基于地学环境效应的卫星遥感降水产品降尺度方法研究

High-quality precipitation data with high spatial and temporal resolution is the core flux driving research on the global water-energy-carbon cycle. Led by NASA, the tropical/global precipitation observation satellite program jointly initiated by JAXA and ESA is known as the TRMM/GPM era, which provides a new historical opportunity for studies on satellite remote sensing precipitation inversion theory and method and water cycle. However, due to the coarse spatial resolution and low quality of official TRMM/GPM products, their practical applications in many fields are seriously hindered. This study will be based on how to improve the spatial resolution of existing satellite precipitation products, studying the relationship between precipitation and different auxiliary variables from the aspect of geo-environmental effects, and identifying the auxiliary variables suitable for downscaling precipitation products at meteorological scale. The downscaling models will be used to obtain the downscaling results based on different auxiliary variables. At the same time, the idea of multi-source fusion is planning to be incorporated into downscaling remote sensing products with coarse resolutions. By using mainstream multi-source fusion algorithms, the downscaling results based on different auxiliary variables will be organically fused to develop high-quality and high-temporal resolution precipitation data and applied to hydrological models. The results of the project will provide technical supports for the improvements of the temporal and spatial resolutions of remote sensing products, as well as promote and promote the wide applications of remote sensing precipitation products in many fields such as hydrometeorology.

高质量高时空分辨率降水数据是驱动全球“水-能-碳”循环研究的核心变量。由NASA主导发起的热带/全球降水观测卫星计划被誉为TRMM/GPM时代，为卫星遥感降水反演理论方法和水循环研究提供了新的历史机遇。但由于TRMM/GPM官方产品空间分辨率较粗且质量较低，严重阻碍了其在诸多领域的实际应用。本研究基于如何提高现有卫星遥感降水产品空间分辨率这一关键科学问题，从地学环境效应的角度，研究降水与不同辅助变量的关系机理，筛选和甄别适用于气象尺度对遥感降水产品进行降尺度的辅助变量，分别构建基于不同辅助变量的降尺度模型，获取相应的降尺度结果，同时，将多源融合思想纳入到遥感产品降尺度的框架，引入主流的融合算法，将多种降尺度结果有机融合，研制高质量高时空分辨率的降水数据，并对其进行统计和水文两个角度的验证。项目成果将为遥感降水产品时空分辨率的提高提供技术支撑，推动和促进遥感降水产品在水文等诸多领域的广泛应用

本项目在率先完成既定“气象尺度遥感降水产品降尺度方法”核心研究内容的基础上，以我国风云卫星观测体系的发展及其业务化降水监测算法的迫切国家应用需为导向，围绕卫星遥感降水领域的关键理论和技术瓶颈进行持续攻关，总体遵循“时空降尺度–多源融合–地面矫正–遥感估算”的研究思路，并取得如下亮点成果：.（1）针对目前缺乏天气尺度高分辨率降水数据的应用需求，提出了一套基于云特性的卫星遥感降水产品GPM-IMERG天气尺度降尺度方法，即地理滑动窗口权重裂解降尺度算法（GMWWDA），该算法也为卫星遥感降水产品的地面矫正提供了理论和方法参考，持续支撑了申请人的研究体系；.（2）针对目前多源融合方法仅考虑降水值融合的缺陷，提出了一种基于形态学理论的多源降水融合方法MASTMA，有效考虑降水事件和降水值对融合结果的双重影响；.（3）创新性提出了基于总量控制思路的遥感/再分析降水数据日尺度地面时空裂解矫正新理论和新算法（DSTDCA和DTVCMDA），显著降低了遥感/再分析降水数据的系统偏差和随机误差，并公开发布了两套亚洲地区高质量降水数据集AIMERG（0.1◦, half-hourly, 2000–2015, Asia）和AERA5-Asia（0.1°, hourly, 1951-2015, Asia）；.（4）针对风云静止气象卫星红外多通道观测的载荷特征，创新性提出了基于层析理论的红外多通道协同降水估算算法PECA-FY4A，显著提升了静止卫星降水监测的能力和精度。.研究成果丰硕：在大气领域旗舰期刊BAMS，地学领域顶级期刊ESSD，遥感领域顶级期刊RSE和TGRS，以及水文领域顶刊JOH等国际刊物上发表SCI论文21篇（第一标记8篇）；申请专利2项（授权1项）；培养博士后/博士/硕士5人；公开发布数据集2套；获浙江省科技进步二等奖（4/9）；总之，全面超额高质完成既定研究内容和指标任务。

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