RMS error is standard in climate science and IMHO would be quite sufficient for these purposes.

If I wanted to get fancy, I'd try to construct a utility-based loss function that relates the Pacific SST field to, say, the probability of extreme temperature or precipitation events at some populated location, and see if that gives a much different predictive model. (I doubt it...)