Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations
Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations
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来自 SMAP、SMOS、AMSR2 和 ESA CCI 的卫星表面土壤湿度：使用全球地面观测的综合评估
DOI：
10.1016/j.rse.2019.111215
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发表时间：
2019-09-15
影响因子：
13.5
通讯作者：
Wang, Wei
中科院分区：
文献类型：
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作者：
Ma, Hongliang;Zeng, Jiangyuan;Wang, Wei
不可否认，对土壤水分遥感产品的可靠性进行全面评估对于其发展和应用是必不可少的。随着全球范围内广泛密集的网络的建立，卫星足迹和地面单点观测之间的不匹配可以得到可行的缓解。在这项研究中，利用全球密集和稀疏网络的土壤水分现场观测，系统地研究了5个遥感土壤水分产品，即土壤水分主动被动(SMAP)、两个土壤水分和海洋盐度(SMOS)产品、土地参数反演模型(LPRM)高级微波扫描辐射计2(AMSR2)和欧洲航天局(ESA)气候变化倡议(CCI)。与以往的研究不同，本研究考虑了地表温度、植被光学厚度(VOD)、地表粗糙度和空间异质性等扰动因素。此外，还对产品在不同气候区域下的技术进行了评估。通过结果，SMAP产品捕捉到了地表土壤水分的时间趋势，平均R为0.729，而在总体精度方面，ESA CCI的子均方根误差略小，为0.041 m(3)m(-3)，偏差为-0.005 m(3)m(-3)。SMAP和ESA CCI的这种互补性在不同的气候条件下得到了进一步的论证，可以为更可靠的全球土壤水分产品的整合提供参考。尽管仍然存在一些低估，但新开发的SMOS-INRA-CESBIO(SMOS-IC)与SMOS-L3产品相比，在R和ubRMSE方面获得了相当大的提升，特别是在密集的VOD条件下，与其他产品相比达到了最高的R。总的来说，欧洲中期天气预报中心(ECMWF)对SMOS在中或高VOD、非均质性和大多数地表粗糙度条件下的地表温度的低估与对土壤水分产品的低估一致，并为产品推广提供了方向。至于LPRM的表面温度，较差的技术可以部分解释LPRM土壤水分产品性能不佳的原因。尽管SMAP和SMOS-IC土壤水分产品在中等或密集VOD、小表面粗糙度、低异质性条件和温带和寒冷气候类型下的土壤水分产品技术相对可接受，但在高VOD或甚至略低VOD、高粗糙度或地形复杂性和异质性以及热带或沙漠地区的土壤水分产品的进展仍然具有挑战性。预计这些发现将有助于算法改进、产品改进(例如，融合和分解)和水文气象用途。
Comprehensive assessments on the reliability of remotely sensed soil moisture products are undeniably essential for their advancement and application. With the establishment of extensive dense networks across the globe, mismatches between satellite footprints and ground single-point observations can be feasibly relieved. In this study, five remotely sensed soil moisture products, namely, the Soil Moisture Active Passive (SMAP), two Soil Moisture and Ocean Salinity (SMOS) products, the Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2) and the European Space Agency (ESA) Climate Change Initiative (CCI), were systematically investigated by utilizing in-situ soil moisture observations from global dense and sparse networks. Distinguished from previous studies, several perturbing factors comprising the surface temperature, vegetation optical depth (VOD), surface roughness and spatial heterogeneity were taken into account in this investigation. Furthermore, products' skills under various climate regions were also evaluated.Through the results, the SMAP product captures temporal trends of ground soil moisture, exhibiting an averaged R of 0.729, whereas for overall accuracy, ESA CCI outperformed other products with a slightly smaller ubRMSE of 0.041 m(3) m(-3) and a bias of -0.005 m(3) m(-3). This complementarity between SMAP and ESA CCI was further demonstrated under different climate conditions and can afford the reference of their integration for a more reliable global soil moisture product. Though some underestimations still exist, the newly developed SMOS- INRA-CESBIO (SMOS-IC) was illustrated to gain considerable upgrades with regard to R and ubRMSE compared to SMOS-L3 product, especially in dense VOD conditions achieving the highest R compared to other products.Generally, the underestimations of the European Centre for Medium-Range-Weather Forecasts (ECMWF) surface temperature used for SMOS under moderate or high VOD, heterogeneity, and most surface roughness conditions were consistent with the underestimations of the soil moisture product and provide the directions of product promotions. As for LPRM surface temperature, the worse skills can partially explain the unsatisfactory performances for LPRM soil moisture products. In spite of relatively acceptable skills of SMAP and SMOS-IC soil moisture products concerning R under moderate or dense VOD, small surface roughness, low heterogeneity conditions and temperate and cold climate types, advances in soil moisture products under high or even slightly low VOD, high roughness or topography complexity and heterogeneity, as well as in tropical or desert regions, remain challenging. It is expected that these findings can contribute to algorithm refinements, product enhancements (e.g., fusion and disaggregation) and hydrometeorological usages.