Python：从 shapefile（多边形/多重多边形）中屏蔽 ERA5 数据（NetCDF）

发布于 2025-01-17 15:30:13 字数 673 浏览 3 评论 0原文

我想从瑞士北部和南部地理掩码（加上雷达缓冲区）内的 ERA5 网格数据（仅表面水平）中选择网格单元，以计算区域平均值。 4 个遮罩 (遮罩) 以多边形/多多边形 (多边形) 在 shapefile 中，到目前为止，对于 2 个蒙版，我能够使用 salem roi得到我想要的：

radar_north = salem.read_shapefile('radar_north140.shp')
file_radar_north = file.salem.roi(shape=radar_north)
file_radar_north.cape.mean(dim='time').salem.quick_map()

但是，对于radar_south和alpensuedseite形状文件，代码一开始不起作用（错误选择或不显示数据），现在什么也不起作用了（？）。我不知道为什么，因为从第一次到第二次我没有改变任何东西。

如果有人看到这个问题或知道屏蔽 ERA 数据的不同方法（可能更快），我将不胜感激！（我在这里没有成功地回答类似问题）。

最好的莉娜

原文

I want to select grid cells from ERA5 gridded data (surface level only) that are inside geographical masks for North- and South-Switzerland (plus the radar buffer), to calculate regional means.
The 4 masks (masks) are given as polygons/multipolygons (polygons) in a shapefile and so far for 2 of the masks I was able to use salem roi to get what I want:

radar_north = salem.read_shapefile('radar_north140.shp')
file_radar_north = file.salem.roi(shape=radar_north)
file_radar_north.cape.mean(dim='time').salem.quick_map()

However, for the radar_south and alpensuedseite shapefiles the code didn´t work at the beginning (wrong selection or shows no data), and now the nothing works anymore (?). I don´t know why, as I have not changed anything from the first time to the second.

If someone sees the issue or knows a different way to mask the ERA data (which is maybe quicker) I would be grateful! (I was unsuccessfull with the answers from similar questions here).

Best
Lena

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那请放手 2025-01-24 15:30:13

如果您正在处理NETCDF文件，这可能会起作用

import geopandas as gpd
import xarray as xr
import rioxarray
from shapely.geometry import mapping

# load shapefile with geopandas
radar_north = gpd.read_file('radar_north140.shp')

# load ERA5 netcdf with xarray
era = xr.open_dataset('ERA5.nc')

# add projection system to nc
era = era.rio.write_crs("EPSG:4326", inplace=True)

# mask ERA5 data with shapefile
era_radar_north = era.rio.clip(radar_north.geometry.apply(mapping), radar_north.crs)

This could work if you are working on netcdf files

import geopandas as gpd
import xarray as xr
import rioxarray
from shapely.geometry import mapping

# load shapefile with geopandas
radar_north = gpd.read_file('radar_north140.shp')

# load ERA5 netcdf with xarray
era = xr.open_dataset('ERA5.nc')

# add projection system to nc
era = era.rio.write_crs("EPSG:4326", inplace=True)

# mask ERA5 data with shapefile
era_radar_north = era.rio.clip(radar_north.geometry.apply(mapping), radar_north.crs)

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