Precipitation Map

Precipitation maps are visual representations of rainfall distribution, crucial for weather forecasting, hydrological modeling, and various socio-economic applications. Current research focuses on improving the accuracy and resolution of these maps using deep learning architectures like U-Nets, ConvLSTMs, and GANs, often incorporating techniques like distributional regression and attention mechanisms to enhance forecast skill and explainability. These advancements aim to address limitations in existing models, particularly concerning the representation of high-intensity events and the incorporation of fine-scale spatial details, ultimately leading to more reliable and informative precipitation forecasts.