如何通过特定变量值从 netcdf 文件中获取 select 数据？

Question

I am searching for an option to select data from a NetCDF file at a specific variable value. The dataset contains time, lat, and lon coordinates and a range of variables. One of these variables is a mask with specific values for Land/ open ocean/ sea-ice /lake. Since the open ocean is represented by ds.mask = 1, I want to extract only sea surface temperature values which are located at the coordinates (time and space) where mask = 1. However, I do not want the sea surface temperature values at other coordinates to be set to NaN, but to keep only those coordinates and variable's values where ds.mask = 1. I know how to select and data with xarray.sel/isel, however, this works only with selecting by coordinates, not by variable values as I am trying it. Any help would be very much appreciated.

lati = stormtrack_lat.values
loni = stormtrack_lon.values
timei = stormtrack_datetime.values
tmax = timei.max() + np.timedelta64(10,'D')
tmin = timei.min() - np.timedelta64(10,'D')
SSTskin_subfile = SSTskin_file.sel(time=slice(tmin, tmax))

#HERE I NEED HELP:
#extract data where mask = ocean (1) and use only these data points and keep these only!
SSTskin_subfile_masked = SSTskin_subfile.sel(SSTskin_subfile.mask == 1) #does not work yet (Thrown error: ValueError: the first argument to .isel must be a dictionary)

This is the NetCDF file's structure:

Answer 1

You can apply the ocean mask with.where:

SSTskin_subfile_masked = SSTskin_subfile.where(SSTskin_subfile.mask)

It is not possible to drop all masked points because the data are gridded. For example if you have just one defined value for a given latitude, you have to keep all the values along it. However you can drop the coordinates where all values are NaN with:

SSTskin_subfile_masked.dropna(dim = ['lat', 'lon'], how = 'all')