arXiv cs.AI· Zijiang Song, Shuang Yang, Yuying Li, Zilong Zhu, Xigang Sun, Ting Liu, Wenye Xiao, Lina Yuan, Min Liu·· 13 小时前AI 评分39
Huayu-Global：跨星座深度学习实现实时准全球降水反演
Huayu-Global: Skillful real-time quasi-global precipitation retrieval
AI 导读
Huayu-Global 是一个跨星座深度学习系统，融合五颗卫星的三路地球静止轨道传感器数据流，每 30 分钟生成一致的准全球降水场。在两个非训练年份的超过一百万条独立站点记录上，其事件检测和降水量估计均优于所评估的实时产品，关键指标达到延迟产品水平。该系统可将业务化地球静止观测转化为高精度实时降水层，用于洪水预报、水资源管理和灾害响应。
正文 · 原文
Abstract:Satellite precipitation products face a persistent trade-off: real-time estimates are timely but less accurate, whereas the most reliable products are often released months after observation. This delay keeps high-quality precipitation information outside the decision window for flood warning and disaster response. Here we report Huayu-Global, a cross-constellation deep-learning system that combines three geostationary sensor streams from five satellites through a common retrieval framework and generates coherent quasi-global precipitation fields every thirty minutes. Across more than a million independent station records from two periods outside the training years, Huayu-Global improves event detection and precipitation-amount estimation relative to the real-time products evaluated and reaches delayed-product-level skill in key metrics. Huayu-Global therefore turns operational geostationary observations into a timely, high-skill precipitation layer for flood forecasting, water management and disaster response. Its cross-constellation design also provides a scalable foundation for incorporating future geostationary missions into hydrological and weather-prediction systems.
| Subjects: | Atmospheric and Oceanic Physics (physics.ao-ph); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.29213 [physics.ao-ph] |
| (or arXiv:2610.29213v1 [physics.ao-ph] for this version) | |
| https://doi.org/10.48550/arXiv.2610.29213 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Zijiang Song [view email]
[v1]
Wed, 21 Oct 2026 05:12:51 UTC (7,143 KB)
来源：arXiv cs.AI · arxiv.org