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pythonpython-xarray

Is there any easy way to compute seasonal mean with xarray?

A lot of monthly NetCDF files contains all months in many years (for example, from Jan1948 to Dec2018).

How to use Xarray to compute the seasonal average of each year conveniently?

There are examples using GroupBy to calculate seasonal average, but it seems to group all the months spanning many years to 4 groups, which can't give the seasonal average of every year.

Solution

  • It sounds like you are looking for a resample-type operation. Using the get_dpm function from the documentation example you linked to, I think something like the following should work:

    month_length = xr.DataArray(
    get_dpm(ds.time.to_index(), calendar='standard'),
    coords=[ds.time],
    name='month_length'
)
result = ((ds * month_length).resample(time='QS-DEC').sum() / 
          month_length.resample(time='QS-DEC').sum())

    Using 'QS-DEC' frequency will split the data into consecutive three-month periods, anchored at December 1st.

    If your data has missing values, you'll need to modify this weighted mean operation to account for that (i.e. we need to mask the month_length before taking the sum in the denominator):

    result = (ds * month_length).resample(time='QS-DEC').sum() / 
          month_length.where(ds.notnull()).resample(time='QS-DEC').sum())