代码实战 | 基于 global-land-mask 的陆地掩膜气象可视化

!pip install global-land-mask -i https://pypi.mirrors.ustc.edu.cn/simple/

Looking in indexes: https://pypi.mirrors.ustc.edu.cn/simple/
Collecting global-land-mask
  Downloading https://mirrors.ustc.edu.cn/pypi/packages/e6/e9/eaac67e39b68f64828a164f8dbfcf13baccd7382704ea120152af475f520/global_land_mask-1.0.0-py3-none-any.whl (1.8 MB)
[K     |████████████████████████████████| 1.8 MB 2.6 MB/s eta 0:00:01
[?25hInstalling collected packages: global-land-mask
Successfully installed global-land-mask-1.0.0

import numpy as np  
import matplotlib.pyplot as plt  
import cartopy.crs as ccrs  
from global_land_mask import globe  
# 定义经纬度范围  
lat = np.linspace(10, 90, 1000)  
lon = np.linspace(60, 140, 1002)  

# 创建经纬度网格  
lon_grid, lat_grid = np.meshgrid(lon, lat)  

# 判断每个点是否在陆地上  
z = globe.is_land(lat_grid, lon_grid)  

import xarray as xr
ds = xr.open_dataset("/home/mw/input/ERA5_Lekima4742/ERA5_Lekima.nc")
ds

<xarray.Dataset> Dimensions:    (longitude: 401, latitude: 321, level: 7, time: 72) Coordinates:
longitude  (longitude) float32 60.0 60.25 60.5 60.75 ... 159.5 159.8 160.0latitude   (latitude) float32 80.0 79.75 79.5 79.25 ... 0.75 0.5 0.25 0.0level      (level) int32 250 500 600 700 850 925 1000time       (time) datetime64[ns] 2019-08-08 ... 2019-08-10T23:00:00 Data variables: z          (time, level, latitude, longitude) float32 ... r          (time, level, latitude, longitude) float32 ... q          (time, level, latitude, longitude) float32 ... t          (time, level, latitude, longitude) float32 ... u          (time, level, latitude, longitude) float32 ... v          (time, level, latitude, longitude) float32 ... w          (time, level, latitude, longitude) float32 ... Attributes: Conventions:  CF-1.6 history:      2023-05-29 04:40:37 GMT by grib_to_netcdf-2.25.1: 

from global_land_mask import globe
import xarray as xr

lat = ds.latitude
lon = ds.longitude
lon_grid, lat_grid = np.meshgrid(lon,lat)

# 使用 global-land-mask 生成掩码
is_land = globe.is_land(lat_grid, lon_grid)

# 3. 应用掩码
u = ds.u[0,0]
# 将海洋上的 u 数据设置为 NaN
u_masked =u.where(is_land, np.nan)
# 打开样例数据
u_masked.plot()

<matplotlib.collections.QuadMesh at 0x7f94f0a296a0>

u_masked2 =u.where(~is_land)
# 打开样例数据
u_masked2.plot()

<matplotlib.collections.QuadMesh at 0x7f94ef179640>