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Clip RADOLAN xarray dataset using rioxarray with shapefile
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RADOLAN_clip_rioxarray.ipynb
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"cell_type": "markdown",
"id": "f598c1cc-99a4-4c0c-9ad4-eff811375d56",
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"# RADOLAN - clipping with box and shape"
]
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"execution_count": 1,
"id": "prospective-omega",
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"source": [
"import numpy as np\n",
"import wradlib as wrl\n",
"import xarray as xr\n",
"import rioxarray \n",
"import geopandas as gpd\n",
"import cartopy\n",
"import cartopy.crs as ccrs\n",
"import shapely\n",
"from shapely.geometry import mapping\n",
"import matplotlib.pyplot as plt"
]
},
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"{'xarray': '2022.11.1.dev4+gcc7e09a3.d20221109',\n",
" 'rioxarray': '0.13.2',\n",
" 'geopandas': '0.12.2',\n",
" 'cartopy': '0.20.2',\n",
" 'shapely': '1.8.2',\n",
" 'wradlib': '1.18'}"
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"source": [
"dict(xarray=xr.__version__, rioxarray=rioxarray.__version__, geopandas=gpd.__version__, cartopy=cartopy.__version__, \n",
" shapely=shapely.__version__, wradlib=wrl.__version__)"
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{
"cell_type": "markdown",
"id": "272bb73b-c8f3-4e9f-b702-aa41fe32ce88",
"metadata": {},
"source": [
"## Load RADOLAN raster data\n",
"\n",
"Make sure, that data is imported as dask arrays!"
]
},
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"cell_type": "code",
"execution_count": 3,
"id": "9cc43599-936f-4376-ba34-bb96b386bd7e",
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"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
" new_vars[k] = decode_cf_variable(\n",
"/home/kai/miniconda/envs/wradlib_310/lib/python3.10/site-packages/xarray/conventions.py:523: SerializationWarning: variable 'RW' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 10, y: 900, x: 900)\n",
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" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:50:00\n",
" * y (y) float64 -4.658e+06 -4.657e+06 ... -3.76e+06 -3.759e+06\n",
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" RW (time, y, x) float32 dask.array&lt;chunksize=(1, 900, 900), meta=np.ndarray&gt;\n",
"Attributes:\n",
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" radolanversion: 2.13.1\n",
" radarlocations: [&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;,...</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-048e94e0-0cab-4841-8db1-54169e65f665' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-048e94e0-0cab-4841-8db1-54169e65f665' 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>: 10</li><li><span class='xr-has-index'>y</span>: 900</li><li><span class='xr-has-index'>x</span>: 900</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2a4896e1-0e5b-4631-a267-29321affa192' class='xr-section-summary-in' type='checkbox' checked><label for='section-2a4896e1-0e5b-4631-a267-29321affa192' 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'>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'>2016-02-01T00:50:00 ... 2016-02-...</div><input id='attrs-8691573a-f5bc-4c0d-987e-e3d241da5c8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8691573a-f5bc-4c0d-987e-e3d241da5c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4514f242-3b58-4d0a-aa6b-8f2be8b4eaad' class='xr-var-data-in' type='checkbox'><label for='data-4514f242-3b58-4d0a-aa6b-8f2be8b4eaad' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-02-01T00:50:00.000000000&#x27;, &#x27;2016-02-01T01:50:00.000000000&#x27;,\n",
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" &#x27;2016-02-01T06:50:00.000000000&#x27;, &#x27;2016-02-01T07:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T08:50:00.000000000&#x27;, &#x27;2016-02-01T09:50:00.000000000&#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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.658e+06 ... -3.759e+06</div><input id='attrs-00d9f121-84e4-4aad-a3f7-4ed0c6d621a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00d9f121-84e4-4aad-a3f7-4ed0c6d621a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33cc1ba5-7cfc-4610-b1f8-1efa86535053' class='xr-var-data-in' type='checkbox'><label for='data-33cc1ba5-7cfc-4610-b1f8-1efa86535053' 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>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4658144.724266, -4657144.724266, -4656144.724266, ..., -3761144.724266,\n",
" -3760144.724266, -3759144.724266])</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'>-5.23e+05 -5.22e+05 ... 3.76e+05</div><input id='attrs-ecbaedcd-63aa-4620-ba7a-0f646ad189c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecbaedcd-63aa-4620-ba7a-0f646ad189c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44fabf49-a59d-4fe2-9023-c338d53ebaa5' class='xr-var-data-in' type='checkbox'><label for='data-44fabf49-a59d-4fe2-9023-c338d53ebaa5' 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>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-522962.166922, -521962.166922, -520962.166922, ..., 374037.833078,\n",
" 375037.833078, 376037.833078])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c625060-72ca-44ea-ad84-c10dbc857112' class='xr-section-summary-in' type='checkbox' checked><label for='section-9c625060-72ca-44ea-ad84-c10dbc857112' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>RW</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&lt;chunksize=(1, 900, 900), meta=np.ndarray&gt;</div><input id='attrs-301699d9-7b69-4515-b64f-5490b1378354' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-301699d9-7b69-4515-b64f-5490b1378354' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07549471-793e-4c4c-9a78-7d4e99078215' class='xr-var-data-in' type='checkbox'><label for='data-07549471-793e-4c4c-9a78-7d4e99078215' 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>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>rainfall_rate</dd><dt><span>long_name :</span></dt><dd>RW</dd><dt><span>unit :</span></dt><dd>mm h-1</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table>\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> 30.90 MiB </td>\n",
" <td> 3.09 MiB </td>\n",
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" \n",
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" <th> Shape </th>\n",
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" <td> (1, 900, 900) </td>\n",
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" <tr>\n",
" <th> Count </th>\n",
" <td> 31 Graph Layers </td>\n",
" <td> 10 Chunks </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Type </th>\n",
" <td> float32 </td>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ccff1af2-12da-422a-bb5b-6e0e14db6159' class='xr-section-summary-in' type='checkbox' ><label for='section-ccff1af2-12da-422a-bb5b-6e0e14db6159' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-26a055fe-9bf8-4b94-88b7-8d485cff68ad' class='xr-index-data-in' type='checkbox'/><label for='index-26a055fe-9bf8-4b94-88b7-8d485cff68ad' 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;2016-02-01 00:50:00&#x27;, &#x27;2016-02-01 01:50:00&#x27;,\n",
" &#x27;2016-02-01 02:50:00&#x27;, &#x27;2016-02-01 03:50:00&#x27;,\n",
" &#x27;2016-02-01 04:50:00&#x27;, &#x27;2016-02-01 05:50:00&#x27;,\n",
" &#x27;2016-02-01 06:50:00&#x27;, &#x27;2016-02-01 07:50:00&#x27;,\n",
" &#x27;2016-02-01 08:50:00&#x27;, &#x27;2016-02-01 09:50:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-915b9d29-1bdc-409e-9741-07f4b9e759b2' class='xr-index-data-in' type='checkbox'/><label for='index-915b9d29-1bdc-409e-9741-07f4b9e759b2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -4658144.724265573, -4657144.724265573, -4656144.724265573,\n",
" -4655144.724265573, -4654144.724265573, -4653144.724265573,\n",
" -4652144.724265573, -4651144.724265573, -4650144.724265573,\n",
" -4649144.724265573,\n",
" ...\n",
" -3768144.7242655726, -3767144.7242655726, -3766144.7242655726,\n",
" -3765144.7242655726, -3764144.7242655726, -3763144.7242655726,\n",
" -3762144.7242655726, -3761144.7242655726, -3760144.7242655726,\n",
" -3759144.7242655726],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=900))</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-5116e8f5-5f3d-49b3-9ab7-826202a52cb1' class='xr-index-data-in' type='checkbox'/><label for='index-5116e8f5-5f3d-49b3-9ab7-826202a52cb1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-522962.16692185594, -521962.16692185594, -520962.16692185594,\n",
" -519962.16692185594, -518962.16692185594, -517962.16692185594,\n",
" -516962.16692185594, -515962.16692185594, -514962.16692185594,\n",
" -513962.16692185594,\n",
" ...\n",
" 367037.83307814406, 368037.83307814406, 369037.83307814406,\n",
" 370037.83307814406, 371037.83307814406, 372037.83307814406,\n",
" 373037.83307814406, 374037.83307814406, 375037.83307814406,\n",
" 376037.83307814406],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=900))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8926ac5b-52c7-4460-b37c-693ab29cb5e8' class='xr-section-summary-in' type='checkbox' checked><label for='section-8926ac5b-52c7-4460-b37c-693ab29cb5e8' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>2.13.1</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;, &#x27;drs&#x27;, &#x27;neu&#x27;, &#x27;oft&#x27;, &#x27;eis&#x27;, &#x27;isn&#x27;, &#x27;fbg&#x27;, &#x27;mem&#x27;]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 10, y: 900, x: 900)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:50:00\n",
" * y (y) float64 -4.658e+06 -4.657e+06 ... -3.76e+06 -3.759e+06\n",
" * x (x) float64 -5.23e+05 -5.22e+05 -5.21e+05 ... 3.75e+05 3.76e+05\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array<chunksize=(1, 900, 900), meta=np.ndarray>\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: ['boo', 'ros', 'emd', 'hnr', 'umd', 'pro', 'ess', 'fld',..."
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fname = \"/automount/radar/dwd/rw/2016/2016-02/2016-02-01/raa01-rw_10000-1602010*-dwd---bin.gz\"\n",
"rad = xr.open_mfdataset(fname, engine=\"radolan\")\n",
"# fix encoding _FillValue\n",
"rad.RW.encoding[\"_FillValue\"] = 65536\n",
"rad"
]
},
{
"cell_type": "markdown",
"id": "88489bd1-5804-4eb7-9f56-51674f27a217",
"metadata": {},
"source": [
"## Setup Projection"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0372ce14-01a5-447f-81ab-c41fe36d90aa",
"metadata": {},
"outputs": [],
"source": [
"proj_radolan = ccrs.Stereographic(\n",
" true_scale_latitude=60.0, central_latitude=90.0, central_longitude=10.0\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "1bdd2750-5ee8-42ac-b388-5f7fde59a9aa",
"metadata": {},
"outputs": [
{
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" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: '►';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: '▼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 10, y: 900, x: 900)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.658e+06 -4.657e+06 ... -3.76e+06 -3.759e+06\n",
" * x (x) float64 -5.23e+05 -5.22e+05 -5.21e+05 ... 3.75e+05 3.76e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array&lt;chunksize=(1, 900, 900), meta=np.ndarray&gt;\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: [&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;,...</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-53340827-65c9-4dc1-8529-a9881de9609a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-53340827-65c9-4dc1-8529-a9881de9609a' 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>: 10</li><li><span class='xr-has-index'>y</span>: 900</li><li><span class='xr-has-index'>x</span>: 900</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c9a9fc09-e365-455b-9c4a-853e21d84fe4' class='xr-section-summary-in' type='checkbox' checked><label for='section-c9a9fc09-e365-455b-9c4a-853e21d84fe4' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>2016-02-01T00:50:00 ... 2016-02-...</div><input id='attrs-648ff2ce-3635-4337-82b7-3ff18386eafb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-648ff2ce-3635-4337-82b7-3ff18386eafb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d1d531a-ce57-454a-b4b5-ff17a623bef9' class='xr-var-data-in' type='checkbox'><label for='data-4d1d531a-ce57-454a-b4b5-ff17a623bef9' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-02-01T00:50:00.000000000&#x27;, &#x27;2016-02-01T01:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T02:50:00.000000000&#x27;, &#x27;2016-02-01T03:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T04:50:00.000000000&#x27;, &#x27;2016-02-01T05:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T06:50:00.000000000&#x27;, &#x27;2016-02-01T07:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T08:50:00.000000000&#x27;, &#x27;2016-02-01T09:50:00.000000000&#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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.658e+06 ... -3.759e+06</div><input id='attrs-98fe9706-cdfb-477d-b194-7fc96ce1337c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98fe9706-cdfb-477d-b194-7fc96ce1337c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33f0a36a-28d3-48df-9ca1-94a98bb4dae5' class='xr-var-data-in' type='checkbox'><label for='data-33f0a36a-28d3-48df-9ca1-94a98bb4dae5' 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>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4658144.724266, -4657144.724266, -4656144.724266, ..., -3761144.724266,\n",
" -3760144.724266, -3759144.724266])</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'>-5.23e+05 -5.22e+05 ... 3.76e+05</div><input id='attrs-8d168a1c-6881-4328-884b-bd9d53772a66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d168a1c-6881-4328-884b-bd9d53772a66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1941f07-9534-42da-b756-5ab0cbd508c9' class='xr-var-data-in' type='checkbox'><label for='data-f1941f07-9534-42da-b756-5ab0cbd508c9' 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>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-522962.166922, -521962.166922, -520962.166922, ..., 374037.833078,\n",
" 375037.833078, 376037.833078])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-0866149b-2570-4f80-9c24-db705389df34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0866149b-2570-4f80-9c24-db705389df34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff9e6a8-f070-4ef5-a85e-eeb2647f7e28' class='xr-var-data-in' type='checkbox'><label for='data-8ff9e6a8-f070-4ef5-a85e-eeb2647f7e28' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>Unknown based on WGS84 ellipsoid</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>polar_stereographic</dd><dt><span>standard_parallel :</span></dt><dd>60.0</dd><dt><span>straight_vertical_longitude_from_pole :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba5146a5-eea4-40bb-b305-141c8c4589ef' class='xr-section-summary-in' type='checkbox' checked><label for='section-ba5146a5-eea4-40bb-b305-141c8c4589ef' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>RW</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&lt;chunksize=(1, 900, 900), meta=np.ndarray&gt;</div><input id='attrs-78d5428a-008e-4ec1-8ef6-cc29bf178021' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78d5428a-008e-4ec1-8ef6-cc29bf178021' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9504ef78-8b58-4b54-abbf-bda46289396f' class='xr-var-data-in' type='checkbox'><label for='data-9504ef78-8b58-4b54-abbf-bda46289396f' 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>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>rainfall_rate</dd><dt><span>long_name :</span></dt><dd>RW</dd><dt><span>unit :</span></dt><dd>mm h-1</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table>\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> 30.90 MiB </td>\n",
" <td> 3.09 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (10, 900, 900) </td>\n",
" <td> (1, 900, 900) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Count </th>\n",
" <td> 31 Graph Layers </td>\n",
" <td> 10 Chunks </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Type </th>\n",
" <td> float32 </td>\n",
" <td> numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"195\" height=\"185\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"25\" y2=\"15\" style=\"stroke-width:2\" />\n",
" <line x1=\"10\" y1=\"120\" x2=\"25\" y2=\"135\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
" <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"121\" />\n",
" <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"123\" />\n",
" <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"124\" />\n",
" <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"126\" />\n",
" <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"127\" />\n",
" <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"129\" />\n",
" <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"130\" />\n",
" <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"132\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"133\" />\n",
" <line x1=\"25\" y1=\"15\" x2=\"25\" y2=\"135\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
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"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
" <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
" <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
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" <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
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" <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
" <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
" <line x1=\"25\" y1=\"15\" x2=\"145\" y2=\"15\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"25\" y2=\"15\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"0\" x2=\"145\" y2=\"15\" style=\"stroke-width:2\" />\n",
"\n",
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"\n",
" <!-- Horizontal lines -->\n",
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"\n",
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" <line x1=\"25\" y1=\"15\" x2=\"25\" y2=\"135\" style=\"stroke-width:2\" />\n",
" <line x1=\"145\" y1=\"15\" x2=\"145\" y2=\"135\" style=\"stroke-width:2\" />\n",
"\n",
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"\n",
" <!-- Text -->\n",
" <text x=\"85.249506\" y=\"155.249506\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >900</text>\n",
" <text x=\"165.249506\" y=\"75.249506\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,165.249506,75.249506)\">900</text>\n",
" <text x=\"7.624753\" y=\"147.624753\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.624753,147.624753)\">10</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-99d41383-1cca-47ea-8118-422ae369c65d' class='xr-section-summary-in' type='checkbox' ><label for='section-99d41383-1cca-47ea-8118-422ae369c65d' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3edcb2f-1bcb-4c91-bed2-d2240ee2cf1b' class='xr-index-data-in' type='checkbox'/><label for='index-a3edcb2f-1bcb-4c91-bed2-d2240ee2cf1b' 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;2016-02-01 00:50:00&#x27;, &#x27;2016-02-01 01:50:00&#x27;,\n",
" &#x27;2016-02-01 02:50:00&#x27;, &#x27;2016-02-01 03:50:00&#x27;,\n",
" &#x27;2016-02-01 04:50:00&#x27;, &#x27;2016-02-01 05:50:00&#x27;,\n",
" &#x27;2016-02-01 06:50:00&#x27;, &#x27;2016-02-01 07:50:00&#x27;,\n",
" &#x27;2016-02-01 08:50:00&#x27;, &#x27;2016-02-01 09:50:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d39150e1-2647-458e-9dda-af7fd097d30f' class='xr-index-data-in' type='checkbox'/><label for='index-d39150e1-2647-458e-9dda-af7fd097d30f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -4658144.724265573, -4657144.724265573, -4656144.724265573,\n",
" -4655144.724265573, -4654144.724265573, -4653144.724265573,\n",
" -4652144.724265573, -4651144.724265573, -4650144.724265573,\n",
" -4649144.724265573,\n",
" ...\n",
" -3768144.7242655726, -3767144.7242655726, -3766144.7242655726,\n",
" -3765144.7242655726, -3764144.7242655726, -3763144.7242655726,\n",
" -3762144.7242655726, -3761144.7242655726, -3760144.7242655726,\n",
" -3759144.7242655726],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=900))</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-d27d1a70-5686-4e79-86c2-2d6df121b64d' class='xr-index-data-in' type='checkbox'/><label for='index-d27d1a70-5686-4e79-86c2-2d6df121b64d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-522962.16692185594, -521962.16692185594, -520962.16692185594,\n",
" -519962.16692185594, -518962.16692185594, -517962.16692185594,\n",
" -516962.16692185594, -515962.16692185594, -514962.16692185594,\n",
" -513962.16692185594,\n",
" ...\n",
" 367037.83307814406, 368037.83307814406, 369037.83307814406,\n",
" 370037.83307814406, 371037.83307814406, 372037.83307814406,\n",
" 373037.83307814406, 374037.83307814406, 375037.83307814406,\n",
" 376037.83307814406],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=900))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bd526f3b-fb6c-4236-89e0-4587ab45362b' class='xr-section-summary-in' type='checkbox' checked><label for='section-bd526f3b-fb6c-4236-89e0-4587ab45362b' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>2.13.1</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;, &#x27;drs&#x27;, &#x27;neu&#x27;, &#x27;oft&#x27;, &#x27;eis&#x27;, &#x27;isn&#x27;, &#x27;fbg&#x27;, &#x27;mem&#x27;]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 10, y: 900, x: 900)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.658e+06 -4.657e+06 ... -3.76e+06 -3.759e+06\n",
" * x (x) float64 -5.23e+05 -5.22e+05 -5.21e+05 ... 3.75e+05 3.76e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array<chunksize=(1, 900, 900), meta=np.ndarray>\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: ['boo', 'ros', 'emd', 'hnr', 'umd', 'pro', 'ess', 'fld',..."
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rad.rio.set_spatial_dims(x_dim=\"x\", y_dim=\"y\", inplace=True)\n",
"rad.rio.write_crs(proj_radolan, inplace=True)"
]
},
{
"cell_type": "markdown",
"id": "feeead76-80b2-4143-bac7-653153b33ba8",
"metadata": {},
"source": [
"## Load German federal states shapefile"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "d55bdfcd-376a-4ece-b6c8-f8fedd1ba1c8",
"metadata": {},
"outputs": [],
"source": [
"bld = gpd.read_file(\"/automount/db01/python/data/ADM/germany/vg250_0101.gk3.shape.ebenen/vg250_ebenen/vg250_bld.shp\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "5b85c587-bca9-49be-99cb-15ca68b2c3f5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Derived Projected CRS: EPSG:31467>\n",
"Name: DHDN / 3-degree Gauss-Kruger zone 3\n",
"Axis Info [cartesian]:\n",
"- X[north]: Northing (metre)\n",
"- Y[east]: Easting (metre)\n",
"Area of Use:\n",
"- name: Germany - former West Germany onshore between 7°30'E and 10°30'E - states of Baden-Wurtemberg, Bayern, Bremen, Hamberg, Hessen, Niedersachsen, Nordrhein-Westfalen, Rhineland-Pfalz, Schleswig-Holstein.\n",
"- bounds: (7.5, 47.27, 10.51, 55.09)\n",
"Coordinate Operation:\n",
"- name: 3-degree Gauss-Kruger zone 3\n",
"- method: Transverse Mercator\n",
"Datum: Deutsches Hauptdreiecksnetz\n",
"- Ellipsoid: Bessel 1841\n",
"- Prime Meridian: Greenwich"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bld.crs"
]
},
{
"cell_type": "markdown",
"id": "a048d3cc-6408-465c-91a0-8bf1163b0113",
"metadata": {},
"source": [
"## Extract Brandenburg"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "47bc8b9c-9665-43d4-8ba8-759c890476c7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9 MULTIPOLYGON (((3818085.771 5947040.567, 38181...\n",
"Name: geometry, dtype: geometry"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"brandenburg = bld.loc[[9], \"geometry\"]\n",
"brandenburg"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "37a39a4a-fe19-45ae-af75-d2e23602c8dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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YWFTNxqJqAyPWQtnwxCh+/7XQSxAQxEmi2e5k+bbDLN92GHAXfGkXgv+fNBOblDqA574xi8SY4J/X05WgvbsyY0QCo5Niutym17nRAmXKsHie/vrMoK+I3Z2gTRLR4Tb+efscpqcnnHYfERiVFKNbFprPxUbYuO2cUbx0+xzSBkYbHY5fBW13A2BYQhRv3jWP772Wy4pOMzXHJMdw7/kZTEtLYFRSDF8UVvKN5zdj96JYi6b1ZN6YQTx900wGRIYZHUpABG1Lop3FIvzi8kmkD4zGZhFuO2cUb999NldOH8YoT3dk3pgklt00k3DPs2vdstB66/uLMnnptjn9JkEAiBkXqs3OzlY5OWdW+qy+pY3GVidDuplYs/XgcT7edYwrpw9j64HjPPRWPuBuOg5PjGLPUf8XstWC10+WTOCGOelEhwd1A/wUIrLl5EJSnYXMTxsXGUZcD9l9RnoiM9ITAchMiWPK8Hi2l9bylclDiYmwMv93n/qtJL4W/K6eMTzkEoQ3gr670ReTUuO5fnY68dFhPL2mUCcIrVt7jvbPWp79Okl0FhcZRmSYha9MGRJStQA03yksb+h5pxCkk4THLfNGsvuXi/nLjTO589zRRoejmdBH/XRSoE4SnbQPqY30FAzJSkvgLzfO4OazRhgZlmYSW0qqMeONfn/rf3dhvHBl1jDiIm1cMnkoVovwlSlDsYjwwhclRoemGajR7uSzfRU+WdQomOiWRBeiwq1cOjX1hOnk912QQfaIRGLCrUSG6cvWX20pOW50CAGnWxJeGhgTzhvfngeAy6X4y2cF/GHVvh6O0kLN6OSu5wuFMv1PYi9YLEJYCFUe0rwzPyOJK7KGGR1GwOnf9F54N6+MR/6zx+gwtAAKt1r4zVVT+mVFM50keqGwon8+L+/PRifHhPxsz9PR9yR64Z7zxrIgM5nYCBuvbDrI8+tLjA5J87N9x+pZmX+EOaMGkhgdjqUftSh0kugFm9XCdM8ckB9/ZQKDYsIpqmikye5kXUFlR/3MwXERzBo5kOY2J60OJ9tLa6lvcTBteDw7y+pw6PXygoZLwXde3gpAuM3CgEgb0eE2Hlw8niVTQ3uhJ50k+ijMauGe8/+7mkBhRQN//GgfLqW457wMJqYOANxPRDYWVfHZvgqSYyPIK63tOGZp9nDe3laG3anrXQQDu8NFZYMdsPPj5fkMjAnnrDGDjA7Lb0Jmqniw+cbzm9hScpxvnjOK+y/I4JM95ew6UsdjH+nHqsEmLtLG89+YRfbI4FwVrqep4vrGpUGum5XGl/97Ad9blInFIlw4MYVbzhoZUkvW9xf1LQ5uePZLXtt8KCSHbeskYZDFk4eeUpsgPjqMhf1syG+osDtc/OjN7Vz+5Hpe+fIg5XWhU3ZAJwmTmTwsdNaQ7I/yD9fy4+X5XPDYGp74eH9ItCx0kjCZCyfolkQoqG9x8MeP9/HnTwpoaXMaHU6f6CRhMlOHJ3DeuGSjw9B85LGP9vHIyt1Gh9EnOkmYjFKKAj2iM6T8Y8MB/rw6eLseOkmYyMe7jrHkT+s4VN1sdCiajz360T5WB2llK50kTGRTSTW7jvTPYqv9wbdf3sLafRVGh3HGvBpxKSIlQD3gBBwnD7wQkXjgJSDd85l/UEo9782xmlttcxtvbS01OgzNj9qcimfWFhIZZmXWyMSgWYH8TFoS5ymlsk7zR343sEspNQ1YCDwqIuFeHqvhXiDonLFJRoeh+dn6giqWPrOBjUXVRofiNV91NxQQJ+7UGAtUAw4ffXa/YLUIV0zvfwVN+qufrtjBl0VVRofhFW+ThAJWicgWEbmzi+1PAhOAMiAfuF8p5fLyWABE5E4RyRGRnIqK4Ou39VVVQyv3vbLN6DC0ACkob+DaZRu555WtlNebe3Smt0nibKXUDOAS4G4ROfek7RcDuUAqkAU8KSIDvDwWAKXUMqVUtlIqOzm5/40TON5kJzLcanQYphMT4tfkve1HmPub1dz36jbTFjPyKkkopco8X8uB5cDsk3a5FXhLuRUAxcB4L4/VgDHJsXxn4Ri94nknS6YO5W83ZzMmxIvPuhS8k1fGhY+tYekzGyirMdcj8B6ThIjEiEhc+2vgImDHSbsdBC7w7JMCjAOKvDxWw70w0NzRgwjS8TZnbPbIgaQNjOp2n20HjiMiXJOdRrgt9J/WKwWbiqtZ+IfPTPWky5srnwKsE5E8YBPwvlLqAxG5S0Tu8uzzK2CeiOQDq4EHlVKVpzvW9z9GaBg/JK7fLDH42LXTGJUUe8r7S6YMJS7CxqVTh/Lvb53F3NEDuWvBGD7/0XlMS0sIfKAGsDtc/PTtHbSZpAhRj+MklFJFwLQu3n+60+sy3K0Er47VuiYifHvBGP72eVFItyiun51GbISNmemJJwwump+RxBPXZXGwuokwq+WEwrORNitHTNYM96dGu5OnPi3g3vMzDK/QrcvXmUyrwxWSCSLcaiFzSCyxETa+PncECdHhzBk9kKtnDGP/sQbSB0bz88snYbNaGJ18agvjdx/uoby+1YDIjfP4x/vZVVbHspuNHV6kk4TJBPu04tNZNCmFp26YccJ7c0cPYu5o72pDbigMjjEFvhQdbuUmEyxWHfp3g4KMS6mQK2Fntbi7UX2xePKQfvfk54qsVOZnGD8cQCcJE2ifQtxsd/Lx7mOESqX98UPiGJ4YhdOl2Hqwbwvtfn9RJvt/fQnv3nMOCzKN/8MJhOwR5iisq7sbJvDXNYXsLKujtLrphFL7wezyaan8/PJJJEaHsb6gioLy+j59ns2z9uqU4fE8c9NMfrZiJ//OOeSLUE1r3JA4o0MAdEvCFAbHRfL+9iMhkyAAaprbWFdQiYhwTkYS3zh7lM8+OzLMym+/OoWUARE++0wzWr7tsNEhADpJmMKQAZFGh+Bza/dVEBfhv4aqiHDJ5KGEh/Dq7su3HebNLcYPqgrdKxxEokJwfkJmSiwjk/w7nPrnl09ixy8u5rGloTkUp7rRzg9ez+tYNtIoOkmYwNjkWKJDLFH845uzGeXnJAHudTkXZCbz0ffOZbxJ+vC+dGVWKrF+bJF5QycJE3j4nR002UNnfERidBgpcYHrQg2KjeCJ1fvZc7RvN0fNJsJm4dGlWUaHoZOE0Wqa7KzILTM6DJ9KGRBJU5uTupa2gJyvrKaZ97YfCci5Aml+RrLhQ7JBJwnDrS+oIi7CZopfBl8pKG9g2i9WsfD3n5F7qMbv5wtUMgqk5LgIfnnFJKPDAHSSMNyxuhY++N65pvmF8AWHS+F0KSalDmBy6oCeD+ijFzccIGVABANjwnveOQjMHJHI/311CqkJ3U+lDxQ9mMpg3zxnFDVNdv60en/He6/cMYe1+yp5ek2hgZH1TWJ0GI9eM61jEJQ/pcZH8p/7z8VmFT7bW8FvV+5GRDgchLNGZ41M5LVvnWWqSto6SZhAo91JXbP7MVdqfCSzRw5kcFwkL208YPjjr956+uszGRyg8R/3nJ/R8fryaaksyExm5+FaHl+9n03FwVOVGmDwgEhTJQjQScIUhiVE8dLtczha28LCccnYrBbGDo5lzqiBxETYCLNaKK9v4fP9lUaH6pXxQ+KY4+XsTn+Ijwpj3tgk5owexL5j9dz9ylaKKhoNi+dMuEw4cUcnCZOYOSLxlPceuzaLAZE2VuYf5cE3txsQVe+YZcyH1SK8m1dGZRDVoVg6K83oEE6hb1yaWHxUmGf48RDuvyCj5wNM4mB1E6XHm4wOA4fTxcr8I9S1BE+X7Z3cMtMtLKyTRBCwWIRVu44aHYbXjje1+exeSk2TnR2HezfxTeGeDBZMlm87zBqTrReqk0QQeDevjO1BMkM0KszKb66azPghJz76bHO6WLuvgp+t2NHxR1DX0kZ1o71je2ctbU4eXbWX+b/7lO+8vPWM++pKKVbvPkajPXhaEe12lplr0Wh9TyII7CirpdVhjsrJPRkSH0lUuA2nS3UMEFu9+xgPr9jZ8UiyqLKRhhYHz60vJjk2gutmp/HIyj08unQak4fFA2AR4cUNB6hvcVDf4uCvawo5WNVEUWUDd583loXjBtNsd1Jc2cjEk8ZiKKV46M38oK03UdVgNzqEE4jZ+j8A2dnZKicnx+gwTKGyoZVzf/dpUM3tEIFfXD6Js0YPoqa5jW/9c0tHi6E7Novwyysms2TqUOKjwnjg9Txe72KqdNrAKBKiwimubCQyzMqrd8yhrsXBlGHxhNssNLQ6uP/VbazeU+6PH8/vosOtfPbDhQF7hCwiW7pbzFu3JExMKcV3XtoaVAkC3IvMPLxiJ2OSYyg8g0ePDpfix8vzOVjdxMJxyRyo6vrm56HqZg7hbpU0tDq48qn1NNqd3HdBBvedP5a3tx2m9HjwDaRq12R3crC6KWBJoie6JWFyx+paeOrTAl7ccMDoUEzv2ZuzcSrFt/65xehQ+izcamH1DxacsPaIv/TUktA3Lk0uZUAk9iC5H2G0mAgbzwTxUPbO7E4Xr2w6aHQYgO5uBIX6IB2aHWg/eTufktN0UYLRnFHmqJatWxImV9NkJzE6zOgwgkJhRSNOEw5r7q3l2w6bYj1Q3ZIwuTanYvXu4LxLr/XNitwykmMjGDs4lgsnppAUa0x1cH3jMghsKKziluc2YTfBvyqaMSJsFqYOjyctMZrpIxK5evowYnxU+1I/Ag0BkWEWnSD6uVaHi80lx9lccpy3th1mV1ktj1w9NSDn1vckTE4pxfPrS4wOQzOZVzcdYm2A5nh4lSREpERE8kUkV0RO6QeISLyIvCsieSKyU0Ru7bRtsYjsFZECEXnIl8H3B5/treCdvNAqlKv5RrgtMP/Gn0l34zyl1OmqntwN7FJKXSYiycBeEXkZcAJPAYuAUmCziLyjlNrVp6j7kTe3Gr+Ck2Y+IjBikP8HWoHvuhsKiBN33a1YoBpwALOBAqVUkVLKDvwLuMJH5wx5h6qbQrJUvNZ3D186kaHxgSmU622SUMAqEdkiInd2sf1JYAJQBuQD9yulXMAwoPNUvFLPe6cQkTtFJEdEcioqzDWf3igf7AieGhJa4FgELhifErjzebnf2UqpGcAlwN0icu5J2y8GcoFUIAt4UkQGAF1V9OzymatSaplSKlsplZ2cnOxlWKFty4HjRoegmZBLwdee/oL6AK034lWSUEqVeb6WA8txdyM6uxV4S7kVAMXAeNwth85F+4bjbm1oXoiN1E+ota6V17dSXBmY4r49JgkRiRGRuPbXwEXAjpN2Owhc4NknBRgHFAGbgQwRGSUi4cB1wDu+Cz+0lQdRAVctsGaPGsgUT4Eef/OmJZECrBORPGAT8L5S6gMRuUtE7vLs8ytgnojkA6uBB5VSlUopB3AP8CGwG3hNKbXT9z9GaFp200y+tWC04atKa+bz+LVZAVufo8ffPqVUETCti/ef7vS6DHcLo6vjVwIr+xBjvxUZZuX2c0YzJjmGH72Rb3Q4mokEciKbHnFpYgermnhraym/fm+30aFoJhOIhZjb6Xasib2Wc4gnPy0wOgzNhKoaAne/SrckTOyLwuBY1k8LvEdX7eOLwkpaHf6vf6pbEib14oYSQqh+iuZj9a0Obvjbl0SGWfj+okzumD/abzcydZIwoZomOw+v0A+BtJ61tLn4zco9jE5yF6bxB93dMKH4qDB+smSC0WFoQeTn7/rvHxWdJExIRLg8K1WPj9C8dvs5o/z22TpJmNTguEgeuHgckWH6f5HWs+om/83j0L+BJnbLvJH89eszjQ5DCwLxUf6rqK6ThMnNGTWwY+FdTetKTLiVi/x00xJ0kjC96HAb/3PJeMPKqWvmd/v80X5dDlAniSBw+/zRvHfvOX69OaUFpzCrcNm0oX49h04SQWJIfCT3X5ihn3hoJ2hzKr+XFNBJIojERYZx49x0o8PQTGRGegJZaQl+PYdOEkHmocXjue+CDKPD0EyizamIDvdv61IniSAjItx7/li+s3AMF04IXDFUzZzyD9fyWs6hnnfsA50kglCY1cKPFo/n2VuyTxi+nZkSyxPXZRkXmGaIPD/XltBJIsi1P/lIiA7j+tnpXJE1jMnDBvR43KCYcKYND0yNRM1/EqLD/N791LfKQ8DkYfFs++miju+fuSmbR1buZu/RegoqGuhq4fgHLxnPZVNT+fMn+zlQ1cT7+XoRoGAUFWYlZUCkX8+hk0SI6FxLYFhCFE/eMAOAW5/fxKd7/7vY0dD4SBaOG8zZY5OICrfyo8XjUUqxICeZD3ceJa+0hsoGe8Dj13pn8eQhfj+HThIh7msz00iMDqfNpahpsrMgM5nb548+YR8RYemsNJbOSuNgVRP/b+UuPtx5zKCINW+JwFmjB/n9PDpJhLglU4eyZKr3I/LSB0Vzy1kj2XG4jgibhXMzk6lpsvN2rl5TyUwSosP4xeWTuGiSbkloBpg3Non1D53f8X1ZTbNOEiZz7/kZXJHV5bK6Pqefbmg9Ghp/4o2x1PhIZo8aSNrAwKxqrZ0oLtLGkin+na/RmW5JaD0SEVbeNx+XUizfdphLpw5lenoiTXYHEx/+0Ojw+pVpaQk8tnQaQ+L9+0SjM50kNK9MTHWPvZjcaf3J6HAbuQ8vIuuXHxkVVr8SGWbh8WuzGJUUE9Dz6iSh9YmIcPWMYcSE2zhQ3USYRVi9p9zosELS7eeMZoQf60acjk4SWp/ER4Xx2NIsAFwuxZ6j9awrqKTV4TI2sBA0LS0BiwFVyvSNS81nLBbhjS2lJySIcSlxfPz9c1mQmWxgZKHh7W2HDTmvbkloPvXVmcNIGRCB3eHiutnpJMe5y+4tu3km437ygcHRBbf384+Qvb6YrLQEpqcnBuy8OkloPjUpNZ5JqSdOHFuZf4THP95nUESh5Rfv7gLg+tlpPHL11ICc06vuhoiUiEi+iOSKSE4X2x/wbMsVkR0i4hSRgd4cq4W+jMGx7C9vMDqMkPLqpkMcrW0JyLnO5J7EeUqpLKVU9skblFK/92zLAv4HWKOUqvbmWC30ZaTEcWWARgf2J0frzJckvHU98KofPlcLYt+YN5LocKvRYYSUdfsret7JB7xNEgpYJSJbROTO0+0kItHAYuDNXhx7p4jkiEhORUVgfngtcKalJfCrKyYbHUZIOVTdHJDzeHvj8mylVJmIDAY+EpE9Sqm1Xex3GbD+pK6GV8cqpZYBywCys7O7KJOiBbu5Y/w/rbk/+bK4CrvDRbjNvyMZvPp0pVSZ52s5sByYfZpdr+OkrsYZHKuFuOgwKxmDY40OI2SUVDXxs3d2+P08PSYJEYkRkbj218BFwCmRiUg8sABYcabHav1Dm9Oln3L42KubDvHs50WormoU+og33Y0UYLmnPJoNeEUp9YGI3AWglHras99VwCqlVGNPx/oqeC24/Huzf0u/91e/fn836woq+ePSLBJjwn3++eLPDNRb2dnZKidHD6kINYeqm7j6r19Q4edl6fqrMckxPHTJBBad4QrjIrKlu+EJeu6GFjARYRbio8KMDiNkFVY08uQn+zne6NtCxjpJaAEzOC6SV++Yq9f78KO80lr+8lmBTz9TJwktoBwuF2ePTTI6jJDW5vTtLQQ9wUsLGJdL8av3drEy/6jRoYS0wgrfPkHSLQktYCwWweky343yUOPrxZV0ktAC5lhdCwV6nITf7T5Sx2d7fVdCUCcJLSDe217G4sfXUljR2PPOWp/l+nClcX1PQvOrmiY7P3tnJyv04j5+FRlmITUhiqKKRkYnxXDr2aN89tm6JaH5zSd7jrHoj2t1gggAiwhv3DWPBZnJvHrnXJ+OR9EtCc0v1u2v5Jsv6FGzvpQQHUakzdplsRmLCHuO1vHCrbNOWGHeF3RLQvOLeWMGMWfUQKPDCBnjh8Txp+um8+9vzeXKrNRTtmemxDJvTJLPEwToJKH5icUiPH5dVkc1qoRoPRy7tyJsFi6blsq5mcmMGBTDXQvHAGCzCKOTYhgcF8F1s9P9dn7d3dD8Zmh8FN9flEltcxs3zR3BNc9s4EBVk9Fhmd7NZ41g5ohEJqXG09LmZFBsOEPj/7s487iUOJbdNJORSTFkpsThcim/LtqjZ4FqfqeUQkQ4WtvC02sKeeGLEqNDMiURdzftkaumkj4ocMv59TQLVLckNL9r7ycPiY9kenoCL3xhcEB+YhEIs1o6VjCziLvAa0//Ds8eNZA/XptFS5uTMcnmq9ylk4QWMC6X4u/rio0Ow2+un53Og5eMx+5JEmEWC7XNbfxzYwn1LQ7GDo7lnbwydpbVdQxPn5+RxN9vmeX3OpV9oZOEFjAiMHf0IHYcriXUpnDEhFspqmgkwmZhQOR/b9LGR4fxv0smdnx/+/zR1DTZ+fX7u4mPCuOhS8YTZjVvggB9T0IzQF1LG6/nlPKr93YZHYrPbPif80+4udiTHYdraWh1MHe08RXE9T0JzXQGRIYxd3TojKFIGRBxRgkCYPKw4Cm8Y+52jhayJqXGs2TqUKPD6LOk2Ah+sGic0WH4lU4SmmEevnRizzuZXH1LG2NTzPdEwpd0d0MzjNWPA4D87YqsVK6ZmcaXxVWkDwzcmAYj6CShGcLlUmwsqjI6jF5bkVvG8MQoHrh4vNGh+J3ubmiGKKtt5pGVe4wOo0/W7Kugpc1pdBh+p5OEZohjda0crgnMqtj+Mj8j2egQAkInCc0QWWkJ3HaO99WTwqxCanykHyM6c+dmJBMZZjU6DL/TSUIzhNUiPHDxOMK9HG14z3kZfP+icfihXEKviIDCfAMR/UHfuNQM4XIpHlm5G7vT1eX2mHAr2SMH0tzmpLKhlWuyh5OaEMXxRjvPry+mrPbU6kyBYrUI/+/Kycwb0z8WGdJJQjPEW9sOM3PkQD7ceazLcmzT0hL48w3TGRAZxtHaFiI8E6Bmjkzk9vmj+HDnMX7wWi6N9sDcOBwxKJqjtS20OlxcNDGF6emJATmvGejuhmaIr80czqVThnZUrmpntQi3nzOKZTdnd0yUGhIfSWJMOAAz0hMREc7JSOLXV01mydShjBgU7bduiM0iXD87jQ+/ey4PLh6PCNwwJ51xQ+L8c0IT0i0JzTAWi3DtrDQe+Y/7UWhkmIVBMRH8xIuRmLERNq6aPpyrpg8H4Iqn1pPXx7UmosKs3DJvJPuO1fP5/grOGpPEH5dOY1BsBADDE6OYmZ7IqKSYPp0n2OgkoRlqaXYaNc1t2B0uImwWvrcos1efc9HEFIrKG1g0MYWvzRzOff/KpbKhtWN7XISNVqero9YDwIBIGy0OF9PTEhidHMu5GUlcMsU9n6TN6TplCvdFk4Zw0aQhvYovmHk1VVxESoB6wAk4Tp5WKiIPADd6vrUBE4BkpVS1iCwGngCswLNKqd/2dD49Vbx/qqhvJSE6rNf1FVbkHuaKrGEdrw/XNGN3uBgcF8nZYwfR0uZi77F6Ptl9jPoWB/ecP5a1+yq5/8IMX/4YQaenqeJnkiSylVKVXux7GfA9pdT5ImIF9gGLgFJgM3C9UqrbQgI6SWha4PSUJPxx4/J64FXP69lAgVKqSCllB/4FXOGHc2qa5ifeJgkFrBKRLSJy5+l2EpFoYDHwpuetYcChTruUet7r6tg7RSRHRHIqKiq8DEvTNH/zNkmcrZSaAVwC3C0i555mv8uA9Uqpas/3XT2Y6rJ/o5RappTKVkplJyf3jzHxmhYMvEoSSqkyz9dyYDnubkRXruO/XQ1wtxzSOn0/HNCrx2paEOkxSYhIjIjEtb8GLgJ2dLFfPLAAWNHp7c1AhoiMEpFw3EnkHV8ErmlaYHgzTiIFWO5ZYMUGvKKU+kBE7gJQSj3t2e8qYJVSqrH9QKWUQ0TuAT7E/Qj0OaXUTl/+AJqm+Zcuqa9p/ZwRj0A1TQshOklomtYtU3Y3RKQCONDNLklAj6M/DWb2GHV8fWf2GL2Nb4RS6rTjDkyZJHoiIjnd9aHMwOwx6vj6zuwx+io+3d3QNK1bOklomtatYE0Sy4wOwAtmj1HH13dmj9En8QXlPQlN0wInWFsSmqYFiE4SmqZ1y1RJQkQiRWSTiOSJyE4R+cVp9lsoIrmefdZ0er9ERPI923w+rtub+ETkAc/5c0Vkh4g4RWSgZ9tiEdkrIgUi8pAJ4/Pr9TuDGONF5N1O+9zaaZsZrmF38ZnlGiaKyHIR2e7Zd3KnbWd2DZVSpvkPd/2JWM/rMOBLYO5J+yQAu4B0z/eDO20rAZKMjO+k/S8DPvG8tgKFwGggHMgDJpolvkBcvzP4f/xj4P88r5OBas81M8U1PF18JruGvwd+5nk9Hljd299DU7UklFuD59swz38n31m9AXhLKXXQc0y5yeLrLKCl/PoYX0B4GaMC4sQ99TgW9x+hA/Ncw9PFFxBexjgRWO3Zfw8wUkRS6MU1NFWSABARq4jkAuXAR0qpL0/aJRNIFJHPPOX0bu60zasye36Or32/XpfyMyg+CMD18zLGJ3FXXC8D8oH7lVIuzHMNTxcfmOca5gFXe/adDYzAXfTpjK+h6ZKEUsqplMrC/QPN7tyX8rABM4ElwMXAT0WkfbEGb8vs+TO+dr0u5WdQfBCA6+dljBcDuUAqkAU8KSIDMM81PF18YJ5r+Fvc/5jmAvcC23C3ds74GpouSbRTStUAn+H+166zUuADpVSjcpf4XwtM8xzjbZk9f8bXztBSfr2IL6DXz3OeGrqO8VbcXUqllCoAinH3q81yDU8Xn2muoVKqTil1qyeR3Iz73kkxvbiGpkoSIpIsIgme11HAhcCek3ZbAcwXEZunyTwH2C1eltkLQHyGlfLrS3yBuH5nEONB4ALPPinAOKAI81zDLuMz0zUUkQTPNQK4HVirlKqjF9fQbMv8DQX+Ie5FfSzAa0qp96RTqTyl1G4R+QDYDrhwrwq2Q0RG00WZvUDH59nPqFJ+vY6P05Qp9HF83sb4K+AFEcnH3Tx+0NNqxCTXsMv4AvQ76G2ME4AXRcSJ+2ngbZ5tZ/x7qIdla5rWLVN1NzRNMx+dJDRN65ZOEpqmdUsnCU3TuqWThKYFKRF5TkTKRcSrx6wislREdol7UtgrXp9HP93QtODkGc3ZALyolDrdyNr2fTOA14DzlVLHRWSwt/OedEtC04KUUmot7sllHURkjIh84Jk78rmIjPdsugN4Sil13HOs1xMjdZLQtNCyDLhXKTUT+CHwF8/7mUCmiKwXkY0icrrh+qcw24hLTdN6SURigXnA655RnwARnq82IANYiHu+xuciMtkz96NbOkloWuiwADWeSV0nKwU2KqXagGIR2Ys7aWz25kM1TQsBnglcxSJyDYC4TfNsfhs4z/N+Eu7uR5E3n6uThKYFKRF5FdgAjBORUhG5DbgRuE1E8oCd/Lfq1IdAlYjsAj4FHlBKVXl1Hv0IVNO07uiWhKZp3dJJQtO0bukkoWlat3SS0DStWzpJaJrWLZ0kNE3rlk4SmqZ16/8Dj0Uwfp/iu6oAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"brandenburg.plot()"
]
},
{
"cell_type": "markdown",
"id": "7b14ef36-aca4-4997-b878-16b4fb321f0f",
"metadata": {},
"source": [
"## Clip using rioxarray clip_box"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "93a1f938-6b0b-4de5-9589-61fe30bac4ad",
"metadata": {},
"outputs": [],
"source": [
"bounds = brandenburg.to_crs(proj_radolan).bounds.iloc[0]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "c5d1181f-44ee-4093-a7f9-07a0808a1ad1",
"metadata": {},
"outputs": [
{
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"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 10, y: 256, x: 258)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.172e+06 -4.171e+06 ... -3.918e+06 -3.917e+06\n",
" * x (x) float64 8.804e+04 8.904e+04 9.004e+04 ... 3.44e+05 3.45e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array&lt;chunksize=(1, 256, 258), meta=np.ndarray&gt;\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: [&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;,...</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-b01b29fc-5079-4e96-86a4-80a0960596df' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b01b29fc-5079-4e96-86a4-80a0960596df' 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>: 10</li><li><span class='xr-has-index'>y</span>: 256</li><li><span class='xr-has-index'>x</span>: 258</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-17ead9b5-86e0-4bcf-90d5-538ba88441e2' class='xr-section-summary-in' type='checkbox' checked><label for='section-17ead9b5-86e0-4bcf-90d5-538ba88441e2' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>2016-02-01T00:50:00 ... 2016-02-...</div><input id='attrs-d5cc269e-590c-4dc0-8f8b-e0d254f2222f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5cc269e-590c-4dc0-8f8b-e0d254f2222f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83762436-39a5-49ba-808d-86c863f63e62' class='xr-var-data-in' type='checkbox'><label for='data-83762436-39a5-49ba-808d-86c863f63e62' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-02-01T00:50:00.000000000&#x27;, &#x27;2016-02-01T01:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T02:50:00.000000000&#x27;, &#x27;2016-02-01T03:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T04:50:00.000000000&#x27;, &#x27;2016-02-01T05:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T06:50:00.000000000&#x27;, &#x27;2016-02-01T07:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T08:50:00.000000000&#x27;, &#x27;2016-02-01T09:50:00.000000000&#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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.172e+06 ... -3.917e+06</div><input id='attrs-c594174c-9523-44a5-98e0-dda6e1c0c003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c594174c-9523-44a5-98e0-dda6e1c0c003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0af021-a881-4b28-8bb9-4878c256e31f' class='xr-var-data-in' type='checkbox'><label for='data-bf0af021-a881-4b28-8bb9-4878c256e31f' 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>units :</span></dt><dd>metre</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-4172144.724266, -4171144.724266, -4170144.724266, ..., -3919144.724266,\n",
" -3918144.724266, -3917144.724266])</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'>8.804e+04 8.904e+04 ... 3.45e+05</div><input id='attrs-dc3958ec-c810-43f1-b51d-081707244b6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc3958ec-c810-43f1-b51d-081707244b6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d5eb3fa-6d5e-4520-9fc1-41562f7ba89d' class='xr-var-data-in' type='checkbox'><label for='data-2d5eb3fa-6d5e-4520-9fc1-41562f7ba89d' 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>units :</span></dt><dd>metre</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 88037.833078, 89037.833078, 90037.833078, ..., 343037.833078,\n",
" 344037.833078, 345037.833078])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-65f7ea24-3fed-4b79-9862-65b6d5e78c78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65f7ea24-3fed-4b79-9862-65b6d5e78c78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66f95098-24f4-458e-aee0-9bcd639ee763' class='xr-var-data-in' type='checkbox'><label for='data-66f95098-24f4-458e-aee0-9bcd639ee763' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>Unknown based on WGS84 ellipsoid</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>polar_stereographic</dd><dt><span>standard_parallel :</span></dt><dd>60.0</dd><dt><span>straight_vertical_longitude_from_pole :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd><dt><span>GeoTransform :</span></dt><dd>87537.83307814406 1000.0 0.0 -4172644.7242655726 0.0 1000.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-87a5ec90-5363-4f10-bbfb-921757eaa052' class='xr-section-summary-in' type='checkbox' checked><label for='section-87a5ec90-5363-4f10-bbfb-921757eaa052' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>RW</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&lt;chunksize=(1, 256, 258), meta=np.ndarray&gt;</div><input id='attrs-3d61d2b2-f14e-44bb-bca1-fbfe60f0de55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d61d2b2-f14e-44bb-bca1-fbfe60f0de55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d78fb2d-32eb-4ac5-a895-819205315254' class='xr-var-data-in' type='checkbox'><label for='data-4d78fb2d-32eb-4ac5-a895-819205315254' 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>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>rainfall_rate</dd><dt><span>long_name :</span></dt><dd>RW</dd><dt><span>unit :</span></dt><dd>mm h-1</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table>\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> 2.52 MiB </td>\n",
" <td> 258.00 kiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (10, 256, 258) </td>\n",
" <td> (1, 256, 258) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Count </th>\n",
" <td> 32 Graph Layers </td>\n",
" <td> 10 Chunks </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Type </th>\n",
" <td> float32 </td>\n",
" <td> numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
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"\n",
" <!-- Horizontal lines -->\n",
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" <text x=\"89.377278\" y=\"158.447045\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >258</text>\n",
" <text x=\"169.377278\" y=\"78.912161\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,169.377278,78.912161)\">256</text>\n",
" <text x=\"9.688639\" y=\"148.758406\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,9.688639,148.758406)\">10</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-de5471eb-f066-43cf-838d-0acacfa2b979' class='xr-section-summary-in' type='checkbox' ><label for='section-de5471eb-f066-43cf-838d-0acacfa2b979' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b2f8fae2-512f-4a6b-b4f9-de1766327f00' class='xr-index-data-in' type='checkbox'/><label for='index-b2f8fae2-512f-4a6b-b4f9-de1766327f00' 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;2016-02-01 00:50:00&#x27;, &#x27;2016-02-01 01:50:00&#x27;,\n",
" &#x27;2016-02-01 02:50:00&#x27;, &#x27;2016-02-01 03:50:00&#x27;,\n",
" &#x27;2016-02-01 04:50:00&#x27;, &#x27;2016-02-01 05:50:00&#x27;,\n",
" &#x27;2016-02-01 06:50:00&#x27;, &#x27;2016-02-01 07:50:00&#x27;,\n",
" &#x27;2016-02-01 08:50:00&#x27;, &#x27;2016-02-01 09:50:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b5b45432-d9e8-4b4f-ba62-0a044c80e6ba' class='xr-index-data-in' type='checkbox'/><label for='index-b5b45432-d9e8-4b4f-ba62-0a044c80e6ba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-4172144.7242655726, -4171144.7242655726, -4170144.7242655726,\n",
" -4169144.7242655726, -4168144.7242655726, -4167144.7242655726,\n",
" -4166144.7242655726, -4165144.7242655726, -4164144.7242655726,\n",
" -4163144.7242655726,\n",
" ...\n",
" -3926144.7242655726, -3925144.7242655726, -3924144.7242655726,\n",
" -3923144.7242655726, -3922144.7242655726, -3921144.7242655726,\n",
" -3920144.7242655726, -3919144.7242655726, -3918144.7242655726,\n",
" -3917144.7242655726],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=256))</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-31c86491-46db-401b-91fc-8547ed18c6e8' class='xr-index-data-in' type='checkbox'/><label for='index-31c86491-46db-401b-91fc-8547ed18c6e8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 88037.83307814406, 89037.83307814406, 90037.83307814406,\n",
" 91037.83307814406, 92037.83307814406, 93037.83307814406,\n",
" 94037.83307814406, 95037.83307814406, 96037.83307814406,\n",
" 97037.83307814406,\n",
" ...\n",
" 336037.83307814406, 337037.83307814406, 338037.83307814406,\n",
" 339037.83307814406, 340037.83307814406, 341037.83307814406,\n",
" 342037.83307814406, 343037.83307814406, 344037.83307814406,\n",
" 345037.83307814406],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=258))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-722a25f6-2299-460d-a1f4-d4ea710c7509' class='xr-section-summary-in' type='checkbox' checked><label for='section-722a25f6-2299-460d-a1f4-d4ea710c7509' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>2.13.1</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;, &#x27;drs&#x27;, &#x27;neu&#x27;, &#x27;oft&#x27;, &#x27;eis&#x27;, &#x27;isn&#x27;, &#x27;fbg&#x27;, &#x27;mem&#x27;]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 10, y: 256, x: 258)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.172e+06 -4.171e+06 ... -3.918e+06 -3.917e+06\n",
" * x (x) float64 8.804e+04 8.904e+04 9.004e+04 ... 3.44e+05 3.45e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array<chunksize=(1, 256, 258), meta=np.ndarray>\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: ['boo', 'ros', 'emd', 'hnr', 'umd', 'pro', 'ess', 'fld',..."
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clip_box = rad.rio.clip_box(*bounds)\n",
"clip_box"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "2a6162a4-70df-4805-96a4-a1086eeb4548",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<cartopy.mpl.gridliner.Gridliner at 0x7f57077d18a0>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(12, 6))\n",
"ax = fig.add_subplot(projection=ccrs.PlateCarree())\n",
"clip_box.RW[0].plot(ax=ax, transform=proj_radolan)\n",
"ax.gridlines(draw_labels=True, x_inline=False, y_inline=False)"
]
},
{
"cell_type": "markdown",
"id": "fc2e877f-5157-4a51-bd7d-4c42e790505b",
"metadata": {},
"source": [
"## clip using rioxarray with shape"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7950c802-1d58-42b6-aeae-348660211848",
"metadata": {},
"outputs": [
{
"data": {
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" *\n",
" */\n",
"\n",
":root {\n",
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"body[data-theme=dark],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1F1F1F;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: '►';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: '▼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
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"\n",
".xr-var-name {\n",
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"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
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"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
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"\n",
".xr-var-preview {\n",
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"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
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"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
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"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
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"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
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"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
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"\n",
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"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 10, y: 254, x: 256)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.171e+06 -4.17e+06 ... -3.919e+06 -3.918e+06\n",
" * x (x) float64 8.904e+04 9.004e+04 9.104e+04 ... 3.43e+05 3.44e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array&lt;chunksize=(1, 254, 256), meta=np.ndarray&gt;\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: [&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;,...</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-84c6f4a6-7357-433c-ac79-06e78cdd1e65' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84c6f4a6-7357-433c-ac79-06e78cdd1e65' 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>: 10</li><li><span class='xr-has-index'>y</span>: 254</li><li><span class='xr-has-index'>x</span>: 256</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6aac288d-be3a-4192-8495-5b9780abf60c' class='xr-section-summary-in' type='checkbox' checked><label for='section-6aac288d-be3a-4192-8495-5b9780abf60c' class='xr-section-summary' >Coordinates: <span>(4)</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'>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'>2016-02-01T00:50:00 ... 2016-02-...</div><input id='attrs-186bdbb7-1f1f-49f7-be9c-07c8a14b79bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-186bdbb7-1f1f-49f7-be9c-07c8a14b79bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-180c24e7-d96c-44f0-ae60-d19f28c2cc76' class='xr-var-data-in' type='checkbox'><label for='data-180c24e7-d96c-44f0-ae60-d19f28c2cc76' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-02-01T00:50:00.000000000&#x27;, &#x27;2016-02-01T01:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T02:50:00.000000000&#x27;, &#x27;2016-02-01T03:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T04:50:00.000000000&#x27;, &#x27;2016-02-01T05:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T06:50:00.000000000&#x27;, &#x27;2016-02-01T07:50:00.000000000&#x27;,\n",
" &#x27;2016-02-01T08:50:00.000000000&#x27;, &#x27;2016-02-01T09:50:00.000000000&#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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.171e+06 -4.17e+06 ... -3.918e+06</div><input id='attrs-9733616f-5b98-4568-a671-bd17b97f5fc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9733616f-5b98-4568-a671-bd17b97f5fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b5b72a-cbd3-4382-9a3f-0bef3afbb180' class='xr-var-data-in' type='checkbox'><label for='data-89b5b72a-cbd3-4382-9a3f-0bef3afbb180' 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>units :</span></dt><dd>metre</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-4171144.724266, -4170144.724266, -4169144.724266, ..., -3920144.724266,\n",
" -3919144.724266, -3918144.724266])</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'>8.904e+04 9.004e+04 ... 3.44e+05</div><input id='attrs-f3845644-68a9-4903-bd55-2bbdf21ef910' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3845644-68a9-4903-bd55-2bbdf21ef910' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44febfff-07d7-405b-8f38-887036472e11' class='xr-var-data-in' type='checkbox'><label for='data-44febfff-07d7-405b-8f38-887036472e11' 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>units :</span></dt><dd>metre</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 89037.833078, 90037.833078, 91037.833078, ..., 342037.833078,\n",
" 343037.833078, 344037.833078])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-aa895f53-0da5-472a-a9aa-c0313d94952e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa895f53-0da5-472a-a9aa-c0313d94952e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a62ecaa2-5ce4-4832-91fe-7ac9375646f9' class='xr-var-data-in' type='checkbox'><label for='data-a62ecaa2-5ce4-4832-91fe-7ac9375646f9' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>Unknown based on WGS84 ellipsoid</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>polar_stereographic</dd><dt><span>standard_parallel :</span></dt><dd>60.0</dd><dt><span>straight_vertical_longitude_from_pole :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unknown&quot;,GEOGCS[&quot;unknown&quot;,DATUM[&quot;Unknown based on WGS84 ellipsoid&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,60],PARAMETER[&quot;central_meridian&quot;,10],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,SOUTH],AXIS[&quot;Northing&quot;,SOUTH]]</dd><dt><span>GeoTransform :</span></dt><dd>88537.83307814406 1000.0 0.0 -4171644.7242655726 0.0 1000.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fff6550f-fe2e-4904-83f4-0d51315882ef' class='xr-section-summary-in' type='checkbox' checked><label for='section-fff6550f-fe2e-4904-83f4-0d51315882ef' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>RW</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&lt;chunksize=(1, 254, 256), meta=np.ndarray&gt;</div><input id='attrs-2449e4d5-1da3-4971-859d-00f0c941b16f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2449e4d5-1da3-4971-859d-00f0c941b16f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b52e46b3-c94d-485f-84b4-09a3f8f47cd8' class='xr-var-data-in' type='checkbox'><label for='data-b52e46b3-c94d-485f-84b4-09a3f8f47cd8' 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>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>rainfall_rate</dd><dt><span>long_name :</span></dt><dd>RW</dd><dt><span>unit :</span></dt><dd>mm h-1</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table>\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> 2.48 MiB </td>\n",
" <td> 254.00 kiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (10, 254, 256) </td>\n",
" <td> (1, 254, 256) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Count </th>\n",
" <td> 34 Graph Layers </td>\n",
" <td> 10 Chunks </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Type </th>\n",
" <td> float32 </td>\n",
" <td> numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"199\" height=\"188\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"29\" y2=\"19\" style=\"stroke-width:2\" />\n",
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"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"119\" style=\"stroke-width:2\" />\n",
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" <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"124\" />\n",
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" <line x1=\"29\" y1=\"19\" x2=\"29\" y2=\"138\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
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"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
" <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
" <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
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" <line x1=\"29\" y1=\"19\" x2=\"149\" y2=\"19\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"29\" y2=\"19\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"0\" x2=\"149\" y2=\"19\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"10.0,0.0 130.0,0.0 149.40524078182307,19.405240781823075 29.405240781823075,19.405240781823075\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"29\" y1=\"19\" x2=\"149\" y2=\"19\" style=\"stroke-width:2\" />\n",
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"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"29\" y1=\"19\" x2=\"29\" y2=\"138\" style=\"stroke-width:2\" />\n",
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"\n",
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"\n",
" <!-- Text -->\n",
" <text x=\"89.405241\" y=\"158.467741\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >256</text>\n",
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" <text x=\"9.702620\" y=\"148.765120\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,9.702620,148.765120)\">10</text>\n",
"</svg>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3f8826a-ad0d-4dde-a8c3-18b514b1a893' class='xr-section-summary-in' type='checkbox' ><label for='section-c3f8826a-ad0d-4dde-a8c3-18b514b1a893' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-da35ae5b-640d-42df-bd14-90d6a479e54e' class='xr-index-data-in' type='checkbox'/><label for='index-da35ae5b-640d-42df-bd14-90d6a479e54e' 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;2016-02-01 00:50:00&#x27;, &#x27;2016-02-01 01:50:00&#x27;,\n",
" &#x27;2016-02-01 02:50:00&#x27;, &#x27;2016-02-01 03:50:00&#x27;,\n",
" &#x27;2016-02-01 04:50:00&#x27;, &#x27;2016-02-01 05:50:00&#x27;,\n",
" &#x27;2016-02-01 06:50:00&#x27;, &#x27;2016-02-01 07:50:00&#x27;,\n",
" &#x27;2016-02-01 08:50:00&#x27;, &#x27;2016-02-01 09:50:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-caa10f9b-d7ab-42f8-b874-e9cad394e3a2' class='xr-index-data-in' type='checkbox'/><label for='index-caa10f9b-d7ab-42f8-b874-e9cad394e3a2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-4171144.7242655726, -4170144.7242655726, -4169144.7242655726,\n",
" -4168144.7242655726, -4167144.7242655726, -4166144.7242655726,\n",
" -4165144.7242655726, -4164144.7242655726, -4163144.7242655726,\n",
" -4162144.7242655726,\n",
" ...\n",
" -3927144.7242655726, -3926144.7242655726, -3925144.7242655726,\n",
" -3924144.7242655726, -3923144.7242655726, -3922144.7242655726,\n",
" -3921144.7242655726, -3920144.7242655726, -3919144.7242655726,\n",
" -3918144.7242655726],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=254))</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-3ed1700a-38c2-44fa-9de6-3947a7ce04c9' class='xr-index-data-in' type='checkbox'/><label for='index-3ed1700a-38c2-44fa-9de6-3947a7ce04c9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 89037.83307814406, 90037.83307814406, 91037.83307814406,\n",
" 92037.83307814406, 93037.83307814406, 94037.83307814406,\n",
" 95037.83307814406, 96037.83307814406, 97037.83307814406,\n",
" 98037.83307814406,\n",
" ...\n",
" 335037.83307814406, 336037.83307814406, 337037.83307814406,\n",
" 338037.83307814406, 339037.83307814406, 340037.83307814406,\n",
" 341037.83307814406, 342037.83307814406, 343037.83307814406,\n",
" 344037.83307814406],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=256))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da703377-f6e7-409c-9f42-ecf912c1064b' class='xr-section-summary-in' type='checkbox' checked><label for='section-da703377-f6e7-409c-9f42-ecf912c1064b' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>2.13.1</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;boo&#x27;, &#x27;ros&#x27;, &#x27;emd&#x27;, &#x27;hnr&#x27;, &#x27;umd&#x27;, &#x27;pro&#x27;, &#x27;ess&#x27;, &#x27;fld&#x27;, &#x27;drs&#x27;, &#x27;neu&#x27;, &#x27;oft&#x27;, &#x27;eis&#x27;, &#x27;isn&#x27;, &#x27;fbg&#x27;, &#x27;mem&#x27;]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 10, y: 254, x: 256)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2016-02-01T00:50:00 ... 2016-02-01T09:...\n",
" * y (y) float64 -4.171e+06 -4.17e+06 ... -3.919e+06 -3.918e+06\n",
" * x (x) float64 8.904e+04 9.004e+04 9.104e+04 ... 3.43e+05 3.44e+05\n",
" spatial_ref int64 0\n",
"Data variables:\n",
" RW (time, y, x) float32 dask.array<chunksize=(1, 254, 256), meta=np.ndarray>\n",
"Attributes:\n",
" radarid: 10000\n",
" formatversion: 3\n",
" radolanversion: 2.13.1\n",
" radarlocations: ['boo', 'ros', 'emd', 'hnr', 'umd', 'pro', 'ess', 'fld',..."
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clip_shape = rad.rio.clip(brandenburg.geometry.apply(mapping), brandenburg.crs, drop=True)\n",
"clip_shape"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "4935c57f-705b-46f5-aff5-3f337c867216",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<cartopy.mpl.gridliner.Gridliner at 0x7f57076af550>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(12, 6))\n",
"ax = fig.add_subplot(projection=ccrs.PlateCarree())\n",
"clip_shape.RW[0].plot(ax=ax, transform=proj_radolan)\n",
"ax.gridlines(draw_labels=True, x_inline=False, y_inline=False)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.10.5"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
@SandeepAllampalli
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This is wonderful. For example considering rad_2006 as the radolan dataset that was saved as rad_2006.nc in the local drive. Is it possible to resample the hourly data to quarterly like the below line:

rad_2006_q = rad_2006.resample(time='1Q').mean()

I am little skeptical to use mean() or sum() as the aggregate function. As this is the rainfall data I assume sum() is a better choice over mean(). Please educate me.

@SandeepAllampalli
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Dear @kmuehlbauer,

Everything is good until until this line of code:

bld = gpd.read_file("/automount/db01/python/data/ADM/germany/vg250_0101.gk3.shape.ebenen/vg250_ebenen/vg250_bld.shp") bld.crs

When I run:
brandenburg = bld.loc[[9], "geometry"] brandenburg

it throws me the following error:
Complete code:

import numpy as np
import wradlib as wrl
import xarray as xr
import rioxarray
import geopandas as gpd
import cartopy
import cartopy.crs as ccrs
import shapely
from shapely.geometry import mapping
import matplotlib.pyplot as plt

dict(xarray=xr.__version__, rioxarray=rioxarray.__version__, geopandas=gpd.__version__, cartopy=cartopy.__version__, shapely=shapely.__version__, wradlib=wrl.__version__)

Out[9]: {'xarray': '2022.10.0', 'rioxarray': '0.13.2', 'geopandas': '0.12.2', 'cartopy': '0.20.0', 'shapely': '1.8.0', 'wradlib': '1.18.0'}

load radolan raster data

fname = "D:/Sandeep/Thesis/Data/BIN/Extracted/raa01-rw_10000-*-dwd---bin.gz"
rad = xr.open_mfdataset(fname, engine="radolan")

fix encoding _FillValue

rad.RW.encoding["_FillValue"] = 65536
rad

`Out[10]:
<xarray.Dataset>
Dimensions: (time: 8758, y: 900, x: 900)
Coordinates:

  • time (time) datetime64[ns] 2006-01-01T00:45:00 ... 2006-12-31T23:...
  • y (y) float64 -4.658e+06 -4.657e+06 ... -3.76e+06 -3.759e+06
  • x (x) float64 -5.23e+05 -5.22e+05 -5.21e+05 ... 3.75e+05 3.76e+05
    spatial_ref int32 0
    Data variables:
    RW (time, y, x) float32 dask.array<chunksize=(1, 900, 900), meta=np.ndarray>
    Attributes:
    radarid: 10000
    formatversion: 2
    radolanversion: 01.01.00
    radarlocations: ['bln', 'drs', 'eis', 'emd', 'ess', 'fbg', 'fld', 'fra',...`

setup projection

proj_radolan = ccrs.Stereographic( true_scale_latitude=60.0, central_latitude=90.0, central_longitude=10.0 )

rad.rio.set_spatial_dims(x_dim="x", y_dim="y", inplace=True)
rad.rio.write_crs(proj_radolan, inplace=True)

Load German federal states shapefile

germany = gpd.read_file(r'D:\Sandeep\Thesis\vg2500_12-31.gk3.shape\vg2500\VG2500_LAN.shp')
germany.crs

`Out[11]:

Name: DHDN / 3-degree Gauss-Kruger zone 3
Axis Info [cartesian]:

  • X[north]: Northing (metre)
  • Y[east]: Easting (metre)
    Area of Use:
  • name: Germany - former West Germany onshore between 7°30'E and 10°30'E - states of Baden-Wurtemberg, Bayern, Bremen, Hamberg, Hessen, Niedersachsen, Nordrhein-Westfalen, Rhineland-Pfalz, Schleswig-Holstein.
  • bounds: (7.5, 47.27, 10.51, 55.09)
    Coordinate Operation:
  • name: 3-degree Gauss-Kruger zone 3
  • method: Transverse Mercator
    Datum: Deutsches Hauptdreiecksnetz
  • Ellipsoid: Bessel 1841
  • Prime Meridian: Greenwich`

Extract Brandenburg

brandenburg = germany.loc[[11], "geometry"]
brandenburg

`brandenburg
Traceback (most recent call last):

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\IPython\core\formatters.py", line 702, in call
printer.pretty(obj)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\IPython\lib\pretty.py", line 394, in pretty
return _repr_pprint(obj, self, cycle)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\IPython\lib\pretty.py", line 700, in _repr_pprint
output = repr(obj)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\core\series.py", line 1594, in repr
return self.to_string(**repr_params)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\core\series.py", line 1687, in to_string
result = formatter.to_string()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 397, in to_string
fmt_values = self._get_formatted_values()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 381, in _get_formatted_values
return format_array(

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1328, in format_array
return fmt_obj.get_result()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1359, in get_result
fmt_values = self._format_strings()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1662, in _format_strings
fmt_values = format_array(

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1328, in format_array
return fmt_obj.get_result()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1359, in get_result
fmt_values = self._format_strings()

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1422, in _format_strings
fmt_values.append(f" {_format(v)}")

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\pandas\io\formats\format.py", line 1402, in _format
return str(formatter(x))

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\geopandas\array.py", line 1306, in
return lambda geom: shapely.wkt.dumps(geom, rounding_precision=precision)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\shapely\wkt.py", line 62, in dumps
return geos.WKTWriter(geos.lgeos, trim=trim, **kw).write(ob)

File "C:\Users\Admin\anaconda3\envs\wradlib\lib\site-packages\shapely\geos.py", line 401, in write
result = self._lgeos.GEOSWKTWriter_write(self._writer, geom._geom)

OSError: exception: access violation writing 0x0000000000000000`

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