Enhancing NWP precipitation forecasting with Rain-PostEFNet: A multi-scale deep learning approach

Deep learning techniques for extreme rainfall prediction: a review of state-of-the-art

The analysis reveals a transition from deterministic DI models to hybrid, physics-informed, uncertainty-aware, and operational forecasting systems that increasingly integrate AI with physical knowledge and heterogeneous environmental observations.

RainAtlas: A Multi-Continental Dataset for Precipitation Downscaling

Extreme rainfall events are increasing in intensity and frequency as climate change accelerates. While kilometer-scale precipitation forecasts are critical for supporting local decision-making, the limited availability of high-resolution precipitation observations hinders their accuracy, especially in under-resourced r...

MAGPIE-Net: Predicting short-duration heavy-rainfall events in station neighborhoods from multitemporal FY-4A AGRI observations

Short-duration heavy-rainfall warning determines whether 1 h rainfall will exceed a threshold within a target-station neighborhood over the next few hours. Multitemporal infrared and water-vapor observations from the Fengyun-4A Advanced Geostationary Radiation Imager (FY-4A AGRI) capture cloud-top cooling, moisture evo...

A transformer-based post-processing framework with a band-wise differentiable threat score loss for regional heavy-precipitation bias correction

Deep Learning-Based Multi-Step Ahead Streamflow Forecasting under RCP 4.5 and 8.5 Scenarios

The results demonstrate that deep learning models, particularly when enriched with spatially interpolated inputs and land cover variability, significantly enhance forecasting accuracy and provide valuable projections for future water availability but also informs sustainable water management strategies in climate-sensi...

Multi-step Marine-oriented Daily Runoff Forecasting by Integrating Convolutional and Sparse Attention Mechanisms

Accurate runoff marine-influenced forecasting is essential for extending lead time, optimizing nearshore water resource management, and supporting coastal flood control and disaster mitigation. A novel model, called LogConvFormer, has been developed to address the temporal lag in multi-step runoff prediction and improv...