-8a0b-9786ee3ebecb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-809f0d04-637b-4d67-8a0b-9786ee3ebecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71572b5b-e2a7-45ea-962f-075748ddf289' class='xr-var-data-in' type='checkbox'><label for='data-71572b5b-e2a7-45ea-962f-075748ddf289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>ncpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Large scale precipitation (non-convective)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260009</dd><dt><span>shortName :</span></dt><dd>ncpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orog</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2606c5b8-42d6-47c1-a61b-f5b7192c0110' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2606c5b8-42d6-47c1-a61b-f5b7192c0110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b05ad80-6d2c-47c9-90e0-e8c057ba87f4' class='xr-var-data-in' type='checkbox'><label for='data-5b05ad80-6d2c-47c9-90e0-e8c057ba87f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>geopotential_height</dd><dt><span>cfVarName :</span></dt><dd>orog</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Orography</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228002</dd><dt><span>shortName :</span></dt><dd>orog</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sdwe</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-099bc0f7-69e4-49d5-80ec-3e7e39168547' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-099bc0f7-69e4-49d5-80ec-3e7e39168547' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b9d48ef-7142-4ed5-9479-57a517d10db4' class='xr-var-data-in' type='checkbox'><label for='data-2b9d48ef-7142-4ed5-9479-57a517d10db4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>sdwe</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Water equivalent of accumulated snow depth (deprecated)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260056</dd><dt><span>shortName :</span></dt><dd>sdwe</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shtfl</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cc309af8-2c36-4f4e-a395-6180e0f9969b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc309af8-2c36-4f4e-a395-6180e0f9969b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0bde8d5-61fa-4ba4-aa77-df63640eeec5' class='xr-var-data-in' type='checkbox'><label for='data-a0bde8d5-61fa-4ba4-aa77-df63640eeec5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>shtfl</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Sensible heat net flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260003</dd><dt><span>shortName :</span></dt><dd>shtfl</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sp</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7597a511-c880-449b-9738-236898eec851' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7597a511-c880-449b-9738-236898eec851' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25688069-aa2a-4856-a1ce-472af3b734ef' class='xr-var-data-in' type='checkbox'><label for='data-25688069-aa2a-4856-a1ce-472af3b734ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>cfVarName :</span></dt><dd>sp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Surface pressure</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>134</dd><dt><span>shortName :</span></dt><dd>sp</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sr</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d60ec6ce-365a-4ea0-8dc1-acf57d0dda6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d60ec6ce-365a-4ea0-8dc1-acf57d0dda6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e6478d-146a-4f4f-8119-01c52953f9e1' class='xr-var-data-in' type='checkbox'><label for='data-f2e6478d-146a-4f4f-8119-01c52953f9e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>surface_roughness_length</dd><dt><span>cfVarName :</span></dt><dd>sr</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Surface roughness</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>173</dd><dt><span>shortName :</span></dt><dd>sr</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e8e2df6a-29a0-4943-bce6-ce1166edb65a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8e2df6a-29a0-4943-bce6-ce1166edb65a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f529642-a2bd-43c3-9eda-ac46c206e701' class='xr-var-data-in' type='checkbox'><label for='data-2f529642-a2bd-43c3-9eda-ac46c206e701' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Temperature</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>130</dd><dt><span>shortName :</span></dt><dd>t</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cffcd102-dc18-4bbb-9f69-7f8dd747873b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cffcd102-dc18-4bbb-9f69-7f8dd747873b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ad94a0d-cf04-4980-9723-e4a7d1ca2aa3' class='xr-var-data-in' type='checkbox'><label for='data-4ad94a0d-cf04-4980-9723-e4a7d1ca2aa3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Total Precipitation</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228228</dd><dt><span>shortName :</span></dt><dd>tp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uflx</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a84b9140-1338-4812-8299-48f84c7e65f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a84b9140-1338-4812-8299-48f84c7e65f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-249622e8-ceae-4f04-9d56-c2375c3c38e2' class='xr-var-data-in' type='checkbox'><label for='data-249622e8-ceae-4f04-9d56-c2375c3c38e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>uflx</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Momentum flux, u component</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260062</dd><dt><span>shortName :</span></dt><dd>uflx</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>N m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ulwrf</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c1a948a8-28ec-4c0b-bc09-2910fe89b7e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1a948a8-28ec-4c0b-bc09-2910fe89b7e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74e3adcc-9acd-41a7-b539-0680de1f7b61' class='xr-var-data-in' type='checkbox'><label for='data-74e3adcc-9acd-41a7-b539-0680de1f7b61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Upward long-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260098</dd><dt><span>shortName :</span></dt><dd>ulwrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uswrf</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c9004ef6-39bd-43dc-b950-3094aa61076f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9004ef6-39bd-43dc-b950-3094aa61076f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79f09906-9429-47d3-95cd-06aa328d97cc' class='xr-var-data-in' type='checkbox'><label for='data-79f09906-9429-47d3-95cd-06aa328d97cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Upward short-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260088</dd><dt><span>shortName :</span></dt><dd>uswrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vflx</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-819477db-312d-4ff9-97e7-0267e8ad3a98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-819477db-312d-4ff9-97e7-0267e8ad3a98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0be3791e-230d-44d4-bb03-2a35a6837d13' class='xr-var-data-in' type='checkbox'><label for='data-0be3791e-230d-44d4-bb03-2a35a6837d13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>vflx</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Momentum flux, v component</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260063</dd><dt><span>shortName :</span></dt><dd>vflx</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>N m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>watr</span></div><div class='xr-var-dims'>(surface, time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7088ca42-c854-489c-9586-7e32bc9c5dd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7088ca42-c854-489c-9586-7e32bc9c5dd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80afc8e5-fa15-410a-81ca-01f543b76bdf' class='xr-var-data-in' type='checkbox'><label for='data-80afc8e5-fa15-410a-81ca-01f543b76bdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>watr</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Water runoff</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260181</dd><dt><span>shortName :</span></dt><dd>watr</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-78ca016f-b941-475c-9198-a54f3c06fb56' class='xr-section-summary-in' type='checkbox'  checked><label for='section-78ca016f-b941-475c-9198-a54f3c06fb56' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>centre :</span></dt><dd>kwbc</dd><dt><span>centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>edition :</span></dt><dd>2</dd><dt><span>subCentre :</span></dt><dd>2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "DataTree('surface', parent=\"None\")\n",
       "    Dimensions:     (surface: 1, time: 3, number: 5, step: 80, latitude: 721,\n",
       "                     longitude: 1440, valid_time: 1)\n",
       "    Coordinates:\n",
       "      * latitude    (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "      * longitude   (longitude) float64 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "      * number      (number) int64 0 1 2 3 4\n",
       "      * step        (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "      * surface     (surface) int64 0\n",
       "      * time        (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "      * valid_time  (valid_time) datetime64[ns] 2019-12-29T03:00:00\n",
       "    Data variables: (12/22)\n",
       "        acpcp       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        cape        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        cin         (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        dlwrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        dswrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        gflux       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        ...          ...\n",
       "        tp          (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        uflx        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        ulwrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        uswrf       (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        vflx        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "        watr        (surface, time, number, step, latitude, longitude) float64 ...\n",
       "    Attributes:\n",
       "        centre:             kwbc\n",
       "        centreDescription:  US National Weather Service - NCEP\n",
       "        edition:            2\n",
       "        subCentre:          2"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_surface = dt['surface']\n",
    "ds_surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "24bcc7ca-0c91-4796-8c58-57133d054ca4",
   "metadata": {},
   "outputs": [
    {
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       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt;\n",
       "Dimensions:    (time: 3, number: 5, step: 80, latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude  (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
       "  * number     (number) int64 0 1 2 3 4\n",
       "  * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "Data variables: (12/22)\n",
       "    acpcp      (time, number, step, latitude, longitude) float64 ...\n",
       "    cape       (time, number, step, latitude, longitude) float64 ...\n",
       "    cin        (time, number, step, latitude, longitude) float64 ...\n",
       "    dlwrf      (time, number, step, latitude, longitude) float64 ...\n",
       "    dswrf      (time, number, step, latitude, longitude) float64 ...\n",
       "    gflux      (time, number, step, latitude, longitude) float64 ...\n",
       "    ...         ...\n",
       "    tp         (time, number, step, latitude, longitude) float64 ...\n",
       "    uflx       (time, number, step, latitude, longitude) float64 ...\n",
       "    ulwrf      (time, number, step, latitude, longitude) float64 ...\n",
       "    uswrf      (time, number, step, latitude, longitude) float64 ...\n",
       "    vflx       (time, number, step, latitude, longitude) float64 ...\n",
       "    watr       (time, number, step, latitude, longitude) float64 ...\n",
       "Attributes:\n",
       "    centre:             kwbc\n",
       "    centreDescription:  US National Weather Service - NCEP\n",
       "    edition:            2\n",
       "    subCentre:          2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>datatree.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1e395d2c-451e-4e7a-9cdd-b020166829ab' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1e395d2c-451e-4e7a-9cdd-b020166829ab' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%'></div></div></li><li class='xr-section-item'><input id='section-54984ad5-a56f-4dae-96bd-43bf24db8547' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-54984ad5-a56f-4dae-96bd-43bf24db8547' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3</li><li><span class='xr-has-index'>number</span>: 5</li><li><span class='xr-has-index'>step</span>: 80</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f6785c98-a320-4ebd-a834-1981d6178bb1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f6785c98-a320-4ebd-a834-1981d6178bb1' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-3263336b-ae44-4f4a-81dc-cad8f99978b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3263336b-ae44-4f4a-81dc-cad8f99978b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4911b055-af3a-4b81-a8ba-b6da69384f11' class='xr-var-data-in' type='checkbox'><label for='data-4911b055-af3a-4b81-a8ba-b6da69384f11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-ca44690e-bb60-49dc-aa0b-17fc288c9e4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca44690e-bb60-49dc-aa0b-17fc288c9e4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edbd80f5-6c4d-4beb-9c1d-7b10206e01e9' class='xr-var-data-in' type='checkbox'><label for='data-edbd80f5-6c4d-4beb-9c1d-7b10206e01e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-1e846b07-e6c9-4815-92eb-1bb0c56d26d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e846b07-e6c9-4815-92eb-1bb0c56d26d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e20e962-f5e5-4607-969d-3f6e56fe8c58' class='xr-var-data-in' type='checkbox'><label for='data-8e20e962-f5e5-4607-969d-3f6e56fe8c58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>standard_name :</span></dt><dd>realization</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 03:00:00 ... 10 days 00:0...</div><input id='attrs-a8959f86-f820-440b-84a8-5a2b84b1c586' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8959f86-f820-440b-84a8-5a2b84b1c586' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d53a63c8-33c2-4fff-993e-783d0d998c54' class='xr-var-data-in' type='checkbox'><label for='data-d53a63c8-33c2-4fff-993e-783d0d998c54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 10800000000000,  21600000000000,  32400000000000,  43200000000000,\n",
       "        54000000000000,  64800000000000,  75600000000000,  86400000000000,\n",
       "        97200000000000, 108000000000000, 118800000000000, 129600000000000,\n",
       "       140400000000000, 151200000000000, 162000000000000, 172800000000000,\n",
       "       183600000000000, 194400000000000, 205200000000000, 216000000000000,\n",
       "       226800000000000, 237600000000000, 248400000000000, 259200000000000,\n",
       "       270000000000000, 280800000000000, 291600000000000, 302400000000000,\n",
       "       313200000000000, 324000000000000, 334800000000000, 345600000000000,\n",
       "       356400000000000, 367200000000000, 378000000000000, 388800000000000,\n",
       "       399600000000000, 410400000000000, 421200000000000, 432000000000000,\n",
       "       442800000000000, 453600000000000, 464400000000000, 475200000000000,\n",
       "       486000000000000, 496800000000000, 507600000000000, 518400000000000,\n",
       "       529200000000000, 540000000000000, 550800000000000, 561600000000000,\n",
       "       572400000000000, 583200000000000, 594000000000000, 604800000000000,\n",
       "       615600000000000, 626400000000000, 637200000000000, 648000000000000,\n",
       "       658800000000000, 669600000000000, 680400000000000, 691200000000000,\n",
       "       702000000000000, 712800000000000, 723600000000000, 734400000000000,\n",
       "       745200000000000, 756000000000000, 766800000000000, 777600000000000,\n",
       "       788400000000000, 799200000000000, 810000000000000, 820800000000000,\n",
       "       831600000000000, 842400000000000, 853200000000000, 864000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29 2019-12-30 2019-12-31</div><input id='attrs-ec07d2b9-3915-42de-bbaf-8343a167eb73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec07d2b9-3915-42de-bbaf-8343a167eb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abf0217d-e6ad-421c-87c1-c0c774721091' class='xr-var-data-in' type='checkbox'><label for='data-abf0217d-e6ad-421c-87c1-c0c774721091' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T00:00:00.000000000&#x27;, &#x27;2019-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3bbfe762-b9b9-454f-ae65-68f19dba14d7' class='xr-section-summary-in' type='checkbox'  ><label for='section-3bbfe762-b9b9-454f-ae65-68f19dba14d7' class='xr-section-summary' >Data variables: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acpcp</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2b8f3363-72ad-45f0-872b-2e4ee200fd58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b8f3363-72ad-45f0-872b-2e4ee200fd58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5809d8bf-eb22-4a9d-b718-5f68de898726' class='xr-var-data-in' type='checkbox'><label for='data-5809d8bf-eb22-4a9d-b718-5f68de898726' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_convective_precipitation_amount</dd><dt><span>cfVarName :</span></dt><dd>acpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective precipitation (water)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>3063</dd><dt><span>shortName :</span></dt><dd>acpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cape</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a839607c-e027-434f-95d2-4758ed366478' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a839607c-e027-434f-95d2-4758ed366478' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-124e9f2f-1e39-486c-91cc-179b413e7ae9' class='xr-var-data-in' type='checkbox'><label for='data-124e9f2f-1e39-486c-91cc-179b413e7ae9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective available potential energy</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>59</dd><dt><span>shortName :</span></dt><dd>cape</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>J kg**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cin</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0ed3b3ea-eabc-4e71-bec2-a7f40ac8979a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ed3b3ea-eabc-4e71-bec2-a7f40ac8979a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-157c3c7f-b96c-4391-9f12-92ce5b609077' class='xr-var-data-in' type='checkbox'><label for='data-157c3c7f-b96c-4391-9f12-92ce5b609077' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Convective inhibition</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228001</dd><dt><span>shortName :</span></dt><dd>cin</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>J kg**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dlwrf</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-82053115-3560-4156-9a2f-e71848551a07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82053115-3560-4156-9a2f-e71848551a07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c431372d-92b6-4d89-acb6-d3db58a15133' class='xr-var-data-in' type='checkbox'><label for='data-c431372d-92b6-4d89-acb6-d3db58a15133' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Downward long-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260097</dd><dt><span>shortName :</span></dt><dd>dlwrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dswrf</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d4b4dfb0-b7a4-4b27-bc4a-e0255a0bfecf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4b4dfb0-b7a4-4b27-bc4a-e0255a0bfecf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b6b3cb4-ec0c-4dbf-a715-608b16a2d17b' class='xr-var-data-in' type='checkbox'><label for='data-2b6b3cb4-ec0c-4dbf-a715-608b16a2d17b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Downward short-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260087</dd><dt><span>shortName :</span></dt><dd>dswrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gflux</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ae6a3dde-89d5-4665-8aa4-0fde2f837d78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae6a3dde-89d5-4665-8aa4-0fde2f837d78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10092832-5ba8-4ead-9976-f805de42566b' class='xr-var-data-in' type='checkbox'><label for='data-10092832-5ba8-4ead-9976-f805de42566b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Ground heat flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260186</dd><dt><span>shortName :</span></dt><dd>gflux</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gust</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fcf5a93f-cf61-4993-bec8-176aefdc294d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcf5a93f-cf61-4993-bec8-176aefdc294d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0891abab-621b-4753-b00f-a0397e7bf941' class='xr-var-data-in' type='checkbox'><label for='data-0891abab-621b-4753-b00f-a0397e7bf941' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>gust</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Wind speed (gust)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260065</dd><dt><span>shortName :</span></dt><dd>gust</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m s**-1</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hpbl</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64afa081-a640-4587-9b55-be80d38795f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64afa081-a640-4587-9b55-be80d38795f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39e8cf7a-b049-4a51-bc0c-bd80e0198f57' class='xr-var-data-in' type='checkbox'><label for='data-39e8cf7a-b049-4a51-bc0c-bd80e0198f57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Planetary boundary layer height</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260083</dd><dt><span>shortName :</span></dt><dd>hpbl</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lhtfl</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b9cbe73a-4dba-4fe1-a8b6-2cffc804c199' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9cbe73a-4dba-4fe1-a8b6-2cffc804c199' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39ccccf3-9dde-4b15-8aa7-66b507988836' class='xr-var-data-in' type='checkbox'><label for='data-39ccccf3-9dde-4b15-8aa7-66b507988836' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>lhtfl</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Latent heat net flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260002</dd><dt><span>shortName :</span></dt><dd>lhtfl</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ncpcp</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0bc48d71-0023-4d33-a23f-6a518ad565f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bc48d71-0023-4d33-a23f-6a518ad565f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b83f3752-eb78-49c0-a72a-83724474bcce' class='xr-var-data-in' type='checkbox'><label for='data-b83f3752-eb78-49c0-a72a-83724474bcce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>ncpcp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Large scale precipitation (non-convective)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260009</dd><dt><span>shortName :</span></dt><dd>ncpcp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orog</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3b4afd90-c6e3-4c52-a992-ed31df794cd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b4afd90-c6e3-4c52-a992-ed31df794cd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b70584c1-afd4-4ca7-8464-49360b8e63e6' class='xr-var-data-in' type='checkbox'><label for='data-b70584c1-afd4-4ca7-8464-49360b8e63e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>geopotential_height</dd><dt><span>cfVarName :</span></dt><dd>orog</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Orography</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228002</dd><dt><span>shortName :</span></dt><dd>orog</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sdwe</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-95e8c970-1298-4b5a-8973-78e46db32598' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95e8c970-1298-4b5a-8973-78e46db32598' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbdf9203-0274-4e24-884d-bd25f59b15c8' class='xr-var-data-in' type='checkbox'><label for='data-bbdf9203-0274-4e24-884d-bd25f59b15c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>sdwe</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Water equivalent of accumulated snow depth (deprecated)</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260056</dd><dt><span>shortName :</span></dt><dd>sdwe</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shtfl</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cb5e8f7d-555d-49ef-9168-81f996b24ccb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb5e8f7d-555d-49ef-9168-81f996b24ccb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de4ca485-f84d-4b80-9f4f-cfb4ef126026' class='xr-var-data-in' type='checkbox'><label for='data-de4ca485-f84d-4b80-9f4f-cfb4ef126026' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>shtfl</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Sensible heat net flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260003</dd><dt><span>shortName :</span></dt><dd>shtfl</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sp</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a3b64d5-0957-4566-b1cb-e1048b9c3516' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a3b64d5-0957-4566-b1cb-e1048b9c3516' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dc811dc-fffd-4399-b1c6-62a425492e08' class='xr-var-data-in' type='checkbox'><label for='data-0dc811dc-fffd-4399-b1c6-62a425492e08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>cfVarName :</span></dt><dd>sp</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Surface pressure</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>134</dd><dt><span>shortName :</span></dt><dd>sp</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sr</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-45ed53fc-be77-4550-a560-37948ee02cbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45ed53fc-be77-4550-a560-37948ee02cbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7d2b8df-92e1-4fe8-9118-f536dc6cff5a' class='xr-var-data-in' type='checkbox'><label for='data-f7d2b8df-92e1-4fe8-9118-f536dc6cff5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>surface_roughness_length</dd><dt><span>cfVarName :</span></dt><dd>sr</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Surface roughness</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>173</dd><dt><span>shortName :</span></dt><dd>sr</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-762b8b65-3d8c-4282-9050-ab93ca4da709' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-762b8b65-3d8c-4282-9050-ab93ca4da709' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3efb80de-1f36-4cc9-b6ec-6ba00bc9bce3' class='xr-var-data-in' type='checkbox'><label for='data-3efb80de-1f36-4cc9-b6ec-6ba00bc9bce3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Temperature</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>130</dd><dt><span>shortName :</span></dt><dd>t</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b7889b44-972d-4d28-ae2c-abbb075c60f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7889b44-972d-4d28-ae2c-abbb075c60f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f95544c-872a-4334-937c-6c1ae8365c9b' class='xr-var-data-in' type='checkbox'><label for='data-9f95544c-872a-4334-937c-6c1ae8365c9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Total Precipitation</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>228228</dd><dt><span>shortName :</span></dt><dd>tp</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uflx</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c56ea4aa-ce31-4b74-9d3f-0526ec8d2688' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c56ea4aa-ce31-4b74-9d3f-0526ec8d2688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfa4793d-dc37-482e-90b3-467d7ab31e90' class='xr-var-data-in' type='checkbox'><label for='data-dfa4793d-dc37-482e-90b3-467d7ab31e90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>uflx</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Momentum flux, u component</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260062</dd><dt><span>shortName :</span></dt><dd>uflx</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>N m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ulwrf</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c2d211a-ec9e-4381-8a67-c6111e474d45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c2d211a-ec9e-4381-8a67-c6111e474d45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e42b046-638a-4c68-a598-9913301af819' class='xr-var-data-in' type='checkbox'><label for='data-2e42b046-638a-4c68-a598-9913301af819' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Upward long-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260098</dd><dt><span>shortName :</span></dt><dd>ulwrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uswrf</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-515540e1-08cf-4dfb-9d09-6e863af64464' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-515540e1-08cf-4dfb-9d09-6e863af64464' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5a76d72-ad3b-408f-b152-1f0f0ab86e48' class='xr-var-data-in' type='checkbox'><label for='data-f5a76d72-ad3b-408f-b152-1f0f0ab86e48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>unknown</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Upward short-wave radiation flux</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260088</dd><dt><span>shortName :</span></dt><dd>uswrf</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>W m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vflx</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0f1ffcfc-871f-43a3-aa54-f6008ed831de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f1ffcfc-871f-43a3-aa54-f6008ed831de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c8a07ab-6aae-486d-bc8e-06f7a5ae3351' class='xr-var-data-in' type='checkbox'><label for='data-8c8a07ab-6aae-486d-bc8e-06f7a5ae3351' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>vflx</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Momentum flux, v component</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260063</dd><dt><span>shortName :</span></dt><dd>vflx</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>N m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>watr</span></div><div class='xr-var-dims'>(time, number, step, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-34bd4138-ba57-4858-a51b-f77f26a3436c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34bd4138-ba57-4858-a51b-f77f26a3436c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc2ae0be-1a38-4c15-86cc-05f9dc6d687f' class='xr-var-data-in' type='checkbox'><label for='data-fc2ae0be-1a38-4c15-86cc-05f9dc6d687f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>unknown</dd><dt><span>cfVarName :</span></dt><dd>watr</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Water runoff</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>260181</dd><dt><span>shortName :</span></dt><dd>watr</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>20</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>kg m**-2</dd></dl></div><div class='xr-var-data'><pre>[1245888000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-105bbba6-a698-4fa1-aee5-dff2a5765c80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-105bbba6-a698-4fa1-aee5-dff2a5765c80' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>centre :</span></dt><dd>kwbc</dd><dt><span>centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>edition :</span></dt><dd>2</dd><dt><span>subCentre :</span></dt><dd>2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "DataTree('surface', parent=None)\n",
       "    Dimensions:    (time: 3, number: 5, step: 80, latitude: 721, longitude: 1440)\n",
       "    Coordinates:\n",
       "      * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "      * longitude  (longitude) float64 0.0 0.25 0.5 0.75 ... 359.0 359.2 359.5 359.8\n",
       "      * number     (number) int64 0 1 2 3 4\n",
       "      * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "      * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "    Data variables: (12/22)\n",
       "        acpcp      (time, number, step, latitude, longitude) float64 ...\n",
       "        cape       (time, number, step, latitude, longitude) float64 ...\n",
       "        cin        (time, number, step, latitude, longitude) float64 ...\n",
       "        dlwrf      (time, number, step, latitude, longitude) float64 ...\n",
       "        dswrf      (time, number, step, latitude, longitude) float64 ...\n",
       "        gflux      (time, number, step, latitude, longitude) float64 ...\n",
       "        ...         ...\n",
       "        tp         (time, number, step, latitude, longitude) float64 ...\n",
       "        uflx       (time, number, step, latitude, longitude) float64 ...\n",
       "        ulwrf      (time, number, step, latitude, longitude) float64 ...\n",
       "        uswrf      (time, number, step, latitude, longitude) float64 ...\n",
       "        vflx       (time, number, step, latitude, longitude) float64 ...\n",
       "        watr       (time, number, step, latitude, longitude) float64 ...\n",
       "    Attributes:\n",
       "        centre:             kwbc\n",
       "        centreDescription:  US National Weather Service - NCEP\n",
       "        edition:            2\n",
       "        subCentre:          2"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_surface = dt['surface'].squeeze('surface',drop=True).squeeze('valid_time',drop=True)\n",
    "ds_surface\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "f88b1c9f-613a-4ce0-8b4b-4adfbb8eda20",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_surface = ds_surface.assign_coords(longitude=(((ds.longitude + 180) % 360) - 180)).sortby('longitude')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "efe769dc-069d-4b12-9d4c-cd551beb95b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "var = 't'\n",
    "da = ds_surface[var]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "4451256b-98e9-481d-972d-cb1ca7f993cc",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;t&#x27; (time: 3, number: 5, step: 80, latitude: 721,\n",
       "                       longitude: 1440)&gt;\n",
       "[1245888000 values with dtype=float64]\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude  (longitude) float64 -180.0 -179.8 -179.5 ... 179.2 179.5 179.8\n",
       "  * number     (number) int64 0 1 2 3 4\n",
       "  * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "Attributes: (12/19)\n",
       "    NV:                         0\n",
       "    cfName:                     air_temperature\n",
       "    cfVarName:                  t\n",
       "    dataDate:                   20191229\n",
       "    dataTime:                   0\n",
       "    dataType:                   cf\n",
       "    ...                         ...\n",
       "    shortName:                  t\n",
       "    stepType:                   instant\n",
       "    stepUnits:                  1\n",
       "    totalNumber:                10\n",
       "    typeOfLevel:                surface\n",
       "    units:                      K</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 3</li><li><span class='xr-has-index'>number</span>: 5</li><li><span class='xr-has-index'>step</span>: 80</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9f59ad6d-9264-4ff4-9479-06384ad0cb07' class='xr-array-in' type='checkbox' checked><label for='section-9f59ad6d-9264-4ff4-9479-06384ad0cb07' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[1245888000 values with dtype=float64]</pre></div></div></li><li class='xr-section-item'><input id='section-944e7417-021b-42f1-9036-6909521dc160' class='xr-section-summary-in' type='checkbox'  checked><label for='section-944e7417-021b-42f1-9036-6909521dc160' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-c374480b-647a-42b1-ac6e-aa13b2650a72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c374480b-647a-42b1-ac6e-aa13b2650a72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-712a3bc4-0174-4bda-b354-c926adc32cd7' class='xr-var-data-in' type='checkbox'><label for='data-712a3bc4-0174-4bda-b354-c926adc32cd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.8 ... 179.5 179.8</div><input id='attrs-566f65df-68ff-41f7-bb80-bdcadee59c23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-566f65df-68ff-41f7-bb80-bdcadee59c23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c587418f-5996-42d2-a2f4-89352e3c1f1e' class='xr-var-data-in' type='checkbox'><label for='data-c587418f-5996-42d2-a2f4-89352e3c1f1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-180.  , -179.75, -179.5 , ...,  179.25,  179.5 ,  179.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-030e4647-bf16-4548-bafe-0a740aad6c7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-030e4647-bf16-4548-bafe-0a740aad6c7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4af03ea7-cb03-471c-bbf6-0329011775a0' class='xr-var-data-in' type='checkbox'><label for='data-4af03ea7-cb03-471c-bbf6-0329011775a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>standard_name :</span></dt><dd>realization</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 03:00:00 ... 10 days 00:0...</div><input id='attrs-8a97c74c-da3f-411e-bfcd-6caddacc71f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a97c74c-da3f-411e-bfcd-6caddacc71f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef1b611c-54e0-4e91-b1bf-d6b45d50cf9d' class='xr-var-data-in' type='checkbox'><label for='data-ef1b611c-54e0-4e91-b1bf-d6b45d50cf9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 10800000000000,  21600000000000,  32400000000000,  43200000000000,\n",
       "        54000000000000,  64800000000000,  75600000000000,  86400000000000,\n",
       "        97200000000000, 108000000000000, 118800000000000, 129600000000000,\n",
       "       140400000000000, 151200000000000, 162000000000000, 172800000000000,\n",
       "       183600000000000, 194400000000000, 205200000000000, 216000000000000,\n",
       "       226800000000000, 237600000000000, 248400000000000, 259200000000000,\n",
       "       270000000000000, 280800000000000, 291600000000000, 302400000000000,\n",
       "       313200000000000, 324000000000000, 334800000000000, 345600000000000,\n",
       "       356400000000000, 367200000000000, 378000000000000, 388800000000000,\n",
       "       399600000000000, 410400000000000, 421200000000000, 432000000000000,\n",
       "       442800000000000, 453600000000000, 464400000000000, 475200000000000,\n",
       "       486000000000000, 496800000000000, 507600000000000, 518400000000000,\n",
       "       529200000000000, 540000000000000, 550800000000000, 561600000000000,\n",
       "       572400000000000, 583200000000000, 594000000000000, 604800000000000,\n",
       "       615600000000000, 626400000000000, 637200000000000, 648000000000000,\n",
       "       658800000000000, 669600000000000, 680400000000000, 691200000000000,\n",
       "       702000000000000, 712800000000000, 723600000000000, 734400000000000,\n",
       "       745200000000000, 756000000000000, 766800000000000, 777600000000000,\n",
       "       788400000000000, 799200000000000, 810000000000000, 820800000000000,\n",
       "       831600000000000, 842400000000000, 853200000000000, 864000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-12-29 2019-12-30 2019-12-31</div><input id='attrs-6a67702b-4a57-459a-a222-293610c9a53b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a67702b-4a57-459a-a222-293610c9a53b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48e72c6e-ef92-473d-be5f-7290fbcb6fc8' class='xr-var-data-in' type='checkbox'><label for='data-48e72c6e-ef92-473d-be5f-7290fbcb6fc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-12-29T00:00:00.000000000&#x27;, &#x27;2019-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c1161c2-952a-457e-989c-6e73c76b154f' class='xr-section-summary-in' type='checkbox'  ><label for='section-7c1161c2-952a-457e-989c-6e73c76b154f' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ec197da8-1a9f-48e7-b413-8d0be5dfbfb1' class='xr-index-data-in' type='checkbox'/><label for='index-ec197da8-1a9f-48e7-b413-8d0be5dfbfb1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  90.0,  89.75,   89.5,  89.25,   89.0,  88.75,   88.5,  88.25,\n",
       "                88.0,  87.75,\n",
       "              ...\n",
       "              -87.75,  -88.0, -88.25,  -88.5, -88.75,  -89.0, -89.25,  -89.5,\n",
       "              -89.75,  -90.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=721))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ec9e622f-c6f6-4520-991a-de0349f9d0b2' class='xr-index-data-in' type='checkbox'/><label for='index-ec9e622f-c6f6-4520-991a-de0349f9d0b2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -180.0, -179.75,  -179.5, -179.25,  -179.0, -178.75,  -178.5,\n",
       "              -178.25,  -178.0, -177.75,\n",
       "              ...\n",
       "                177.5,  177.75,   178.0,  178.25,   178.5,  178.75,   179.0,\n",
       "               179.25,   179.5,  179.75],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1e13f3f9-e6ef-4cb0-ad5a-e011885f8962' class='xr-index-data-in' type='checkbox'/><label for='index-1e13f3f9-e6ef-4cb0-ad5a-e011885f8962' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-553a446e-9c27-40c9-b76a-f0193c8fe301' class='xr-index-data-in' type='checkbox'/><label for='index-553a446e-9c27-40c9-b76a-f0193c8fe301' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(TimedeltaIndex([ &#x27;0 days 03:00:00&#x27;,  &#x27;0 days 06:00:00&#x27;,  &#x27;0 days 09:00:00&#x27;,\n",
       "                 &#x27;0 days 12:00:00&#x27;,  &#x27;0 days 15:00:00&#x27;,  &#x27;0 days 18:00:00&#x27;,\n",
       "                 &#x27;0 days 21:00:00&#x27;,  &#x27;1 days 00:00:00&#x27;,  &#x27;1 days 03:00:00&#x27;,\n",
       "                 &#x27;1 days 06:00:00&#x27;,  &#x27;1 days 09:00:00&#x27;,  &#x27;1 days 12:00:00&#x27;,\n",
       "                 &#x27;1 days 15:00:00&#x27;,  &#x27;1 days 18:00:00&#x27;,  &#x27;1 days 21:00:00&#x27;,\n",
       "                 &#x27;2 days 00:00:00&#x27;,  &#x27;2 days 03:00:00&#x27;,  &#x27;2 days 06:00:00&#x27;,\n",
       "                 &#x27;2 days 09:00:00&#x27;,  &#x27;2 days 12:00:00&#x27;,  &#x27;2 days 15:00:00&#x27;,\n",
       "                 &#x27;2 days 18:00:00&#x27;,  &#x27;2 days 21:00:00&#x27;,  &#x27;3 days 00:00:00&#x27;,\n",
       "                 &#x27;3 days 03:00:00&#x27;,  &#x27;3 days 06:00:00&#x27;,  &#x27;3 days 09:00:00&#x27;,\n",
       "                 &#x27;3 days 12:00:00&#x27;,  &#x27;3 days 15:00:00&#x27;,  &#x27;3 days 18:00:00&#x27;,\n",
       "                 &#x27;3 days 21:00:00&#x27;,  &#x27;4 days 00:00:00&#x27;,  &#x27;4 days 03:00:00&#x27;,\n",
       "                 &#x27;4 days 06:00:00&#x27;,  &#x27;4 days 09:00:00&#x27;,  &#x27;4 days 12:00:00&#x27;,\n",
       "                 &#x27;4 days 15:00:00&#x27;,  &#x27;4 days 18:00:00&#x27;,  &#x27;4 days 21:00:00&#x27;,\n",
       "                 &#x27;5 days 00:00:00&#x27;,  &#x27;5 days 03:00:00&#x27;,  &#x27;5 days 06:00:00&#x27;,\n",
       "                 &#x27;5 days 09:00:00&#x27;,  &#x27;5 days 12:00:00&#x27;,  &#x27;5 days 15:00:00&#x27;,\n",
       "                 &#x27;5 days 18:00:00&#x27;,  &#x27;5 days 21:00:00&#x27;,  &#x27;6 days 00:00:00&#x27;,\n",
       "                 &#x27;6 days 03:00:00&#x27;,  &#x27;6 days 06:00:00&#x27;,  &#x27;6 days 09:00:00&#x27;,\n",
       "                 &#x27;6 days 12:00:00&#x27;,  &#x27;6 days 15:00:00&#x27;,  &#x27;6 days 18:00:00&#x27;,\n",
       "                 &#x27;6 days 21:00:00&#x27;,  &#x27;7 days 00:00:00&#x27;,  &#x27;7 days 03:00:00&#x27;,\n",
       "                 &#x27;7 days 06:00:00&#x27;,  &#x27;7 days 09:00:00&#x27;,  &#x27;7 days 12:00:00&#x27;,\n",
       "                 &#x27;7 days 15:00:00&#x27;,  &#x27;7 days 18:00:00&#x27;,  &#x27;7 days 21:00:00&#x27;,\n",
       "                 &#x27;8 days 00:00:00&#x27;,  &#x27;8 days 03:00:00&#x27;,  &#x27;8 days 06:00:00&#x27;,\n",
       "                 &#x27;8 days 09:00:00&#x27;,  &#x27;8 days 12:00:00&#x27;,  &#x27;8 days 15:00:00&#x27;,\n",
       "                 &#x27;8 days 18:00:00&#x27;,  &#x27;8 days 21:00:00&#x27;,  &#x27;9 days 00:00:00&#x27;,\n",
       "                 &#x27;9 days 03:00:00&#x27;,  &#x27;9 days 06:00:00&#x27;,  &#x27;9 days 09:00:00&#x27;,\n",
       "                 &#x27;9 days 12:00:00&#x27;,  &#x27;9 days 15:00:00&#x27;,  &#x27;9 days 18:00:00&#x27;,\n",
       "                 &#x27;9 days 21:00:00&#x27;, &#x27;10 days 00:00:00&#x27;],\n",
       "               dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77fc5a13-814e-4b30-b446-cffb07763ddb' class='xr-index-data-in' type='checkbox'/><label for='index-77fc5a13-814e-4b30-b446-cffb07763ddb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-12-29&#x27;, &#x27;2019-12-30&#x27;, &#x27;2019-12-31&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a829982-5454-4ef8-9b1e-bd418b76e50c' class='xr-section-summary-in' type='checkbox'  ><label for='section-1a829982-5454-4ef8-9b1e-bd418b76e50c' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t</dd><dt><span>dataDate :</span></dt><dd>20191229</dd><dt><span>dataTime :</span></dt><dd>0</dd><dt><span>dataType :</span></dt><dd>cf</dd><dt><span>endStep :</span></dt><dd>3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>gridType :</span></dt><dd>regular_ll</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Temperature</dd><dt><span>numberOfPoints :</span></dt><dd>1038240</dd><dt><span>paramId :</span></dt><dd>130</dd><dt><span>shortName :</span></dt><dd>t</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>totalNumber :</span></dt><dd>10</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>units :</span></dt><dd>K</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 't' (time: 3, number: 5, step: 80, latitude: 721,\n",
       "                       longitude: 1440)>\n",
       "[1245888000 values with dtype=float64]\n",
       "Coordinates:\n",
       "  * latitude   (latitude) float64 90.0 89.75 89.5 89.25 ... -89.5 -89.75 -90.0\n",
       "  * longitude  (longitude) float64 -180.0 -179.8 -179.5 ... 179.2 179.5 179.8\n",
       "  * number     (number) int64 0 1 2 3 4\n",
       "  * step       (step) timedelta64[ns] 0 days 03:00:00 ... 10 days 00:00:00\n",
       "  * time       (time) datetime64[ns] 2019-12-29 2019-12-30 2019-12-31\n",
       "Attributes: (12/19)\n",
       "    NV:                         0\n",
       "    cfName:                     air_temperature\n",
       "    cfVarName:                  t\n",
       "    dataDate:                   20191229\n",
       "    dataTime:                   0\n",
       "    dataType:                   cf\n",
       "    ...                         ...\n",
       "    shortName:                  t\n",
       "    stepType:                   instant\n",
       "    stepUnits:                  1\n",
       "    totalNumber:                10\n",
       "    typeOfLevel:                surface\n",
       "    units:                      K"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22a55d75-aa32-4aab-87c9-e6445fcc1169",
   "metadata": {},
   "source": [
    "Use hvplot selection widgets for all extra coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "35eacca2-7695-4724-827c-4a6d8f926e66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "latitude\n",
      "longitude\n",
      "number\n",
      "step\n",
      "time\n"
     ]
    }
   ],
   "source": [
    "for coord in da.indexes:\n",
    "    print(coord)\n",
    "    pn.pane.HoloViews.widgets[coord]=pn.widgets.Select"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "3651935c-c80c-423c-8c14-173b9ac8f0c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.datetime64('2019-12-30T15:00:00.000000000')"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date = '2019-12-30'\n",
    "step = 4\n",
    "valid_time = da.time.sel(time=date).values + da.step.isel(step=step).values\n",
    "valid_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "d97c1c7e-f90a-4d53-bf96-13e3c3e03fc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "datestr = pd.to_datetime(valid_time).strftime('%Y-%m-%d %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "5cee3811-7a53-466d-901f-7ddd85f6db77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 252 ms, sys: 79.8 ms, total: 332 ms\n",
      "Wall time: 669 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "das = da.sel(time=date).isel(step=step).load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "2873e474-7c26-4bd7-942d-f5b70c16d2eb",
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
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