A Novel RFAt-UNet3+ Learning Model for Rainfall Forecast with
Meteorological Radar
Abstract
Rainfall forecast is generally defined as the prediction of
precipitation or severe convective weather in a specific region over a
short time interval, recognized as playing an extremely important role
in daily meteorological disaster prevention. Traditional precipitation
forecasting methods, which primarily rely on numerical weather
prediction, have limited the capability to utilize the latest
information for short-term precipitation nowcast. A novel deep learning
model based on the RFAt- UNet3+ is proposed for precipitation
nowcasting, which is composed of the attention and receptive field
modules additionally. An accurate precipitation forecast is accomplished
by employing a data-driven neural network approach.