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Not to take away from the excitement but ML weather prediction builds upon the years of data produced by numerical models on supercomputers. It cannot do anythi
by wenc 3y ago
Not to take away from the excitement but ML weather prediction builds upon the years of data produced by numerical models on supercomputers. It cannot do anything without that computation and its forecasts are dependent on the quality of that computation. Ensemble models are already used to quantify uncertainty (it’s referenced in their paper).
But it is exciting that they are able to recognize patterns in multi year and produce medium term forecasts.
Some comments here suggest this replaces supercomputers models. This would a wrong conclusion.It does not (the paper explicitly states this). It uses their output as input data.
- boxed 3y agoI don't get this. Surely past and real weather should be the input training data, not the output of numerical modeling?
- counters 3y agoWell, what is "real weather data?" We have dozens of complementary and contradictory sources of weather information. Different types of satellites measuring EM radiation in different bands, weather stations, terrestrial weather radars, buoys, weather balloons... it's a massive hodge-podge of different systems measuring different things in an uncoordinated fashion. Today, it's not really practical to assemble that data and directly feed it into an AI system. So the state-of-the-art in AI weather forecasting involves using an intermediate representation - "reanalysis" datasets which apply a sophisticated physics based weather model to assimilate all of these data sets into a single, self-consistent 3D and time-varying record of the state of the atmosphere. This data is the unsung hero of the weather revolution - just as the WMO's coordinated synoptic time observations for weather balloons catalyzed effective early numerical weather prediction in the 50's and 60's, accessible re-analysis data - and the computational tools and platforms to actually work with these peta-scale datasets - has catalyzed the advent of "pure AI" weather forecasting systems.
- goosinmouse 3y agoGreat comment, thank you for sharing your insights. I don't think many people truly understand just how massive these weather models are and the sheer volume of data assimilation work that's been done for decades to get us to this point today. I always have a lot of ideas about using AI to solve very small scale weather forecasting issues, but there's just so much to it. It's always a learning experience for sure.
- boxed 3y agoOh yea, sure. But the article makes it seems like the model is trained on some predictive model, instead of a synthesis model. That seems weird to me.