联合哨兵-1号和土壤湿度主动被动遥感卫星数据同化以改进土壤湿度估计
Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates.
作者信息
Lievens H, Reichle R H, Liu Q, De Lannoy G J M, Dunbar R S, Kim S B, Das N N, Cosh M, Walker J P, Wagner W
机构信息
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium.
Global Modeling and Assimilation office, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
出版信息
Geophys Res Lett. 2017 Jun 28;44(12):6145-6153. doi: 10.1002/2017GL073904. Epub 2017 Jun 9.
SMAP (Soil Moisture Active and Passive) radiometer observations at ~40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9-km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatio-temporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9-km surface and root-zone soil moisture simulations with measurements from 9-km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations.
分辨率约为40公里的土壤湿度主动和被动（SMAP）辐射计观测数据通常被同化到美国国家航空航天局（NASA）集水区陆地表面模型中，以生成9公里分辨率的SMAP四级土壤湿度产品。本研究表明，将哨兵-1号的高分辨率雷达观测数据添加到SMAP同化过程中，可以提高土壤湿度估计的时空准确性。雷达观测数据要么与辐射计观测数据分开同化，要么同时同化。通过将2015年5月至2016年12月期间每3小时一次、9公里分辨率的地表和根区土壤湿度模拟结果与9公里分辨率的SMAP核心验证站点和稀疏网络的测量结果进行比较，评估同化影响。哨兵-1号同化始终能改善地表土壤湿度，而对根区的影响大多呈中性。从SMAP同化中获得了相对更大的改善。SMAP和哨兵-1号观测数据的联合同化效果最佳，证明了雷达和辐射计观测数据的互补价值。
Zotero 插件