ML/AI has been used in the weather forecasting world since the 1970's - most often to post-process forecast model output to better calibrate it against observat

ML/AI has been used in the weather forecasting world since the 1970's - most often to post-process forecast model output to better calibrate it against observations and correct for biases. > One would think this would be one of the first areas that would adopt AI given the data available. Actually, the challenge has been that there _isn't_ enough data available. Sure, we have lots of satellite observations and many other sources, but none of these paint a holistic picture of the atmosphere of the sort you'd need to actually forecast the weather with any precision. ERA-5 - a model-based "re-analysis" that assimilates many observations and tries to create a coherent picture - is only a few years old, and has been the keystone that unlocked all of this development over the past few years.