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September 9, 2020 09:44
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Load Himawari-8 infrared imagery from NCI
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| "execution_count": 1, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "# Setup tools is now broken\n", | |
| "# See here: https://github.com/mozilla/DeepSpeech/issues/3295\n", | |
| "#!pip install --upgrade pip==20.0.2 wheel==0.34.2 setuptools==49.6.0\n", | |
| "#!pip install --user --force pandas h5netcdf netcdf4 zarr xarray s3fs\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import xarray as xr\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "import numpy as np\n", | |
| "import pandas as pd\n", | |
| "from pyproj import Proj\n", | |
| "\n", | |
| "from s3fs import S3FileSystem, S3Map" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "plt.rcParams['font.size']=14\n", | |
| "plt.rcParams['axes.labelsize']='large'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "\n", | |
| "\n", | |
| "def get_hw8_ncistr(band, yyyy, mm, dd, hhmm):\n", | |
| " ncipath = 'http://dapds00.nci.org.au/thredds/dodsC/rr5/satellite/obs/himawari8/FLDK/'\n", | |
| " hstr = '00-P1S-ABOM_OBS_B{}-PRJ_GEOS141_2000-HIMAWARI8-AHI.nc'.format(band)\n", | |
| "\n", | |
| " timestr = '{}/{}/{}/{}/{}{}{}{}{}'.format(yyyy,mm,dd,hhmm,yyyy,mm,dd,hhmm,hstr)\n", | |
| " fullurl = '{}{}'.format(ncipath,timestr)\n", | |
| " return fullurl\n", | |
| "\n", | |
| "\n", | |
| "def open_hw8_nci(t1, t2, xlim, ylim, band=14):\n", | |
| "\n", | |
| " times = pd.date_range(t1,t2,freq='1H')\n", | |
| " url = []\n", | |
| " for tt in times:\n", | |
| " hhmm = '%02d00'%(tt.hour)\n", | |
| " url.append(get_hw8_ncistr(band, str(tt.year), '%02d'%(tt.month), '%02d'%(tt.day), hhmm))\n", | |
| "\n", | |
| " ds = xr.open_mfdataset(url)\n", | |
| " \n", | |
| " # Reproject the coordinates\n", | |
| " P = Proj(ds.geostationary.proj4, init=None)\n", | |
| "\n", | |
| " lon,lat = P(ds.x.values, ds.y.values, inverse=True)\n", | |
| " lon[lon>1e10] = np.nan\n", | |
| " lat[lat>1e10] = np.nan\n", | |
| " \n", | |
| " x1,x2 = xlim\n", | |
| " y1,y2 = ylim\n", | |
| " \n", | |
| " i1 = np.argwhere(lon>x1)[0,0]\n", | |
| " i2 = np.argwhere(lon>x2)[0,0]\n", | |
| " j1 = np.argwhere(lat<y1)[0,0]\n", | |
| " j2 = np.argwhere(lat<y2)[0,0]\n", | |
| "\n", | |
| " x = lon[i1:i2]\n", | |
| " y = lat[j2:j1]\n", | |
| "\n", | |
| " # Subset the data and assign lat/lon values to the x/y coordinates\n", | |
| " return ds.isel(x=slice(i1,i2), y=slice(j2,j1)).assign_coords({'x':x, 'y':y})\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 130, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "/usr/local/bin/start_ipykernel.py:32: RuntimeWarning: invalid value encountered in greater\n", | |
| "/usr/local/bin/start_ipykernel.py:33: RuntimeWarning: invalid value encountered in greater\n", | |
| "/usr/local/bin/start_ipykernel.py:34: RuntimeWarning: invalid value encountered in less\n", | |
| "/usr/local/bin/start_ipykernel.py:35: RuntimeWarning: invalid value encountered in less\n" | |
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| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (time: 97, x: 134, y: 156)\n", | |
| "Coordinates:\n", | |
| " * x (x) float64 122.0 122.0 ... 125.0 125.0\n", | |
| " * y (y) float64 -12.01 -12.03 ... -14.99\n", | |
| " * time (time) datetime64[ns] 2020-08-29 ......\n", | |
| "Data variables:\n", | |
| " geostationary (time) float32 9.96921e+36 ... 9.969...\n", | |
| " scan_line_time (time, y) datetime64[ns] dask.array<chunksize=(1, 156), meta=np.ndarray>\n", | |
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| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " Metadata_Conventions: Unidata Dataset Discovery v1.0\n", | |
| " acknowledgment: See disclaimer\n", | |
| " cdm_data_type: grid\n", | |
| " comment: AGLS observations geometry product\n", | |
| " contributor_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " contributor_role: Development; Operations\n", | |
| " creator_email: sat_support@bom.gov.au\n", | |
| " creator_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " creator_url: http://www.bom.gov.au/satellite/\n", | |
| " disclaimer: You have requested that the Bureau of Me...\n", | |
| " geospatial_lat_resolution: 0.02\n", | |
| " geospatial_lat_units: degree_north\n", | |
| " geospatial_lon_resolution: 0.02\n", | |
| " geospatial_lon_units: degree_east\n", | |
| " geospatial_vertical_max: 0\n", | |
| " geospatial_vertical_min: 0\n", | |
| " geospatial_vertical_positive: up\n", | |
| " geospatial_vertical_resolution: 0\n", | |
| " geospatial_vertical_units: m\n", | |
| " institution: ABOM\n", | |
| " instrument: AHI\n", | |
| " keywords: EARTH SCIENCE\n", | |
| " keywords_vocabulary: NASA Global Change Master Directory (GCM...\n", | |
| " license: See disclaimer\n", | |
| " naming_authority: au.gov.bom\n", | |
| " processing_level: L2\n", | |
| " product_specification: AGLS-OBS_data-product-specification_rev0...\n", | |
| " product_suite: OBS_B14\n", | |
| " project: AGLS\n", | |
| " publisher_email: sat_support@bom.gov.au\n", | |
| " publisher_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " publisher_url: http://www.bom.gov.au/satellite/\n", | |
| " references: AGLS observations product\n", | |
| " standard_name_vocabulary: CF-1.6\n", | |
| " summary: AGLS observations product\n", | |
| " time_coverage_duration: P1S\n", | |
| " time_coverage_resolution: P1S\n", | |
| " title: AGLS observations product suite\n", | |
| " wmo_instrument_name: Advanced Himawari Imager\n", | |
| " wmo_instrument_type: 297\n", | |
| " wmo_satellite_series: 273\n", | |
| " date_created: 20200829T000002Z\n", | |
| " history: saturnc\n", | |
| " id: ABOM_AGLS_OBS_B14_P1S_GRID_v1.1\n", | |
| " netCDF_version: 4.3.3.1 of Dec 10 2015 16:44:18 $\n", | |
| " processing_version: 1.1\n", | |
| " uuid: 5d048400-4666-4367-ba04-eb43b01032c8\n", | |
| " geospatial_lat_max: 81.13851\n", | |
| " geospatial_lat_min: -81.13851\n", | |
| " geospatial_lon_max: 221.89696\n", | |
| " geospatial_lon_min: 59.50304\n", | |
| " platform: Himawari-8\n", | |
| " platform_launch_date: 20141007T051600Z\n", | |
| " time_coverage_end: 20200829T000939Z\n", | |
| " time_coverage_start: 20200829T000021Z\n", | |
| " wmo_platform_name: Himawari-8\n", | |
| " wmo_satellite_number: 173</pre><div class='xr-wrap' hidden><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-6c56ed7c-027a-489f-ba9f-00072aa876c6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6c56ed7c-027a-489f-ba9f-00072aa876c6' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 97</li><li><span class='xr-has-index'>x</span>: 134</li><li><span class='xr-has-index'>y</span>: 156</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8bbab5a1-7938-4de3-b43c-32a9e3a1a1f3' class='xr-section-summary-in' type='checkbox' checked><label for='section-8bbab5a1-7938-4de3-b43c-32a9e3a1a1f3' class='xr-section-summary' >Coordinates: <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-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'>122.0 122.0 122.0 ... 125.0 125.0</div><input id='attrs-6352aa38-c541-42b7-aa22-c5510bc83fc9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6352aa38-c541-42b7-aa22-c5510bc83fc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dba9f149-3b58-448c-ae52-c670d0a0f5ad' class='xr-var-data-in' type='checkbox'><label for='data-dba9f149-3b58-448c-ae52-c670d0a0f5ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([122.000393, 122.023685, 122.046963, 122.070227, 122.093476, 122.116711,\n", | |
| " 122.139932, 122.163139, 122.186332, 122.209511, 122.232676, 122.255826,\n", | |
| " 122.278963, 122.302086, 122.325195, 122.34829 , 122.371371, 122.394438,\n", | |
| " 122.417492, 122.440532, 122.463558, 122.48657 , 122.509569, 122.532554,\n", | |
| " 122.555526, 122.578484, 122.601428, 122.624359, 122.647276, 122.67018 ,\n", | |
| " 122.693071, 122.715948, 122.738812, 122.761662, 122.784499, 122.807323,\n", | |
| " 122.830134, 122.852931, 122.875715, 122.898486, 122.921244, 122.943989,\n", | |
| " 122.966721, 122.989439, 123.012145, 123.034838, 123.057517, 123.080184,\n", | |
| " 123.102838, 123.125479, 123.148107, 123.170723, 123.193325, 123.215915,\n", | |
| " 123.238492, 123.261056, 123.283608, 123.306147, 123.328673, 123.351187,\n", | |
| " 123.373689, 123.396177, 123.418653, 123.441117, 123.463568, 123.486007,\n", | |
| " 123.508434, 123.530848, 123.553249, 123.575639, 123.598016, 123.62038 ,\n", | |
| " 123.642733, 123.665073, 123.687401, 123.709717, 123.732021, 123.754313,\n", | |
| " 123.776593, 123.79886 , 123.821116, 123.843359, 123.865591, 123.887811,\n", | |
| " 123.910018, 123.932214, 123.954398, 123.97657 , 123.99873 , 124.020879,\n", | |
| " 124.043016, 124.065141, 124.087254, 124.109355, 124.131445, 124.153523,\n", | |
| " 124.17559 , 124.197645, 124.219688, 124.24172 , 124.263741, 124.28575 ,\n", | |
| " 124.307747, 124.329733, 124.351708, 124.373671, 124.395623, 124.417563,\n", | |
| " 124.439492, 124.46141 , 124.483317, 124.505212, 124.527096, 124.548969,\n", | |
| " 124.570831, 124.592681, 124.614521, 124.636349, 124.658166, 124.679972,\n", | |
| " 124.701768, 124.723552, 124.745325, 124.767087, 124.788839, 124.810579,\n", | |
| " 124.832309, 124.854027, 124.875735, 124.897432, 124.919118, 124.940794,\n", | |
| " 124.962458, 124.984112])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-12.01 -12.03 ... -14.98 -14.99</div><input id='attrs-b8a5c953-e908-4453-b3f4-e77ca55347a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8a5c953-e908-4453-b3f4-e77ca55347a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e687c03e-ea45-41f0-8bce-e1712da85f19' class='xr-var-data-in' type='checkbox'><label for='data-e687c03e-ea45-41f0-8bce-e1712da85f19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-12.011745, -12.030738, -12.049734, -12.068733, -12.087735, -12.106741,\n", | |
| " -12.125749, -12.14476 , -12.163774, -12.182791, -12.201811, -12.220834,\n", | |
| " -12.239861, -12.25889 , -12.277922, -12.296957, -12.315996, -12.335037,\n", | |
| " -12.354082, -12.373129, -12.39218 , -12.411234, -12.430291, -12.449351,\n", | |
| " -12.468414, -12.48748 , -12.506549, -12.525621, -12.544697, -12.563775,\n", | |
| " -12.582857, -12.601942, -12.62103 , -12.640121, -12.659216, -12.678313,\n", | |
| " -12.697414, -12.716518, -12.735625, -12.754735, -12.773849, -12.792965,\n", | |
| " -12.812085, -12.831208, -12.850335, -12.869464, -12.888597, -12.907733,\n", | |
| " -12.926873, -12.946015, -12.965161, -12.98431 , -13.003462, -13.022618,\n", | |
| " -13.041777, -13.060939, -13.080105, -13.099273, -13.118445, -13.137621,\n", | |
| " -13.1568 , -13.175982, -13.195167, -13.214356, -13.233548, -13.252744,\n", | |
| " -13.271942, -13.291145, -13.31035 , -13.329559, -13.348771, -13.367987,\n", | |
| " -13.387206, -13.406429, -13.425655, -13.444884, -13.464117, -13.483353,\n", | |
| " -13.502593, -13.521836, -13.541083, -13.560333, -13.579586, -13.598843,\n", | |
| " -13.618103, -13.637367, -13.656635, -13.675906, -13.69518 , -13.714458,\n", | |
| " -13.733739, -13.753024, -13.772313, -13.791605, -13.8109 , -13.8302 ,\n", | |
| " -13.849502, -13.868809, -13.888118, -13.907432, -13.926749, -13.946069,\n", | |
| " -13.965393, -13.984721, -14.004053, -14.023387, -14.042726, -14.062068,\n", | |
| " -14.081414, -14.100764, -14.120117, -14.139474, -14.158834, -14.178198,\n", | |
| " -14.197566, -14.216938, -14.236313, -14.255692, -14.275074, -14.294461,\n", | |
| " -14.313851, -14.333244, -14.352642, -14.372043, -14.391448, -14.410857,\n", | |
| " -14.430269, -14.449686, -14.469106, -14.488529, -14.507957, -14.527388,\n", | |
| " -14.546824, -14.566263, -14.585705, -14.605152, -14.624603, -14.644057,\n", | |
| " -14.663515, -14.682977, -14.702443, -14.721913, -14.741386, -14.760864,\n", | |
| " -14.780345, -14.79983 , -14.819319, -14.838812, -14.858309, -14.87781 ,\n", | |
| " -14.897315, -14.916824, -14.936336, -14.955853, -14.975374, -14.994898])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-29 ... 2020-09-02</div><input id='attrs-43f3fffd-da03-4231-a880-0df6ebdbe93a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43f3fffd-da03-4231-a880-0df6ebdbe93a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9148da6a-cf9b-4002-82db-7489ca4c74c5' class='xr-var-data-in' type='checkbox'><label for='data-9148da6a-cf9b-4002-82db-7489ca4c74c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(['2020-08-29T00:00:00.000000000', '2020-08-29T01:00:00.000000000',\n", | |
| " '2020-08-29T02:00:00.000000000', '2020-08-29T03:00:00.000000000',\n", | |
| " '2020-08-29T04:00:00.000000000', '2020-08-29T05:00:00.000000000',\n", | |
| " '2020-08-29T06:00:00.000000000', '2020-08-29T07:00:00.000000000',\n", | |
| " '2020-08-29T08:00:00.000000000', '2020-08-29T09:00:00.000000000',\n", | |
| " '2020-08-29T10:00:00.000000000', '2020-08-29T11:00:00.000000000',\n", | |
| " '2020-08-29T12:00:00.000000000', '2020-08-29T13:00:00.000000000',\n", | |
| " '2020-08-29T14:00:00.000000000', '2020-08-29T15:00:00.000000000',\n", | |
| " '2020-08-29T16:00:00.000000000', '2020-08-29T17:00:00.000000000',\n", | |
| " '2020-08-29T18:00:00.000000000', '2020-08-29T19:00:00.000000000',\n", | |
| " '2020-08-29T20:00:00.000000000', '2020-08-29T21:00:00.000000000',\n", | |
| " '2020-08-29T22:00:00.000000000', '2020-08-29T23:00:00.000000000',\n", | |
| " '2020-08-30T00:00:00.000000000', '2020-08-30T01:00:00.000000000',\n", | |
| " '2020-08-30T02:00:00.000000000', '2020-08-30T03:00:00.000000000',\n", | |
| " '2020-08-30T04:00:00.000000000', '2020-08-30T05:00:00.000000000',\n", | |
| " '2020-08-30T06:00:00.000000000', '2020-08-30T07:00:00.000000000',\n", | |
| " '2020-08-30T08:00:00.000000000', '2020-08-30T09:00:00.000000000',\n", | |
| " '2020-08-30T10:00:00.000000000', '2020-08-30T11:00:00.000000000',\n", | |
| " '2020-08-30T12:00:00.000000000', '2020-08-30T13:00:00.000000000',\n", | |
| " '2020-08-30T14:00:00.000000000', '2020-08-30T15:00:00.000000000',\n", | |
| " '2020-08-30T16:00:00.000000000', '2020-08-30T17:00:00.000000000',\n", | |
| " '2020-08-30T18:00:00.000000000', '2020-08-30T19:00:00.000000000',\n", | |
| " '2020-08-30T20:00:00.000000000', '2020-08-30T21:00:00.000000000',\n", | |
| " '2020-08-30T22:00:00.000000000', '2020-08-30T23:00:00.000000000',\n", | |
| " '2020-08-31T00:00:00.000000000', '2020-08-31T01:00:00.000000000',\n", | |
| " '2020-08-31T02:00:00.000000000', '2020-08-31T03:00:00.000000000',\n", | |
| " '2020-08-31T04:00:00.000000000', '2020-08-31T05:00:00.000000000',\n", | |
| " '2020-08-31T06:00:00.000000000', '2020-08-31T07:00:00.000000000',\n", | |
| " '2020-08-31T08:00:00.000000000', '2020-08-31T09:00:00.000000000',\n", | |
| " '2020-08-31T10:00:00.000000000', '2020-08-31T11:00:00.000000000',\n", | |
| " '2020-08-31T12:00:00.000000000', '2020-08-31T13:00:00.000000000',\n", | |
| " '2020-08-31T14:00:00.000000000', '2020-08-31T15:00:00.000000000',\n", | |
| " '2020-08-31T16:00:00.000000000', '2020-08-31T17:00:00.000000000',\n", | |
| " '2020-08-31T18:00:00.000000000', '2020-08-31T19:00:00.000000000',\n", | |
| " '2020-08-31T20:00:00.000000000', '2020-08-31T21:00:00.000000000',\n", | |
| " '2020-08-31T22:00:00.000000000', '2020-08-31T23:00:00.000000000',\n", | |
| " '2020-09-01T00:00:00.000000000', '2020-09-01T01:00:00.000000000',\n", | |
| " '2020-09-01T02:00:00.000000000', '2020-09-01T03:00:00.000000000',\n", | |
| " '2020-09-01T04:00:00.000000000', '2020-09-01T05:00:00.000000000',\n", | |
| " '2020-09-01T06:00:00.000000000', '2020-09-01T07:00:00.000000000',\n", | |
| " '2020-09-01T08:00:00.000000000', '2020-09-01T09:00:00.000000000',\n", | |
| " '2020-09-01T10:00:00.000000000', '2020-09-01T11:00:00.000000000',\n", | |
| " '2020-09-01T12:00:00.000000000', '2020-09-01T13:00:00.000000000',\n", | |
| " '2020-09-01T14:00:00.000000000', '2020-09-01T15:00:00.000000000',\n", | |
| " '2020-09-01T16:00:00.000000000', '2020-09-01T17:00:00.000000000',\n", | |
| " '2020-09-01T18:00:00.000000000', '2020-09-01T19:00:00.000000000',\n", | |
| " '2020-09-01T20:00:00.000000000', '2020-09-01T21:00:00.000000000',\n", | |
| " '2020-09-01T22:00:00.000000000', '2020-09-01T23:00:00.000000000',\n", | |
| " '2020-09-02T00:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a07da6ef-06ec-42e1-a291-7a09187bbae2' class='xr-section-summary-in' type='checkbox' checked><label for='section-a07da6ef-06ec-42e1-a291-7a09187bbae2' class='xr-section-summary' >Data variables: <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-var-name'><span>geostationary</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.96921e+36 ... 9.96921e+36</div><input id='attrs-95891440-e5b0-4afc-899a-c325c00fea1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95891440-e5b0-4afc-899a-c325c00fea1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-559aa71b-6063-40c8-b0fe-86c3e8c00fc7' class='xr-var-data-in' type='checkbox'><label for='data-559aa71b-6063-40c8-b0fe-86c3e8c00fc7' 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>proj_name :</span></dt><dd>GEOS141</dd><dt><span>sweep_angle_axis :</span></dt><dd>y</dd><dt><span>false_northing :</span></dt><dd>0</dd><dt><span>grid_mapping_name :</span></dt><dd>geostationary</dd><dt><span>false_easting :</span></dt><dd>0</dd><dt><span>satellite_height :</span></dt><dd>35785863.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.3</dd><dt><span>perspective_point_height :</span></dt><dd>35785863.0</dd><dt><span>GeoTransform :</span></dt><dd>[-5.5e+06 2.0e+03 0.0e+00 5.5e+06 0.0e+00 -2.0e+03]</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>140.7</dd><dt><span>proj4 :</span></dt><dd>+proj=geos +lon_0=140.7 +h=35785863 +x_0=0 +y_0=0 +a=6378137 +b=6356752.3 +units=m +no_defs </dd><dt><span>spatial_ref :</span></dt><dd>PROJCS["unnamed",GEOGCS["unnamed ellipse",DATUM["unknown",SPHEROID["unnamed",6378137,298.2570248822731]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433]],PROJECTION["Geostationary_Satellite"],PARAMETER["central_meridian",140.7],PARAMETER["satellite_height",35785863],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["Meter",1]]</dd></dl></div><div class='xr-var-data'><pre>array([9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,\n", | |
| " 9.96921e+36, 9.96921e+36], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scan_line_time</span></div><div class='xr-var-dims'>(time, y)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 156), meta=np.ndarray></div><input id='attrs-33a472cf-e84c-40d6-b460-8cc6c2db9159' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33a472cf-e84c-40d6-b460-8cc6c2db9159' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-181227b0-49a1-414e-93a2-ae3fc935f0e9' class='xr-var-data-in' type='checkbox'><label for='data-181227b0-49a1-414e-93a2-ae3fc935f0e9' 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>estimated scan line time</dd><dt><span>_ChunkSizes :</span></dt><dd>5500</dd></dl></div><div class='xr-var-data'><pre>dask.array<getitem, shape=(97, 156), dtype=datetime64[ns], chunksize=(1, 156)></pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_0014_brightness_temperature</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 156, 134), meta=np.ndarray></div><input id='attrs-f45b65ed-852c-4bb3-9e84-1bc7dc46e717' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f45b65ed-852c-4bb3-9e84-1bc7dc46e717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-139444fb-8813-4577-a07a-4dd06324a252' class='xr-var-data-in' type='checkbox'><label for='data-139444fb-8813-4577-a07a-4dd06324a252' 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_name :</span></dt><dd>channel_14_brightness_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>valid_max :</span></dt><dd>350.0</dd><dt><span>valid_min :</span></dt><dd>180.0</dd><dt><span>grid_mapping :</span></dt><dd>geostationary</dd><dt><span>central_wavelength :</span></dt><dd>1.12395e-05</dd><dt><span>comment :</span></dt><dd>brightness temperature observed by the Advanced Himawari Imager at 11.24 um (Band 14)</dd><dt><span>long_name :</span></dt><dd>brightness temperature for channel 14 at 11.24 um</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 1 1 5500]</dd></dl></div><div class='xr-var-data'><pre>dask.array<getitem, shape=(97, 156, 134), dtype=float32, chunksize=(1, 156, 134)></pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-273735bd-729c-4646-b9f9-b01761737c92' class='xr-section-summary-in' type='checkbox' ><label for='section-273735bd-729c-4646-b9f9-b01761737c92' class='xr-section-summary' >Attributes: <span>(58)</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-1.6</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>acknowledgment :</span></dt><dd>See disclaimer</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd>AGLS observations geometry product</dd><dt><span>contributor_name :</span></dt><dd>Commonwealth of Australia, Bureau of Meteorology, Science and Innovation, Science to Services, Weather and Environmental Prediction, Satellite Applications; Commonwealth of Australia, Bureau of Meteorology, Data and Digital, Observing Systems and Operations, Satellite Operations</dd><dt><span>contributor_role :</span></dt><dd>Development; Operations</dd><dt><span>creator_email :</span></dt><dd>sat_support@bom.gov.au</dd><dt><span>creator_name :</span></dt><dd>Commonwealth of Australia, Bureau of Meteorology, Data and Digital, Observing Systems and Operations, Satellite Operations</dd><dt><span>creator_url :</span></dt><dd>http://www.bom.gov.au/satellite/</dd><dt><span>disclaimer :</span></dt><dd>You have requested that the Bureau of Meteorology (\\'Bureau\\') provide you with an enhanced version of satellite data, images, information or other material (\\'Material\\').\\nYou understand that the Bureau does not operate the satellites and that the Material is subject to the uncertainties of imaging capabilities, adverse weather conditions and technical malfunction and may change without notice.\\nTo the maximum extent permitted by law, the Bureau: \\ndoes not make any representations or give any warranty that either the original Material or any Material enhanced by the Bureau is accurate, reliable, current, complete or fit for any purpose, and \\nexcludes all liability of the Bureau, and any suppliers of Material to the Bureau, for any loss, damage, cost, expense and any other consequences arising directly or indirectly from your use of the Material.</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.02</dd><dt><span>geospatial_lat_units :</span></dt><dd>degree_north</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.02</dd><dt><span>geospatial_lon_units :</span></dt><dd>degree_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>m</dd><dt><span>institution :</span></dt><dd>ABOM</dd><dt><span>instrument :</span></dt><dd>AHI</dd><dt><span>keywords :</span></dt><dd>EARTH SCIENCE</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>See disclaimer</dd><dt><span>naming_authority :</span></dt><dd>au.gov.bom</dd><dt><span>processing_level :</span></dt><dd>L2</dd><dt><span>product_specification :</span></dt><dd>AGLS-OBS_data-product-specification_rev01.00</dd><dt><span>product_suite :</span></dt><dd>OBS_B14</dd><dt><span>project :</span></dt><dd>AGLS</dd><dt><span>publisher_email :</span></dt><dd>sat_support@bom.gov.au</dd><dt><span>publisher_name :</span></dt><dd>Commonwealth of Australia, Bureau of Meteorology, Data and Digital, Observing Systems and Operations, Satellite Operations</dd><dt><span>publisher_url :</span></dt><dd>http://www.bom.gov.au/satellite/</dd><dt><span>references :</span></dt><dd>AGLS observations product</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.6</dd><dt><span>summary :</span></dt><dd>AGLS observations product</dd><dt><span>time_coverage_duration :</span></dt><dd>P1S</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1S</dd><dt><span>title :</span></dt><dd>AGLS observations product suite</dd><dt><span>wmo_instrument_name :</span></dt><dd>Advanced Himawari Imager</dd><dt><span>wmo_instrument_type :</span></dt><dd>297</dd><dt><span>wmo_satellite_series :</span></dt><dd>273</dd><dt><span>date_created :</span></dt><dd>20200829T000002Z</dd><dt><span>history :</span></dt><dd>saturnc</dd><dt><span>id :</span></dt><dd>ABOM_AGLS_OBS_B14_P1S_GRID_v1.1</dd><dt><span>netCDF_version :</span></dt><dd>4.3.3.1 of Dec 10 2015 16:44:18 $</dd><dt><span>processing_version :</span></dt><dd>1.1</dd><dt><span>uuid :</span></dt><dd>5d048400-4666-4367-ba04-eb43b01032c8</dd><dt><span>geospatial_lat_max :</span></dt><dd>81.13851</dd><dt><span>geospatial_lat_min :</span></dt><dd>-81.13851</dd><dt><span>geospatial_lon_max :</span></dt><dd>221.89696</dd><dt><span>geospatial_lon_min :</span></dt><dd>59.50304</dd><dt><span>platform :</span></dt><dd>Himawari-8</dd><dt><span>platform_launch_date :</span></dt><dd>20141007T051600Z</dd><dt><span>time_coverage_end :</span></dt><dd>20200829T000939Z</dd><dt><span>time_coverage_start :</span></dt><dd>20200829T000021Z</dd><dt><span>wmo_platform_name :</span></dt><dd>Himawari-8</dd><dt><span>wmo_satellite_number :</span></dt><dd>173</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (time: 97, x: 134, y: 156)\n", | |
| "Coordinates:\n", | |
| " * x (x) float64 122.0 122.0 ... 125.0 125.0\n", | |
| " * y (y) float64 -12.01 -12.03 ... -14.99\n", | |
| " * time (time) datetime64[ns] 2020-08-29 ......\n", | |
| "Data variables:\n", | |
| " geostationary (time) float32 9.96921e+36 ... 9.969...\n", | |
| " scan_line_time (time, y) datetime64[ns] dask.array<chunksize=(1, 156), meta=np.ndarray>\n", | |
| " channel_0014_brightness_temperature (time, y, x) float32 dask.array<chunksize=(1, 156, 134), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " Conventions: CF-1.6\n", | |
| " Metadata_Conventions: Unidata Dataset Discovery v1.0\n", | |
| " acknowledgment: See disclaimer\n", | |
| " cdm_data_type: grid\n", | |
| " comment: AGLS observations geometry product\n", | |
| " contributor_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " contributor_role: Development; Operations\n", | |
| " creator_email: sat_support@bom.gov.au\n", | |
| " creator_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " creator_url: http://www.bom.gov.au/satellite/\n", | |
| " disclaimer: You have requested that the Bureau of Me...\n", | |
| " geospatial_lat_resolution: 0.02\n", | |
| " geospatial_lat_units: degree_north\n", | |
| " geospatial_lon_resolution: 0.02\n", | |
| " geospatial_lon_units: degree_east\n", | |
| " geospatial_vertical_max: 0\n", | |
| " geospatial_vertical_min: 0\n", | |
| " geospatial_vertical_positive: up\n", | |
| " geospatial_vertical_resolution: 0\n", | |
| " geospatial_vertical_units: m\n", | |
| " institution: ABOM\n", | |
| " instrument: AHI\n", | |
| " keywords: EARTH SCIENCE\n", | |
| " keywords_vocabulary: NASA Global Change Master Directory (GCM...\n", | |
| " license: See disclaimer\n", | |
| " naming_authority: au.gov.bom\n", | |
| " processing_level: L2\n", | |
| " product_specification: AGLS-OBS_data-product-specification_rev0...\n", | |
| " product_suite: OBS_B14\n", | |
| " project: AGLS\n", | |
| " publisher_email: sat_support@bom.gov.au\n", | |
| " publisher_name: Commonwealth of Australia, Bureau of Met...\n", | |
| " publisher_url: http://www.bom.gov.au/satellite/\n", | |
| " references: AGLS observations product\n", | |
| " standard_name_vocabulary: CF-1.6\n", | |
| " summary: AGLS observations product\n", | |
| " time_coverage_duration: P1S\n", | |
| " time_coverage_resolution: P1S\n", | |
| " title: AGLS observations product suite\n", | |
| " wmo_instrument_name: Advanced Himawari Imager\n", | |
| " wmo_instrument_type: 297\n", | |
| " wmo_satellite_series: 273\n", | |
| " date_created: 20200829T000002Z\n", | |
| " history: saturnc\n", | |
| " id: ABOM_AGLS_OBS_B14_P1S_GRID_v1.1\n", | |
| " netCDF_version: 4.3.3.1 of Dec 10 2015 16:44:18 $\n", | |
| " processing_version: 1.1\n", | |
| " uuid: 5d048400-4666-4367-ba04-eb43b01032c8\n", | |
| " geospatial_lat_max: 81.13851\n", | |
| " geospatial_lat_min: -81.13851\n", | |
| " geospatial_lon_max: 221.89696\n", | |
| " geospatial_lon_min: 59.50304\n", | |
| " platform: Himawari-8\n", | |
| " platform_launch_date: 20141007T051600Z\n", | |
| " time_coverage_end: 20200829T000939Z\n", | |
| " time_coverage_start: 20200829T000021Z\n", | |
| " wmo_platform_name: Himawari-8\n", | |
| " wmo_satellite_number: 173" | |
| ] | |
| }, | |
| "execution_count": 130, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "t1 = '2020-08-29 00:00:00'\n", | |
| "t2 = '2020-09-02 00:00:00'\n", | |
| "\n", | |
| "# x1,x2 = 120,125\n", | |
| "# y1,y2 = -16,-12\n", | |
| "\n", | |
| "x1,x2 = 122,125\n", | |
| "y1,y2 = -15,-12\n", | |
| "\n", | |
| "band = 14 # Bands 11 - 15 all in the IR range\n", | |
| "\n", | |
| "ds = open_hw8_nci(t1, t2, (x1,x2), (y1,y2), band=band)\n", | |
| "ds" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 135, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 576x864 with 4 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "datavar = 'channel_00{}_brightness_temperature'.format(band)\n", | |
| "tstep = 18\n", | |
| "\n", | |
| "# Compute the gradient \n", | |
| "i1 = 100\n", | |
| "#dx = ds.x.values[i1+1]-ds.x.values[i1]\n", | |
| "dx = 2e3\n", | |
| "mydata = ds[datavar][tstep,...].values\n", | |
| "tnow = ds['time'].values[tstep]\n", | |
| "dtdx,dtdy = np.gradient(mydata.squeeze(),dx)\n", | |
| "x,y = ds.x.values, ds.y.values\n", | |
| "\n", | |
| "plt.figure(figsize=(8,12))\n", | |
| "ax=plt.subplot(211)\n", | |
| "ds[datavar][tstep,...].plot(vmin=294, vmax=299, cmap='inferno')\n", | |
| "ax.set_aspect('equal')\n", | |
| "\n", | |
| "ax=plt.subplot(212)\n", | |
| "plt.pcolormesh(x,y,np.abs(dtdx+1j*dtdy)*1e3, vmin=0.01, vmax=0.1, cmap='bone_r')\n", | |
| "#plt.pcolormesh(x,y,np.log(abs(dtdx+1j*dtdy)*1e3), vmin=-4, vmax=-2, cmap='bone_r')\n", | |
| "\n", | |
| "plt.colorbar()\n", | |
| "plt.gca().set_aspect('equal')\n", | |
| "# plt.title('Himawari Band {} brightness temp gradient [C/km]\\n{}'.format(band, str(tnow)[0:19]))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0.023053590661277212" | |
| ] | |
| }, | |
| "execution_count": 18, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "dx" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.7.6" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 4 | |
| } |
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