python ERA5 画水汽通量散度图地图：风速风向矢量图、叠加等高线、色彩分级、添加shp文件、添加位置点及备注

import matplotlib.pyplot as plt
import numpy as np
from metpy.units import units
import xarray as xr
from metpy.calc import dewpoint, theta
from metpy.plots import plot_crosshairs, plot_barb, plot_dove_tail_vorticity, plot_planet

# 假设已经有了ERA5的数据，并且存储在了netCDF文件中
era5_file = 'era5_data.nc'

# 读取数据
era5 = xr.open_dataset(era5_file)

# 选择一个特定的站点
lat = 40.0
lon = -105.0

# 选择需要的变量
u = era5['u'][0, :, :].values * units('m/s')  # 东西风
v = era5['v'][0, :, :].values * units('m/s')  # 南北风
t = era5['temperature'][0, :, :].values * units('K')  # 温度
td = era5['dewpoint_temperature'][0, :, :].values * units('K')  # 湿度
hgt = era5['geopotential'][0, :, :].values * units('m^2/s^2')  # 地球气压高度

# 计算相对湿度
rh = np.clip(dewpoint(t, td).to('degC'), 0, None)

# 计算水汽通量
evaporation = (
    6.112 * np.exp(5419. / (t - rh)) * (hgt / 9.8) ** 2
) * units('mm/day')  # 假设数据单位是mm/day

# 创建画图
fig = plt.figure(figsize=(12, 9))
ax = fig.add_subplot(1, 1, 1, projection=era5.metpy.cartopy_crs)

# 绘制等高线
ax.contourf(era5['level'].values, era5.metpy.y, era5.metpy.x, hgt.m, 15, cmap='Spectral_r')

# 绘制色彩分级的水汽通量
plot_planet(era5.metpy.y, era5.metpy.x, evaporation, cmap='viridis', norm=None, ax=ax)

# 绘制风速和风向
plot_barb(era5.metpy.y, era5.metpy.x, u, v, ax=ax)

# 绘制笛卡尔流向和笛卡尔强度
plot_dove_tail_vorticity(era5.metpy.y, era5.metpy.x, u, v, ax=ax)

# 绘制坐标
plot_crosshairs(lat, lon, ax=ax, linewidth=2)

# 设置标题和坐标轴
ax.set_title(f'ERA5 Wind, Vorticity, and Evaporation at {lat:.2f}°N, {lon:.2f}°W')
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')

# 显示图例
plt.legend()

# 保存图片
plt.savefig('era5_map.png', bbox_inches='tight', pad_inches=0.1)

# 显示图像
plt.show()