如何在xarray中绘制不规则的经纬度？

Question

我有一个包含一个月每日数据的 netcdf 文件。在这个文件中，有 irregular latitude and longitude 个点数据。我想创建 time[0] 或此数据的任何时间的图，但结果似乎不正确。如何用 nan-space 显示情节？

数据文件 https://www.dropbox.com/s/ll35zh4k5ws7nnh/day1.nc?dl=0

代码

import xarray as xr
month_daily1 = xr.open_dataset('/Daily_Month/1/day1.nc')
month_daily1

<xarray.Dataset>
Dimensions:                 (Lat: 175, Lon: 200, time: 31)
Coordinates:
  * time                    (time) datetime64[ns] 2018-01-01 ... 2018-01-31
  * Lat                     (Lat) float64 29.92 29.93 29.94 ... 33.0 33.01 33.02
  * Lon                     (Lon) float64 47.61 47.62 47.63 ... 50.5 50.51 50.52
Data variables:
    Alt                     (time, Lat, Lon) float64 ...
    Temperature             (time, Lat, Lon) float64 ...
    Relative Humidity       (time, Lat, Lon) float64 ...
    Wind speed              (time, Lat, Lon) float64 ...
    Wind direction          (time, Lat, Lon) float64 ...
    Short-wave irradiation  (time, Lat, Lon) float64 ...


# convert kelvin to celsius
data_nonnull = month_daily1.dropna(dim ='time', how='all')
air = data_nonnull.Temperature - 273.15
air


<xarray.DataArray 'Temperature' (time: 31, Lat: 175, Lon: 200)>
array([[[nan, nan, ..., nan, nan],
        [nan, nan, ..., nan, nan],
      ...,

       [[nan, nan, ..., nan, nan],
        [nan, nan, ..., nan, nan],

       [[nan, nan, ..., nan, nan],
        [nan, nan, ..., nan, nan],

Coordinates:
  * time     (time) datetime64[ns] 2018-01-01 2018-01-02 ... 2018-01-31
  * Lat      (Lat) float64 29.92 29.93 29.94 29.95 ... 32.99 33.0 33.01 33.02
  * Lon      (Lon) float64 47.61 47.62 47.63 47.64 ... 50.41 50.5 50.51 50.52


%matplotlib inline

import matplotlib.pyplot as plt
ax = plt.subplot(projection=ccrs.PlateCarree())
air2d = air.isel(time= 0)
air2d.plot.pcolormesh('Lon', 'Lat');

结果

Answer 1

我不太擅长 XArray，因此建议使用模块 netCDF4 解决方案：

#!/usr/bin/env ipython
import xarray as xr
import matplotlib as mpl
mpl.use('tkagg')
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
# =======================================================
from netCDF4 import Dataset
ncin=Dataset('day1.nc');
tempin=ncin.variables['Temperature'][0,:,:]- 273.15;
lonin=ncin.variables['Lon'][:];
latin=ncin.variables['Lat'][:];
ncin.close()
# -------------------------------------------------------
from scipy.interpolate import griddata
import numpy as np
kk=np.where(np.isnan(np.array(tempin).flatten())==False)
lonm,latm=np.meshgrid(lonin,latin);
tinterp=griddata((lonm.flatten()[kk],latm.flatten()[kk]),tempin.flatten()[kk],(lonm,latm));

ax = plt.subplot(121,projection=ccrs.PlateCarree())
ax.pcolormesh(lonin,latin,tempin);
ax = plt.subplot(122,projection=ccrs.PlateCarree())
ax.pcolormesh(lonin,latin,tinterp);
plt.show()

最终结果是这样的：左边是原始的，右边是插值的（nan dropped figure）。

我可以提出一个答案，我将 XArray 和 Scipy 网格数据结合起来，因为 interpolate_na 工作得不是很好（查看 filled_a 的部分和结果, filled_b) 对我来说:

#!/usr/bin/env ipython
import xarray as xr
import matplotlib as mpl
mpl.use('tkagg')
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
# =======================================================
month_daily1 = xr.open_dataset('day1.nc')

# convert kelvin to celsius
data_nonnull = month_daily1.dropna(dim ='time', how='all')
air = data_nonnull.Temperature - 273.15
air2d = air.isel(time= 0)
# =======================================================
ax = plt.subplot(121,projection=ccrs.PlateCarree())
air2d.plot.pcolormesh('Lon', 'Lat');
ax = plt.subplot(122,projection=ccrs.PlateCarree())
filled_a=air2d.interpolate_na(dim='Lat');
filled_b=filled_a.interpolate_na(dim='Lon');
filled_c=filled_b.interpolate_na(dim='Lat');
filled_c.plot.pcolormesh('Lon', 'Lat');
plt.show()
# =======================================================
tempin=air2d.values[:];
lonin=air2d.Lon
latin=air2d.Lat
# -------------------------------------------------------
from scipy.interpolate import griddata
import numpy as np
kk=np.where(np.isnan(np.array(tempin).flatten())==False)
lonm,latm=np.meshgrid(lonin,latin);
tinterp=griddata((lonm.flatten()[kk],latm.flatten()[kk]),tempin.flatten()[kk],(lonm,latm));

ax = plt.subplot(121,projection=ccrs.PlateCarree())
ax.pcolormesh(lonin,latin,tempin);
ax = plt.subplot(122,projection=ccrs.PlateCarree())
ax.pcolormesh(lonin,latin,tinterp);
plt.show()

如何在xarray中绘制不规则的经纬度？

How to plot irregular latitude and longitude in xarray?

plot

nan

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python-xarray