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</style><pre class='xr-text-repr-fallback'><xarray.Dataset>
Dimensions: (category: 3, forecast_time: 53, latitude: 121, lead_time: 2, longitude: 240)
Coordinates:
* forecast_time (forecast_time) datetime64[ns] 2020-01-02 ... 2020-12-31
* latitude (latitude) float64 90.0 88.5 87.0 85.5 ... -87.0 -88.5 -90.0
* lead_time (lead_time) timedelta64[ns] 14 days 28 days
* longitude (longitude) float64 0.0 1.5 3.0 4.5 ... 355.5 357.0 358.5
valid_time (lead_time, forecast_time) datetime64[ns] 2020-01-16 ... 2...
* category (category) object 'below normal' 'near normal' 'above normal'
Data variables:
t2m (category, lead_time, forecast_time, latitude, longitude) float32 ...
tp (category, lead_time, forecast_time, latitude, longitude) float32 ...
Attributes:
author: Aaron Spring
author_email: aaron.spring@mpimet.mpg.de
comment: created for the s2s-ai-challenge as a template for the web...
website: https://s2s-ai-challenge.github.io/#evaluation</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8b051f4c-09d2-4bd7-8a93-238694e273f2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8b051f4c-09d2-4bd7-8a93-238694e273f2' 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'>category</span>: 3</li><li><span class='xr-has-index'>forecast_time</span>: 53</li><li><span class='xr-has-index'>latitude</span>: 121</li><li><span class='xr-has-index'>lead_time</span>: 2</li><li><span class='xr-has-index'>longitude</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4de0372f-2b44-4f2b-864b-2a7f3f7a7fc5' class='xr-section-summary-in' type='checkbox' checked><label for='section-4de0372f-2b44-4f2b-864b-2a7f3f7a7fc5' class='xr-section-summary' >Coordinates: <span>(6)</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'>forecast_time</span></div><div class='xr-var-dims'>(forecast_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-02 ... 2020-12-31</div><input id='attrs-387fa3f7-67ad-4066-81b8-34c974e42883' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-387fa3f7-67ad-4066-81b8-34c974e42883' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20896913-b2ae-457b-98a1-7ac19146417c' class='xr-var-data-in' type='checkbox'><label for='data-20896913-b2ae-457b-98a1-7ac19146417c' 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>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd><dt><span>description :</span></dt><dd>The forecast reference time in NWP is the data time, the time of the analysis from which the forecast was made. It is not the time for which the forecast is valid.</dd></dl></div><div class='xr-var-data'><pre>array(['2020-01-02T00:00:00.000000000', '2020-01-09T00:00:00.000000000',
'2020-01-16T00:00:00.000000000', '2020-01-23T00:00:00.000000000',
'2020-01-30T00:00:00.000000000', '2020-02-06T00:00:00.000000000',
'2020-02-13T00:00:00.000000000', '2020-02-20T00:00:00.000000000',
'2020-02-27T00:00:00.000000000', '2020-03-05T00:00:00.000000000',
'2020-03-12T00:00:00.000000000', '2020-03-19T00:00:00.000000000',
'2020-03-26T00:00:00.000000000', '2020-04-02T00:00:00.000000000',
'2020-04-09T00:00:00.000000000', '2020-04-16T00:00:00.000000000',
'2020-04-23T00:00:00.000000000', '2020-04-30T00:00:00.000000000',
'2020-05-07T00:00:00.000000000', '2020-05-14T00:00:00.000000000',
'2020-05-21T00:00:00.000000000', '2020-05-28T00:00:00.000000000',
'2020-06-04T00:00:00.000000000', '2020-06-11T00:00:00.000000000',
'2020-06-18T00:00:00.000000000', '2020-06-25T00:00:00.000000000',
'2020-07-02T00:00:00.000000000', '2020-07-09T00:00:00.000000000',
'2020-07-16T00:00:00.000000000', '2020-07-23T00:00:00.000000000',
'2020-07-30T00:00:00.000000000', '2020-08-06T00:00:00.000000000',
'2020-08-13T00:00:00.000000000', '2020-08-20T00:00:00.000000000',
'2020-08-27T00:00:00.000000000', '2020-09-03T00:00:00.000000000',
'2020-09-10T00:00:00.000000000', '2020-09-17T00:00:00.000000000',
'2020-09-24T00:00:00.000000000', '2020-10-01T00:00:00.000000000',
'2020-10-08T00:00:00.000000000', '2020-10-15T00:00:00.000000000',
'2020-10-22T00:00:00.000000000', '2020-10-29T00:00:00.000000000',
'2020-11-05T00:00:00.000000000', '2020-11-12T00:00:00.000000000',
'2020-11-19T00:00:00.000000000', '2020-11-26T00:00:00.000000000',
'2020-12-03T00:00:00.000000000', '2020-12-10T00:00:00.000000000',
'2020-12-17T00:00:00.000000000', '2020-12-24T00:00:00.000000000',
'2020-12-31T00:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 88.5 87.0 ... -88.5 -90.0</div><input id='attrs-2fadcdb8-972f-440d-b036-1d972c38bd00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fadcdb8-972f-440d-b036-1d972c38bd00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c7e1382-08f9-4a65-aedd-a21e5447f331' class='xr-var-data-in' type='checkbox'><label for='data-6c7e1382-08f9-4a65-aedd-a21e5447f331' 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</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90. , 88.5, 87. , 85.5, 84. , 82.5, 81. , 79.5, 78. , 76.5,
75. , 73.5, 72. , 70.5, 69. , 67.5, 66. , 64.5, 63. , 61.5,
60. , 58.5, 57. , 55.5, 54. , 52.5, 51. , 49.5, 48. , 46.5,
45. , 43.5, 42. , 40.5, 39. , 37.5, 36. , 34.5, 33. , 31.5,
30. , 28.5, 27. , 25.5, 24. , 22.5, 21. , 19.5, 18. , 16.5,
15. , 13.5, 12. , 10.5, 9. , 7.5, 6. , 4.5, 3. , 1.5,
0. , -1.5, -3. , -4.5, -6. , -7.5, -9. , -10.5, -12. , -13.5,
-15. , -16.5, -18. , -19.5, -21. , -22.5, -24. , -25.5, -27. , -28.5,
-30. , -31.5, -33. , -34.5, -36. , -37.5, -39. , -40.5, -42. , -43.5,
-45. , -46.5, -48. , -49.5, -51. , -52.5, -54. , -55.5, -57. , -58.5,
-60. , -61.5, -63. , -64.5, -66. , -67.5, -69. , -70.5, -72. , -73.5,
-75. , -76.5, -78. , -79.5, -81. , -82.5, -84. , -85.5, -87. , -88.5,
-90. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lead_time</span></div><div class='xr-var-dims'>(lead_time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>14 days 28 days</div><input id='attrs-79f2bcf4-27ee-479d-88db-0ffa74b355ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79f2bcf4-27ee-479d-88db-0ffa74b355ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-405e7159-013c-47b3-8ba8-52a7e790b2f3' class='xr-var-data-in' type='checkbox'><label for='data-405e7159-013c-47b3-8ba8-52a7e790b2f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>forecast_period</dd><dt><span>description :</span></dt><dd>Forecast period is the time interval between the forecast reference time and the validity time.</dd><dt><span>long_name :</span></dt><dd>lead time</dd><dt><span>aggregate :</span></dt><dd>The pd.Timedelta corresponds to the first day of a biweekly aggregate.</dd><dt><span>week34_t2m :</span></dt><dd>mean[14 days, 27 days]</dd><dt><span>week56_t2m :</span></dt><dd>mean[28 days, 41 days]</dd><dt><span>week34_tp :</span></dt><dd>28 days minus 14 days</dd><dt><span>week56_tp :</span></dt><dd>42 days minus 28 days</dd></dl></div><div class='xr-var-data'><pre>array([1209600000000000, 2419200000000000], dtype='timedelta64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.5 3.0 ... 355.5 357.0 358.5</div><input id='attrs-22ad6c22-7a37-4748-92a7-2e2deca6e085' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22ad6c22-7a37-4748-92a7-2e2deca6e085' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-071accfe-c420-483c-85c9-33563e6d855b' class='xr-var-data-in' type='checkbox'><label for='data-071accfe-c420-483c-85c9-33563e6d855b' 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</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 1.5, 3. , ..., 355.5, 357. , 358.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>(lead_time, forecast_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-16 ... 2021-01-28</div><input id='attrs-213e022d-e2c4-4542-a1cb-e9a41eb4effb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-213e022d-e2c4-4542-a1cb-e9a41eb4effb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-398891b8-48b9-460c-a7aa-da531ba73ed7' class='xr-var-data-in' type='checkbox'><label for='data-398891b8-48b9-460c-a7aa-da531ba73ed7' 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>validity time</dd><dt><span>description :</span></dt><dd>time for which the forecast is valid</dd><dt><span>calculate :</span></dt><dd>forecast_time + lead_time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([['2020-01-16T00:00:00.000000000', '2020-01-23T00:00:00.000000000',
'2020-01-30T00:00:00.000000000', '2020-02-06T00:00:00.000000000',
'2020-02-13T00:00:00.000000000', '2020-02-20T00:00:00.000000000',
'2020-02-27T00:00:00.000000000', '2020-03-05T00:00:00.000000000',
'2020-03-12T00:00:00.000000000', '2020-03-19T00:00:00.000000000',
'2020-03-26T00:00:00.000000000', '2020-04-02T00:00:00.000000000',
'2020-04-09T00:00:00.000000000', '2020-04-16T00:00:00.000000000',
'2020-04-23T00:00:00.000000000', '2020-04-30T00:00:00.000000000',
'2020-05-07T00:00:00.000000000', '2020-05-14T00:00:00.000000000',
'2020-05-21T00:00:00.000000000', '2020-05-28T00:00:00.000000000',
'2020-06-04T00:00:00.000000000', '2020-06-11T00:00:00.000000000',
'2020-06-18T00:00:00.000000000', '2020-06-25T00:00:00.000000000',
'2020-07-02T00:00:00.000000000', '2020-07-09T00:00:00.000000000',
'2020-07-16T00:00:00.000000000', '2020-07-23T00:00:00.000000000',
'2020-07-30T00:00:00.000000000', '2020-08-06T00:00:00.000000000',
'2020-08-13T00:00:00.000000000', '2020-08-20T00:00:00.000000000',
'2020-08-27T00:00:00.000000000', '2020-09-03T00:00:00.000000000',
'2020-09-10T00:00:00.000000000', '2020-09-17T00:00:00.000000000',
'2020-09-24T00:00:00.000000000', '2020-10-01T00:00:00.000000000',
'2020-10-08T00:00:00.000000000', '2020-10-15T00:00:00.000000000',
...
'2020-05-07T00:00:00.000000000', '2020-05-14T00:00:00.000000000',
'2020-05-21T00:00:00.000000000', '2020-05-28T00:00:00.000000000',
'2020-06-04T00:00:00.000000000', '2020-06-11T00:00:00.000000000',
'2020-06-18T00:00:00.000000000', '2020-06-25T00:00:00.000000000',
'2020-07-02T00:00:00.000000000', '2020-07-09T00:00:00.000000000',
'2020-07-16T00:00:00.000000000', '2020-07-23T00:00:00.000000000',
'2020-07-30T00:00:00.000000000', '2020-08-06T00:00:00.000000000',
'2020-08-13T00:00:00.000000000', '2020-08-20T00:00:00.000000000',
'2020-08-27T00:00:00.000000000', '2020-09-03T00:00:00.000000000',
'2020-09-10T00:00:00.000000000', '2020-09-17T00:00:00.000000000',
'2020-09-24T00:00:00.000000000', '2020-10-01T00:00:00.000000000',
'2020-10-08T00:00:00.000000000', '2020-10-15T00:00:00.000000000',
'2020-10-22T00:00:00.000000000', '2020-10-29T00:00:00.000000000',
'2020-11-05T00:00:00.000000000', '2020-11-12T00:00:00.000000000',
'2020-11-19T00:00:00.000000000', '2020-11-26T00:00:00.000000000',
'2020-12-03T00:00:00.000000000', '2020-12-10T00:00:00.000000000',
'2020-12-17T00:00:00.000000000', '2020-12-24T00:00:00.000000000',
'2020-12-31T00:00:00.000000000', '2021-01-07T00:00:00.000000000',
'2021-01-14T00:00:00.000000000', '2021-01-21T00:00:00.000000000',
'2021-01-28T00:00:00.000000000']], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>category</span></div><div class='xr-var-dims'>(category)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>'below normal' ... 'above normal'</div><input id='attrs-84d635b5-d943-4bd0-9242-f5438f4572eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84d635b5-d943-4bd0-9242-f5438f4572eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c184c61a-8f31-4f53-a32f-7f0776716533' class='xr-var-data-in' type='checkbox'><label for='data-c184c61a-8f31-4f53-a32f-7f0776716533' 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>tercile category probabilities</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>description :</span></dt><dd>Probabilities for three tercile categories. All three tercile category probabilities must add up to 1.</dd></dl></div><div class='xr-var-data'><pre>array(['below normal', 'near normal', 'above normal'], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ca27c1a1-477e-46ed-9c6a-61b4b2df824f' class='xr-section-summary-in' type='checkbox' checked><label for='section-ca27c1a1-477e-46ed-9c6a-61b4b2df824f' class='xr-section-summary' >Data variables: <span>(2)</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>t2m</span></div><div class='xr-var-dims'>(category, lead_time, forecast_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c0f9107e-24a7-45c6-90d5-ec7e277f2b7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0f9107e-24a7-45c6-90d5-ec7e277f2b7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0aa04140-4f75-4124-8bad-8da3c43c485d' class='xr-var-data-in' type='checkbox'><label for='data-0aa04140-4f75-4124-8bad-8da3c43c485d' 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>Probability of 2m temperature in tercile categories</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>comment :</span></dt><dd>All three tercile category probabilities must add up to 1.</dd><dt><span>aggregate_week34 :</span></dt><dd>mean[14 days, 27 days]</dd><dt><span>aggregate_week56 :</span></dt><dd>mean[28 days, 41 days]</dd><dt><span>variable_before_categorization :</span></dt><dd>https://confluence.ecmwf.int/display/S2S/S2S+Surface+Air+Temperature</dd></dl></div><div class='xr-var-data'><pre>[9234720 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(category, lead_time, forecast_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd494fb5-0cff-42c9-be73-7570a1af9f7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd494fb5-0cff-42c9-be73-7570a1af9f7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87d3c2fa-c859-4cde-9c6a-e856dc870619' class='xr-var-data-in' type='checkbox'><label for='data-87d3c2fa-c859-4cde-9c6a-e856dc870619' 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>Probability of total precipitation in tercile categories</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>comment :</span></dt><dd>All three tercile category probabilities must add up to 1.</dd><dt><span>aggregate_week34 :</span></dt><dd>28 days minus 14 days</dd><dt><span>aggregate_week56 :</span></dt><dd>42 days minus 28 days</dd><dt><span>variable_before_categorization :</span></dt><dd>https://confluence.ecmwf.int/display/S2S/S2S+Total+Precipitation</dd></dl></div><div class='xr-var-data'><pre>[9234720 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-198adc4c-7d19-4a24-af7e-99754fd53212' class='xr-section-summary-in' type='checkbox' checked><label for='section-198adc4c-7d19-4a24-af7e-99754fd53212' 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>author :</span></dt><dd>Aaron Spring</dd><dt><span>author_email :</span></dt><dd>aaron.spring@mpimet.mpg.de</dd><dt><span>comment :</span></dt><dd>created for the s2s-ai-challenge as a template for the website</dd><dt><span>website :</span></dt><dd>https://s2s-ai-challenge.github.io/#evaluation</dd></dl></div></li></ul></div></div>