Why does it work for weather at all? Is there something that the mathematical models are over-simulating? Is weather easier to predict than we thought? Just curious what the intuition is to regarding the success of ML weather modelling...
There is just A LOT of data available- usually an order of magnitude more than in any other related problem.
And general weather forecasts are not that hard - we have semi useful forecasts for more than 50 years. It’s when you want to do something special: long range, nowcasting of convective storm, other extreme weather etc. that is hard. And even then it’s as much a problem of input data accuracy than the models themselves.
There is just A LOT of data available- usually an order of magnitude more than in any other related problem.
And general weather forecasts are not that hard - we have semi useful forecasts for more than 50 years. It’s when you want to do something special: long range, nowcasting of convective storm, other extreme weather etc. that is hard. And even then it’s as much a problem of input data accuracy than the models themselves.