RStudio AI Blog: An introduction to weather forecasting with deep learning

With all that is going on in the world these days, is it frivolous to talk about weather prediction? Asked in the 21st century, this is bound to be a rhetorical question. Today, no lengthy justification is needed as to why prediction of atmospheric states is vital: Due to global warming, frequency and intensity of severe weather conditions – droughts, wildfires, hurricanes, heatwaves – have risen and will continue to rise. And while accurate forecasts don't change those events per se, they constitute essential information in mitigating their consequences. This goes for atmospheric forecasts on all scales: from so-called "nowcasting" (operating on a range of about six hours), over medium-range (three to five days) and sub-seasonal (weekly/monthly), to climate forecasts (concerned with years and decades).