globalop field in griddata is incorrect when grid cells are missing

[rplzzz]

When part of a grid is missing, as, for example, in the land-only data files provided by ISIMIP, we drop all of the grid cells containing NA values:

fldgen/R/handle_NAs.R

Lines 50 to 55 in c8e220d

	## Find the grid cells with valid data
	valid_cells <- which(nmiss == 0)
	## Drop missing cells from vardata and globalop
	griddata$vardata <- griddata$vardata[ , valid_cells]
	griddata$globalop <- griddata$globalop[valid_cells, ]

The globalop field is the global mean operator; we have to drop the missing values from there too. However, for the global mean operator to do its job, it has to be scaled so that it sums up to 1, and we don't rescale it here. This causes our global mean temperatures to be bogus.

> emu <- train_models('IPSL-CM5A-LR')
> sum(emu$griddataT$globalop)
[1] 0.2869764
> summary(emu$tgav)
       V1       
 Min.   :81.73  
 1st Qu.:82.01  
 Median :82.16  
 Mean   :82.39  
 3rd Qu.:82.73  
 Max.   :84.28