用xarray读取grib2文件

时间:2017-09-06 12:50:40

标签: python-2.7 python-xarray

我需要用xarray打开一个grib2文件。为此,我在xarray中使用python 2.7和pynio作为引擎:

grbs = xr.open_dataset('hrrr.t06z.wrfsubhf02.grib2'], engine = 'pynio')

输出:

<xarray.Dataset>
Dimensions:                    (forecast_time0: 4, lv_HTGL0: 2, lv_HTGL1: 2, xgrid_0: 1799, ygrid_0: 1059)
Coordinates:
  * forecast_time0             (forecast_time0) timedelta64[ns] 5 days 15:00:00 ...
  * lv_HTGL1                   (lv_HTGL1) float32 1000.0 4000.0
  * lv_HTGL0                   (lv_HTGL0) float32 10.0 80.0
    gridlat_0                  (ygrid_0, xgrid_0) float32 21.1381 21.1451 ...
    gridlon_0                  (ygrid_0, xgrid_0) float32 -122.72 -122.693 ...
Dimensions without coordinates: xgrid_0, ygrid_0
Data variables:
    ULWRF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 446.3 ...
    WIND_P8_L103_GLC0_avg5min  (forecast_time0, ygrid_0, xgrid_0) float64 5.31 ...
    SBT124_P0_L8_GLC0          (forecast_time0, ygrid_0, xgrid_0) float64 288.7 ...
    VDDSF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    VIS_P0_L1_GLC0             (forecast_time0, ygrid_0, xgrid_0) float64 8.4e+03 ...
    DSWRF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    CICEP_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    DLWRF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 429.7 ...
    USWRF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    ULWRF_P0_L8_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 291.0 ...
    HGT_P0_L3_GLC0             (forecast_time0, ygrid_0, xgrid_0) float64 1.4e+03 ...
    VGRD_P8_L103_GLC0_avg5min  (forecast_time0, ygrid_0, xgrid_0) float64 -4.92 ...
    gridrot_0                  (ygrid_0, xgrid_0) float32 -0.274008 ...
    VIL_P0_L10_GLC0            (forecast_time0, ygrid_0, xgrid_0) float64 0.0048 ...
    CSNOW_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    SBT123_P0_L8_GLC0          (forecast_time0, ygrid_0, xgrid_0) float64 251.5 ...
    GUST_P0_L1_GLC0            (forecast_time0, ygrid_0, xgrid_0) float64 6.469 ...
    SBT114_P0_L8_GLC0          (forecast_time0, ygrid_0, xgrid_0) float64 289.4 ...
    DPT_P0_L103_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 295.8 ...
    UGRD_P8_L103_GLC0_avg5min  (forecast_time0, ygrid_0, xgrid_0) float64 -2.02 ...
    RETOP_P0_L3_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 -999.0 ...
    REFD_P0_L103_GLC0          (forecast_time0, lv_HTGL1, ygrid_0, xgrid_0) float64 -10.0 ...
    TMP_P0_L103_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 297.0 ...
    UGRD_P0_L103_GLC0          (forecast_time0, lv_HTGL0, ygrid_0, xgrid_0) float64 -1.998 ...
    HGT_P0_L215_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 461.2 ...
    UPHL_P0_2L103_GLC0         (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    SBT113_P0_L8_GLC0          (forecast_time0, ygrid_0, xgrid_0) float64 253.9 ...
    VBDSF_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    PRATE_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    CFRZR_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    CPOFP_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 -50.0 ...
    CRAIN_P0_L1_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    REFC_P0_L10_GLC0           (forecast_time0, ygrid_0, xgrid_0) float64 1.0 ...
    DSWRF_P8_L1_GLC0_avg15min  (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    VBDSF_P8_L1_GLC0_avg15min  (forecast_time0, ygrid_0, xgrid_0) float64 0.0 ...
    PRES_P0_L1_GLC0            (forecast_time0, ygrid_0, xgrid_0) float64 1.014e+05 ...
    SPFH_P0_L103_GLC0          (forecast_time0, ygrid_0, xgrid_0) float64 0.01705 ...
    VGRD_P0_L103_GLC0          (forecast_time0, lv_HTGL0, ygrid_0, xgrid_0) float64 -4.939 ...
    HGT_P0_L2_GLC0             (forecast_time0, ygrid_0, xgrid_0) float64 869.5 ...

我可以加载文件并查看它的内容,我也可以用切片方法读取给定变量的数据:

   data = grbs['DSWRF_P8_L1_GLC0_avg15min'].isel(**{'forecast_time0': 0}).sel(**{'ygrid_0': slice(22,24), 'xgrid_0': slice(-115,-110)}) 

输出:

0}).sel(**{'ygrid_0': slice(22,24), 'xgrid_0': slice(-115,-110)}) 
<xarray.DataArray 'DSWRF_P8_L1_GLC0_avg15min' (ygrid_0: 2, xgrid_0: 5)>
array([[ 0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.]])
Coordinates:
    forecast_time0  timedelta64[ns] 5 days 15:00:00
    gridlat_0       (ygrid_0, xgrid_0) float32 22.4459 22.4396 22.4334 ...
    gridlon_0       (ygrid_0, xgrid_0) float32 -75.2096 -75.1823 -75.155 ...
Dimensions without coordinates: ygrid_0, xgrid_0
Attributes:
    production_status:                              Operational products
    center:                                         US National Weather Servi...
    level:                                          [ 0.]
    type_of_statistical_processing:                 Average
    long_name:                                      Downward short-wave radia...
    parameter_template_discipline_category_number:  [8 0 4 7]
    initial_time:                                   09/06/2017 (06:00)
    grid_type:                                      Lambert Conformal can be ...
    units:                                          W m-2
    statistical_process_duration:                   15 minutes (ending at for...
    level_type:                                     Ground or water surface
    parameter_discipline_and_category:              Meteorological products, ...

现在我想使用插值=&#39;最近的&#39;检索给定纬度/经度附近的给定变量值的方法:

   data = grbs['DSWRF_P8_L1_GLC0_avg15min'].sel(gridlon_0=-75.2096, gridlat_0=22.4396, method='nearest')

输出:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-37-0c24d2bdb040> in <module>()
      7 #data = grbs['DSWRF_P8_L1_GLC0_avg15min'].sel(gridlon_0=-75.2096, gridlat_0=22.4396, method='nearest') # ValueError: dimensions or multi-index levels ['gridlat_0', 'gridlon_0'] do not exist
      8 #data = grbs['DSWRF_P8_L1_GLC0_avg15min'].sel(lat=gridlat_0, lon = gridlon_0) # ValueError: dimensions or multi-index levels ['gridlat_0', 'gridlon_0'] do not exist
----> 9 data = grbs['DSWRF_P8_L1_GLC0_avg15min'].sel(gridlon_0=-75.2096, gridlat_0=22.4396, method='nearest')

/Users/maurice/anaconda3/envs/py27/lib/python2.7/site-packages/xarray/core/dataarray.pyc in sel(self, method, tolerance, drop, **indexers)
    690         """
    691         pos_indexers, new_indexes = indexing.remap_label_indexers(
--> 692             self, indexers, method=method, tolerance=tolerance
    693         )
    694         result = self.isel(drop=drop, **pos_indexers)

/Users/maurice/anaconda3/envs/py27/lib/python2.7/site-packages/xarray/core/indexing.pyc in remap_label_indexers(data_obj, indexers, method, tolerance)
    275     new_indexes = {}
    276 
--> 277     dim_indexers = get_dim_indexers(data_obj, indexers)
    278     for dim, label in iteritems(dim_indexers):
    279         try:

/Users/maurice/anaconda3/envs/py27/lib/python2.7/site-packages/xarray/core/indexing.pyc in get_dim_indexers(data_obj, indexers)
    243     if invalid:
    244         raise ValueError("dimensions or multi-index levels %r do not exist"
--> 245                          % invalid)
    246 
    247     level_indexers = defaultdict(dict)

ValueError: dimensions or multi-index levels ['gridlat_0', 'gridlon_0'] do not exist

任何帮助将不胜感激!

注意:文件可以在http://nomads.ncep.noaa.gov/pub/data/nccf/com/hrrr/prod/找到,然后是格式为hrrr.YYYMMDD / hrrr.tHHz.wrfsubhf的链接**。grib2)

1 个答案:

答案 0 :(得分:1)

您的纬度/经度坐标变量是二维的。 xarray目前无法使用这样的最近邻居查找。 xarray开发人员正在积极讨论如何将其包含在软件包中,但尚未具体实现。这个github问题非常重要:https://github.com/pydata/xarray/issues/475