AI 中文总结
本研究提出一种视频扩散框架，以IMERG为数据源、ERA5/ERA5-Land补充环境信息，生成卫星基HiDFiP降水场，其时空保真度优于基线方法，可泛化至新区域，为全球雷达级降水记录提供支撑。
AI 中文摘要
能够准确捕捉风暴空间结构、传播路径及生命周期演变的高时空保真降水产品，对于推进区域和全球尺度的水文气象研究与业务应用至关重要。卫星产品提供了唯一近全球覆盖的降水观测数据，但由于卫星反演的非均匀性、间歇性和间接性导致的动态失真，它们仍无法复现地基参考数据的时空结构。本文提出一种用于卫星基高动态保真降水（HiDFiP）场生成的视频扩散框架，以雷达数据丰富的美国大陆（CONUS）作为测试平台，其覆盖范围超出了地基雷达的时空覆盖范围。该框架以全球降水测量（GPM）的第五代卫星产品（IMERG）作为主要数据源进行显式时空建模，并利用约40个欧洲中期天气预报中心第五代再分析数据集（ERA5/ERA5-Land）的四维风暴-环境大气/陆面场信息，以弥补卫星反演固有的时间信息缺失。我们引入了一套全面的指标体系，在时间重建和空间迁移场景下，针对美国大陆的多雷达多传感器系统（MRMS）地基雷达降水数据评估HiDFiP的动态保真度。与IMERG及基于图像的扩散基线方法相比，HiDFiP能够准确复现风暴的时空谱特征、风暴的发生时间、位置及定向传播路径、降水事件的 episodicity（ episodicity 译为“ episodicity”，此处保留原术语）和时间结构、降水系统的形态及空间组织，以及风暴路径的运动学特征和生命周期演变。迁移性实验表明，HiDFiP能够合理地泛化到未见过的区域。本研究推进了用于卫星基高时空保真降水生成的视频扩散范式，并为长期全球雷达级降水记录提供了算法和诊断基础。
英文摘要
High spatiotemporal fidelity precipitation products that accurately capture storm spatial organization, propagation, and lifecycle evolution, are essential for advancing hydrometeorological research and operations at regional and global scales. Satellite products offer the only near-global precipitation observations, but they still fall short of reproducing the spatiotemporal structure of ground-based references, due largely to dynamic distortions from the inhomogeneity, intermittency, and indirectness of satellite retrievals. Here we propose a video-diffusion framework for satellite-based High-Dynamical-Fidelity Precipitation (HiDFiP) field generation beyond the space-time coverage of ground-radar, using radar-rich CONUS as a testbed. The framework performs explicit spatiotemporal modeling with IMERG as the primary source and leverages four-dimensional storm-environment information from about 40 ERA5/ERA5-Land atmospheric/land fields to compensate for the temporal information deficit inherent to satellite retrievals. We introduce an extensive metric suite to assess HiDFiP dynamical fidelity in temporal-reconstruction and spatial-transfer settings against MRMS ground-radar precipitation over CONUS. Relative to IMERG and image-wise diffusion baselines, HiDFiP accurately reproduces the storm space-time spectral characteristics; storm timing, location, and directional propagation; precipitation-event episodicity and temporal structure; precipitation-system morphology and spatial organization; and storm-track kinematics and lifecycle evolution. Transferability experiments indicate that HiDFiP generalizes reasonably well to an unseen region. This work advances a video-diffusion paradigm for satellite-based high-spatiotemporal-fidelity precipitation generation and provides an algorithmic and diagnostic foundation for long-term global radar-grade precipitation records.
