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When averaging over time dimension, weight by number of days per month #3

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mnlevy1981 opened this issue Nov 30, 2018 · 0 comments

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mnlevy1981 commented Nov 30, 2018

Plotting climatologies now produces annual and seasonal means. Currently, each month is weighted evenly:

# set up time dimension for averaging
time_dims = dict()
time_dims['ANN'] = range(0,12)
time_dims['DJF'] = [11, 0, 1]
time_dims['MAM'] = range(2,5)
time_dims['JJA'] = range(5,8)
time_dims['SON'] = range(8,11)

field = ds[var_name].sel(**indexer).isel(time=time_dims[time_period]).mean('time')

These are fine as a placeholder, but I assume the CESM diagnostics package weights by days per month in which case we should do so as well.

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