简单地将NetCDF4.DataSet转换为Xarray数据集

Question

我知道如何手动将netcdf4.dataset转换为Xarray DataArray。但是，我想知道是否有任何简单而优雅的方式，例如使用Xarray后端，对于以下" NetCDF4.DataSet"对象的简单转换为Xarray DataArray对象：

<type 'netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
    Originating_or_generating_Center: US National Weather Service, National Centres for Environmental Prediction (NCEP)
    Originating_or_generating_Subcenter: NCEP Ensemble Products
    GRIB_table_version: 2,1
    Type_of_generating_process: Ensemble forecast
    Analysis_or_forecast_generating_process_identifier_defined_by_originating_centre: Global Ensemble Forecast System (GEFS)
    Conventions: CF-1.6
    history: Read using CDM IOSP GribCollection v3
    featureType: GRID
    History: Translated to CF-1.0 Conventions by Netcdf-Java CDM (CFGridWriter2)
Original Dataset = /data/ldm/pub/native/grid/NCEP/GEFS/Global_1p0deg_Ensemble/member/GEFS_Global_1p0deg_Ensemble_20170926_0600.grib2.ncx3#LatLon_181X360-p5S-180p0E; Translation Date = 2017-09-26T17:50:23.259Z
    geospatial_lat_min: 0.0
    geospatial_lat_max: 90.0
    geospatial_lon_min: 0.0
    geospatial_lon_max: 359.0
    dimensions(sizes): time2(2), ens(21), isobaric1(12), lat(91), lon(360)
    variables(dimensions): float32 u-component_of_wind_isobaric_ens(time2,ens,isobaric1,lat,lon), float64 time2(time2), int32 ens(ens), float32 isobaric1(isobaric1), float32 lat(lat), float32 lon(lon), float32 v-component_of_wind_isobaric_ens(time2,ens,isobaric1,lat,lon)
    groups: 

我使用了siphon.ncss。

Answer 1

Xarray（0.10）的下一个版本（0.10）对此有所支持，或者至少是从NetCDF4中获得Xarray dataset 的支持'试图使用它：

import xarray as xr
nc = nc4.Dataset('filename.nc', mode='r')  # Or from siphon.ncss
dataset = xr.open_dataset(xr.backends.NetCDF4DataStore(nc))

或使用siphon.ncss，这看起来像：

from datetime import datetime
from siphon.catalog import TDSCatalog
import xarray as xr
gfs_cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog'
                     '/grib/NCEP/GFS/Global_0p5deg/catalog.xml')
latest = gfs_cat.latest
ncss = latest.subset()
query = ncss.query().variables('Temperature_isobaric')
query.time(datetime.utcnow()).accept('netCDF4')
nc = ncss.get_data(query)
dataset = xr.open_dataset(xr.backends.NetCDF4DataStore(nc))

在发布之前，您可以从Master安装Xarray。否则，唯一的解决方案是手动执行所有操作。