loading page

A Novel RFAt-UNet3+ Learning Model for Rainfall Forecast with Meteorological Radar
  • Genhua Chen,
  • Man Hu
Genhua Chen
Nanchang Institute of Technology

Corresponding Author:cgh@nit.edu.cn

Author Profile
Man Hu
Nanchang Institute of Technology
Author Profile

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.
27 Dec 2024Submitted to Electronics Letters
09 Jan 2025Submission Checks Completed
09 Jan 2025Assigned to Editor
09 Jan 2025Review(s) Completed, Editorial Evaluation Pending
12 Jan 2025Reviewer(s) Assigned