I am using sea surface temperature, chlorophyll, and other data parameters as covariants in a model, and I would like to average them over a particular time period.
I am currently doing this using a simple average of the values across the days in my time period, but this is flawed due to missing data from cloud-cover, etc. (and perhaps other reasons).
filledsst = np.average((datafile.variables["FilledSST"][idx1:idx2,:,:]), axis=0)
What technique is typically used for accounting for such missing data?