Description:

Weather events, especially extremes, are causing ever-larger socioeconomic impacts in recent decades due to changes in their statistics and societal changes. Hence, there is an increased need for a more accurate representation of climate and weather events in observations, forecasts (both on the weather and S2S time scales), and climate projections. With the advent of modern AI and its applications to the prediction and estimation of weather and climate variables using multiple sources of information, traditional forecasting methods are being challenged and improved. We welcome contributions to the applications of AI to improve the estimation, forecasting, and projections of hydrometeorological variables that take advantage of the complementary nature of remote sensing information (satellite sensors and radars), in conjunction with in-situ observations and numerical prediction models.