Weather forecasting without the difficult bits
Philip Brohan
Hadley Centre, UK Met Office
Tuesday, Jul 23, 2019, 11:00 am
DSRC Room GC402
Abstract
Modern weather-forecast models are amazing: amazingly powerful, amazingly accurate - amazingly complicated, amazingly expensive to run and to develop, amazingly difficult to use and to experiment with. Quite often, I'd rather have something less amazing, but much faster and easier to use. Modern machine learning methods offer sophisticated statistical approximators even to very complex systems like the weather, and we now have hundreds of years of reanalysis output to train them on. How good a model can we build without using any physics, dynamics, chemistry, etc. at all?
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