数值模式 | 如何对WRF变量场的地形缺测进行填补

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Installing collected packages: skyborn
Successfully installed skyborn-0.3.14

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.util import add_cyclic_point
from netCDF4 import Dataset
from wrf import getvar, interplevel, latlon_coords, get_cartopy
from skyborn.gridfill.xarray import fill as xr_fill
import xarray as xr

# 路径替换成你的 wrfout 文件
wrf_file = Dataset('/home/mw/input/typhoon9537/wrfout_d01_2019-08-08_23_00_00')

# 提取变量
print("🌀 提取WRF变量中...")
lon = getvar(wrf_file, 'lon')
lat = getvar(wrf_file, 'lat')
p = getvar(wrf_file, 'pressure')

t = getvar(wrf_file, 'tc')

t850 = interplevel(t, p, 850)
t850.plot()

🌀 提取WRF变量中...





<matplotlib.collections.QuadMesh at 0x7f47525a58b0>

# GridFill 填补
temp_filled = xr_fill(t850, x_dim='west_east',
    y_dim='south_north',eps=1e-4, relax=0.6, itermax=300, initzonal=True)
temp_filled.plot()

🔧 开始 GridFill 填补...


/opt/conda/lib/python3.9/site-packages/skyborn/gridfill/xarray.py:403: UserWarning: gridfill did not converge on 1 out of 1 slices. Consider increasing itermax or relaxing eps tolerance.
  warnings.warn(





<matplotlib.collections.QuadMesh at 0x7f4741442550>

import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
from matplotlib import ticker
import cartopy.crs as ccrs
import cartopy.feature as cfeature

# 设置论文级别的绘图参数
plt.rcParams.update({
    'font.family': 'serif',
    'font.serif': ['Times New Roman', 'DejaVu Serif'],
    'font.size': 12,
    'axes.labelsize': 14,
    'axes.titlesize': 16,
    'xtick.labelsize': 12,
    'ytick.labelsize': 12,
    'legend.fontsize': 12,
    'figure.dpi': 300,
    'savefig.dpi': 600,
    'savefig.bbox': 'tight',
    'savefig.pad_inches': 0.1,
    'figure.constrained_layout.use': True
})

# 创建填补前后的对比图
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 8), 
                              subplot_kw={'projection': ccrs.PlateCarree()})

# 颜色映射和等级设置
temp_levels = np.linspace(10, 30, 21)
diff_levels = np.linspace(-1.5, 1.5, 21)
cmap_temp = 'RdBu_r'
cmap_diff = 'coolwarm'

# 第一幅图：原始温度场
im1 = ax1.contourf(lon.values, lat.values, t850.values, 
                  levels=temp_levels, cmap=cmap_temp, extend='both')
ax1.coastlines(linewidth=0.8, color='black')
ax1.add_feature(cfeature.BORDERS, linewidth=0.5, edgecolor='gray')
ax1.set_title('(a) Original 850 hPa Temperature Field', fontsize=16, pad=20, fontweight='bold')
ax1.set_xlabel('Longitude (°E)', fontsize=14, labelpad=10)
ax1.set_ylabel('Latitude (°N)', fontsize=14, labelpad=10)

# 添加经纬度网格
gl1 = ax1.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                   linewidth=0.5, color='gray', alpha=0.7, linestyle='--')
gl1.top_labels = False
gl1.right_labels = False
gl1.xlabel_style = {'size': 10}
gl1.ylabel_style = {'size': 10}

# 第二幅图：填补后的温度场
im2 = ax2.contourf(lon.values, lat.values, temp_filled.values, 
                  levels=temp_levels, cmap=cmap_temp, extend='both')
ax2.coastlines(linewidth=0.8, color='black')
ax2.add_feature(cfeature.BORDERS, linewidth=0.5, edgecolor='gray')
ax2.set_title('(b) GridFill Interpolated 850 hPa Temperature Field', 
              fontsize=16, pad=20, fontweight='bold')
ax2.set_xlabel('Longitude (°E)', fontsize=14, labelpad=10)
ax2.set_ylabel('Latitude (°N)', fontsize=14, labelpad=10)

gl2 = ax2.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                   linewidth=0.5, color='gray', alpha=0.7, linestyle='--')
gl2.top_labels = False
gl2.right_labels = False
gl2.xlabel_style = {'size': 10}
gl2.ylabel_style = {'size': 10}

# 添加颜色条
cbar_ax = fig.add_axes([0.15, 0.05, 0.7, 0.02])  # 将y位置从0.08改为0.05，高度从0.03改为0.02
cbar = fig.colorbar(im1, cax=cbar_ax, orientation='horizontal', 
                   label='Temperature (°C)', extend='both')
cbar.ax.tick_params(labelsize=12)
cbar.set_label('Temperature (°C)', fontsize=14, labelpad=10)
plt.show()