quickstarts/reading-zarr-data.ipynb

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    "## Reading Zarr Data\n",
    "\n",
    "[Zarr](https://zarr.readthedocs.io/en/stable/) is a storage format for chunked, N-dimensional arrays. It works well with object storage systems like [Azure Blob Storage](https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) and open-source libraries like [xarray](https://xarray.pydata.org/en/stable/). It's widely used in the geosciences, especially within the [Pangeo](https://pangeo.io/) community.\n",
    "\n",
    "This example loads [Daymet](https://aka.ms/ai4edata-daymet) data that are stored in Zarr format into an xarray Dataset.  Daymet provides gridded weather data for North America. We'll look at [daily frequency data covering Hawaii](https://planetarycomputer.microsoft.com/dataset/daymet-daily-hi).\n",
    "\n",
    "The [STAC Collections](../reading-stac) provided by the Planetary Computer contain assets with links to the root of the Zarr store."
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   "outputs": [],
   "source": [
    "import pystac_client\n",
    "import planetary_computer\n",
    "\n",
    "catalog = pystac_client.Client.open(\n",
    "    \"https://planetarycomputer.microsoft.com/api/stac/v1/\",\n",
    "    modifier=planetary_computer.sign_inplace,\n",
    ")\n",
    "collection = catalog.get_collection(\"daymet-daily-hi\")"
   ]
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   "cell_type": "markdown",
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   "source": [
    "We'll access the data using the `zarr-abfs` asset, which uses [adlfs](https://github.com/fsspec/adlfs) and [fsspec](https://filesystem-spec.readthedocs.io/) to load the data from Azure Blob Storage."
   ]
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "asset = collection.assets[\"zarr-abfs\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Zarr assets provided by the Planetary Computer implement the [xarray-assets](https://github.com/stac-extensions/xarray-assets) extension. These specify the necessary and recommended keywords when loading data from [`fssspec`-based filesystems](https://filesystem-spec.readthedocs.io/en/latest/) and xarray."
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['xarray:open_kwargs', 'xarray:storage_options']"
      ]
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     "execution_count": 3,
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   ],
   "source": [
    "list(asset.extra_fields.keys())"
   ]
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   "cell_type": "markdown",
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   "source": [
    "In this case, the dataset should be opened with consolidated metadata."
   ]
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   "cell_type": "code",
   "execution_count": 4,
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       "Dimensions:                  (time: 14965, y: 584, x: 284, nv: 2)\n",
       "Coordinates:\n",
       "    lat                      (y, x) float32 dask.array&lt;chunksize=(584, 284), meta=np.ndarray&gt;\n",
       "    lon                      (y, x) float32 dask.array&lt;chunksize=(584, 284), meta=np.ndarray&gt;\n",
       "  * time                     (time) datetime64[ns] 1980-01-01T12:00:00 ... 20...\n",
       "  * x                        (x) float32 -5.802e+06 -5.801e+06 ... -5.519e+06\n",
       "  * y                        (y) float32 -3.9e+04 -4e+04 ... -6.21e+05 -6.22e+05\n",
       "Dimensions without coordinates: nv\n",
       "Data variables:\n",
       "    dayl                     (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    lambert_conformal_conic  int16 ...\n",
       "    prcp                     (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    srad                     (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    swe                      (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    time_bnds                (time, nv) datetime64[ns] dask.array&lt;chunksize=(365, 2), meta=np.ndarray&gt;\n",
       "    tmax                     (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    tmin                     (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    vp                       (time, y, x) float32 dask.array&lt;chunksize=(365, 584, 284), meta=np.ndarray&gt;\n",
       "    yearday                  (time) int16 dask.array&lt;chunksize=(365,), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:       CF-1.6\n",
       "    Version_data:      Daymet Data Version 4.0\n",
       "    Version_software:  Daymet Software Version 4.0\n",
       "    citation:          Please see http://daymet.ornl.gov/ for current Daymet ...\n",
       "    references:        Please see http://daymet.ornl.gov/ for current informa...\n",
       "    source:            Daymet Software Version 4.0\n",
       "    start_year:        1980</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-65e920b7-7335-4577-8c32-c3489e44725a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-65e920b7-7335-4577-8c32-c3489e44725a' 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>: 14965</li><li><span class='xr-has-index'>y</span>: 584</li><li><span class='xr-has-index'>x</span>: 284</li><li><span>nv</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f7d744e2-3e70-46d8-891f-90100966c6c2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f7d744e2-3e70-46d8-891f-90100966c6c2' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(584, 284), meta=np.ndarray&gt;</div><input id='attrs-178dd9b1-7a84-4971-bb5b-6f30185881ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-178dd9b1-7a84-4971-bb5b-6f30185881ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ac2a1a1-5425-4166-b1e8-352bdb09524e' class='xr-var-data-in' type='checkbox'><label for='data-3ac2a1a1-5425-4166-b1e8-352bdb09524e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 647.88 kiB </td>\n",
       "                        <td> 647.88 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (584, 284) </td>\n",
       "                        <td> (584, 284) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(584, 284), meta=np.ndarray&gt;</div><input id='attrs-dbf15fcf-19e6-47fa-8795-b8eada151430' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbf15fcf-19e6-47fa-8795-b8eada151430' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2d2e391-6ccd-4870-9085-fb3e59a59534' class='xr-var-data-in' type='checkbox'><label for='data-c2d2e391-6ccd-4870-9085-fb3e59a59534' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\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> 647.88 kiB </td>\n",
       "                        <td> 647.88 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (584, 284) </td>\n",
       "                        <td> (584, 284) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-01T12:00:00 ... 2020-12-...</div><input id='attrs-bd93ce38-ab00-4b1e-b99c-5d106e9f025d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd93ce38-ab00-4b1e-b99c-5d106e9f025d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-718cfd03-88dc-4a8c-a589-d3a6dd4f3dca' class='xr-var-data-in' type='checkbox'><label for='data-718cfd03-88dc-4a8c-a589-d3a6dd4f3dca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>24-hour day based on local time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T12:00:00.000000000&#x27;, &#x27;1980-01-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T12:00:00.000000000&#x27;, ..., &#x27;2020-12-28T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-29T12:00:00.000000000&#x27;, &#x27;2020-12-30T12:00:00.000000000&#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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.802e+06 ... -5.519e+06</div><input id='attrs-7065633b-9f87-45c1-84c1-49def895e8cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7065633b-9f87-45c1-84c1-49def895e8cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a171014-68af-4387-920d-66f58b21dd11' class='xr-var-data-in' type='checkbox'><label for='data-3a171014-68af-4387-920d-66f58b21dd11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-5802250., -5801250., -5800250., ..., -5521250., -5520250., -5519250.],\n",
       "      dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>-3.9e+04 -4e+04 ... -6.22e+05</div><input id='attrs-6f8cf5b6-62df-4013-841a-97cdd1dfeda1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f8cf5b6-62df-4013-841a-97cdd1dfeda1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01c34e90-3ecc-4272-8f9e-9c038a911194' class='xr-var-data-in' type='checkbox'><label for='data-01c34e90-3ecc-4272-8f9e-9c038a911194' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ -39000.,  -40000.,  -41000., ..., -620000., -621000., -622000.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e6127086-84d1-45b3-b891-2ce5e842abc0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e6127086-84d1-45b3-b891-2ce5e842abc0' class='xr-section-summary' >Data variables: <span>(10)</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>dayl</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=(365, 584, 284), meta=np.ndarray&gt;</div><input id='attrs-73f9d02b-f904-4bc1-8d5f-cd152248ea4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73f9d02b-f904-4bc1-8d5f-cd152248ea4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5152e77c-046b-411b-935d-d2948dabf9e6' class='xr-var-data-in' type='checkbox'><label for='data-5152e77c-046b-411b-935d-d2948dabf9e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daylength</dd><dt><span>units :</span></dt><dd>s</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> 9.25 GiB </td>\n",
       "                        <td> 230.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (14965, 584, 284) </td>\n",
       "                        <td> (365, 584, 284) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 42 Tasks </td>\n",
       "                        <td> 41 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambert_conformal_conic</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ced5959c-f8bd-40a2-9868-1668cf34a8a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ced5959c-f8bd-40a2-9868-1668cf34a8a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-867952b6-ff6e-481c-b47a-504cd7d6f7fe' class='xr-var-data-in' type='checkbox'><label for='data-867952b6-ff6e-481c-b47a-504cd7d6f7fe' 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>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>42.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-100.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>standard_parallel :</span></dt><dd>[25.0, 60.0]</dd></dl></div><div class='xr-var-data'><pre>array(-32767, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcp</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=(365, 584, 284), meta=np.ndarray&gt;</div><input id='attrs-f9c6af97-cf44-4fdf-aa65-7437548b27e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9c6af97-cf44-4fdf-aa65-7437548b27e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b21a93c-d254-485b-89ef-b17fb73bf41e' class='xr-var-data-in' type='checkbox'><label for='data-1b21a93c-d254-485b-89ef-b17fb73bf41e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: sum</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daily total precipitation</dd><dt><span>units :</span></dt><dd>mm/day</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vp</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=(365, 584, 284), meta=np.ndarray&gt;</div><input id='attrs-42c107d6-4030-4161-98fe-8b6032edc1a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42c107d6-4030-4161-98fe-8b6032edc1a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f34493c9-9eab-4b35-b15f-a9813fd64e6f' class='xr-var-data-in' type='checkbox'><label for='data-f34493c9-9eab-4b35-b15f-a9813fd64e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daily average vapor pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>yearday</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(365,), meta=np.ndarray&gt;</div><input id='attrs-2740e029-8f68-432f-b690-e8e49882220d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2740e029-8f68-432f-b690-e8e49882220d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68e2c5c3-5a95-409e-b99c-e7594db66f55' class='xr-var-data-in' type='checkbox'><label for='data-68e2c5c3-5a95-409e-b99c-e7594db66f55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>day of year (DOY) starting with day 1 on Januaray 1st</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 29.23 kiB </td>\n",
       "                        <td> 730 B </td>\n",
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       "                        <td> (365,) </td>\n",
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       "                        <th> Count </th>\n",
       "                        <td> 42 Tasks </td>\n",
       "                        <td> 41 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> int16 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6eb1cd79-4851-4433-be4d-8c736e1a045f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6eb1cd79-4851-4433-be4d-8c736e1a045f' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>Version_data :</span></dt><dd>Daymet Data Version 4.0</dd><dt><span>Version_software :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>citation :</span></dt><dd>Please see http://daymet.ornl.gov/ for current Daymet data citation information</dd><dt><span>references :</span></dt><dd>Please see http://daymet.ornl.gov/ for current information on Daymet references</dd><dt><span>source :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>start_year :</span></dt><dd>1980</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                  (time: 14965, y: 584, x: 284, nv: 2)\n",
       "Coordinates:\n",
       "    lat                      (y, x) float32 dask.array<chunksize=(584, 284), meta=np.ndarray>\n",
       "    lon                      (y, x) float32 dask.array<chunksize=(584, 284), meta=np.ndarray>\n",
       "  * time                     (time) datetime64[ns] 1980-01-01T12:00:00 ... 20...\n",
       "  * x                        (x) float32 -5.802e+06 -5.801e+06 ... -5.519e+06\n",
       "  * y                        (y) float32 -3.9e+04 -4e+04 ... -6.21e+05 -6.22e+05\n",
       "Dimensions without coordinates: nv\n",
       "Data variables:\n",
       "    dayl                     (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    lambert_conformal_conic  int16 ...\n",
       "    prcp                     (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    srad                     (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    swe                      (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    time_bnds                (time, nv) datetime64[ns] dask.array<chunksize=(365, 2), meta=np.ndarray>\n",
       "    tmax                     (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    tmin                     (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    vp                       (time, y, x) float32 dask.array<chunksize=(365, 584, 284), meta=np.ndarray>\n",
       "    yearday                  (time) int16 dask.array<chunksize=(365,), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:       CF-1.6\n",
       "    Version_data:      Daymet Data Version 4.0\n",
       "    Version_software:  Daymet Software Version 4.0\n",
       "    citation:          Please see http://daymet.ornl.gov/ for current Daymet ...\n",
       "    references:        Please see http://daymet.ornl.gov/ for current informa...\n",
       "    source:            Daymet Software Version 4.0\n",
       "    start_year:        1980"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray as xr\n",
    "\n",
    "ds = xr.open_zarr(\n",
    "    asset.href,\n",
    "    **asset.extra_fields[\"xarray:open_kwargs\"],\n",
    "    storage_options=asset.extra_fields[\"xarray:storage_options\"]\n",
    ")\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point we can load the data, aggregate it, and plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://ai4edatasetspublicassets.blob.core.windows.net/assets/notebook-output/quickstarts-reading-zarr-data.ipynb/5.png\"/>"
      ],
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "warnings.simplefilter(\"ignore\", RuntimeWarning)\n",
    "fig, ax = plt.subplots(figsize=(12, 12))\n",
    "ds.sel(time=\"2009\")[\"tmax\"].mean(dim=\"time\").plot.imshow(ax=ax, cmap=\"inferno\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Learn more\n",
    "\n",
    "The xarray [User Guide](https://xarray.pydata.org/en/stable/io.html#zarr) has more information on reading Zarr data. For more about the Daymet dataset, see [here](http://aka.ms/ai4edata-daymet)."
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