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@rsignell
Created May 22, 2024 19:47
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goes_kerchunk.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Create Kerchunk references for GOES data on AWS S3 \n",
"* create a list of remote NetCDF files on S3\n",
"* create JSON references for each NetCDF file (parallel process, using a remote Dask cluster)\n",
"* create a combined set of references for all the files\n",
"* save the combined set of references in Parquet files\n",
"* push the Parquet files to S3 (here an Open Storage Network pod)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import kerchunk"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"from kerchunk.hdf import SingleHdf5ToZarr\n",
"from kerchunk.combine import MultiZarrToZarr\n",
"from fsspec.implementations.reference import LazyReferenceMapper\n",
"\n",
"import fsspec\n",
"import ujson\n",
"from pathlib import Path\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Convert OSN S3 Credentials in .env file to python environment variables\n",
"from dotenv import load_dotenv\n",
"osn_keys = 'osn_keys.env'\n",
"_ = load_dotenv(osn_keys)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"env_vars = {\"AWS_ACCESS_KEY_ID\":os.environ['AWS_ACCESS_KEY_ID'],\n",
" \"AWS_SECRET_ACCESS_KEY\":os.environ['AWS_SECRET_ACCESS_KEY']}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"osn_endpoint_url = 'https://ncsa.osn.xsede.org'\n",
"json_dir = '/esip/rsignell/testing/goes_jsons'\n",
"combined_parquet = '/esip/rsignell/testing/combined.json'"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"fs_read = fsspec.filesystem('s3', anon=True, skip_instance_cache=True, use_listings_cache=False)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"fs_write = fsspec.filesystem('s3', anon=False, skip_instance_cache=True, use_listings_cache=False,\n",
" client_kwargs={'endpoint_url': osn_endpoint_url})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use fsspec glob to generate a list of files in a certain directory. Goes data is stored in `s3://noaa-goes16/<product>/<year>/<day_of_year>/<hour>/<datafile>.nc` format.\n",
"\n",
"This `glob()` returns all files in the 210th day of 2020 (July 28th, 2020)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['noaa-goes16/ABI-L2-SSTF/2020/210/01/OR_ABI-L2-SSTF-M6_G16_s20202100100205_e20202100159512_c20202100205423.nc']"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fs_read.ls('/noaa-goes16/ABI-L2-SSTF/2020/210/01/')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"flist = fs_read.glob(\"s3://noaa-goes16/ABI-L2-SSTF/2020/210/*/*.nc\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"24\n"
]
}
],
"source": [
"print(len(flist))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'noaa-goes16/ABI-L2-SSTF/2020/210/00/OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.nc'"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flist[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example of creating a single reference"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'noaa-goes16/ABI-L2-SSTF/2020/210/00/OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.nc'"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"u = flist[0]\n",
"u"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 984 ms, sys: 216 ms, total: 1.2 s\n",
"Wall time: 12.7 s\n"
]
}
],
"source": [
"%%time\n",
"with fs_read.open(u) as infile:\n",
" reference = SingleHdf5ToZarr(infile, u, inline_threshold=100).translate()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create references for all 24 files in `flist`"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"## With a Dask cluster\n",
"[Dask](https://dask.org/) is a python package that allows for easily parallelizing python code. "
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"cluster_type = 'Coiled'"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"if cluster_type == 'local':\n",
" from dask.distributed import Client\n",
" client = Client()\n",
" client"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"n_workers = 6"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
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"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Output()"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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"output_type": "display_data"
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{
"name": "stderr",
"output_type": "stream",
"text": [
"Could not get token from client GCP session. This is not a concern unless you're planning to use forwarded GCP credentials on your cluster. The error was: Could not automatically determine credentials. Please set GOOGLE_APPLICATION_CREDENTIALS or explicitly create credentials and re-run the application. For more information, please see https://cloud.google.com/docs/authentication/getting-started\n",
"/home/conda/global/c8f657ec50b664d51b8978abfb095367686f47c54c0dd21ecae5a6571ad23124-20240520-183801-692371-131-pangeo-dev/lib/python3.11/site-packages/distributed/client.py:1393: VersionMismatchWarning: Mismatched versions found\n",
"\n",
"+-------------+----------------+----------------+---------+\n",
"| Package | Client | Scheduler | Workers |\n",
"+-------------+----------------+----------------+---------+\n",
"| dask | 2024.5.1 | 2024.5.0 | None |\n",
"| distributed | 2024.5.1 | 2024.5.0 | None |\n",
"| python | 3.11.0.final.0 | 3.11.9.final.0 | None |\n",
"+-------------+----------------+----------------+---------+\n",
" warnings.warn(version_module.VersionMismatchWarning(msg[0][\"warning\"]))\n"
]
}
],
"source": [
"if cluster_type == 'Coiled':\n",
" import coiled\n",
"\n",
" cluster = coiled.Cluster(\n",
" region='us-east-1',\n",
" name='rechunk',\n",
" compute_purchase_option='spot_with_fallback',\n",
" environ=env_vars,\n",
" wait_for_workers=True,\n",
" n_workers=n_workers,\n",
" software='rechunk',\n",
" workspace='esip-lab'\n",
" )\n",
"\n",
" client = cluster.get_client()"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"## Define function to return a reference dictionary for a given S3 file URL\n",
"\n",
"This function does the following:\n",
"1. `so` is a dictionary of options for `fsspec.open()`\n",
"2. Use `fsspec.open()` to open the file given by URL `f`\n",
"3. Using `kerchunk.SingleHdf5ToZarr()` and supplying the file object `infile` and URL `f`, generate reference with `.translate()`"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"def gen_ref(f):\n",
" with fs_read.open(f) as infile:\n",
" fname = Path(f).stem\n",
" h5chunks = SingleHdf5ToZarr(infile, f, inline_threshold=300)\n",
" outf = f'{json_dir}/{fname}.json'\n",
" with fs_write.open(outf, 'wb') as f:\n",
" f.write(ujson.dumps(h5chunks.translate()).encode());\n",
" return outf"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"### Map `gen_ref` to each member of `flist_bag` and compute\n",
"Dask bag is a way to map a function to a set of inputs. This next couple blocks of code tell Dask to take all the files in `flist`, break them up into the same amount of partitions and map each partition to the `gen_ref()` function -- essentially mapping each file path to `gen_ref()`. Calling `bag.compute()` on this runs `gen_ref()` in parallel with as many workers as are available in Dask client.\n",
"\n",
"_Note: if running interactively on Binder, this will take a while since only one worker is available and the references will have to be generated in serial. See option for loading from jsons below_"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"import dask.bag as db\n",
"bag = db.from_sequence(flist, npartitions=n_workers).map(gen_ref)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"#bag.visualize() "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 317 ms, sys: 103 ms, total: 420 ms\n",
"Wall time: 1min 30s\n"
]
},
{
"data": {
"text/plain": [
"['/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100100205_e20202100159512_c20202100205423.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100200204_e20202100259512_c20202100305437.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100300204_e20202100359512_c20202100405457.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100400204_e20202100459511_c20202100505540.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100500203_e20202100559513_c20202100605464.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100600205_e20202100659513_c20202100705486.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100700205_e20202100759512_c20202100805387.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100800204_e20202100859512_c20202100905438.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202100900204_e20202100959512_c20202101005423.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101000204_e20202101059511_c20202101105541.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101100203_e20202101159511_c20202101205475.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101200203_e20202101259511_c20202101305369.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101300203_e20202101359511_c20202101405450.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101400203_e20202101459511_c20202101505559.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101500203_e20202101559510_c20202101605521.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101600202_e20202101659510_c20202101705463.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101700202_e20202101759507_c20202101805539.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101800199_e20202101859507_c20202101905591.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202101900199_e20202101959506_c20202102005463.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202102000198_e20202102059506_c20202102105409.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202102100198_e20202102159506_c20202102205566.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202102200198_e20202102259505_c20202102305469.json',\n",
" '/esip/rsignell/testing/goes_jsons/OR_ABI-L2-SSTF-M6_G16_s20202102300197_e20202102359505_c20202110005368.json']"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time \n",
"bag.compute(retries=20)"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"### _Save/load references to/from JSON files (optional)_\n",
"The individual dictionaries can be saved as JSON files if desired"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"***\n",
"### Use `MultiZarrToZarr` to combine the individual references into a single reference\n",
"In this example we passed a list of reference dictionaries, but you can also give it a list of `.json` filepaths (commented out)\n",
"\n",
"Please see https://fsspec.github.io/kerchunk/reference.html#kerchunk.combine.MultiZarrToZarr for more details_"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"combined_json = 'combined.json'"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"24\n"
]
}
],
"source": [
"json_list = fs_write.ls(json_dir)\n",
"json_list = [f's3://{j}' for j in json_list] # prepend \"s3://\" to jsons\n",
"print(len(json_list))"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"mzz = MultiZarrToZarr(\n",
" json_list,\n",
" remote_protocol=\"s3\",\n",
" remote_options=dict(anon=True), # NetCDF files on AWS Public Data \n",
" target_options=dict(anon=True, client_kwargs={'endpoint_url': 'https://ncsa.osn.xsede.org'}), # JSON files on OSN\n",
" concat_dims=[\"t\"],\n",
" inline_threshold=300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"References can be saved to a file (`combined.json`) or passed back as a dictionary (`mzz_dict`)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 935 ms, sys: 244 ms, total: 1.18 s\n",
"Wall time: 2.02 s\n"
]
}
],
"source": [
"%%time \n",
"_ = mzz.translate(combined_json) # creates json\n",
"#mzz_dict = mzz.translate() # creates dict\n",
"#mzz_dict"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Upload to Open Storage Network"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[None]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fs_write.upload(combined_json, 's3://esip/rsignell/testing/combined.json')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Write directly to Parquet on OSN"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"combined_parquet = 's3://esip/rsignell/testing/combined.parq'\n",
"out = LazyReferenceMapper.create(combined_parquet, fs=fs_write, record_size=100000)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 2.73 s, sys: 156 ms, total: 2.88 s\n",
"Wall time: 20.5 s\n"
]
}
],
"source": [
"%%time\n",
"_ = MultiZarrToZarr(\n",
" json_list,\n",
" remote_protocol=\"s3\",\n",
" remote_options=dict(anon=True), # NetCDF files on AWS Public Data \n",
" target_options=dict(anon=True, client_kwargs={'endpoint_url': 'https://ncsa.osn.xsede.org'}), # JSON files on OSN\n",
" concat_dims=[\"t\"],\n",
" inline_threshold=300,\n",
" out=out).translate()\n",
"out.flush()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"ds = xr.open_dataset(combined_parquet,\n",
" engine='kerchunk', chunks={},\n",
" backend_kwargs=dict(storage_options=dict(remote_protocol='s3', lazy=True,\n",
" target_options=dict(anon=True, client_kwargs={'endpoint_url': 'https://ncsa.osn.xsede.org'}),\n",
" remote_options=dict(anon=True))))"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8GB\n",
"Dimensions: (t: 24, y: 5424,\n",
" x: 5424,\n",
" SST_day_night_emissive_bands: 4,\n",
" SST_night_only_emissive_band: 1,\n",
" number_of_SZA_bounds: 2,\n",
" number_of_LZA_bounds: 2,\n",
" number_of_time_bounds: 2,\n",
" number_of_image_bounds: 2)\n",
"Coordinates: (12/14)\n",
" SST_day_night_emissive_band_ids (t, SST_day_night_emissive_bands) float32 384B dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;\n",
" SST_day_night_emissive_wavelengths (t, SST_day_night_emissive_bands) float32 384B dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;\n",
" SST_night_only_emissive_band_id (t, SST_night_only_emissive_band) int8 24B dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
" SST_night_only_emissive_wavelength (t, SST_night_only_emissive_band) float32 96B dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
" day_solar_zenith_angle (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" night_solar_zenith_angle (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" ... ...\n",
" retrieval_solar_zenith_angle (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" * t (t) datetime64[ns] 192B ...\n",
" * x (x) float64 43kB ...\n",
" x_image (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" * y (y) float64 43kB ...\n",
" y_image (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
"Dimensions without coordinates: SST_day_night_emissive_bands,\n",
" SST_night_only_emissive_band,\n",
" number_of_SZA_bounds, number_of_LZA_bounds,\n",
" number_of_time_bounds, number_of_image_bounds\n",
"Data variables: (12/42)\n",
" DQF (t, y, x) float32 3GB dask.array&lt;chunksize=(1, 226, 226), meta=np.ndarray&gt;\n",
" SST (t, y, x) float64 6GB dask.array&lt;chunksize=(1, 226, 226), meta=np.ndarray&gt;\n",
" algorithm_dynamic_input_data_container (t) float64 192B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" algorithm_product_version_container (t) float64 192B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" day_solar_zenith_angle_bounds (t, number_of_SZA_bounds) float32 192B dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
" geospatial_lat_lon_extent (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" ... ...\n",
" total_number_of_severely_degraded_quality_ocean_pixels (t) float64 192B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" total_number_of_unprocessed_pixels (t) float64 192B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" twilight_solar_zenith_angle (t) float32 96B dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" twilight_solar_zenith_angle_bounds (t, number_of_SZA_bounds) float32 192B dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
" x_image_bounds (t, number_of_image_bounds) float32 192B dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
" y_image_bounds (t, number_of_image_bounds) float32 192B dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
"Attributes: (12/33)\n",
" Conventions: CF-1.7\n",
" Metadata_Conventions: Unidata Dataset Discovery v1.0\n",
" cdm_data_type: Image\n",
" cell_methods: quantitative_local_zenith_angle: sum retrieval...\n",
" dataset_name: OR_ABI-L2-SSTF-M6_G16_s20202100000205_e2020210...\n",
" date_created: 2020-07-28T01:05:45.6Z\n",
" ... ...\n",
" summary: The ABI Sea Surface Temperature (SST) is calcu...\n",
" time_coverage_end: 2020-07-28T00:59:51.3Z\n",
" time_coverage_start: 2020-07-28T00:00:20.5Z\n",
" timeline_id: ABI Mode 6\n",
" title: ABI L2 Sea Surface (Skin) Temperature\n",
" units: K</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-06f647c1-86aa-48d1-9cc6-3b6ff5e30f97' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-06f647c1-86aa-48d1-9cc6-3b6ff5e30f97' 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'>t</span>: 24</li><li><span class='xr-has-index'>y</span>: 5424</li><li><span class='xr-has-index'>x</span>: 5424</li><li><span>SST_day_night_emissive_bands</span>: 4</li><li><span>SST_night_only_emissive_band</span>: 1</li><li><span>number_of_SZA_bounds</span>: 2</li><li><span>number_of_LZA_bounds</span>: 2</li><li><span>number_of_time_bounds</span>: 2</li><li><span>number_of_image_bounds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-275d7a9b-e75d-4e28-8a45-0d327a051aa8' class='xr-section-summary-in' type='checkbox' checked><label for='section-275d7a9b-e75d-4e28-8a45-0d327a051aa8' class='xr-section-summary' >Coordinates: <span>(14)</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>SST_day_night_emissive_band_ids</span></div><div class='xr-var-dims'>(t, SST_day_night_emissive_bands)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;</div><input id='attrs-57119750-6734-4ac6-ba4f-2a9c14c0c555' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57119750-6734-4ac6-ba4f-2a9c14c0c555' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a955acf1-7e22-4905-b176-a0593fb04754' class='xr-var-data-in' type='checkbox'><label for='data-a955acf1-7e22-4905-b176-a0593fb04754' 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>ABI band identifiers used to generate Sea Surface (Skin) Temperature product (day and night pixels)</dd><dt><span>standard_name :</span></dt><dd>sensor_band_identifier</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST_day_night_emissive_wavelengths</span></div><div class='xr-var-dims'>(t, SST_day_night_emissive_bands)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;</div><input id='attrs-d5425258-c152-4a2f-ac0b-c9a51a2dcfc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5425258-c152-4a2f-ac0b-c9a51a2dcfc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7858c4ea-282f-4ae8-9daf-c5e27e3d7965' class='xr-var-data-in' type='checkbox'><label for='data-7858c4ea-282f-4ae8-9daf-c5e27e3d7965' 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>ABI band central emissive wavelengths used to generate Sea Surface (Skin) Temperature product (day and night pixels)</dd><dt><span>standard_name :</span></dt><dd>sensor_band_central_radiation_wavelength</dd><dt><span>units :</span></dt><dd>um</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
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" <tr>\n",
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" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 384 B </td>\n",
" <td> 16 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 4) </td>\n",
" <td> (1, 4) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST_night_only_emissive_band_id</span></div><div class='xr-var-dims'>(t, SST_night_only_emissive_band)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-4bcfe912-a947-4522-a389-e24b9ae3065c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bcfe912-a947-4522-a389-e24b9ae3065c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc6686f6-b70c-4e05-b266-e30dda4188e6' class='xr-var-data-in' type='checkbox'><label for='data-fc6686f6-b70c-4e05-b266-e30dda4188e6' 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>ABI band identifier used to generate Sea Surface (Skin) Temperature product (night pixels only)</dd><dt><span>standard_name :</span></dt><dd>sensor_band_identifier</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
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" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 24 B </td>\n",
" <td> 1 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 1) </td>\n",
" <td> (1, 1) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> int8 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST_night_only_emissive_wavelength</span></div><div class='xr-var-dims'>(t, SST_night_only_emissive_band)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-a175c387-3cdb-4d67-b656-d0590fc153d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a175c387-3cdb-4d67-b656-d0590fc153d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-943a2258-8abc-4857-ba21-dbb0034f768a' class='xr-var-data-in' type='checkbox'><label for='data-943a2258-8abc-4857-ba21-dbb0034f768a' 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>ABI band central emissive wavelength used to generate Sea Surface (Skin) Temperature product (night pixels only)</dd><dt><span>standard_name :</span></dt><dd>sensor_band_central_radiation_wavelength</dd><dt><span>units :</span></dt><dd>um</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 1) </td>\n",
" <td> (1, 1) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_solar_zenith_angle</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-57ac1386-a83c-4021-bb0d-ea1cdf67efd7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57ac1386-a83c-4021-bb0d-ea1cdf67efd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53bdaf3a-78d7-43e3-ab76-1e8b54349eca' class='xr-var-data-in' type='checkbox'><label for='data-53bdaf3a-78d7-43e3-ab76-1e8b54349eca' 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>bounds :</span></dt><dd>day_solar_zenith_angle_bounds</dd><dt><span>long_name :</span></dt><dd>threshold angle of the day region for the angle between the line of sight to the sun and the local zenith at the observation target</dd><dt><span>standard_name :</span></dt><dd>solar_zenith_angle</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>night_solar_zenith_angle</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-210a3d19-5d0c-4996-8eb7-8c40ea2802c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-210a3d19-5d0c-4996-8eb7-8c40ea2802c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0aaf9b88-cc39-4c8d-9419-25620b883084' class='xr-var-data-in' type='checkbox'><label for='data-0aaf9b88-cc39-4c8d-9419-25620b883084' 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>bounds :</span></dt><dd>night_solar_zenith_angle_bounds</dd><dt><span>long_name :</span></dt><dd>threshold angle of the night region for the angle between the line of sight to the sun and the local zenith at the observation target</dd><dt><span>standard_name :</span></dt><dd>solar_zenith_angle</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
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" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quantitative_local_zenith_angle</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-664e0dc2-b353-466c-8c78-2367c1d07a40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-664e0dc2-b353-466c-8c78-2367c1d07a40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba2d143e-a146-4c4d-a977-aaf8d5fcfa01' class='xr-var-data-in' type='checkbox'><label for='data-ba2d143e-a146-4c4d-a977-aaf8d5fcfa01' 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>bounds :</span></dt><dd>quantitative_local_zenith_angle_bounds</dd><dt><span>long_name :</span></dt><dd>threshold angle between the line of sight to the satellite and the local zenith at the observation target for good quality sea surface (skin) temperature data production</dd><dt><span>standard_name :</span></dt><dd>platform_zenith_angle</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
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" </thead>\n",
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" \n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>retrieval_local_zenith_angle</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-34a8cf8d-3b09-4dbb-b918-cadc9c4fc888' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34a8cf8d-3b09-4dbb-b918-cadc9c4fc888' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55da5207-e551-4874-84ad-3a316665ce58' class='xr-var-data-in' type='checkbox'><label for='data-55da5207-e551-4874-84ad-3a316665ce58' 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>bounds :</span></dt><dd>retrieval_local_zenith_angle_bounds</dd><dt><span>long_name :</span></dt><dd>threshold angle between the line of sight to the satellite and the local zenith at the observation target for good or degraded quality sea surface (skin) temperature data production</dd><dt><span>standard_name :</span></dt><dd>platform_zenith_angle</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><table>\n",
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" &#x27;2020-07-28T22:30:05.200251008&#x27;, &#x27;2020-07-28T23:30:05.159278080&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.1518 -0.1518 ... 0.1518 0.1518</div><input id='attrs-28437034-ac90-4bac-b721-fa846746697d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28437034-ac90-4bac-b721-fa846746697d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39dbe1e8-6798-46ae-bb67-e5e9b28ba058' class='xr-var-data-in' type='checkbox'><label for='data-39dbe1e8-6798-46ae-bb67-e5e9b28ba058' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>GOES fixed grid projection x-coordinate</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>array([-0.151844, -0.151788, -0.151732, ..., 0.151732, 0.151788, 0.151844])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_image</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-2f32a469-9c1a-4cf6-835f-ac496d1638e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f32a469-9c1a-4cf6-835f-ac496d1638e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b3bf6a9-5068-4d20-b4b4-ae59b5af1107' class='xr-var-data-in' type='checkbox'><label for='data-9b3bf6a9-5068-4d20-b4b4-ae59b5af1107' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>GOES-R fixed grid projection x-coordinate center of image</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
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" <td>\n",
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" <td>\n",
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" <th> Array </th>\n",
" <th> Chunk </th>\n",
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" </thead>\n",
" <tbody>\n",
" \n",
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" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
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" \n",
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" <tr>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
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" <tr>\n",
" <td>\n",
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" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 2.63 GiB </td>\n",
" <td> 199.52 kiB </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(t, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 226), meta=np.ndarray&gt;</div><input id='attrs-a7590fc8-7ea8-4efc-a35d-235db5b50e35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7590fc8-7ea8-4efc-a35d-235db5b50e35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56fd7450-fbe0-4e1b-910a-94b3698c6ee5' class='xr-var-data-in' type='checkbox'><label for='data-56fd7450-fbe0-4e1b-910a-94b3698c6ee5' 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>algorithm_type :</span></dt><dd>regression</dd><dt><span>ancillary_variables :</span></dt><dd>DQF</dd><dt><span>cell_methods :</span></dt><dd>retrieval_local_zenith_angle: point (good or degraded quality pixel produced) quantitative_local_zenith_angle: point (good quality pixel produced) retrieval_solar_zenith_angle: point (good quality pixel produced) t: point area: point</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>ABI L2+ Sea Surface (Skin) Temperature</dd><dt><span>resolution :</span></dt><dd>y: 0.000056 rad x: 0.000056 rad</dd><dt><span>standard_name :</span></dt><dd>sea_surface_skin_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>valid_range :</span></dt><dd>[0, -6]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
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" <th> Array </th>\n",
" <th> Chunk </th>\n",
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" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 5.26 GiB </td>\n",
" <td> 399.03 kiB </td>\n",
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" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 5424, 5424) </td>\n",
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" <td colspan=\"2\"> 13824 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>algorithm_product_version_container</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-8cfc2c95-d1f3-4438-ac74-26c67b61ebf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cfc2c95-d1f3-4438-ac74-26c67b61ebf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1202fb4c-b0fc-496e-9b89-73c926f7948f' class='xr-var-data-in' type='checkbox'><label for='data-1202fb4c-b0fc-496e-9b89-73c926f7948f' 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>algorithm_version :</span></dt><dd>OR_ABI-L2-ALG-SST_v01r00.zip</dd><dt><span>long_name :</span></dt><dd>container for algorithm package filename and product version</dd><dt><span>product_version :</span></dt><dd>v01r00</dd></dl></div><div class='xr-var-data'><table>\n",
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" \n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_solar_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_SZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-f4cfc9a6-1260-4fa0-9cc9-fcc338ea20df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4cfc9a6-1260-4fa0-9cc9-fcc338ea20df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9292c440-3bf1-494c-83a0-d8a7d48b1689' class='xr-var-data-in' type='checkbox'><label for='data-9292c440-3bf1-494c-83a0-d8a7d48b1689' 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>solar zenith angle degree range for the day region</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
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" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" \n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geospatial_lat_lon_extent</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-612d0cb1-c6a2-4254-accf-e44032d90749' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-612d0cb1-c6a2-4254-accf-e44032d90749' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fa7a37a-3ec8-490f-9552-0b3d63fee0d2' class='xr-var-data-in' type='checkbox'><label for='data-4fa7a37a-3ec8-490f-9552-0b3d63fee0d2' 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>geospatial_eastbound_longitude :</span></dt><dd>6.299499988555908</dd><dt><span>geospatial_lat_center :</span></dt><dd>0.0</dd><dt><span>geospatial_lat_nadir :</span></dt><dd>0.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_center :</span></dt><dd>-75.0</dd><dt><span>geospatial_lon_nadir :</span></dt><dd>-75.0</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_northbound_latitude :</span></dt><dd>81.32820129394531</dd><dt><span>geospatial_southbound_latitude :</span></dt><dd>-81.32820129394531</dd><dt><span>geospatial_westbound_longitude :</span></dt><dd>-156.29949951171875</dd><dt><span>long_name :</span></dt><dd>geospatial latitude and longitude references</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
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" <th> Chunk </th>\n",
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" </thead>\n",
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" \n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>goes_imager_projection</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-30704a8e-eab9-4888-94b6-0b90ba4e0e0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30704a8e-eab9-4888-94b6-0b90ba4e0e0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d07cdb4b-c45b-4177-8940-27b9ecd64d7f' class='xr-var-data-in' type='checkbox'><label for='data-d07cdb4b-c45b-4177-8940-27b9ecd64d7f' 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>grid_mapping_name :</span></dt><dd>geostationary</dd><dt><span>inverse_flattening :</span></dt><dd>298.2572221</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>GOES-R ABI fixed grid projection</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-75.0</dd><dt><span>perspective_point_height :</span></dt><dd>35786023.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.31414</dd><dt><span>sweep_angle_axis :</span></dt><dd>x</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" <td> 8 B </td>\n",
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" \n",
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" <th> Shape </th>\n",
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" <tr>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_obs_modeled_diff_SST_night_only_emissive_band</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-0236ec10-10f9-4492-abd2-7214719a1a6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0236ec10-10f9-4492-abd2-7214719a1a6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b4a4b7b-4518-4392-9ccd-d5683cc5a4cb' class='xr-var-data-in' type='checkbox'><label for='data-0b4a4b7b-4518-4392-9ccd-d5683cc5a4cb' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>maximum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
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" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
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" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_retrieved_Reynolds_SST_diff</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-cb48cbc0-f6d9-49dd-8e57-cb821047a329' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb48cbc0-f6d9-49dd-8e57-cb821047a329' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98d21b39-acc5-4729-bdb5-9f865bf95acc' class='xr-var-data-in' type='checkbox'><label for='data-98d21b39-acc5-4729-bdb5-9f865bf95acc' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>maximum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </tbody>\n",
" </table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maximum_sea_surface_temp</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-bcf54c98-66d1-459c-8a57-80cb5805c07c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcf54c98-66d1-459c-8a57-80cb5805c07c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b7ed675-91f9-4f78-b204-3b660c783ef9' class='xr-var-data-in' type='checkbox'><label for='data-8b7ed675-91f9-4f78-b204-3b660c783ef9' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>maximum sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>valid_range :</span></dt><dd>[180.0, 340.0]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
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" \n",
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" <td> (24,) </td>\n",
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" <tr>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
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" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_obs_modeled_diff_SST_night_only_emissive_band</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-548d7f9e-f8f5-48b6-84e0-127f55f19a7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-548d7f9e-f8f5-48b6-84e0-127f55f19a7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9d0e770-7e28-4ca5-adc3-c9e9e9b41bba' class='xr-var-data-in' type='checkbox'><label for='data-c9d0e770-7e28-4ca5-adc3-c9e9e9b41bba' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>mean difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
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" \n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_retrieved_Reynolds_SST_diff</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-985bb2c9-5b04-414b-a9f0-b8121d8f24a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-985bb2c9-5b04-414b-a9f0-b8121d8f24a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-522df316-ef88-4140-bd3d-95667da3ecfc' class='xr-var-data-in' type='checkbox'><label for='data-522df316-ef88-4140-bd3d-95667da3ecfc' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>mean difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
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" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_sea_surface_temp</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-6fe06640-7fd7-4395-b839-4cb8cf26162e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fe06640-7fd7-4395-b839-4cb8cf26162e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7d3ee6e-9ee8-474b-8d38-e692e9558866' class='xr-var-data-in' type='checkbox'><label for='data-e7d3ee6e-9ee8-474b-8d38-e692e9558866' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>mean sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>valid_range :</span></dt><dd>[180.0, 340.0]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
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" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_obs_modeled_diff_SST_night_only_emissive_band</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-6818091a-108c-484f-8901-0358a9d5abaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6818091a-108c-484f-8901-0358a9d5abaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-581a8e90-8aa6-4730-9446-94df554f5b13' class='xr-var-data-in' type='checkbox'><label for='data-581a8e90-8aa6-4730-9446-94df554f5b13' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>minimum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
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" <tbody>\n",
" \n",
" <tr>\n",
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" <td> 96 B </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_retrieved_Reynolds_SST_diff</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-c9d1b78e-37b2-4813-ac2a-8cf3eb51ca08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9d1b78e-37b2-4813-ac2a-8cf3eb51ca08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23e146f2-c0a4-4200-b65b-2da951030a13' class='xr-var-data-in' type='checkbox'><label for='data-23e146f2-c0a4-4200-b65b-2da951030a13' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>minimum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>minimum_sea_surface_temp</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-b0e5c88a-f1be-4370-81f2-3cb622b13e1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0e5c88a-f1be-4370-81f2-3cb622b13e1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21d9ed98-3797-4194-bf03-ef1e887d0e7d' class='xr-var-data-in' type='checkbox'><label for='data-21d9ed98-3797-4194-bf03-ef1e887d0e7d' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>minimum sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>valid_range :</span></dt><dd>[180.0, 340.0]</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>night_solar_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_SZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-5d7f425e-8aba-4eeb-affe-0210742bb4f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d7f425e-8aba-4eeb-affe-0210742bb4f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64810b53-eda9-435a-9110-af005cf01796' class='xr-var-data-in' type='checkbox'><label for='data-64810b53-eda9-435a-9110-af005cf01796' 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>solar zenith angle degree range for the night region</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nominal_satellite_height</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-8d45a79f-f298-4cff-99fe-1c9169715b97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d45a79f-f298-4cff-99fe-1c9169715b97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1f5152b-a516-4e78-908c-1e8452691ab8' class='xr-var-data-in' type='checkbox'><label for='data-a1f5152b-a516-4e78-908c-1e8452691ab8' 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>nominal satellite height above GRS 80 ellipsoid (platform altitude)</dd><dt><span>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>units :</span></dt><dd>km</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
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" </thead>\n",
" <tbody>\n",
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" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
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" \n",
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" <th> Shape </th>\n",
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" <td> (1,) </td>\n",
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" <tr>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nominal_satellite_subpoint_lat</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-466d2d03-04f2-4f0c-aee7-eb4f9bcc2f36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-466d2d03-04f2-4f0c-aee7-eb4f9bcc2f36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9414953-5039-4e24-a60b-5f377bf6363e' class='xr-var-data-in' type='checkbox'><label for='data-f9414953-5039-4e24-a60b-5f377bf6363e' 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>nominal satellite subpoint latitude (platform 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'><table>\n",
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" <td> 96 B </td>\n",
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" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
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" <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"33\" />\n",
" <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"33\" />\n",
" <line x1=\"85\" y1=\"0\" x2=\"85\" y2=\"33\" />\n",
" <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"33\" />\n",
" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"33\" />\n",
" <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"33\" />\n",
" <line x1=\"110\" y1=\"0\" x2=\"110\" y2=\"33\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
"\n",
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" <polygon points=\"0.0,0.0 120.0,0.0 120.0,33.38369844152673 0.0,33.38369844152673\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
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" <text x=\"60.000000\" y=\"53.383698\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >24</text>\n",
" <text x=\"140.000000\" y=\"16.691849\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,16.691849)\">1</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nominal_satellite_subpoint_lon</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-d076a543-6eed-4d83-90af-19e0ed8568f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d076a543-6eed-4d83-90af-19e0ed8568f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8931c985-b5ee-462d-99ed-da4fca5391cd' class='xr-var-data-in' type='checkbox'><label for='data-8931c985-b5ee-462d-99ed-da4fca5391cd' 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>nominal satellite subpoint longitude (platform 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'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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"\n",
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" <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"33\" />\n",
" <line x1=\"110\" y1=\"0\" x2=\"110\" y2=\"33\" />\n",
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"\n",
" <!-- Colored Rectangle -->\n",
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"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"53.383698\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >24</text>\n",
" <text x=\"140.000000\" y=\"16.691849\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,16.691849)\">1</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>number_of_day_SST_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-4f91c4bd-fc57-4f12-954f-e828fa4cf23f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f91c4bd-fc57-4f12-954f-e828fa4cf23f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f26bbbfc-4fb2-4b9e-8a90-d63afa639fdd' class='xr-var-data-in' type='checkbox'><label for='data-f26bbbfc-4fb2-4b9e-8a90-d63afa639fdd' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum day_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of day sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"33\" style=\"stroke-width:2\" />\n",
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" <line x1=\"85\" y1=\"0\" x2=\"85\" y2=\"33\" />\n",
" <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"33\" />\n",
" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"33\" />\n",
" <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"33\" />\n",
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" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
"\n",
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" <polygon points=\"0.0,0.0 120.0,0.0 120.0,33.38369844152673 0.0,33.38369844152673\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"53.383698\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >24</text>\n",
" <text x=\"140.000000\" y=\"16.691849\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,16.691849)\">1</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>number_of_night_SST_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-10ddce40-311e-45a9-9f84-316da0433b64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10ddce40-311e-45a9-9f84-316da0433b64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0010091b-3636-4208-94ba-428e62c93bc5' class='xr-var-data-in' type='checkbox'><label for='data-0010091b-3636-4208-94ba-428e62c93bc5' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of night sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"33\" style=\"stroke-width:2\" />\n",
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" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"33\" />\n",
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" <line x1=\"110\" y1=\"0\" x2=\"110\" y2=\"33\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
"\n",
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"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"53.383698\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >24</text>\n",
" <text x=\"140.000000\" y=\"16.691849\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,16.691849)\">1</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>number_of_twilight_SST_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-8f7a5796-3db7-4ac2-8d7b-cc1297f431ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f7a5796-3db7-4ac2-8d7b-cc1297f431ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af17711-b694-4a29-b30d-c434ba088af6' class='xr-var-data-in' type='checkbox'><label for='data-8af17711-b694-4a29-b30d-c434ba088af6' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum twilight_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of twilight sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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"\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>percent_uncorrectable_GRB_errors</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-f76ffdbb-414b-4b3f-aa8b-09a39c8050ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f76ffdbb-414b-4b3f-aa8b-09a39c8050ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-882dbd70-9dbf-47bf-9e8a-5de15187db60' class='xr-var-data-in' type='checkbox'><label for='data-882dbd70-9dbf-47bf-9e8a-5de15187db60' 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>cell_methods :</span></dt><dd>t: sum area: sum (uncorrectable GRB errors only)</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>percent data lost due to uncorrectable GRB errors</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>percent_uncorrectable_L0_errors</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-81c824d7-7d76-4caf-bb97-ec4a3028fae6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81c824d7-7d76-4caf-bb97-ec4a3028fae6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dc044dd-cf91-4529-8a9f-e1e6b9fa525b' class='xr-var-data-in' type='checkbox'><label for='data-6dc044dd-cf91-4529-8a9f-e1e6b9fa525b' 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>cell_methods :</span></dt><dd>t: sum area: sum (uncorrectable L0 errors only)</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>percent data lost due to uncorrectable L0 errors</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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"\n",
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" <text x=\"60.000000\" y=\"53.383698\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >24</text>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>processing_parm_version_container</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-0fe32455-136f-46ba-b4d2-19b1fd40e3c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fe32455-136f-46ba-b4d2-19b1fd40e3c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d622384e-dc33-4656-b9df-9c3a8be6a6ec' class='xr-var-data-in' type='checkbox'><label for='data-d622384e-dc33-4656-b9df-9c3a8be6a6ec' 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>L2_processing_parm_version :</span></dt><dd>OR-PARM-SST_v01r00.zip, OR-PARM-SEMISTATIC_v01r00.zip, OR-PARM-ANCILLARY_v01r00.zip, OR-PARM-AUXILIARY_v01r00.zip, OR-PARM-TARP_v01r00.zip</dd><dt><span>long_name :</span></dt><dd>container for processing parameter filenames</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"83\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" style=\"stroke-width:2\" />\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quantitative_local_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_LZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-3586cc23-c092-41e3-9d07-c7948a1cc6b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3586cc23-c092-41e3-9d07-c7948a1cc6b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0dd97f9-0f96-4d7c-9753-a4af2b4854ca' class='xr-var-data-in' type='checkbox'><label for='data-c0dd97f9-0f96-4d7c-9753-a4af2b4854ca' 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>local zenith angle degree range where good quality sea surface (skin) temperature data is produced</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 2) </td>\n",
" <td> (1, 2) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
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"\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>retrieval_local_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_LZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-705fd163-86b5-44a3-88ec-a5c887d21122' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-705fd163-86b5-44a3-88ec-a5c887d21122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44dfe7b8-2b41-4b3d-b85c-c9bdc55a9dd3' class='xr-var-data-in' type='checkbox'><label for='data-44dfe7b8-2b41-4b3d-b85c-c9bdc55a9dd3' 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>local zenith angle degree range where good or degraded quality sea surface (skin) temperature data is produced</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
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" \n",
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" <td> (1, 2) </td>\n",
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" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>retrieval_solar_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_SZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-c1dd6b4f-058e-42f6-8e94-8ff9448418cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1dd6b4f-058e-42f6-8e94-8ff9448418cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92426421-4237-406b-8976-b123bf3a29af' class='xr-var-data-in' type='checkbox'><label for='data-92426421-4237-406b-8976-b123bf3a29af' 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>solar zenith angle degree range where good quality sea surface (skin) temperature data is produced</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 2) </td>\n",
" <td> (1, 2) </td>\n",
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" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_surface_temp_outlier_pixel_count</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-3192c4c2-a35a-4316-9317-41f553cb7b45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3192c4c2-a35a-4316-9317-41f553cb7b45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1440820-8151-4eb1-9ed0-b3de9ce64802' class='xr-var-data-in' type='checkbox'><label for='data-f1440820-8151-4eb1-9ed0-b3de9ce64802' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels whose values are outside valid measurement range only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of sea surface temperature pixels whose value is outside valid measurement range</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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" </tbody>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>standard_deviation_sea_surface_temp</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-2594a672-920b-439e-85f7-748df1c96f6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2594a672-920b-439e-85f7-748df1c96f6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14fc6eb5-f69c-400c-a936-de786886eb05' class='xr-var-data-in' type='checkbox'><label for='data-14fc6eb5-f69c-400c-a936-de786886eb05' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>standard deviation of sea surface temperature values</dd><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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"\n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>std_dev_obs_modeled_diff_SST_night_only_emissive_band</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-0263b3d0-34b0-4e74-88fe-ecff4ce86002' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0263b3d0-34b0-4e74-88fe-ecff4ce86002' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f4898a-d75b-4414-9c8c-81ae9b536008' class='xr-var-data-in' type='checkbox'><label for='data-b3f4898a-d75b-4414-9c8c-81ae9b536008' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the night only emissive band central wavelength used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>std_dev_retrieved_Reynolds_SST_diff</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-b71510b7-7f50-481d-b5c6-4cf78007a1f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b71510b7-7f50-481d-b5c6-4cf78007a1f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba4999bf-d757-4e31-9a82-4421d982df0b' class='xr-var-data-in' type='checkbox'><label for='data-ba4999bf-d757-4e31-9a82-4421d982df0b' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>standard_deviation of the difference of the retrieved SST and Reynolds real-time global SST analysis values used in the generation of the sea surface temperature product</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(t, number_of_time_bounds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-87c3c590-036d-44ce-87af-70683884c36e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87c3c590-036d-44ce-87af-70683884c36e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0926f3ad-4e33-4b74-92b1-e277b7acaac3' class='xr-var-data-in' type='checkbox'><label for='data-0926f3ad-4e33-4b74-92b1-e277b7acaac3' 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>Scan start and end times in seconds since epoch (2000-01-01 12:00:00)</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 384 B </td>\n",
" <td> 16 B </td>\n",
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" \n",
" <tr>\n",
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" <td> (1, 2) </td>\n",
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" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_number_of_degraded_quality_ocean_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-ab13b7af-11ca-4cdf-b9f6-f036ca416617' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab13b7af-11ca-4cdf-b9f6-f036ca416617' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78f84b81-fbcd-46ae-8f3e-1ce549a6eff5' class='xr-var-data-in' type='checkbox'><label for='data-78f84b81-fbcd-46ae-8f3e-1ce549a6eff5' 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>cell_methods :</span></dt><dd>retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: degraded quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of degraded quality sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
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" \n",
" <tr>\n",
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" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_number_of_good_quality_ocean_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-a827c563-5e33-47a1-a444-b27dced7a051' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a827c563-5e33-47a1-a444-b27dced7a051' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc851807-911f-4ecc-be7a-c0b05a5264d2' class='xr-var-data-in' type='checkbox'><label for='data-cc851807-911f-4ecc-be7a-c0b05a5264d2' 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>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of good quality sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tbody>\n",
" \n",
" <tr>\n",
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" <td> 192 B </td>\n",
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" <tr>\n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_number_of_severely_degraded_quality_ocean_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-b89411e8-7a10-4387-aa15-d08bdf05a2a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b89411e8-7a10-4387-aa15-d08bdf05a2a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4ff8270-1196-4215-b663-b692a1154c1e' class='xr-var-data-in' type='checkbox'><label for='data-a4ff8270-1196-4215-b663-b692a1154c1e' 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>cell_methods :</span></dt><dd>retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: severely degraded quality pixels only) where sea</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of severely degraded quality sea surface temperature pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
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" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_number_of_unprocessed_pixels</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-b5c18d24-2cae-469d-bb84-df32571b7816' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5c18d24-2cae-469d-bb84-df32571b7816' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-540f61b7-5b7b-4b73-a476-3c037c53879a' class='xr-var-data-in' type='checkbox'><label for='data-540f61b7-5b7b-4b73-a476-3c037c53879a' 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>cell_methods :</span></dt><dd>retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: invalid due to unprocessed pixels only)</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>long_name :</span></dt><dd>number of unprocessed pixels</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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" </tbody>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>twilight_solar_zenith_angle</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-5d73a43e-88f2-4497-a38a-2dd955530b23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d73a43e-88f2-4497-a38a-2dd955530b23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0113119a-7ddd-465e-96db-cc6395b23a27' class='xr-var-data-in' type='checkbox'><label for='data-0113119a-7ddd-465e-96db-cc6395b23a27' 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>bounds :</span></dt><dd>twilight_solar_zenith_angle_bounds</dd><dt><span>long_name :</span></dt><dd>midpoint of the twilight region for the angle between the line of sight to the sun and the local zenith at the observation target</dd><dt><span>standard_name :</span></dt><dd>solar_zenith_angle</dd><dt><span>units :</span></dt><dd>degree</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 96 B </td>\n",
" <td> 4 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24,) </td>\n",
" <td> (1,) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>twilight_solar_zenith_angle_bounds</span></div><div class='xr-var-dims'>(t, number_of_SZA_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-59828fed-1d66-42a4-a90d-018fb923ca2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59828fed-1d66-42a4-a90d-018fb923ca2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c5c4095-f8ad-44a9-b12a-3fd33b162212' class='xr-var-data-in' type='checkbox'><label for='data-5c5c4095-f8ad-44a9-b12a-3fd33b162212' 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>solar zenith angle degree range for the twilight region</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
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" \n",
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" <th> Shape </th>\n",
" <td> (24, 2) </td>\n",
" <td> (1, 2) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_image_bounds</span></div><div class='xr-var-dims'>(t, number_of_image_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-d7544cff-7114-4e5c-9429-c424ae0211c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7544cff-7114-4e5c-9429-c424ae0211c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-616482ba-6891-4a43-a0b9-6537bd63fe5f' class='xr-var-data-in' type='checkbox'><label for='data-616482ba-6891-4a43-a0b9-6537bd63fe5f' 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>GOES-R fixed grid projection x-coordinate west/east extent of image</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 192 B </td>\n",
" <td> 8 B </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (24, 2) </td>\n",
" <td> (1, 2) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
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" <td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_image_bounds</span></div><div class='xr-var-dims'>(t, number_of_image_bounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-42d27551-132a-48c3-9012-6878ff6b2ec3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42d27551-132a-48c3-9012-6878ff6b2ec3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee2b96d3-1d24-49db-8848-aefee3a281d1' class='xr-var-data-in' type='checkbox'><label for='data-ee2b96d3-1d24-49db-8848-aefee3a281d1' 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>GOES-R fixed grid projection y-coordinate north/south extent of image</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
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" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 24 chunks in 2 graph layers </td>\n",
" </tr>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e6475da-ffba-49e7-9906-dddddee42871' class='xr-section-summary-in' type='checkbox' ><label for='section-6e6475da-ffba-49e7-9906-dddddee42871' class='xr-section-summary' >Indexes: <span>(3)</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>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-27f6a47d-0068-4afb-a85b-a16b4808e6bd' class='xr-index-data-in' type='checkbox'/><label for='index-27f6a47d-0068-4afb-a85b-a16b4808e6bd' 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;2020-07-28 00:30:05.934142976&#x27;,\n",
" &#x27;2020-07-28 01:30:05.901723008&#x27;,\n",
" &#x27;2020-07-28 02:30:05.864743936&#x27;,\n",
" &#x27;2020-07-28 03:30:05.828807936&#x27;,\n",
" &#x27;2020-07-28 04:30:05.789944960&#x27;,\n",
" &#x27;2020-07-28 05:30:05.866763904&#x27;,\n",
" &#x27;2020-07-28 06:30:05.943120&#x27;,\n",
" &#x27;2020-07-28 07:30:05.902876032&#x27;,\n",
" &#x27;2020-07-28 08:30:05.866008960&#x27;,\n",
" &#x27;2020-07-28 09:30:05.823889024&#x27;,\n",
" &#x27;2020-07-28 10:30:05.785832960&#x27;,\n",
" &#x27;2020-07-28 11:30:05.747997056&#x27;,\n",
" &#x27;2020-07-28 12:30:05.725508992&#x27;,\n",
" &#x27;2020-07-28 13:30:05.716819072&#x27;,\n",
" &#x27;2020-07-28 14:30:05.711737088&#x27;,\n",
" &#x27;2020-07-28 15:30:05.688460928&#x27;,\n",
" &#x27;2020-07-28 16:30:05.651743104&#x27;,\n",
" &#x27;2020-07-28 17:30:05.499197056&#x27;,\n",
" &#x27;2020-07-28 18:30:05.346963968&#x27;,\n",
" &#x27;2020-07-28 19:30:05.309723008&#x27;,\n",
" &#x27;2020-07-28 20:30:05.273282944&#x27;,\n",
" &#x27;2020-07-28 21:30:05.235561984&#x27;,\n",
" &#x27;2020-07-28 22:30:05.200251008&#x27;,\n",
" &#x27;2020-07-28 23:30:05.159278080&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6118fce0-9fe7-441c-9ee8-82d6157bb756' class='xr-index-data-in' type='checkbox'/><label for='index-6118fce0-9fe7-441c-9ee8-82d6157bb756' 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(Index([-0.15184399485588074, -0.15178799485511263, -0.15173199485434452,\n",
" -0.1516759948535764, -0.1516199948528083, -0.1515639948520402,\n",
" -0.1515079948512721, -0.15145199485050398, -0.15139599484973587,\n",
" -0.15133999484896776,\n",
" ...\n",
" 0.15134000930265756, 0.15139600930342567, 0.15145200930419378,\n",
" 0.1515080093049619, 0.15156400930573, 0.1516200093064981,\n",
" 0.1516760093072662, 0.15173200930803432, 0.15178800930880243,\n",
" 0.15184400930957054],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=5424))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5d02a701-c220-4867-8aa8-242cfdfbcf75' class='xr-index-data-in' type='checkbox'/><label for='index-5d02a701-c220-4867-8aa8-242cfdfbcf75' 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(Index([ 0.15184399485588074, 0.15178799485511263, 0.15173199485434452,\n",
" 0.1516759948535764, 0.1516199948528083, 0.1515639948520402,\n",
" 0.1515079948512721, 0.15145199485050398, 0.15139599484973587,\n",
" 0.15133999484896776,\n",
" ...\n",
" -0.15134000930265756, -0.15139600930342567, -0.15145200930419378,\n",
" -0.1515080093049619, -0.15156400930573, -0.1516200093064981,\n",
" -0.1516760093072662, -0.15173200930803432, -0.15178800930880243,\n",
" -0.15184400930957054],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=5424))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1c02fbc5-2c85-4d81-b31e-b8415b27c293' class='xr-section-summary-in' type='checkbox' ><label for='section-1c02fbc5-2c85-4d81-b31e-b8415b27c293' class='xr-section-summary' >Attributes: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>cdm_data_type :</span></dt><dd>Image</dd><dt><span>cell_methods :</span></dt><dd>quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea</dd><dt><span>dataset_name :</span></dt><dd>OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.nc</dd><dt><span>date_created :</span></dt><dd>2020-07-28T01:05:45.6Z</dd><dt><span>grid_mapping :</span></dt><dd>goes_imager_projection</dd><dt><span>id :</span></dt><dd>14a121c9-41b8-4552-9c28-69e6bcd4952f</dd><dt><span>institution :</span></dt><dd>DOC/NOAA/NESDIS &gt; U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Services</dd><dt><span>instrument_ID :</span></dt><dd>FM1</dd><dt><span>instrument_type :</span></dt><dd>GOES R Series Advanced Baseline Imager</dd><dt><span>iso_series_metadata_id :</span></dt><dd>d70be540-c38a-11e0-962b-0800200c9a66</dd><dt><span>keywords :</span></dt><dd>OCEANS &gt; OCEAN TEMPERATURE &gt; SEA SURFACE TEMPERATURE</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 7.0.0.0.0</dd><dt><span>license :</span></dt><dd>Unclassified data. Access is restricted to approved users only.</dd><dt><span>long_name :</span></dt><dd>standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the day and night emissive band central wavelengths used in the generation of the sea surface temperature product</dd><dt><span>naming_authority :</span></dt><dd>gov.nesdis.noaa</dd><dt><span>orbital_slot :</span></dt><dd>GOES-East</dd><dt><span>platform_ID :</span></dt><dd>G16</dd><dt><span>processing_level :</span></dt><dd>National Aeronautics and Space Administration (NASA) L2</dd><dt><span>production_data_source :</span></dt><dd>Realtime</dd><dt><span>production_environment :</span></dt><dd>OE</dd><dt><span>production_site :</span></dt><dd>NSOF</dd><dt><span>project :</span></dt><dd>GOES</dd><dt><span>scene_id :</span></dt><dd>Full Disk</dd><dt><span>spatial_resolution :</span></dt><dd>2km at nadir</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (v35, 20 July 2016)</dd><dt><span>summary :</span></dt><dd>The ABI Sea Surface Temperature (SST) is calculated using a 4-band (8.44, 10.33, 11.19, and 12.27 um) non-linear SST (NLSST) regression equation with coefficients calculated using match-ups with in situ SSTs from drifting and tropical moored buoys. Hence on average, ABI SST is close to in situ (bulk) SST, but its spatial and temporal variations are representative of skin SST (to which ABI BTs are sensitive). One regression equation, and one set of regression coefficients are used across day and night, resulting in consistent and continuous SST diurnal cycle. Note that SST is reported over all water pixels, and only data with quality flag DQF=0 should be used to select clear-sky pixels.</dd><dt><span>time_coverage_end :</span></dt><dd>2020-07-28T00:59:51.3Z</dd><dt><span>time_coverage_start :</span></dt><dd>2020-07-28T00:00:20.5Z</dd><dt><span>timeline_id :</span></dt><dd>ABI Mode 6</dd><dt><span>title :</span></dt><dd>ABI L2 Sea Surface (Skin) Temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 8GB\n",
"Dimensions: (t: 24, y: 5424,\n",
" x: 5424,\n",
" SST_day_night_emissive_bands: 4,\n",
" SST_night_only_emissive_band: 1,\n",
" number_of_SZA_bounds: 2,\n",
" number_of_LZA_bounds: 2,\n",
" number_of_time_bounds: 2,\n",
" number_of_image_bounds: 2)\n",
"Coordinates: (12/14)\n",
" SST_day_night_emissive_band_ids (t, SST_day_night_emissive_bands) float32 384B dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
" SST_day_night_emissive_wavelengths (t, SST_day_night_emissive_bands) float32 384B dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
" SST_night_only_emissive_band_id (t, SST_night_only_emissive_band) int8 24B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
" SST_night_only_emissive_wavelength (t, SST_night_only_emissive_band) float32 96B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
" day_solar_zenith_angle (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" night_solar_zenith_angle (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" ... ...\n",
" retrieval_solar_zenith_angle (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" * t (t) datetime64[ns] 192B ...\n",
" * x (x) float64 43kB ...\n",
" x_image (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" * y (y) float64 43kB ...\n",
" y_image (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
"Dimensions without coordinates: SST_day_night_emissive_bands,\n",
" SST_night_only_emissive_band,\n",
" number_of_SZA_bounds, number_of_LZA_bounds,\n",
" number_of_time_bounds, number_of_image_bounds\n",
"Data variables: (12/42)\n",
" DQF (t, y, x) float32 3GB dask.array<chunksize=(1, 226, 226), meta=np.ndarray>\n",
" SST (t, y, x) float64 6GB dask.array<chunksize=(1, 226, 226), meta=np.ndarray>\n",
" algorithm_dynamic_input_data_container (t) float64 192B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" algorithm_product_version_container (t) float64 192B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" day_solar_zenith_angle_bounds (t, number_of_SZA_bounds) float32 192B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
" geospatial_lat_lon_extent (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" ... ...\n",
" total_number_of_severely_degraded_quality_ocean_pixels (t) float64 192B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" total_number_of_unprocessed_pixels (t) float64 192B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" twilight_solar_zenith_angle (t) float32 96B dask.array<chunksize=(1,), meta=np.ndarray>\n",
" twilight_solar_zenith_angle_bounds (t, number_of_SZA_bounds) float32 192B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
" x_image_bounds (t, number_of_image_bounds) float32 192B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
" y_image_bounds (t, number_of_image_bounds) float32 192B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
"Attributes: (12/33)\n",
" Conventions: CF-1.7\n",
" Metadata_Conventions: Unidata Dataset Discovery v1.0\n",
" cdm_data_type: Image\n",
" cell_methods: quantitative_local_zenith_angle: sum retrieval...\n",
" dataset_name: OR_ABI-L2-SSTF-M6_G16_s20202100000205_e2020210...\n",
" date_created: 2020-07-28T01:05:45.6Z\n",
" ... ...\n",
" summary: The ABI Sea Surface Temperature (SST) is calcu...\n",
" time_coverage_end: 2020-07-28T00:59:51.3Z\n",
" time_coverage_start: 2020-07-28T00:00:20.5Z\n",
" timeline_id: ABI Mode 6\n",
" title: ABI L2 Sea Surface (Skin) Temperature\n",
" units: K"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds"
]
}
],
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