diff --git a/docs/src/examples/Using-rio-tiler-XarrayReader.ipynb b/docs/src/examples/Using-rio-tiler-XarrayReader.ipynb
index 4542aed1..26d75134 100644
--- a/docs/src/examples/Using-rio-tiler-XarrayReader.ipynb
+++ b/docs/src/examples/Using-rio-tiler-XarrayReader.ipynb
@@ -418,11 +418,11 @@
        "    time_coverage_start:        20200115T210000Z\n",
        "    title:                      Daily MUR SST, Final product\n",
        "    uuid:                       27665bc0-d5fc-11e1-9b23-0800200c9a66\n",
-       "    westernmost_longitude:      -180.0</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-3cbb9720-89bf-4454-bb65-d4425a734324' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3cbb9720-89bf-4454-bb65-d4425a734324' 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>: 6443</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b2f4858c-6f2c-4137-a35f-6ef3c4c8f08b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b2f4858c-6f2c-4137-a35f-6ef3c4c8f08b' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-22a242ad-dfaf-4f27-a7b8-8b59edbd1d7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22a242ad-dfaf-4f27-a7b8-8b59edbd1d7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0d5144b-35b8-4477-8431-be3094024baf' class='xr-var-data-in' type='checkbox'><label for='data-e0d5144b-35b8-4477-8431-be3094024baf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-c196ed31-5e28-48bf-af8e-ca6f764be876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c196ed31-5e28-48bf-af8e-ca6f764be876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb82f997-de29-4696-ac3a-250106176860' class='xr-var-data-in' type='checkbox'><label for='data-eb82f997-de29-4696-ac3a-250106176860' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-06-01T09:00:00 ... 2020-01-...</div><input id='attrs-1e941d59-e89c-42f9-9702-6f382d11df20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e941d59-e89c-42f9-9702-6f382d11df20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0091ff27-403c-4737-973e-2bf5e8b134c4' class='xr-var-data-in' type='checkbox'><label for='data-0091ff27-403c-4737-973e-2bf5e8b134c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>comment :</span></dt><dd>Nominal time of analyzed fields</dd><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-06-01T09:00:00.000000000&#x27;, &#x27;2002-06-02T09:00:00.000000000&#x27;,\n",
+       "    westernmost_longitude:      -180.0</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-84439cea-a6b0-4b29-afd3-adb2fc7e90a7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84439cea-a6b0-4b29-afd3-adb2fc7e90a7' 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>: 6443</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-722e8c49-3424-488a-9a29-dbaf90a996fa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-722e8c49-3424-488a-9a29-dbaf90a996fa' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-aaea3748-c138-495d-ae46-aec27f66a88a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aaea3748-c138-495d-ae46-aec27f66a88a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cabccf2f-2a7d-4e3e-bb16-85c5c66bdce1' class='xr-var-data-in' type='checkbox'><label for='data-cabccf2f-2a7d-4e3e-bb16-85c5c66bdce1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-71177d9f-44a2-4bee-bdbd-f6f4b200f666' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71177d9f-44a2-4bee-bdbd-f6f4b200f666' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92a70c6b-c367-4533-a8c5-9fecd30c2047' class='xr-var-data-in' type='checkbox'><label for='data-92a70c6b-c367-4533-a8c5-9fecd30c2047' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-06-01T09:00:00 ... 2020-01-...</div><input id='attrs-69e75a3e-db23-4b04-848a-2337e839f73b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69e75a3e-db23-4b04-848a-2337e839f73b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d84a1ae6-b62e-423a-93f0-812bf63002e0' class='xr-var-data-in' type='checkbox'><label for='data-d84a1ae6-b62e-423a-93f0-812bf63002e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>comment :</span></dt><dd>Nominal time of analyzed fields</dd><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-06-01T09:00:00.000000000&#x27;, &#x27;2002-06-02T09:00:00.000000000&#x27;,\n",
        "       &#x27;2002-06-03T09:00:00.000000000&#x27;, ..., &#x27;2020-01-18T09:00:00.000000000&#x27;,\n",
        "       &#x27;2020-01-19T09:00:00.000000000&#x27;, &#x27;2020-01-20T09:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7a3293d-3518-426c-84ca-d32e20a68701' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7a3293d-3518-426c-84ca-d32e20a68701' class='xr-section-summary' >Data variables: <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>analysed_sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42ebaf5e-b4cc-4048-8b0a-1cf164caeed8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42ebaf5e-b4cc-4048-8b0a-1cf164caeed8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bdc0a59-a761-431e-8fcf-faee921a55cf' class='xr-var-data-in' type='checkbox'><label for='data-9bdc0a59-a761-431e-8fcf-faee921a55cf' 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>comment :</span></dt><dd>&quot;Final&quot; version using Multi-Resolution Variational Analysis (MRVA) method for interpolation</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>-32767</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>analysis_error</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b77af259-3211-4e26-a1f7-b3a83a55ea20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b77af259-3211-4e26-a1f7-b3a83a55ea20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74ce1a7a-890b-46f9-a33d-20ecf0f2aa74' class='xr-var-data-in' type='checkbox'><label for='data-74ce1a7a-890b-46f9-a33d-20ecf0f2aa74' 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>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>estimated error standard deviation of analysed_sst</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-835dff86-35f8-4939-b1a8-d42261b89e97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-835dff86-35f8-4939-b1a8-d42261b89e97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f79ff98f-df84-41cd-945a-61fb1db63913' class='xr-var-data-in' type='checkbox'><label for='data-f79ff98f-df84-41cd-945a-61fb1db63913' 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>comment :</span></dt><dd>mask can be used to further filter the data.</dd><dt><span>flag_masks :</span></dt><dd>[1, 2, 4, 8, 16]</dd><dt><span>flag_meanings :</span></dt><dd>1=open-sea, 2=land, 5=open-lake, 9=open-sea with ice in the grid, 13=open-lake with ice in the grid</dd><dt><span>flag_values :</span></dt><dd>[1, 2, 5, 9, 13]</dd><dt><span>long_name :</span></dt><dd>sea/land field composite mask</dd><dt><span>source :</span></dt><dd>GMT &quot;grdlandmask&quot;, ice flag from sea_ice_fraction data</dd><dt><span>valid_max :</span></dt><dd>31</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_ice_fraction</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f321a0e8-c8f4-4d6d-979b-873a11e1ca92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f321a0e8-c8f4-4d6d-979b-873a11e1ca92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66b94105-7db9-474d-9ec0-33cc4d7ddc9c' class='xr-var-data-in' type='checkbox'><label for='data-66b94105-7db9-474d-9ec0-33cc4d7ddc9c' 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>comment :</span></dt><dd>ice data interpolated by a nearest neighbor approach.</dd><dt><span>long_name :</span></dt><dd>sea ice area fraction</dd><dt><span>source :</span></dt><dd>EUMETSAT OSI-SAF, copyright EUMETSAT</dd><dt><span>standard_name :</span></dt><dd>sea ice area fraction</dd><dt><span>units :</span></dt><dd>fraction (between 0 and 1)</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9343d203-d959-48be-93f4-4df35b981995' class='xr-section-summary-in' type='checkbox'  ><label for='section-9343d203-d959-48be-93f4-4df35b981995' 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>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dcbb9580-0869-4424-9cbe-d9a4faf4f604' class='xr-index-data-in' type='checkbox'/><label for='index-dcbb9580-0869-4424-9cbe-d9a4faf4f604' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e0b0bc0-b608-45f6-bf16-3c9a2070fa32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8e0b0bc0-b608-45f6-bf16-3c9a2070fa32' class='xr-section-summary' >Data variables: <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>analysed_sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-711fd80f-7905-44e7-bb89-a67bc5258da0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-711fd80f-7905-44e7-bb89-a67bc5258da0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c610dd35-89ea-4f71-aabe-379c440e75fc' class='xr-var-data-in' type='checkbox'><label for='data-c610dd35-89ea-4f71-aabe-379c440e75fc' 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>comment :</span></dt><dd>&quot;Final&quot; version using Multi-Resolution Variational Analysis (MRVA) method for interpolation</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>-32767</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>analysis_error</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c086f87-d957-4e40-ab45-5c8836ba4ee7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c086f87-d957-4e40-ab45-5c8836ba4ee7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32ed3363-2d88-4d92-932e-2f161453705a' class='xr-var-data-in' type='checkbox'><label for='data-32ed3363-2d88-4d92-932e-2f161453705a' 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>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>estimated error standard deviation of analysed_sst</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c5fbab5-7c9b-4b10-87f0-01970afee89b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c5fbab5-7c9b-4b10-87f0-01970afee89b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c58a995-d1ad-4e9d-9500-b35cbd3d6fb6' class='xr-var-data-in' type='checkbox'><label for='data-1c58a995-d1ad-4e9d-9500-b35cbd3d6fb6' 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>comment :</span></dt><dd>mask can be used to further filter the data.</dd><dt><span>flag_masks :</span></dt><dd>[1, 2, 4, 8, 16]</dd><dt><span>flag_meanings :</span></dt><dd>1=open-sea, 2=land, 5=open-lake, 9=open-sea with ice in the grid, 13=open-lake with ice in the grid</dd><dt><span>flag_values :</span></dt><dd>[1, 2, 5, 9, 13]</dd><dt><span>long_name :</span></dt><dd>sea/land field composite mask</dd><dt><span>source :</span></dt><dd>GMT &quot;grdlandmask&quot;, ice flag from sea_ice_fraction data</dd><dt><span>valid_max :</span></dt><dd>31</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_ice_fraction</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b4c2e5ab-272c-4d89-bebc-02d93b0c1c32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4c2e5ab-272c-4d89-bebc-02d93b0c1c32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f1ce93-8eec-42b8-9d25-64bf98357976' class='xr-var-data-in' type='checkbox'><label for='data-05f1ce93-8eec-42b8-9d25-64bf98357976' 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>comment :</span></dt><dd>ice data interpolated by a nearest neighbor approach.</dd><dt><span>long_name :</span></dt><dd>sea ice area fraction</dd><dt><span>source :</span></dt><dd>EUMETSAT OSI-SAF, copyright EUMETSAT</dd><dt><span>standard_name :</span></dt><dd>sea ice area fraction</dd><dt><span>units :</span></dt><dd>fraction (between 0 and 1)</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[4174832052000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0490d458-fe44-460d-b562-32424e27b899' class='xr-section-summary-in' type='checkbox'  ><label for='section-0490d458-fe44-460d-b562-32424e27b899' 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>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14923655-c8ff-4041-8858-4e2b4469f4fd' class='xr-index-data-in' type='checkbox'/><label for='index-14923655-c8ff-4041-8858-4e2b4469f4fd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
        "       -89.95999908447266, -89.94999694824219, -89.94000244140625,\n",
        "       -89.93000030517578, -89.91999816894531, -89.91000366210938,\n",
        "        -89.9000015258789,\n",
@@ -431,7 +431,7 @@
        "        89.93000030517578,  89.94000244140625,  89.94999694824219,\n",
        "        89.95999908447266,  89.97000122070312,   89.9800033569336,\n",
        "        89.98999786376953],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5e3f7d34-e87f-4822-adac-49acbea820d5' class='xr-index-data-in' type='checkbox'/><label for='index-5e3f7d34-e87f-4822-adac-49acbea820d5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0daa01cc-1eea-4670-a08f-e1374d7f3a55' class='xr-index-data-in' type='checkbox'/><label for='index-0daa01cc-1eea-4670-a08f-e1374d7f3a55' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
        "        -179.9600067138672,  -179.9499969482422, -179.94000244140625,\n",
        "       -179.92999267578125,  -179.9199981689453, -179.91000366210938,\n",
        "       -179.89999389648438,\n",
@@ -440,7 +440,7 @@
        "        179.94000244140625,   179.9499969482422,   179.9600067138672,\n",
        "        179.97000122070312,  179.97999572753906,  179.99000549316406,\n",
        "                     180.0],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1cb8fa85-ed17-42d9-af27-7f47ee5e9298' class='xr-index-data-in' type='checkbox'/><label for='index-1cb8fa85-ed17-42d9-af27-7f47ee5e9298' 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;2002-06-01 09:00:00&#x27;, &#x27;2002-06-02 09:00:00&#x27;,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2077c4e-76ad-467b-94bf-7a972b57956e' class='xr-index-data-in' type='checkbox'/><label for='index-a2077c4e-76ad-467b-94bf-7a972b57956e' 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;2002-06-01 09:00:00&#x27;, &#x27;2002-06-02 09:00:00&#x27;,\n",
        "               &#x27;2002-06-03 09:00:00&#x27;, &#x27;2002-06-04 09:00:00&#x27;,\n",
        "               &#x27;2002-06-05 09:00:00&#x27;, &#x27;2002-06-06 09:00:00&#x27;,\n",
        "               &#x27;2002-06-07 09:00:00&#x27;, &#x27;2002-06-08 09:00:00&#x27;,\n",
@@ -451,7 +451,7 @@
        "               &#x27;2020-01-15 09:00:00&#x27;, &#x27;2020-01-16 09:00:00&#x27;,\n",
        "               &#x27;2020-01-17 09:00:00&#x27;, &#x27;2020-01-18 09:00:00&#x27;,\n",
        "               &#x27;2020-01-19 09:00:00&#x27;, &#x27;2020-01-20 09:00:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=6443, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55cded82-061c-4b06-81c8-ccab7db1ed8a' class='xr-section-summary-in' type='checkbox'  ><label for='section-55cded82-061c-4b06-81c8-ccab7db1ed8a' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Observation Dataset v1.0</dd><dt><span>acknowledgment :</span></dt><dd>Please acknowledge the use of these data with the following statement:  These data were provided by JPL under support by NASA MEaSUREs program.</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd>MUR = &quot;Multi-scale Ultra-high Resolution&quot;</dd><dt><span>creator_email :</span></dt><dd>ghrsst@podaac.jpl.nasa.gov</dd><dt><span>creator_name :</span></dt><dd>JPL MUR SST project</dd><dt><span>creator_url :</span></dt><dd>http://mur.jpl.nasa.gov</dd><dt><span>date_created :</span></dt><dd>20200124T010755Z</dd><dt><span>easternmost_longitude :</span></dt><dd>180.0</dd><dt><span>file_quality_level :</span></dt><dd>3</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees north</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees east</dd><dt><span>history :</span></dt><dd>created at nominal 4-day latency; replaced nrt (1-day latency) version.</dd><dt><span>id :</span></dt><dd>MUR-JPL-L4-GLOB-v04.1</dd><dt><span>institution :</span></dt><dd>Jet Propulsion Laboratory</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>These data are available free of charge under data policy of JPL PO.DAAC.</dd><dt><span>metadata_link :</span></dt><dd>http://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&amp;shortName=MUR-JPL-L4-GLOB-v04.1</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>netcdf_version_id :</span></dt><dd>4.1</dd><dt><span>northernmost_latitude :</span></dt><dd>90.0</dd><dt><span>platform :</span></dt><dd>Terra, Aqua, GCOM-W, MetOp-A, MetOp-B, Buoys/Ships</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>product_version :</span></dt><dd>04.1</dd><dt><span>project :</span></dt><dd>NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Program</dd><dt><span>publisher_email :</span></dt><dd>ghrsst-po@nceo.ac.uk</dd><dt><span>publisher_name :</span></dt><dd>GHRSST Project Office</dd><dt><span>publisher_url :</span></dt><dd>http://www.ghrsst.org</dd><dt><span>references :</span></dt><dd>http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SST</dd><dt><span>sensor :</span></dt><dd>MODIS, AMSR2, AVHRR, in-situ</dd><dt><span>source :</span></dt><dd>MODIS_T-JPL, MODIS_A-JPL, AMSR2-REMSS, AVHRRMTA_G-NAVO, AVHRRMTB_G-NAVO, iQUAM-NOAA/NESDIS, Ice_Conc-OSISAF</dd><dt><span>southernmost_latitude :</span></dt><dd>-90.0</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degrees</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>start_time :</span></dt><dd>20200116T090000Z</dd><dt><span>stop_time :</span></dt><dd>20200116T090000Z</dd><dt><span>summary :</span></dt><dd>A merged, multi-sensor L4 Foundation SST analysis product from JPL.</dd><dt><span>time_coverage_end :</span></dt><dd>20200116T210000Z</dd><dt><span>time_coverage_start :</span></dt><dd>20200115T210000Z</dd><dt><span>title :</span></dt><dd>Daily MUR SST, Final product</dd><dt><span>uuid :</span></dt><dd>27665bc0-d5fc-11e1-9b23-0800200c9a66</dd><dt><span>westernmost_longitude :</span></dt><dd>-180.0</dd></dl></div></li></ul></div></div>"
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=6443, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30451db9-6545-4bc8-8fa8-a4c5507d42f5' class='xr-section-summary-in' type='checkbox'  ><label for='section-30451db9-6545-4bc8-8fa8-a4c5507d42f5' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Observation Dataset v1.0</dd><dt><span>acknowledgment :</span></dt><dd>Please acknowledge the use of these data with the following statement:  These data were provided by JPL under support by NASA MEaSUREs program.</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd>MUR = &quot;Multi-scale Ultra-high Resolution&quot;</dd><dt><span>creator_email :</span></dt><dd>ghrsst@podaac.jpl.nasa.gov</dd><dt><span>creator_name :</span></dt><dd>JPL MUR SST project</dd><dt><span>creator_url :</span></dt><dd>http://mur.jpl.nasa.gov</dd><dt><span>date_created :</span></dt><dd>20200124T010755Z</dd><dt><span>easternmost_longitude :</span></dt><dd>180.0</dd><dt><span>file_quality_level :</span></dt><dd>3</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees north</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.009999999776482582</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees east</dd><dt><span>history :</span></dt><dd>created at nominal 4-day latency; replaced nrt (1-day latency) version.</dd><dt><span>id :</span></dt><dd>MUR-JPL-L4-GLOB-v04.1</dd><dt><span>institution :</span></dt><dd>Jet Propulsion Laboratory</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>These data are available free of charge under data policy of JPL PO.DAAC.</dd><dt><span>metadata_link :</span></dt><dd>http://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&amp;shortName=MUR-JPL-L4-GLOB-v04.1</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>netcdf_version_id :</span></dt><dd>4.1</dd><dt><span>northernmost_latitude :</span></dt><dd>90.0</dd><dt><span>platform :</span></dt><dd>Terra, Aqua, GCOM-W, MetOp-A, MetOp-B, Buoys/Ships</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>product_version :</span></dt><dd>04.1</dd><dt><span>project :</span></dt><dd>NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Program</dd><dt><span>publisher_email :</span></dt><dd>ghrsst-po@nceo.ac.uk</dd><dt><span>publisher_name :</span></dt><dd>GHRSST Project Office</dd><dt><span>publisher_url :</span></dt><dd>http://www.ghrsst.org</dd><dt><span>references :</span></dt><dd>http://podaac.jpl.nasa.gov/Multi-scale_Ultra-high_Resolution_MUR-SST</dd><dt><span>sensor :</span></dt><dd>MODIS, AMSR2, AVHRR, in-situ</dd><dt><span>source :</span></dt><dd>MODIS_T-JPL, MODIS_A-JPL, AMSR2-REMSS, AVHRRMTA_G-NAVO, AVHRRMTB_G-NAVO, iQUAM-NOAA/NESDIS, Ice_Conc-OSISAF</dd><dt><span>southernmost_latitude :</span></dt><dd>-90.0</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degrees</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>start_time :</span></dt><dd>20200116T090000Z</dd><dt><span>stop_time :</span></dt><dd>20200116T090000Z</dd><dt><span>summary :</span></dt><dd>A merged, multi-sensor L4 Foundation SST analysis product from JPL.</dd><dt><span>time_coverage_end :</span></dt><dd>20200116T210000Z</dd><dt><span>time_coverage_start :</span></dt><dd>20200115T210000Z</dd><dt><span>title :</span></dt><dd>Daily MUR SST, Final product</dd><dt><span>uuid :</span></dt><dd>27665bc0-d5fc-11e1-9b23-0800200c9a66</dd><dt><span>westernmost_longitude :</span></dt><dd>-180.0</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 117TB\n",
@@ -881,11 +881,11 @@
        "    standard_name:  sea_surface_foundation_temperature\n",
        "    units:          kelvin\n",
        "    valid_max:      32767\n",
-       "    valid_min:      -32767</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'analysed_sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 6443</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-48b80a33-47ac-4bf6-aae2-11de1cdc9cd8' class='xr-array-in' type='checkbox' checked><label for='section-48b80a33-47ac-4bf6-aae2-11de1cdc9cd8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[4174832052000 values with dtype=float64]</pre></div></div></li><li class='xr-section-item'><input id='section-d40dc7c4-a337-4642-a9cb-054dd88064f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d40dc7c4-a337-4642-a9cb-054dd88064f5' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-a66d6c27-79bd-42df-b4c8-6367e854418b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a66d6c27-79bd-42df-b4c8-6367e854418b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d1c18fd-b1bf-4d72-b434-860e1e24bba3' class='xr-var-data-in' type='checkbox'><label for='data-9d1c18fd-b1bf-4d72-b434-860e1e24bba3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-6772989f-72dd-4bdd-91c6-ced688959e1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6772989f-72dd-4bdd-91c6-ced688959e1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11072c09-f2af-4ee1-9a72-e361f350e1cb' class='xr-var-data-in' type='checkbox'><label for='data-11072c09-f2af-4ee1-9a72-e361f350e1cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-06-01T09:00:00 ... 2020-01-...</div><input id='attrs-e07a4e7b-44cc-4904-ba2a-b68987bbff94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e07a4e7b-44cc-4904-ba2a-b68987bbff94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d82ce52-e25d-4ab7-83d2-d001fb2af05a' class='xr-var-data-in' type='checkbox'><label for='data-0d82ce52-e25d-4ab7-83d2-d001fb2af05a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>comment :</span></dt><dd>Nominal time of analyzed fields</dd><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-06-01T09:00:00.000000000&#x27;, &#x27;2002-06-02T09:00:00.000000000&#x27;,\n",
+       "    valid_min:      -32767</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'analysed_sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 6443</li><li><span class='xr-has-index'>lat</span>: 17999</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f27a240e-c6d7-4f49-9299-4c0e17417862' class='xr-array-in' type='checkbox' checked><label for='section-f27a240e-c6d7-4f49-9299-4c0e17417862' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[4174832052000 values with dtype=float64]</pre></div></div></li><li class='xr-section-item'><input id='section-1678d7c8-ee76-4561-8eb2-05cffd56ca59' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1678d7c8-ee76-4561-8eb2-05cffd56ca59' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.99 -89.98 ... 89.98 89.99</div><input id='attrs-08ac1e68-d2b3-43c4-aa87-21baf3ed855f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08ac1e68-d2b3-43c4-aa87-21baf3ed855f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1ac9c79-e303-4995-b4a3-9ef72772d5ce' class='xr-var-data-in' type='checkbox'><label for='data-a1ac9c79-e303-4995-b4a3-9ef72772d5ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-89.99, -89.98, -89.97, ...,  89.97,  89.98,  89.99], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-477d57dc-c68d-4da1-b5cb-576dec39dff7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-477d57dc-c68d-4da1-b5cb-576dec39dff7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32021e7a-8a9b-4cc2-9788-082de1997603' class='xr-var-data-in' type='checkbox'><label for='data-32021e7a-8a9b-4cc2-9788-082de1997603' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.99, -179.98, -179.97, ...,  179.98,  179.99,  180.  ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-06-01T09:00:00 ... 2020-01-...</div><input id='attrs-4613af57-ff59-4e19-8bbb-6cde352ba709' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4613af57-ff59-4e19-8bbb-6cde352ba709' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f6107a7-320a-4bcb-9500-346c704df9a4' class='xr-var-data-in' type='checkbox'><label for='data-3f6107a7-320a-4bcb-9500-346c704df9a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>comment :</span></dt><dd>Nominal time of analyzed fields</dd><dt><span>long_name :</span></dt><dd>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-06-01T09:00:00.000000000&#x27;, &#x27;2002-06-02T09:00:00.000000000&#x27;,\n",
        "       &#x27;2002-06-03T09:00:00.000000000&#x27;, ..., &#x27;2020-01-18T09:00:00.000000000&#x27;,\n",
        "       &#x27;2020-01-19T09:00:00.000000000&#x27;, &#x27;2020-01-20T09:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1de61402-443d-4379-9dcb-e9fb6cc1f793' class='xr-section-summary-in' type='checkbox'  ><label for='section-1de61402-443d-4379-9dcb-e9fb6cc1f793' 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>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-20e21362-300c-4e1a-8008-05c7b3d2d0af' class='xr-index-data-in' type='checkbox'/><label for='index-20e21362-300c-4e1a-8008-05c7b3d2d0af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ba35f82-bf57-487a-a06c-8547b3c7c061' class='xr-section-summary-in' type='checkbox'  ><label for='section-3ba35f82-bf57-487a-a06c-8547b3c7c061' 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>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9359c295-1573-4eee-8411-1162ba1ce4fb' class='xr-index-data-in' type='checkbox'/><label for='index-9359c295-1573-4eee-8411-1162ba1ce4fb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.98999786376953,  -89.9800033569336, -89.97000122070312,\n",
        "       -89.95999908447266, -89.94999694824219, -89.94000244140625,\n",
        "       -89.93000030517578, -89.91999816894531, -89.91000366210938,\n",
        "        -89.9000015258789,\n",
@@ -894,7 +894,7 @@
        "        89.93000030517578,  89.94000244140625,  89.94999694824219,\n",
        "        89.95999908447266,  89.97000122070312,   89.9800033569336,\n",
        "        89.98999786376953],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6249f900-0884-41c0-8b65-54cf583c9ae0' class='xr-index-data-in' type='checkbox'/><label for='index-6249f900-0884-41c0-8b65-54cf583c9ae0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=17999))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-370279f3-b71c-4507-8186-277168025ed5' class='xr-index-data-in' type='checkbox'/><label for='index-370279f3-b71c-4507-8186-277168025ed5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99000549316406, -179.97999572753906, -179.97000122070312,\n",
        "        -179.9600067138672,  -179.9499969482422, -179.94000244140625,\n",
        "       -179.92999267578125,  -179.9199981689453, -179.91000366210938,\n",
        "       -179.89999389648438,\n",
@@ -903,7 +903,7 @@
        "        179.94000244140625,   179.9499969482422,   179.9600067138672,\n",
        "        179.97000122070312,  179.97999572753906,  179.99000549316406,\n",
        "                     180.0],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9a7ec8f4-52dd-457e-8b2d-8eda3c67af72' class='xr-index-data-in' type='checkbox'/><label for='index-9a7ec8f4-52dd-457e-8b2d-8eda3c67af72' 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;2002-06-01 09:00:00&#x27;, &#x27;2002-06-02 09:00:00&#x27;,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c4be29e5-70f2-48e1-9446-9c93646f6043' class='xr-index-data-in' type='checkbox'/><label for='index-c4be29e5-70f2-48e1-9446-9c93646f6043' 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;2002-06-01 09:00:00&#x27;, &#x27;2002-06-02 09:00:00&#x27;,\n",
        "               &#x27;2002-06-03 09:00:00&#x27;, &#x27;2002-06-04 09:00:00&#x27;,\n",
        "               &#x27;2002-06-05 09:00:00&#x27;, &#x27;2002-06-06 09:00:00&#x27;,\n",
        "               &#x27;2002-06-07 09:00:00&#x27;, &#x27;2002-06-08 09:00:00&#x27;,\n",
@@ -914,7 +914,7 @@
        "               &#x27;2020-01-15 09:00:00&#x27;, &#x27;2020-01-16 09:00:00&#x27;,\n",
        "               &#x27;2020-01-17 09:00:00&#x27;, &#x27;2020-01-18 09:00:00&#x27;,\n",
        "               &#x27;2020-01-19 09:00:00&#x27;, &#x27;2020-01-20 09:00:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=6443, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9a8d0afb-0c5f-433d-8370-0722ce6f566e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a8d0afb-0c5f-433d-8370-0722ce6f566e' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>&quot;Final&quot; version using Multi-Resolution Variational Analysis (MRVA) method for interpolation</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>-32767</dd></dl></div></li></ul></div></div>"
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=6443, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a89bb85c-20e7-4a03-8fc3-842575fcfaee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a89bb85c-20e7-4a03-8fc3-842575fcfaee' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>&quot;Final&quot; version using Multi-Resolution Variational Analysis (MRVA) method for interpolation</dd><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_foundation_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>-32767</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'analysed_sst' (time: 6443, lat: 17999, lon: 36000)> Size: 33TB\n",
@@ -954,7 +954,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "bounds=(-179.99500549324037, -89.99499786365084, 180.0050000000763, 89.99499786365084) crs='http://www.opengis.net/def/crs/EPSG/0/4326' band_metadata=[] band_descriptions=[] dtype='float64' nodata_type='Nodata' colorinterp=None scales=None offsets=None colormap=None name='analysed_sst' count=1 width=36000 height=17999 attrs={'comment': '\"Final\" version using Multi-Resolution Variational Analysis (MRVA) method for interpolation', 'long_name': 'analysed sea surface temperature', 'standard_name': 'sea_surface_foundation_temperature', 'units': 'kelvin', 'valid_max': 32767, 'valid_min': -32767}\n",
+      "bounds=(-179.99500549324037, -89.99499786365084, 180.0050000000763, 89.99499786365084) crs='http://www.opengis.net/def/crs/EPSG/0/4326' band_metadata=[('b1', {})] band_descriptions=[('b1', 'value')] dtype='float64' nodata_type='Nodata' colorinterp=None scales=None offsets=None colormap=None name='analysed_sst' count=1 width=36000 height=17999 attrs={'comment': '\"Final\" version using Multi-Resolution Variational Analysis (MRVA) method for interpolation', 'long_name': 'analysed sea surface temperature', 'standard_name': 'sea_surface_foundation_temperature', 'units': 'kelvin', 'valid_max': 32767, 'valid_min': -32767}\n",
       "0 6\n"
      ]
     }
@@ -980,6 +980,16 @@
    "id": "93d11d9c",
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x11aeca1f0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
     {
      "data": {
       "image/png": 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",
@@ -1006,7 +1016,17 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x11b6b6c40>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1033,7 +1053,17 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x11aeb80d0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1082,7 +1112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 8,
    "id": "07310f05",
    "metadata": {},
    "outputs": [
@@ -1489,11 +1519,11 @@
        "    key_variables:              land_surface_temperature\n",
        "    format_version:             CCI Data Standards v2.2\n",
        "    spatial_resolution:         0.01 degree\n",
-       "    doi:                        10.5285/785ef9d3965442669bff899540747e28</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-5cd70b5d-4c4d-49ca-ade7-7915f2e3f256' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5cd70b5d-4c4d-49ca-ade7-7915f2e3f256' 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>: 1</li><li><span class='xr-has-index'>lat</span>: 18000</li><li><span class='xr-has-index'>lon</span>: 36000</li><li><span>length_scale</span>: 1</li><li><span class='xr-has-index'>channel</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b57212b6-aa2a-4287-af76-60c50ced542b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b57212b6-aa2a-4287-af76-60c50ced542b' 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'>2020-11-01</div><input id='attrs-a5ca88b7-f496-4a07-98af-4e041d98b5fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5ca88b7-f496-4a07-98af-4e041d98b5fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d23829b-b27e-4cc7-aae8-565b589ef5e8' class='xr-var-data-in' type='checkbox'><label for='data-3d23829b-b27e-4cc7-aae8-565b589ef5e8' 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>reference time of file</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-11-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.98 ... 89.98 89.99</div><input id='attrs-974c55cf-2d1f-45b5-9d41-fa18f0150a52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-974c55cf-2d1f-45b5-9d41-fa18f0150a52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-074d9d29-3e04-4a58-8b59-055a85a26eff' class='xr-var-data-in' type='checkbox'><label for='data-074d9d29-3e04-4a58-8b59-055a85a26eff' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-89.995   , -89.985   , -89.975006, ...,  89.975   ,  89.98499 ,\n",
-       "        89.99499 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-6f817d06-9ef2-4539-abd4-a6f3e448b295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f817d06-9ef2-4539-abd4-a6f3e448b295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7568cf8e-d250-48b3-86c0-74686379f599' class='xr-var-data-in' type='checkbox'><label for='data-7568cf8e-d250-48b3-86c0-74686379f599' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-179.995  , -179.985  , -179.97499, ...,  179.975  ,  179.98499,\n",
-       "        179.995  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.0 12.0</div><input id='attrs-9366c12e-88a6-4caf-95ba-868804fae3ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9366c12e-88a6-4caf-95ba-868804fae3ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e123ea63-8b10-43f0-9690-6a65d8c46cf4' class='xr-var-data-in' type='checkbox'><label for='data-e123ea63-8b10-43f0-9690-6a65d8c46cf4' 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>channel wavelength in microns</dd><dt><span>units :</span></dt><dd>microns</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>15000</dd></dl></div><div class='xr-var-data'><pre>array([10.999001, 11.999001], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-625231e7-fca5-4fe3-a73d-7f6545ac02bb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-625231e7-fca5-4fe3-a73d-7f6545ac02bb' class='xr-section-summary' >Data variables: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>dtime</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ca6030f5-2978-4703-bd4b-76bbce4ca4cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca6030f5-2978-4703-bd4b-76bbce4ca4cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c4cc40c-9913-4af3-af60-5320f9ec2431' class='xr-var-data-in' type='checkbox'><label for='data-6c4cc40c-9913-4af3-af60-5320f9ec2431' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time difference from reference time</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>2592000.0</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satze</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1899dbd0-2d42-45fe-a63d-55c0177b87df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1899dbd0-2d42-45fe-a63d-55c0177b87df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71a6ee38-6cd1-483f-8c0f-53dec2235055' class='xr-var-data-in' type='checkbox'><label for='data-71a6ee38-6cd1-483f-8c0f-53dec2235055' 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>satellite zenith angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sataz</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4f33b00a-f768-4d5c-92ee-8a649e315f2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f33b00a-f768-4d5c-92ee-8a649e315f2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d34b14e9-aafe-459c-ad31-ad4412d9ec07' class='xr-var-data-in' type='checkbox'><label for='data-d34b14e9-aafe-459c-ad31-ad4412d9ec07' 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>satellite azimuth angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>-18000</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>solze</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c593a712-21f9-44b2-a466-19348aab4dd5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c593a712-21f9-44b2-a466-19348aab4dd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b292317-3e5a-4beb-be70-47b358701b3a' class='xr-var-data-in' type='checkbox'><label for='data-8b292317-3e5a-4beb-be70-47b358701b3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>solar zenith angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>solaz</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2b70b9df-3694-4f81-97cf-6f1f1d901741' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b70b9df-3694-4f81-97cf-6f1f1d901741' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13f28a6c-24ab-4851-ab4a-fa62088b77bf' class='xr-var-data-in' type='checkbox'><label for='data-13f28a6c-24ab-4851-ab4a-fa62088b77bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>solar azimuth angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>-18000</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cda2b077-0e50-4925-b6d4-f0c6161e5d72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cda2b077-0e50-4925-b6d4-f0c6161e5d72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-106e92ad-1ea0-4e43-a79c-e707cabb915b' class='xr-var-data-in' type='checkbox'><label for='data-106e92ad-1ea0-4e43-a79c-e707cabb915b' 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>land surface temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-8315</dd><dt><span>valid_max :</span></dt><dd>7685</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_uncertainty</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-045c94c5-2251-4221-938a-1102561f8275' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-045c94c5-2251-4221-938a-1102561f8275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dadd5431-a03d-435a-a15c-31876cc0b2ad' class='xr-var-data-in' type='checkbox'><label for='data-dadd5431-a03d-435a-a15c-31876cc0b2ad' 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>land surface temperature total uncertainty</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_ran</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-025291e0-4969-4ce4-a516-3404829a34ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-025291e0-4969-4ce4-a516-3404829a34ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e10b2bc6-aec4-451c-9539-1c255038e737' class='xr-var-data-in' type='checkbox'><label for='data-e10b2bc6-aec4-451c-9539-1c255038e737' 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>uncertainty from uncorrelated errors</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_atm</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0adce70a-c4bd-41e1-8a6c-5bbb4574e1c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0adce70a-c4bd-41e1-8a6c-5bbb4574e1c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8876e349-a89d-4467-9f2c-d5685bb0805e' class='xr-var-data-in' type='checkbox'><label for='data-8876e349-a89d-4467-9f2c-d5685bb0805e' 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>uncertainty from locally correlated errors on atmospheric scales</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_sfc</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6c5bef72-d8a6-4352-a16b-472f03462aae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c5bef72-d8a6-4352-a16b-472f03462aae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52c842c8-1b07-48a9-b5c2-debe241c3b62' class='xr-var-data-in' type='checkbox'><label for='data-52c842c8-1b07-48a9-b5c2-debe241c3b62' 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>uncertainty from locally correlated errors on surface scales</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_sys</span></div><div class='xr-var-dims'>(length_scale)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0a13ec36-ffb2-4219-b85d-3d5543b8a281' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a13ec36-ffb2-4219-b85d-3d5543b8a281' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-435ef39e-6659-4433-b5b2-0f146010a51f' class='xr-var-data-in' type='checkbox'><label for='data-435ef39e-6659-4433-b5b2-0f146010a51f' 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>uncertainty from large-scale systematic errors</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lcc</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b83d3e4a-2d9f-4d69-b88d-57bfce11ad9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b83d3e4a-2d9f-4d69-b88d-57bfce11ad9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54c0b5ec-bbc4-4d36-8693-102e16316436' class='xr-var-data-in' type='checkbox'><label for='data-54c0b5ec-bbc4-4d36-8693-102e16316436' 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>land cover class</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>flag_meanings :</span></dt><dd>cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban Bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Unconsolidated_bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Consolidated_bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Bare_areas_of_soil_type_Entisols_Orthents Bare_areas_of_soil_type_Shifting_sand Bare_areas_of_soil_type_Aridisols_Calcids Bare_areas_of_soil_type_Aridisols_Cambids Bare_areas_of_soil_type_Gelisols_Orthels water snow_and_ice Sea_ice</dd><dt><span>flag_values :</span></dt><dd>[ 10  11  12  20  30  40  50  60  61  62  70  71  72  80  81  82  90 100\n",
+       "    doi:                        10.5285/785ef9d3965442669bff899540747e28</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-839ce964-c57d-4277-ac3a-bfe3ebca6adf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-839ce964-c57d-4277-ac3a-bfe3ebca6adf' 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>: 1</li><li><span class='xr-has-index'>lat</span>: 18000</li><li><span class='xr-has-index'>lon</span>: 36000</li><li><span>length_scale</span>: 1</li><li><span class='xr-has-index'>channel</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-03c30c95-a48f-460a-b38f-e5a648002200' class='xr-section-summary-in' type='checkbox'  checked><label for='section-03c30c95-a48f-460a-b38f-e5a648002200' 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'>2020-11-01</div><input id='attrs-e03d6bb2-c46e-4340-9d1c-57ae6505f23e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e03d6bb2-c46e-4340-9d1c-57ae6505f23e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07b93e5e-16f8-46da-a45f-b12e71c8e321' class='xr-var-data-in' type='checkbox'><label for='data-07b93e5e-16f8-46da-a45f-b12e71c8e321' 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>reference time of file</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-11-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.98 ... 89.98 89.99</div><input id='attrs-dce01655-dd8b-41f4-b748-ed56d260bcb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce01655-dd8b-41f4-b748-ed56d260bcb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-294db271-7de6-4a40-ab4b-ddb42f59f4b7' class='xr-var-data-in' type='checkbox'><label for='data-294db271-7de6-4a40-ab4b-ddb42f59f4b7' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-89.995   , -89.985   , -89.975006, ...,  89.975   ,  89.98499 ,\n",
+       "        89.99499 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-e00d089f-a057-40a2-9757-b66f02b7281b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e00d089f-a057-40a2-9757-b66f02b7281b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c84f12c7-2863-4209-9722-8aab07aba4f9' class='xr-var-data-in' type='checkbox'><label for='data-c84f12c7-2863-4209-9722-8aab07aba4f9' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-179.995  , -179.985  , -179.97499, ...,  179.975  ,  179.98499,\n",
+       "        179.995  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.0 12.0</div><input id='attrs-40f94035-5f20-4d21-bff4-d614b6bca6b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40f94035-5f20-4d21-bff4-d614b6bca6b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2eb3f67f-ebd5-4a58-91f0-91fbfad87018' class='xr-var-data-in' type='checkbox'><label for='data-2eb3f67f-ebd5-4a58-91f0-91fbfad87018' 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>channel wavelength in microns</dd><dt><span>units :</span></dt><dd>microns</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>15000</dd></dl></div><div class='xr-var-data'><pre>array([10.999001, 11.999001], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24d14f43-c8f5-43dd-9962-88e07433ad57' class='xr-section-summary-in' type='checkbox'  checked><label for='section-24d14f43-c8f5-43dd-9962-88e07433ad57' class='xr-section-summary' >Data variables: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>dtime</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ecec4757-f673-4445-b4d7-95ccbcfebec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecec4757-f673-4445-b4d7-95ccbcfebec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64e79ed3-3b1a-4a53-8a8a-cb7b689e6b1d' class='xr-var-data-in' type='checkbox'><label for='data-64e79ed3-3b1a-4a53-8a8a-cb7b689e6b1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time difference from reference time</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>2592000.0</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satze</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f4303fca-d18c-4d91-99cb-d5de8dac073b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4303fca-d18c-4d91-99cb-d5de8dac073b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d8102b9-5894-41de-b2f2-c1b262e04779' class='xr-var-data-in' type='checkbox'><label for='data-5d8102b9-5894-41de-b2f2-c1b262e04779' 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>satellite zenith angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sataz</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2e821b8a-b34f-4200-b47b-2c3f632ae2d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e821b8a-b34f-4200-b47b-2c3f632ae2d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40485991-4ce4-4fc6-ad88-1d842bdb27d1' class='xr-var-data-in' type='checkbox'><label for='data-40485991-4ce4-4fc6-ad88-1d842bdb27d1' 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>satellite azimuth angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>-18000</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>solze</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b0ab731-45c8-4cf6-a8a8-7985983e0551' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b0ab731-45c8-4cf6-a8a8-7985983e0551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1d883e1-7388-4242-bb8a-5fcc8ce404e0' class='xr-var-data-in' type='checkbox'><label for='data-c1d883e1-7388-4242-bb8a-5fcc8ce404e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>solar zenith angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>solaz</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2f4d38df-8093-4961-b8d7-cf1b5bc40028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f4d38df-8093-4961-b8d7-cf1b5bc40028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b05eb386-50d3-4238-98ed-d32f98292130' class='xr-var-data-in' type='checkbox'><label for='data-b05eb386-50d3-4238-98ed-d32f98292130' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>solar azimuth angle</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_min :</span></dt><dd>-18000</dd><dt><span>valid_max :</span></dt><dd>18000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d511a63d-0fc6-4d65-9d55-0da53ec9a9a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d511a63d-0fc6-4d65-9d55-0da53ec9a9a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-544e7ebc-bb72-4af4-b7c1-811273c9aec4' class='xr-var-data-in' type='checkbox'><label for='data-544e7ebc-bb72-4af4-b7c1-811273c9aec4' 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>land surface temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-8315</dd><dt><span>valid_max :</span></dt><dd>7685</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_uncertainty</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-354abfe4-7f32-4bf9-a4cb-34f26d0fd897' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-354abfe4-7f32-4bf9-a4cb-34f26d0fd897' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c29de369-458b-44bd-8d46-da60ebe258c4' class='xr-var-data-in' type='checkbox'><label for='data-c29de369-458b-44bd-8d46-da60ebe258c4' 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>land surface temperature total uncertainty</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_ran</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6c266996-f574-4af2-a9c8-6373bfb9c9ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c266996-f574-4af2-a9c8-6373bfb9c9ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e67d356-6061-459c-a821-d556cbf0f470' class='xr-var-data-in' type='checkbox'><label for='data-8e67d356-6061-459c-a821-d556cbf0f470' 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>uncertainty from uncorrelated errors</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_atm</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1b74b0d8-d911-433a-9a8c-f5894d2352a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b74b0d8-d911-433a-9a8c-f5894d2352a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9624be1c-25b8-4bb3-bdf1-a65ffcc9a878' class='xr-var-data-in' type='checkbox'><label for='data-9624be1c-25b8-4bb3-bdf1-a65ffcc9a878' 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>uncertainty from locally correlated errors on atmospheric scales</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_sfc</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0c74101a-6960-4b5a-91b3-024b77d6c8fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c74101a-6960-4b5a-91b3-024b77d6c8fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f2ffbde-4907-4b78-9abb-c112aeda0ed6' class='xr-var-data-in' type='checkbox'><label for='data-4f2ffbde-4907-4b78-9abb-c112aeda0ed6' 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>uncertainty from locally correlated errors on surface scales</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_sys</span></div><div class='xr-var-dims'>(length_scale)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3b2af2c1-ecbe-45dd-943b-cb91ba0c2ba3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b2af2c1-ecbe-45dd-943b-cb91ba0c2ba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86749b5b-ca37-4f0b-9a82-460f120a96c8' class='xr-var-data-in' type='checkbox'><label for='data-86749b5b-ca37-4f0b-9a82-460f120a96c8' 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>uncertainty from large-scale systematic errors</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lcc</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b3cd3cb2-5a5e-47be-bcbb-f94cfcf8e46c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3cd3cb2-5a5e-47be-bcbb-f94cfcf8e46c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13651c97-92e6-4153-9981-8254120acbf5' class='xr-var-data-in' type='checkbox'><label for='data-13651c97-92e6-4153-9981-8254120acbf5' 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>land cover class</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>flag_meanings :</span></dt><dd>cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban Bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Unconsolidated_bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Consolidated_bare_areas_of_soil_types_not_contained_in_biomes_203_to_207 Bare_areas_of_soil_type_Entisols_Orthents Bare_areas_of_soil_type_Shifting_sand Bare_areas_of_soil_type_Aridisols_Calcids Bare_areas_of_soil_type_Aridisols_Cambids Bare_areas_of_soil_type_Gelisols_Orthels water snow_and_ice Sea_ice</dd><dt><span>flag_values :</span></dt><dd>[ 10  11  12  20  30  40  50  60  61  62  70  71  72  80  81  82  90 100\n",
        " 110 120 121 122 130 140 150 151 152 153 160 170 180 190 200 201 202 203\n",
-       " 204 205 206 207 210 220 230]</dd><dt><span>valid_min :</span></dt><dd>10</dd><dt><span>valid_max :</span></dt><dd>230</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9fe45ba7-55ca-4594-8d8d-2399a2a24d0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fe45ba7-55ca-4594-8d8d-2399a2a24d0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1fb38cc-072c-42dc-bb84-a446dc098c9f' class='xr-var-data-in' type='checkbox'><label for='data-f1fb38cc-072c-42dc-bb84-a446dc098c9f' 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>number of clear-sky pixels</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18750</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_cor</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-43f7c014-5e76-44f6-9452-615e26adff5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43f7c014-5e76-44f6-9452-615e26adff5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f910388e-3cd3-49a4-8a46-4d21d25c5ed0' class='xr-var-data-in' type='checkbox'><label for='data-f910388e-3cd3-49a4-8a46-4d21d25c5ed0' 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>uncertainty from locally correlated errors on LST corrections</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c400579-7d97-4888-9493-67fdcb132aef' class='xr-section-summary-in' type='checkbox'  ><label for='section-8c400579-7d97-4888-9493-67fdcb132aef' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77b0632a-ed30-4e13-af90-c572df5ca3bc' class='xr-index-data-in' type='checkbox'/><label for='index-77b0632a-ed30-4e13-af90-c572df5ca3bc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-11-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6ceebf70-ee44-4ac2-8464-e5f19d4b6726' class='xr-index-data-in' type='checkbox'/><label for='index-6ceebf70-ee44-4ac2-8464-e5f19d4b6726' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99500274658203, -89.98500061035156, -89.97500610351562,\n",
+       " 204 205 206 207 210 220 230]</dd><dt><span>valid_min :</span></dt><dd>10</dd><dt><span>valid_max :</span></dt><dd>230</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1aebdcf6-90d4-4312-a33d-101c3dd8af36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1aebdcf6-90d4-4312-a33d-101c3dd8af36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4277e6c-afef-47df-bcf9-dda7b6b2487a' class='xr-var-data-in' type='checkbox'><label for='data-e4277e6c-afef-47df-bcf9-dda7b6b2487a' 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>number of clear-sky pixels</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>18750</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lst_unc_loc_cor</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-78443ea9-3887-4d5f-afe7-620db58aa79d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78443ea9-3887-4d5f-afe7-620db58aa79d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c9c1b79-cd57-4a53-a60a-e8ae12d354aa' class='xr-var-data-in' type='checkbox'><label for='data-4c9c1b79-cd57-4a53-a60a-e8ae12d354aa' 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>uncertainty from locally correlated errors on LST corrections</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[648000000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d239ee20-13c4-4144-9cd0-df9e86b83257' class='xr-section-summary-in' type='checkbox'  ><label for='section-d239ee20-13c4-4144-9cd0-df9e86b83257' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3b6d9efd-c434-4d28-b607-34537db0e349' class='xr-index-data-in' type='checkbox'/><label for='index-3b6d9efd-c434-4d28-b607-34537db0e349' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-11-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ab6f0417-5cfb-43fb-93a1-b1b296b1c726' class='xr-index-data-in' type='checkbox'/><label for='index-ab6f0417-5cfb-43fb-93a1-b1b296b1c726' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99500274658203, -89.98500061035156, -89.97500610351562,\n",
        "       -89.96500396728516, -89.95500183105469, -89.94499969482422,\n",
        "       -89.93500518798828, -89.92500305175781, -89.91500091552734,\n",
        "        -89.9050064086914,\n",
@@ -1502,7 +1532,7 @@
        "        89.93498992919922,  89.94499969482422,  89.95499420166016,\n",
        "         89.9649887084961,   89.9749984741211,  89.98499298095703,\n",
        "        89.99498748779297],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=18000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e5ea9408-df63-4236-b96e-e9ab901a1f11' class='xr-index-data-in' type='checkbox'/><label for='index-e5ea9408-df63-4236-b96e-e9ab901a1f11' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9949951171875, -179.98500061035156, -179.97499084472656,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=18000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-51edb797-0c09-4d3b-93a6-f94c79a45964' class='xr-index-data-in' type='checkbox'/><label for='index-51edb797-0c09-4d3b-93a6-f94c79a45964' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9949951171875, -179.98500061035156, -179.97499084472656,\n",
        "       -179.96499633789062,  -179.9550018310547,  -179.9449920654297,\n",
        "       -179.93499755859375, -179.92498779296875,  -179.9149932861328,\n",
        "       -179.90499877929688,\n",
@@ -1511,7 +1541,7 @@
        "        179.93499755859375,  179.94500732421875,  179.95498657226562,\n",
        "        179.96499633789062,  179.97500610351562,   179.9849853515625,\n",
        "         179.9949951171875],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-de1fe6b5-dded-4ce7-9383-9257ee58676f' class='xr-index-data-in' type='checkbox'/><label for='index-de1fe6b5-dded-4ce7-9383-9257ee58676f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([10.999001, 11.999001], dtype=&#x27;float32&#x27;, name=&#x27;channel&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7f1d2b2-6e4b-4c54-859b-0f693cdaf00b' class='xr-section-summary-in' type='checkbox'  ><label for='section-d7f1d2b2-6e4b-4c54-859b-0f693cdaf00b' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>source :</span></dt><dd>ESA LST CCI IRCDR L3S V2.00</dd><dt><span>title :</span></dt><dd>ESA LST CCI land surface temperature time series from multiple IR sensors on LEO platforms.</dd><dt><span>institution :</span></dt><dd>University of Leicester</dd><dt><span>history :</span></dt><dd>Created using software developed at University of Leicester</dd><dt><span>references :</span></dt><dd>https://climate.esa.int/en/projects/land-surface-temperature</dd><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>product_version :</span></dt><dd>2.00</dd><dt><span>summary :</span></dt><dd>This file contains level L3S global land surface temperatures from SLSTRA. L3S data are derived from more than one sensor combined on a space and/or time grid.</dd><dt><span>keywords :</span></dt><dd>Earth Science; Land Surface; Land Temperature; Land Surface Temperature</dd><dt><span>id :</span></dt><dd>ESACCI-LST-L3S-LST-IRCDR_-0.01deg_1MONTHLY_DAY-20201101000000-fv2.00.nc</dd><dt><span>naming_authority :</span></dt><dd>le.ac.uk</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global change Master Directory (GCMD) Science Keywords</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd>These data were produced as part of the ESA LST CCI project.</dd><dt><span>date_created :</span></dt><dd>20220616T135237Z</dd><dt><span>creator_name :</span></dt><dd>University of Leicester Surface Temperature Group</dd><dt><span>creator_url :</span></dt><dd>https://climate.esa.int/en/projects/land-surface-temperature</dd><dt><span>creator_email :</span></dt><dd>djg20@le.ac.uk</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.995</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.99499</dd><dt><span>geospatial_lon_min :</span></dt><dd>-179.995</dd><dt><span>geospatial_lon_max :</span></dt><dd>179.995</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>time_coverage_start :</span></dt><dd>20201101T000000</dd><dt><span>time_coverage_end :</span></dt><dd>20201130T235959</dd><dt><span>time_coverage_duration :</span></dt><dd>P1M</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1M</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v71</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>platform :</span></dt><dd>Sentinel-3A</dd><dt><span>sensor :</span></dt><dd>SLSTRA</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.01</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.01</dd><dt><span>key_variables :</span></dt><dd>land_surface_temperature</dd><dt><span>format_version :</span></dt><dd>CCI Data Standards v2.2</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degree</dd><dt><span>doi :</span></dt><dd>10.5285/785ef9d3965442669bff899540747e28</dd></dl></div></li></ul></div></div>"
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ebbd047b-6055-42e8-ae0d-d9415837a256' class='xr-index-data-in' type='checkbox'/><label for='index-ebbd047b-6055-42e8-ae0d-d9415837a256' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([10.999001, 11.999001], dtype=&#x27;float32&#x27;, name=&#x27;channel&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-839bb2f0-2f35-4387-ab8a-e5038c8f176c' class='xr-section-summary-in' type='checkbox'  ><label for='section-839bb2f0-2f35-4387-ab8a-e5038c8f176c' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>source :</span></dt><dd>ESA LST CCI IRCDR L3S V2.00</dd><dt><span>title :</span></dt><dd>ESA LST CCI land surface temperature time series from multiple IR sensors on LEO platforms.</dd><dt><span>institution :</span></dt><dd>University of Leicester</dd><dt><span>history :</span></dt><dd>Created using software developed at University of Leicester</dd><dt><span>references :</span></dt><dd>https://climate.esa.int/en/projects/land-surface-temperature</dd><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>product_version :</span></dt><dd>2.00</dd><dt><span>summary :</span></dt><dd>This file contains level L3S global land surface temperatures from SLSTRA. L3S data are derived from more than one sensor combined on a space and/or time grid.</dd><dt><span>keywords :</span></dt><dd>Earth Science; Land Surface; Land Temperature; Land Surface Temperature</dd><dt><span>id :</span></dt><dd>ESACCI-LST-L3S-LST-IRCDR_-0.01deg_1MONTHLY_DAY-20201101000000-fv2.00.nc</dd><dt><span>naming_authority :</span></dt><dd>le.ac.uk</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global change Master Directory (GCMD) Science Keywords</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd>These data were produced as part of the ESA LST CCI project.</dd><dt><span>date_created :</span></dt><dd>20220616T135237Z</dd><dt><span>creator_name :</span></dt><dd>University of Leicester Surface Temperature Group</dd><dt><span>creator_url :</span></dt><dd>https://climate.esa.int/en/projects/land-surface-temperature</dd><dt><span>creator_email :</span></dt><dd>djg20@le.ac.uk</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.995</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.99499</dd><dt><span>geospatial_lon_min :</span></dt><dd>-179.995</dd><dt><span>geospatial_lon_max :</span></dt><dd>179.995</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>time_coverage_start :</span></dt><dd>20201101T000000</dd><dt><span>time_coverage_end :</span></dt><dd>20201130T235959</dd><dt><span>time_coverage_duration :</span></dt><dd>P1M</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1M</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v71</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>platform :</span></dt><dd>Sentinel-3A</dd><dt><span>sensor :</span></dt><dd>SLSTRA</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.01</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.01</dd><dt><span>key_variables :</span></dt><dd>land_surface_temperature</dd><dt><span>format_version :</span></dt><dd>CCI Data Standards v2.2</dd><dt><span>spatial_resolution :</span></dt><dd>0.01 degree</dd><dt><span>doi :</span></dt><dd>10.5285/785ef9d3965442669bff899540747e28</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 36GB\n",
@@ -1553,7 +1583,7 @@
        "    doi:                        10.5285/785ef9d3965442669bff899540747e28"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1576,7 +1606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 9,
    "id": "62a7401c",
    "metadata": {},
    "outputs": [
@@ -1958,9 +1988,9 @@
        "    long_name:  land surface temperature\n",
        "    units:      kelvin\n",
        "    valid_min:  -8315\n",
-       "    valid_max:  7685</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'lst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 18000</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ddf60bd9-f566-4178-8744-99a2d3d5ed41' class='xr-array-in' type='checkbox' checked><label for='section-ddf60bd9-f566-4178-8744-99a2d3d5ed41' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[648000000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-8ebcd944-9f93-4aa8-8584-33fa425887c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8ebcd944-9f93-4aa8-8584-33fa425887c3' 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'>2020-11-01</div><input id='attrs-219203b8-b8cc-4865-ae6a-7563c424e76f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-219203b8-b8cc-4865-ae6a-7563c424e76f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f84ecb0c-a55a-4574-9c62-4291b1954286' class='xr-var-data-in' type='checkbox'><label for='data-f84ecb0c-a55a-4574-9c62-4291b1954286' 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>reference time of file</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-11-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.98 ... 89.98 89.99</div><input id='attrs-cf7730f2-cb10-4d3b-b7f3-1e87d6340155' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf7730f2-cb10-4d3b-b7f3-1e87d6340155' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a70aa97b-f6cb-40af-b627-9726c7a413cb' class='xr-var-data-in' type='checkbox'><label for='data-a70aa97b-f6cb-40af-b627-9726c7a413cb' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-89.995   , -89.985   , -89.975006, ...,  89.975   ,  89.98499 ,\n",
-       "        89.99499 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-538bb730-17d7-4328-9f77-829f4a9baa4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538bb730-17d7-4328-9f77-829f4a9baa4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8a95ad5-6255-44f7-9a62-676f7166ec6c' class='xr-var-data-in' type='checkbox'><label for='data-a8a95ad5-6255-44f7-9a62-676f7166ec6c' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-179.995  , -179.985  , -179.97499, ...,  179.975  ,  179.98499,\n",
-       "        179.995  ], dtype=float32)</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-3185c625-3f97-482d-b810-d99af539152f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3185c625-3f97-482d-b810-d99af539152f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-697fe02e-0b67-485b-8106-3b94b1c78c8d' class='xr-var-data-in' type='checkbox'><label for='data-697fe02e-0b67-485b-8106-3b94b1c78c8d' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</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>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</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-4c8c0096-c756-4e48-b387-beb232be6b0f' class='xr-section-summary-in' type='checkbox'  ><label for='section-4c8c0096-c756-4e48-b387-beb232be6b0f' 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-06fa601e-7ce4-484b-921a-b7d19cf96a7b' class='xr-index-data-in' type='checkbox'/><label for='index-06fa601e-7ce4-484b-921a-b7d19cf96a7b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-11-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b4c4dfa-cccf-4682-850c-72621f6317b5' class='xr-index-data-in' type='checkbox'/><label for='index-4b4c4dfa-cccf-4682-850c-72621f6317b5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99500274658203, -89.98500061035156, -89.97500610351562,\n",
+       "    valid_max:  7685</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'lst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 18000</li><li><span class='xr-has-index'>lon</span>: 36000</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-10d81318-add2-430c-aa41-1ea07c88cb3e' class='xr-array-in' type='checkbox' checked><label for='section-10d81318-add2-430c-aa41-1ea07c88cb3e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[648000000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-2af8b3c3-cea2-4268-8f86-819f20a33cff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2af8b3c3-cea2-4268-8f86-819f20a33cff' 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'>2020-11-01</div><input id='attrs-9aea1749-f83b-4cbb-8d28-a05e15316407' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9aea1749-f83b-4cbb-8d28-a05e15316407' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d951becd-505c-4dae-b508-e3192b7dff49' class='xr-var-data-in' type='checkbox'><label for='data-d951becd-505c-4dae-b508-e3192b7dff49' 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>reference time of file</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-11-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.98 ... 89.98 89.99</div><input id='attrs-3759960f-1b08-48d7-8bdf-ba8925712d54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3759960f-1b08-48d7-8bdf-ba8925712d54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cd95063-051d-4dac-b76c-50d21ccdb586' class='xr-var-data-in' type='checkbox'><label for='data-9cd95063-051d-4dac-b76c-50d21ccdb586' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-89.995   , -89.985   , -89.975006, ...,  89.975   ,  89.98499 ,\n",
+       "        89.99499 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-0553c09a-6e47-4f96-aab6-f7ef431ea597' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0553c09a-6e47-4f96-aab6-f7ef431ea597' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fdbfad3-3a88-4f75-b431-69a2a21a0394' class='xr-var-data-in' type='checkbox'><label for='data-2fdbfad3-3a88-4f75-b431-69a2a21a0394' 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_coordinates</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>array([-179.995  , -179.985  , -179.97499, ...,  179.975  ,  179.98499,\n",
+       "        179.995  ], dtype=float32)</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-81c4e227-92e0-4e82-9d1b-fd4ffcfd3f69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81c4e227-92e0-4e82-9d1b-fd4ffcfd3f69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5baafb91-1046-4340-a148-704506444f39' class='xr-var-data-in' type='checkbox'><label for='data-5baafb91-1046-4340-a148-704506444f39' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</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>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</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-382a30c9-7f39-4b5a-aa07-c5f341c8142d' class='xr-section-summary-in' type='checkbox'  ><label for='section-382a30c9-7f39-4b5a-aa07-c5f341c8142d' 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-38198a70-0016-4aed-bca3-aecf468ad86d' class='xr-index-data-in' type='checkbox'/><label for='index-38198a70-0016-4aed-bca3-aecf468ad86d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-11-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2aac6453-e116-4a8a-b918-b8aaa089074a' class='xr-index-data-in' type='checkbox'/><label for='index-2aac6453-e116-4a8a-b918-b8aaa089074a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99500274658203, -89.98500061035156, -89.97500610351562,\n",
        "       -89.96500396728516, -89.95500183105469, -89.94499969482422,\n",
        "       -89.93500518798828, -89.92500305175781, -89.91500091552734,\n",
        "        -89.9050064086914,\n",
@@ -1969,7 +1999,7 @@
        "        89.93498992919922,  89.94499969482422,  89.95499420166016,\n",
        "         89.9649887084961,   89.9749984741211,  89.98499298095703,\n",
        "        89.99498748779297],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=18000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c455156-5637-4501-9723-72588ec75167' class='xr-index-data-in' type='checkbox'/><label for='index-0c455156-5637-4501-9723-72588ec75167' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9949951171875, -179.98500061035156, -179.97499084472656,\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=18000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cad737ea-b88e-4c13-9c06-48010cac6885' class='xr-index-data-in' type='checkbox'/><label for='index-cad737ea-b88e-4c13-9c06-48010cac6885' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9949951171875, -179.98500061035156, -179.97499084472656,\n",
        "       -179.96499633789062,  -179.9550018310547,  -179.9449920654297,\n",
        "       -179.93499755859375, -179.92498779296875,  -179.9149932861328,\n",
        "       -179.90499877929688,\n",
@@ -1978,7 +2008,7 @@
        "        179.93499755859375,  179.94500732421875,  179.95498657226562,\n",
        "        179.96499633789062,  179.97500610351562,   179.9849853515625,\n",
        "         179.9949951171875],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9e28c9b5-46e7-4edb-a788-7705e2277004' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e28c9b5-46e7-4edb-a788-7705e2277004' 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>long_name :</span></dt><dd>land surface temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-8315</dd><dt><span>valid_max :</span></dt><dd>7685</dd></dl></div></li></ul></div></div>"
+       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=36000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7acf8784-685e-4740-ab82-48ae130d09d5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7acf8784-685e-4740-ab82-48ae130d09d5' 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>long_name :</span></dt><dd>land surface temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-8315</dd><dt><span>valid_max :</span></dt><dd>7685</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'lst' (time: 1, lat: 18000, lon: 36000)> Size: 3GB\n",
@@ -1995,7 +2025,7 @@
        "    valid_max:  7685"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2014,7 +2044,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 10,
    "id": "6b69430d",
    "metadata": {},
    "outputs": [
@@ -2035,17 +2065,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 11,
    "id": "c9678aa9",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x13cc0c3a0>"
+       "<matplotlib.image.AxesImage at 0x11b0d3e20>"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2070,7 +2100,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a29c1282",
+   "id": "665d34ba",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/rio_tiler/io/xarray.py b/rio_tiler/io/xarray.py
index d8916d62..6d7cc346 100644
--- a/rio_tiler/io/xarray.py
+++ b/rio_tiler/io/xarray.py
@@ -239,6 +239,11 @@ def tile(
         arr = ds.to_masked_array()
         arr.mask |= arr.data == ds.rio.nodata
 
+        output_bounds = ds.rio._unordered_bounds()
+        if output_bounds[1] > output_bounds[3] and ds.rio.transform().e > 0:
+            yaxis = self.input.dims.index(self.input.rio.y_dim)
+            arr = numpy.flip(arr, axis=yaxis)
+
         return ImageData(
             arr,
             bounds=tile_bounds,
@@ -321,6 +326,11 @@ def part(
         arr = ds.to_masked_array()
         arr.mask |= arr.data == ds.rio.nodata
 
+        output_bounds = ds.rio._unordered_bounds()
+        if output_bounds[1] > output_bounds[3] and ds.rio.transform().e > 0:
+            yaxis = self.input.dims.index(self.input.rio.y_dim)
+            arr = numpy.flip(arr, axis=yaxis)
+
         img = ImageData(
             arr,
             bounds=ds.rio.bounds(),
@@ -403,6 +413,11 @@ def preview(
         arr = ds.to_masked_array()
         arr.mask |= arr.data == ds.rio.nodata
 
+        output_bounds = ds.rio._unordered_bounds()
+        if output_bounds[1] > output_bounds[3] and ds.rio.transform().e > 0:
+            yaxis = self.input.dims.index(self.input.rio.y_dim)
+            arr = numpy.flip(arr, axis=yaxis)
+
         img = ImageData(
             arr,
             bounds=ds.rio.bounds(),
diff --git a/tests/test_io_xarray.py b/tests/test_io_xarray.py
index 85c999b4..d05eaca3 100644
--- a/tests/test_io_xarray.py
+++ b/tests/test_io_xarray.py
@@ -525,3 +525,77 @@ def test_xarray_reader_no_dims():
         assert img.height == 256
         assert img.band_names == ["value"]
         assert img.dataset_statistics == ((arr.min(), arr.max()),)
+
+        img = dst.part((-160, -80, 160, 80))
+        assert img.count == 1
+        assert img.width == 33
+        assert img.height == 33
+        assert img.band_names == ["value"]
+        assert img.dataset_statistics == ((arr.min(), arr.max()),)
+
+
+def test_xarray_reader_Y_axis():
+    """test XarrayReader with 2D dataset."""
+    # Create a DataArray where the y coordinates are in increasing order
+    # (this is the opposite of typical raster data)
+    # This array will have a positive y resolution in the affine transform
+    # and the data values increase with the y coordinates
+    arr = numpy.arange(0, 33 * 35).reshape(1, 33, 35)
+    data = xarray.DataArray(
+        arr,
+        dims=("time", "y", "x"),
+        coords={
+            "x": numpy.arange(-170, 180, 10),
+            "y": numpy.arange(-80, 85, 5),
+            "time": [datetime(2022, 1, 1)],
+        },
+    )
+    data.attrs.update({"valid_min": arr.min(), "valid_max": arr.max()})
+    data.rio.write_crs("epsg:4326", inplace=True)
+
+    # make sure the data is inverted
+    # y resolution is Positive and origin is bottom left
+    left, bottom, right, top = data.rio._unordered_bounds()
+    assert bottom > top
+    assert data.rio.transform().e > 0
+
+    with XarrayReader(data) as dst:
+        assert dst.bounds == (left, top, right, bottom)
+        img = dst.preview()
+        assert img.bounds == dst.bounds
+        assert img.array[0, 0, 0] > img.array[0, -1, -1]
+
+        img = dst.tile(1, 1, 2)
+        assert img.array[0, 0, 0] > img.array[0, -1, -1]
+
+    # Create a DataArray where the y coordinates are in decreasing order
+    # (this is typical for raster data)
+    # This array will have a negative y resolution in the affine transform
+    # and the data values decrease with the y coordinates
+    arr = numpy.arange(0, 33 * 35).reshape(1, 33, 35)
+    data = xarray.DataArray(
+        arr,
+        dims=("time", "y", "x"),
+        coords={
+            "x": numpy.arange(-170, 180, 10),
+            "y": numpy.flip(numpy.arange(-80, 85, 5)),
+            "time": [datetime(2022, 1, 1)],
+        },
+    )
+    data.attrs.update({"valid_min": arr.min(), "valid_max": arr.max()})
+    data.rio.write_crs("epsg:4326", inplace=True)
+
+    # make sure the data is NOT inverted
+    # y resolution is Negative and origin is top left
+    left, bottom, right, top = data.rio._unordered_bounds()
+    assert bottom < top
+    assert data.rio.transform().e < 0
+
+    with XarrayReader(data) as dst:
+        assert dst.bounds == (left, bottom, right, top)
+        img = dst.preview()
+        assert img.bounds == dst.bounds
+        assert img.array[0, 0, 0] < img.array[0, -1, -1]
+
+        img = dst.tile(1, 1, 2)
+        assert img.array[0, 0, 0] < img.array[0, -1, -1]