如何使用 python 从 netcdf 数据集中找到气候月平均值？

Question

I have a netcdf data set of (monthly timexlatitudexlongitude). No of month is 216, so total 18 years. 1st index represent the january data, 2nd index represent the february data... 12th index represent december data and again 13th index represent january data, 14th index represent february data so on and so forth. Now I want to find mean of all january data, mean of all february data... mean of all december data. So after doing this operation the size of the array will be reduce to 12xlatxlon(previously it was 216xlatxlon). How can I do that?

Answer 1

If you are working on linux or macOS, you can do this in a couple of lines with my nctoolkit package ( https://nctoolkit.readthedocs.io/en/latest/ ):

import nctoolkit as nc

ds = nc.open_data("infile.nc")
# get the mean using month as the averaging period
ds.tmean("month")
# plot to visualize
ds.plot()

Answer 2

You can use the very convenient resample() option from xarray / pandas .

import xarray as xr 

ds = xr.open_dataset('file.nc')
ds_monthly_mean = ds.resample(time="1MS").mean()

print(ds.time.shape)
(5619,)

print(ds_monthly_mean.time.shape)
(12,)

Check out the offset aliases if you don't know what resampling option to use. After defining the dimension over which to resample the data, just select your resampling method (mean, sum, etc....)