This study proposes a data-driven framework, 5 termed P2I-GAN, to reconstruct rainfall directly from irregular point measurements, Inspired by the concept of video inpainting in computer vision, which allows spatial organisation of rainfall to be recovered in a temporally consistent manner, even when observations are limited.
Accurate nowcasting of localized extreme rainfall remains particularly challenging when observations are based on sparse and irregular rain-gauge networks. This article presents a framework for 1-h-ahead severe rainfall nowcasting that integrates spatial reconstruction, spatiotemporal deep learning, and extremes-orient...
Débora S. Rodrigues, A. Caseri, S. Pesco· IEEE Geoscience and Remote S...· 0 citations
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.
Braiton U. Mukhalela, S. Viriri, D. Ndzi et al.· Frontiers in Artificial Inte...· 0 citations
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...
Xiang Lin, Yunying Li, Cheng-Zhi Ye et al.· 0 citations
Subsurface ocean observations remain severely limited in spatial coverage due to the high cost and operational difficulty of
in-situ
deployment. Although moored buoys and profiling floats enable continuous, minute-level sampling at fixed locations, the temporal evolution information they record is largely underutil...
Lu-,-Hong-Feng-,-Li-Zheng-Bao-,-Guo-Zhong-Wen Hong, Meng-Yao Wang, Qing Xu et al.· Frontiers in Marine Science· 0 citations
Flash flooding from intense rainfall causes major damage and loss of life across Africa, particularly in the Sahel, where rainfall is dominated by mesoscale convective systems. Convective cores, which represent regions of intense convective activity, evolve rapidly, limiting short‐term predictability, especially in...
Mendrika Rakotomanga, D. J. Parker, Nadhir Ben Rached et al.· Quarterly Journal of the Roy...· 0 citations
Accurate quantitative precipitation estimation (QPE) is critical for responding to severe weather events such as heavy rainfall. Deep learning (DL) methods, which can establish nonlinear mappings between radar observations and rain rate (R), have been widely applied to reduce QPE errors. This study evaluates point-base...
