hesam eivazy <firstname.lastname@example.org> wrote in message <email@example.com>... > A=180-by-360 matrix of (surface temperature) > B=180-by-360 matrix of latitudes corresponding to A > weighted mean=(sum(A.*B))/(180*360) >
Thanks for your answer! However, I don't get the answer that I need.
I usually use FERRET when I work with global gridded fields. Calculating the global weighted average with FERRET is different. FERRET computes an approximation to the global mean using the gridded field. Given a latitude and longitude vector it defines a grid and already knows how to weight each value depending on the latitude.
In Matlab the data fields are loaded as a matrix. Taken the mean of this matrix does not weight the different elements by its area and gives me only the unweighted-average. This gives me an global average that is not really realistic.
Is there a function or method that accounts for that in Matlab when working with global gridded fields?