使用 Cartopy 和 netCDF4 可视化 WRF 模式数据

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import netCDF4 as nc

fip = '../sample_file/'
fin = 'wrfout_v2_Lambert.nc'

# Dataset 方法用来读取数据，和 open 类似，只是这是用来处理 nc 数据
data = nc.Dataset(fip + fin, 'r')

# 使用 variables 获取变量，可以指定变量名和要获取的变量名索引
t   = data.variables['T2'][6, :, :]
lon = data.variables['XLONG'][6, :, :]
lat = data.variables['XLAT'][6, :, :]

fig, ax = plt.subplots(subplot_kw = dict(projection = ccrs.PlateCarree()))

ax.contourf(lon, lat, t)
ax.coastlines(resolution = '10m')

# 设置 gridlines 和 ticklabels 
gl = ax.gridlines(draw_labels = True, linewidth = 1.5)
gl.xlabels_top = False 
gl.xlines = True
gl.xformatter = LONGITUDE_FORMATTER
gl.ylabels_right = False 
gl.ylines = True
gl.yformatter = LATITUDE_FORMATTER

plt.show()

import matplotlib.pyplot as plt
import numpy as np
import cartopy.crs as ccrs
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import netCDF4 as nc

fip = './'
fin = 'wrfout_v2_Lambert.nc'

data = nc.Dataset(fip + fin, 'r')

lon = data.variables['XLONG'][6, :, :]
lat = data.variables['XLAT'][6, :, :]
u   = data.variables['U10'][6, :, :]
v   = data.variables['V10'][6, :, :]

fig, ax = plt.subplots(subplot_kw = dict(projection = ccrs.PlateCarree()))

ax.contourf(lon, lat, np.sqrt(u**2 + v**2), alpha = 0.4)
ax.barbs(lon[::5,::5], lat[::5,::5], u[::5,::5], v[::5,::5])
ax.coastlines(resolution = '10m')

gl = ax.gridlines(draw_labels = True, linewidth = 1.5)
gl.xlabels_top = False 
gl.xlines = True
gl.xformatter = LONGITUDE_FORMATTER
gl.ylabels_right = False 
gl.ylines = True
gl.yformatter = LATITUDE_FORMATTER

plt.show()