如何解决如何将横截面数据保存到netCDF
我正在遵循Metpy's Cross Section Analysis中描述的示例代码：
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr
import metpy.calc as mpcalc
from metpy.interpolate import cross_section
#use xarray to read the data
data = xr.open_dataset('/home/rik/hrrr/gtgn/gtgn.t2215z.edr.f000.nc')
print(data)
<xarray.Dataset>
Dimensions: (alt: 52,time: 1,x: 451,y: 337)
Coordinates:
* time (time) datetime64[ns] 2020-06-18T22:15:00
* x (x) float64 0.0 1.355e+04 ... 6.082e+06 6.095e+06
* y (y) float64 0.0 1.355e+04 ... 4.538e+06 4.551e+06
* alt (alt) float64 0.0 30.0 304.0 ... 1.494e+04 1.524e+04
Data variables:
LAmbert_Conformal int32 ...
param30.19.0 (time,alt,y,x) float32 ...
Attributes:
CDI: climate Data Interface version 1.9.8 (https://mpimet.mpg.de...
Conventions: CF-1.6
history: Wed Oct 07 17:19:41 2020: cdo -f nc copy gtgn.t2215z.edr.f0...
institution: National Center for Atmospheric Research
CDO: climate Data Operators version 1.9.8 (https://mpimet.mpg.de...
#parse the data and remove crs from coordinate
data = data.metpy.parse_cf().squeeze()
data.drop_vars('crs')
print(data)
<xarray.Dataset>
Dimensions: (alt: 52,y: 337)
Coordinates:
time datetime64[ns] 2020-06-18T22:15:00
* x (x) float64 0.0 1.355e+04 ... 6.082e+06 6.095e+06
* y (y) float64 0.0 1.355e+04 ... 4.538e+06 4.551e+06
* alt (alt) float64 0.0 30.0 304.0 ... 1.494e+04 1.524e+04
crs object Projection: lAmbert_conformal_conic
Data variables:
LAmbert_Conformal int32 ...
param30.19.0 (alt,x) float32 ...
Attributes:
CDI: climate Data Interface version 1.9.8 (https://mpimet.mpg.de...
Conventions: CF-1.6
history: Wed Oct 07 17:19:41 2020: cdo -f nc copy gtgn.t2215z.edr.f0...
institution: National Center for Atmospheric Research
CDO: climate Data Operators version 1.9.8 (https://mpimet.mpg.de...
#define start and end points
start = (37.0,-105.0)
end = (35.5,-90.0)
#get the cross section
cross = cross_section(data,start,end)
print(cross)
<xarray.Dataset>
Dimensions: (alt: 52,index: 100)
Coordinates:
time datetime64[ns] 2020-06-18T22:15:00
crs object Projection: lAmbert_conformal_conic
* alt (alt) float64 0.0 30.0 304.0 ... 1.494e+04 1.524e+04
x (index) float64 2.424e+06 2.438e+06 ... 3.793e+06
y (index) float64 1.967e+06 1.965e+06 ... 1.772e+06
* index (index) int64 0 1 2 3 4 5 6 7 ... 92 93 94 95 96 97 98 99
Data variables:
LAmbert_Conformal int32 ...
param30.19.0 (alt,index) float64 0.3914 0.3687 ... 0.0605 0.0605
Attributes:
CDI: climate Data Interface version 1.9.8 (https://mpimet.mpg.de...
Conventions: CF-1.6
history: Wed Oct 07 17:19:41 2020: cdo -f nc copy gtgn.t2215z.edr.f0...
institution: National Center for Atmospheric Research
CDO: climate Data Operators version 1.9.8 (https://mpimet.mpg.de...
当我尝试将横截面xarray.dataset写入/保存为netCDF文件时，出现以下错误消息：
cross.to_netcdf('/home/rik/hrrr/gtgn/xarray_cross_section_data_to_netcdf.nc')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-12-0b4fce1219bd> in <module>
----> 1 cross.to_netcdf('/home/rik/hrrr/gtgn/xarray_cross_section_data_to_netcdf.nc')
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/core/dataset.py in to_netcdf(self,path,mode,format,group,engine,encoding,unlimited_dims,compute,invalid_netcdf)
1565 unlimited_dims=unlimited_dims,1566 compute=compute,-> 1567 invalid_netcdf=invalid_netcdf,1568 )
1569
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/backends/api.py in to_netcdf(dataset,path_or_file,multifile,invalid_netcdf)
1080 # to be parallelized with dask
1081 dump_to_store(
-> 1082 dataset,store,writer,encoding=encoding,unlimited_dims=unlimited_dims
1083 )
1084 if autoclose:
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/backends/api.py in dump_to_store(dataset,encoder,unlimited_dims)
1126 variables,attrs = encoder(variables,attrs)
1127
-> 1128 store.store(variables,attrs,check_encoding,unlimited_dims=unlimited_dims)
1129
1130
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/backends/common.py in store(self,variables,attributes,check_encoding_set,unlimited_dims)
248 writer = ArrayWriter()
249
--> 250 variables,attributes = self.encode(variables,attributes)
251
252 self.set_attributes(attributes)
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/backends/common.py in encode(self,attributes)
337 # All NetCDF files get CF encoded by default,without this attempting
338 # to write times,for example,would fail.
--> 339 variables,attributes = cf_encoder(variables,attributes)
340 variables = {k: self.encode_variable(v) for k,v in variables.items()}
341 attributes = {k: self.encode_attribute(v) for k,v in attributes.items()}
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/conventions.py in cf_encoder(variables,attributes)
771 _update_bounds_encoding(variables)
772
--> 773 new_vars = {k: encode_cf_variable(v,name=k) for k,v in variables.items()}
774
775 # Remove attrs from bounds variables (issue #2921)
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/conventions.py in <dictcomp>(.0)
771 _update_bounds_encoding(variables)
772
--> 773 new_vars = {k: encode_cf_variable(v,v in variables.items()}
774
775 # Remove attrs from bounds variables (issue #2921)
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/conventions.py in encode_cf_variable(var,needs_copy,name)
256 var = maybe_default_fill_value(var)
257 var = maybe_encode_bools(var)
--> 258 var = ensure_dtype_not_object(var,name=name)
259 return var
260
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/conventions.py in ensure_dtype_not_object(var,name)
214 data[missing] = fill_value
215 else:
--> 216 data = _copy_with_dtype(data,dtype=_infer_dtype(data,name))
217
218 assert data.dtype.kind != "O" or data.dtype.Metadata
~/miniconda3/envs/metpy/lib/python3.7/site-packages/xarray/conventions.py in _infer_dtype(array,name)
150 raise ValueError(
151 "unable to infer dtype on variable {!r}; xarray "
--> 152 "cannot serialize arbitrary Python objects".format(name)
153 )
154
ValueError: unable to infer dtype on variable 'crs'; xarray cannot serialize arbitrary Python objects
我在做什么错了？
解决方法
正如@Robert Wilson在评论中建议的那样，您必须从坐标中删除crs。但是，drop_vars()从数据集中删除变量。如要删除坐标，
cross = cross.reset_coords('crs',drop=True)
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