使用era5数据做行星边界层高度图python代码

以下是使用ERA5数据生成行星边界层高度图的 Python 代码：

import numpy as np
import xarray as xr
import matplotlib.pyplot as plt

# Load ERA5 data using xarray
data = xr.open_dataset('/path/to/era5/data.nc')

# Extract variables
u = data.u10  # 10m zonal wind component
v = data.v10  # 10m meridional wind component
t = data.t2m  # 2m temperature
sp = data.sp  # Surface pressure
z = data.z    # Geopotential

# Calculate potential temperature
theta = t * (1000 / sp) ** 0.286

# Calculate geostrophic wind
f = 2 * 7.2921e-5 * np.sin(np.deg2rad(data.latitude))
ug = -1 / f * v.differentiate('longitude')  # zonal geostrophic wind
vg = 1 / f * u.differentiate('longitude')   # meridional geostrophic wind

# Calculate ageostrophic wind
ua = u - ug  # zonal ageostrophic wind
va = v - vg  # meridional ageostrophic wind

# Calculate absolute vorticity
avort = (vg.differentiate('longitude') - ug.differentiate('latitude')) + f

# Calculate vertical vorticity
vort = avort - f

# Calculate boundary layer height using Ekman layer theory
Cd = 1e-3  # Drag coefficient
rho = 1.225  # Air density
h = (Cd * rho * 2 * np.pi / (24 * 3600)) ** (1 / 3) * (ug ** 2 + vg ** 2) ** (1 / 6)

# Convert geopotential height to meters
z_m = z / 9.81

# Calculate planetary boundary layer height
pblh = xr.DataArray(np.zeros_like(t), dims=t.dims, coords=t.coords)
lev = z_m.level.values
for i in range(len(t.latitude)):
    for j in range(len(t.longitude)):
        # Find the lowest level where vorticity exceeds a threshold
        for k in range(len(lev)):
            if vort[i, k, j] > 0.05:
                pblh[i, j] = lev[k]
                break

# Plot PBL height as a contour map
lon, lat = np.meshgrid(pblh.longitude.values, pblh.latitude.values)
plt.contourf(lon, lat, pblh.T, cmap='jet')
plt.colorbar(label='PBL height (m)')
plt.title('Planetary Boundary Layer Height')
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.show()

注意，此代码仅提供一个示例，具体实现可能需要根据你的数据格式和需求做出一些修改。