数据/读取grib遇到的问题.ipynb

{
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   "source": [
    "import xarray as xr"
   ]
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  {
   "cell_type": "code",
   "execution_count": 2,
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    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 9404, lat: 3, lon: 4)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 110.0 111.0 112.0 113.0\n",
       "  * lat      (lat) float32 24.0 25.0 26.0\n",
       "  * time     (time) datetime64[ns] 1996-10-01 1996-10-02 ... 2022-06-30\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...</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-02de6ed2-a778-4381-91b8-193c52f5ae4a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-02de6ed2-a778-4381-91b8-193c52f5ae4a' 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>: 9404</li><li><span class='xr-has-index'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a296e66e-7f88-496b-be4d-b687c03f6de7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a296e66e-7f88-496b-be4d-b687c03f6de7' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>110.0 111.0 112.0 113.0</div><input id='attrs-c66ecebe-851e-4c76-8f82-cad25b94e83f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c66ecebe-851e-4c76-8f82-cad25b94e83f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf61d106-b209-44f2-a65f-64ea7f7214c5' class='xr-var-data-in' type='checkbox'><label for='data-cf61d106-b209-44f2-a65f-64ea7f7214c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([110., 111., 112., 113.], dtype=float32)</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'>24.0 25.0 26.0</div><input id='attrs-838ee4db-0800-4ceb-88dc-3afb0050c337' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-838ee4db-0800-4ceb-88dc-3afb0050c337' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e9d96e2-5ec1-456b-b904-2ad01c98fda2' class='xr-var-data-in' type='checkbox'><label for='data-4e9d96e2-5ec1-456b-b904-2ad01c98fda2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([24., 25., 26.], 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'>1996-10-01 ... 2022-06-30</div><input id='attrs-ec5efc76-bfdd-4aa0-b006-2512658ade06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec5efc76-bfdd-4aa0-b006-2512658ade06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61bad66e-2635-42ee-8c26-461c6e5b867d' class='xr-var-data-in' type='checkbox'><label for='data-61bad66e-2635-42ee-8c26-461c6e5b867d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1996-10-01T00:00:00.000000000&#x27;, &#x27;1996-10-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-10-03T00:00:00.000000000&#x27;, ..., &#x27;2022-06-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-06-29T00:00:00.000000000&#x27;, &#x27;2022-06-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-254ae5a3-da1e-429b-aefe-63643bf3a146' class='xr-section-summary-in' type='checkbox'  checked><label for='section-254ae5a3-da1e-429b-aefe-63643bf3a146' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</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-fe4b1d09-76a5-4cc1-be16-f804f62029d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe4b1d09-76a5-4cc1-be16-f804f62029d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e583af60-13ed-4993-97d0-683913fc5c96' class='xr-var-data-in' type='checkbox'><label for='data-e583af60-13ed-4993-97d0-683913fc5c96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[112848 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-870a3c38-3166-4bbd-b31a-674293a54c64' class='xr-section-summary-in' type='checkbox'  ><label for='section-870a3c38-3166-4bbd-b31a-674293a54c64' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a22843ef-7ffd-483a-8d50-d74c532872d7' class='xr-index-data-in' type='checkbox'/><label for='index-a22843ef-7ffd-483a-8d50-d74c532872d7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([110.0, 111.0, 112.0, 113.0], dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-4905ca33-ee64-429a-bd88-b14826a291e4' class='xr-index-data-in' type='checkbox'/><label for='index-4905ca33-ee64-429a-bd88-b14826a291e4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([24.0, 25.0, 26.0], dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</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-c923ba6a-0d7e-4886-9333-69709c32617b' class='xr-index-data-in' type='checkbox'/><label for='index-c923ba6a-0d7e-4886-9333-69709c32617b' 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;1996-10-01&#x27;, &#x27;1996-10-02&#x27;, &#x27;1996-10-03&#x27;, &#x27;1996-10-04&#x27;,\n",
       "               &#x27;1996-10-05&#x27;, &#x27;1996-10-06&#x27;, &#x27;1996-10-07&#x27;, &#x27;1996-10-08&#x27;,\n",
       "               &#x27;1996-10-09&#x27;, &#x27;1996-10-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2022-06-21&#x27;, &#x27;2022-06-22&#x27;, &#x27;2022-06-23&#x27;, &#x27;2022-06-24&#x27;,\n",
       "               &#x27;2022-06-25&#x27;, &#x27;2022-06-26&#x27;, &#x27;2022-06-27&#x27;, &#x27;2022-06-28&#x27;,\n",
       "               &#x27;2022-06-29&#x27;, &#x27;2022-06-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9404, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7fa4959-3411-4050-8a17-2d9188b19499' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a7fa4959-3411-4050-8a17-2d9188b19499' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 9404, lat: 3, lon: 4)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 110.0 111.0 112.0 113.0\n",
       "  * lat      (lat) float32 24.0 25.0 26.0\n",
       "  * time     (time) datetime64[ns] 1996-10-01 1996-10-02 ... 2022-06-30\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pre1=xr.open_dataset('./data/precip_daily.nc')\n",
    "pre1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\anaconda\\envs\\py310\\lib\\site-packages\\xarray\\coding\\times.py:699: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)\n",
      "d:\\anaconda\\envs\\py310\\lib\\site-packages\\xarray\\core\\indexing.py:524: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  return np.asarray(array[self.key], dtype=None)\n"
     ]
    },
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       "Dimensions:             (lat: 360, lon: 720, time: 365, nbnds: 2)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n",
       "  * lon                 (lon) float32 0.25 0.75 1.25 1.75 ... 358.8 359.2 359.8\n",
       "  * time                (time) object 0001-01-01 00:00:00 ... 0001-12-31 00:0...\n",
       "Dimensions without coordinates: nbnds\n",
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       "    climatology_bounds  (time, nbnds) datetime64[ns] ...\n",
       "    precip              (time, lat, lon) float32 ...\n",
       "    valid_yr_count      (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:                    CF-1.0\n",
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       "    history:                        Created 2021/02/09 by doDayLTM\n",
       "    title:                          CPC GLOBAL PRCP V1.0\n",
       "    dataset_title:                  CPC GLOBAL PRCP V1.0\n",
       "    Source:                         ftp://ftp.cpc.ncep.noaa.gov/precip/CPC_UN...\n",
       "    References:                     https://www.psl.noaa.gov/data/gridded/dat...\n",
       "    not_missing_threshold_percent:  minimum 3% values input to have non-missi...</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-d1379545-78ea-4aca-a341-abd141a6d0da' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d1379545-78ea-4aca-a341-abd141a6d0da' 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'>lat</span>: 360</li><li><span class='xr-has-index'>lon</span>: 720</li><li><span class='xr-has-index'>time</span>: 365</li><li><span>nbnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2d8b4814-64e4-471e-9f3d-4b9e11503000' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2d8b4814-64e4-471e-9f3d-4b9e11503000' 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'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-3a3c6a7a-ff44-4eaa-a8af-080f4bfd7f40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a3c6a7a-ff44-4eaa-a8af-080f4bfd7f40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02ad03b8-de39-42f5-bc1a-a4136fc7bd1c' class='xr-var-data-in' type='checkbox'><label for='data-02ad03b8-de39-42f5-bc1a-a4136fc7bd1c' 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>actual_range :</span></dt><dd>[ 89.75 -89.75]</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 89.75,  89.25,  88.75, ..., -88.75, -89.25, -89.75], 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'>0.25 0.75 1.25 ... 359.2 359.8</div><input id='attrs-454c3e9e-8941-493b-83a5-78732a297f0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-454c3e9e-8941-493b-83a5-78732a297f0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9714fe3c-ca76-4114-92ea-2600cbc068f0' class='xr-var-data-in' type='checkbox'><label for='data-9714fe3c-ca76-4114-92ea-2600cbc068f0' 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>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>actual_range :</span></dt><dd>[2.5000e-01 3.5975e+02]</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([2.5000e-01, 7.5000e-01, 1.2500e+00, ..., 3.5875e+02, 3.5925e+02,\n",
       "       3.5975e+02], 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'>object</div><div class='xr-var-preview xr-preview'>0001-01-01 00:00:00 ... 0001-12-...</div><input id='attrs-c62d0d53-5f00-479b-9998-50bca52d9f3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c62d0d53-5f00-479b-9998-50bca52d9f3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f894a87-1ed9-447b-909d-3219a3ce0d22' class='xr-var-data-in' type='checkbox'><label for='data-7f894a87-1ed9-447b-909d-3219a3ce0d22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coordinate_defines :</span></dt><dd>start</dd><dt><span>delta_t :</span></dt><dd>0000-00-01 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-01 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0030-00-00 00:00:00</dd><dt><span>climatology :</span></dt><dd>climatology_bounds</dd><dt><span>climo_period :</span></dt><dd>1991/01/01 - 2020/12/31</dd><dt><span>actual_range :</span></dt><dd>[-16646328. -16637592.]</dd><dt><span>ltm_range :</span></dt><dd>[ 797688. 1060656.]</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(1, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1, 1, 2, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1, 1, 3, 0, 0, 0, 0, has_year_zero=False), ...,\n",
       "       cftime.DatetimeGregorian(1, 12, 29, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1, 12, 30, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1, 12, 31, 0, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5839a0d7-c26b-42bf-b640-22fd0e134e3c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5839a0d7-c26b-42bf-b640-22fd0e134e3c' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>climatology_bounds</span></div><div class='xr-var-dims'>(time, nbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-817c44a6-c4bb-4af9-965d-06176772845e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-817c44a6-c4bb-4af9-965d-06176772845e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70bfb486-21f6-4873-a5e0-fb99d19ad013' class='xr-var-data-in' type='checkbox'><label for='data-70bfb486-21f6-4873-a5e0-fb99d19ad013' 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>Climate Time Boundaries</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</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-24d19bde-2e86-4466-8267-70f16f0ce41b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24d19bde-2e86-4466-8267-70f16f0ce41b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4074ffe2-0b28-420b-9c6d-a84dbebbf0c0' class='xr-var-data-in' type='checkbox'><label for='data-4074ffe2-0b28-420b-9c6d-a84dbebbf0c0' 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>var_desc :</span></dt><dd>Precipitation</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Long Term Mean</dd><dt><span>parent_stat :</span></dt><dd>Total</dd><dt><span>long_name :</span></dt><dd>Daily Long Term Mean total of precipitation</dd><dt><span>cell_methods :</span></dt><dd>time: mean within days time: mean over days time: mean over years</dd><dt><span>avg_period :</span></dt><dd>0000-00-01 00:00:00</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>valid_range :</span></dt><dd>[   0. 1000.]</dd><dt><span>dataset :</span></dt><dd>CPC Global Precipitation</dd><dt><span>actual_range :</span></dt><dd>[  0.     327.2972]</dd></dl></div><div class='xr-var-data'><pre>[94608000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_yr_count</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-f81cff11-81b4-4a32-953c-581a7d971168' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f81cff11-81b4-4a32-953c-581a7d971168' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1697029-92a9-4bf2-a33c-ac0584811198' class='xr-var-data-in' type='checkbox'><label for='data-e1697029-92a9-4bf2-a33c-ac0584811198' 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>count of non-missing values used in mean</dd></dl></div><div class='xr-var-data'><pre>[94608000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a910c30-9a38-48e0-a965-278d1b833b04' class='xr-section-summary-in' type='checkbox'  ><label for='section-2a910c30-9a38-48e0-a965-278d1b833b04' 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-2eeb7bb4-4740-4aad-85f2-13beafc87253' class='xr-index-data-in' type='checkbox'/><label for='index-2eeb7bb4-4740-4aad-85f2-13beafc87253' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 89.75,  89.25,  88.75,  88.25,  87.75,  87.25,  86.75,  86.25,\n",
       "               85.75,  85.25,\n",
       "              ...\n",
       "              -85.25, -85.75, -86.25, -86.75, -87.25, -87.75, -88.25, -88.75,\n",
       "              -89.25, -89.75],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=360))</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-26afadf4-c500-4e25-bdb7-91dc8d99a06d' class='xr-index-data-in' type='checkbox'/><label for='index-26afadf4-c500-4e25-bdb7-91dc8d99a06d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.25,   0.75,   1.25,   1.75,   2.25,   2.75,   3.25,   3.75,\n",
       "                4.25,   4.75,\n",
       "              ...\n",
       "              355.25, 355.75, 356.25, 356.75, 357.25, 357.75, 358.25, 358.75,\n",
       "              359.25, 359.75],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=720))</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-700c3959-4866-4094-8b92-55fb333bf0eb' class='xr-index-data-in' type='checkbox'/><label for='index-700c3959-4866-4094-8b92-55fb333bf0eb' 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(CFTimeIndex([0001-01-01 00:00:00, 0001-01-02 00:00:00, 0001-01-03 00:00:00,\n",
       "             0001-01-04 00:00:00, 0001-01-05 00:00:00, 0001-01-06 00:00:00,\n",
       "             0001-01-07 00:00:00, 0001-01-08 00:00:00, 0001-01-09 00:00:00,\n",
       "             0001-01-10 00:00:00,\n",
       "             ...\n",
       "             0001-12-22 00:00:00, 0001-12-23 00:00:00, 0001-12-24 00:00:00,\n",
       "             0001-12-25 00:00:00, 0001-12-26 00:00:00, 0001-12-27 00:00:00,\n",
       "             0001-12-28 00:00:00, 0001-12-29 00:00:00, 0001-12-30 00:00:00,\n",
       "             0001-12-31 00:00:00],\n",
       "            dtype=&#x27;object&#x27;, length=365, calendar=&#x27;gregorian&#x27;, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1fd72a32-f8a5-4f78-9f45-3af7c2604af3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1fd72a32-f8a5-4f78-9f45-3af7c2604af3' class='xr-section-summary' >Attributes: <span>(8)</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-1.0</dd><dt><span>version :</span></dt><dd>V1.0</dd><dt><span>history :</span></dt><dd>Created 2021/02/09 by doDayLTM</dd><dt><span>title :</span></dt><dd>CPC GLOBAL PRCP V1.0</dd><dt><span>dataset_title :</span></dt><dd>CPC GLOBAL PRCP V1.0</dd><dt><span>Source :</span></dt><dd>ftp://ftp.cpc.ncep.noaa.gov/precip/CPC_UNI_PRCP/</dd><dt><span>References :</span></dt><dd>https://www.psl.noaa.gov/data/gridded/data.cpc.globalprecip.html</dd><dt><span>not_missing_threshold_percent :</span></dt><dd>minimum 3% values input to have non-missing output value</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (lat: 360, lon: 720, time: 365, nbnds: 2)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n",
       "  * lon                 (lon) float32 0.25 0.75 1.25 1.75 ... 358.8 359.2 359.8\n",
       "  * time                (time) object 0001-01-01 00:00:00 ... 0001-12-31 00:0...\n",
       "Dimensions without coordinates: nbnds\n",
       "Data variables:\n",
       "    climatology_bounds  (time, nbnds) datetime64[ns] ...\n",
       "    precip              (time, lat, lon) float32 ...\n",
       "    valid_yr_count      (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:                    CF-1.0\n",
       "    version:                        V1.0\n",
       "    history:                        Created 2021/02/09 by doDayLTM\n",
       "    title:                          CPC GLOBAL PRCP V1.0\n",
       "    dataset_title:                  CPC GLOBAL PRCP V1.0\n",
       "    Source:                         ftp://ftp.cpc.ncep.noaa.gov/precip/CPC_UN...\n",
       "    References:                     https://www.psl.noaa.gov/data/gridded/dat...\n",
       "    not_missing_threshold_percent:  minimum 3% values input to have non-missi..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 气候态降水\n",
    "pre=xr.open_dataset('./data/precip.day.ltm.nc')\n",
    "pre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*************************************************************************\n",
      "使用参数 filter_by_keys = {'stepType': 'avgid'}查看到的数据内容为：\n",
      "<xarray.Dataset>\n",
      "Dimensions:     (time: 492, latitude: 41, longitude: 31)\n",
      "Coordinates:\n",
      "    number      int32 ...\n",
      "  * time        (time) datetime64[ns] 1980-01-01 1980-02-01 ... 2020-12-01\n",
      "    step        timedelta64[ns] ...\n",
      "    surface     float64 ...\n",
      "  * latitude    (latitude) float64 26.0 25.9 25.8 25.7 ... 22.3 22.2 22.1 22.0\n",
      "  * longitude   (longitude) float64 109.0 109.1 109.2 ... 111.8 111.9 112.0\n",
      "    valid_time  (time) datetime64[ns] ...\n",
      "Data variables:\n",
      "    u10         (time, latitude, longitude) float32 ...\n",
      "    v10         (time, latitude, longitude) float32 ...\n",
      "    d2m         (time, latitude, longitude) float32 ...\n",
      "    t2m         (time, latitude, longitude) float32 ...\n",
      "    sp          (time, latitude, longitude) float32 ...\n",
      "Attributes:\n",
      "    GRIB_edition:            1\n",
      "    GRIB_centre:             ecmf\n",
      "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
      "    GRIB_subCentre:          0\n",
      "    Conventions:             CF-1.7\n",
      "    institution:             European Centre for Medium-Range Weather Forecasts\n",
      "    history:                 2023-04-30T14:10 GRIB to CDM+CF via cfgrib-0.9.1...\n",
      "\n",
      "请根据以上数据内容信息，确认所需读取的物理量对应的levelType\n",
      "*************************************************************************\n",
      "使用参数 filter_by_keys = {'stepType': 'avgua'}查看到的数据内容为：\n",
      "<xarray.Dataset>\n",
      "Dimensions:     (time: 492, latitude: 41, longitude: 31)\n",
      "Coordinates:\n",
      "    number      int32 ...\n",
      "  * time        (time) datetime64[ns] 1980-01-01 1980-02-01 ... 2020-12-01\n",
      "    step        timedelta64[ns] ...\n",
      "    surface     float64 ...\n",
      "  * latitude    (latitude) float64 26.0 25.9 25.8 25.7 ... 22.3 22.2 22.1 22.0\n",
      "  * longitude   (longitude) float64 109.0 109.1 109.2 ... 111.8 111.9 112.0\n",
      "    valid_time  (time) datetime64[ns] ...\n",
      "Data variables:\n",
      "    skt         (time, latitude, longitude) float32 ...\n",
      "Attributes:\n",
      "    GRIB_edition:            1\n",
      "    GRIB_centre:             ecmf\n",
      "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
      "    GRIB_subCentre:          0\n",
      "    Conventions:             CF-1.7\n",
      "    institution:             European Centre for Medium-Range Weather Forecasts\n",
      "    history:                 2023-04-30T14:10 GRIB to CDM+CF via cfgrib-0.9.1...\n",
      "\n",
      "请根据以上数据内容信息，确认所需读取的物理量对应的levelType\n",
      "*************************************************************************\n",
      "使用参数 filter_by_keys = {'stepType': 'avgas'}查看到的数据内容为：\n",
      "<xarray.Dataset>\n",
      "Dimensions:     (time: 264, latitude: 41, longitude: 31)\n",
      "Coordinates:\n",
      "    number      int32 ...\n",
      "  * time        (time) datetime64[ns] 1980-01-01 1980-02-01 ... 2001-12-01\n",
      "    step        timedelta64[ns] ...\n",
      "    surface     float64 ...\n",
      "  * latitude    (latitude) float64 26.0 25.9 25.8 25.7 ... 22.3 22.2 22.1 22.0\n",
      "  * longitude   (longitude) float64 109.0 109.1 109.2 ... 111.8 111.9 112.0\n",
      "    valid_time  (time) datetime64[ns] ...\n",
      "Data variables:\n",
      "    tp          (time, latitude, longitude) float32 ...\n",
      "Attributes:\n",
      "    GRIB_edition:            1\n",
      "    GRIB_centre:             ecmf\n",
      "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
      "    GRIB_subCentre:          0\n",
      "    Conventions:             CF-1.7\n",
      "    institution:             European Centre for Medium-Range Weather Forecasts\n",
      "    history:                 2023-04-30T14:10 GRIB to CDM+CF via cfgrib-0.9.1...\n",
      "\n",
      "请根据以上数据内容信息，确认所需读取的物理量对应的levelType\n",
      "*************************************************************************\n",
      "使用参数 filter_by_keys = {'stepType': 'avgad'}查看到的数据内容为：\n",
      "<xarray.Dataset>\n",
      "Dimensions:     (time: 228, latitude: 41, longitude: 31)\n",
      "Coordinates:\n",
      "    number      int32 ...\n",
      "  * time        (time) datetime64[ns] 2002-01-01 2002-02-01 ... 2020-12-01\n",
      "    step        timedelta64[ns] ...\n",
      "    surface     float64 ...\n",
      "  * latitude    (latitude) float64 26.0 25.9 25.8 25.7 ... 22.3 22.2 22.1 22.0\n",
      "  * longitude   (longitude) float64 109.0 109.1 109.2 ... 111.8 111.9 112.0\n",
      "    valid_time  (time) datetime64[ns] ...\n",
      "Data variables:\n",
      "    tp          (time, latitude, longitude) float32 ...\n",
      "Attributes:\n",
      "    GRIB_edition:            1\n",
      "    GRIB_centre:             ecmf\n",
      "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
      "    GRIB_subCentre:          0\n",
      "    Conventions:             CF-1.7\n",
      "    institution:             European Centre for Medium-Range Weather Forecasts\n",
      "    history:                 2023-04-30T14:11 GRIB to CDM+CF via cfgrib-0.9.1...\n",
      "\n",
      "请根据以上数据内容信息，确认所需读取的物理量对应的levelType\n",
      "在读取数据时需添加如下参数当中的一个\n",
      "filter_by_keys = {'stepType': 'avgid'}\n",
      "filter_by_keys = {'stepType': 'avgua'}\n",
      "filter_by_keys = {'stepType': 'avgas'}\n",
      "filter_by_keys = {'stepType': 'avgad'}\n"
     ]
    }
   ],
   "source": [
    "# land\n",
    "import xarray as xr\n",
    "import cfgrib\n",
    "import meteva.base as meb\n",
    "# lands=xr.open_dataset('./data/land_monthly.grib',engine='cfgrib',)\n",
    "# lands\n",
    "meb.print_grib_file_info('./data/land_monthly.grib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lands=xr.open_dataset('./data/land_monthly.grib',engine='cfgrib',backend_kwargs={'filter_by_keys':{'stepType': 'avgid','typeOfLevel': 'surface'}})\n",
    "lands"
   ]
  }
 ],
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