亚洲区域AMSR2与SMOS土壤水分产品对比研究

遥感反演土壤水分(SM)产品越来越多地应用于农业、气象、水文等研究,而微波土壤水分数据产品的区域适用性分析是其合理使用的必要前提。使用MERRA-2(Modern Era Retrospective-analysis for Research and Applications,Version 2)模拟土壤水分为参考数据,运用传统统计方法(原始数据相关性、距平相关性、偏差以及无偏均方根差)和TC(Triple-Collocation)不确定性误差模型分析的方法,对亚洲区域2012年7月～2016年7月两种被动微波土壤水分SMOS-L3-SM(Soil Moisture and Ocean Salinity,L3)和AMSR2-LPRM-SM(The Advanced Microwave Scanning Radiometer 2,Land Parameter Retrieval Model Product)进行对比评估。结果表明:①空间上SMOS-L3较AMSR2-LPRM数据与参考数据MERRA-2土壤水分的相关性较好,表现为SMOS-L3-SM具有较好的空间连续性,且在亚洲大多数地区有较小的无偏均方根差;②湿季条件下遥感土壤水分与参考值的相关性比干季条件下的相关性更好,且干季出现高纬地区(约55°)缺失值较多的情况;③两遥感土壤水分的TC误差呈现相似的分布,区域TC平均误差两者均为0.076 m~3/m~3。总之,SMOS-L3-SM和AMSR2-LPRM-SM在空间相关性及TC误差评价方面都具有合理性,为遥感土壤水分在农业、气象、水文等方面的应用提供参考。

A Regional-Scale Performance Evaluation of SMOS and AMSR2 Soil Moisture Products over Asia

Soil Moisture (SM)products derived from satellite missions have been widely applied in agriculture，meteorology，hydrology，and other fields.It is very necessary to assess the reliability of satellite soil moisture products over regional scale before using them.Two passive satellite soil moisture products，obtained from SMOS (the Soil Moisture Ocean Salinity；L3)and AMSR2 (the Advanced Microwave Scanning Radiometer 2；LPRM)，were evaluated over Asia with reference to MERRA-2 (the Modern Era Retrospective-analysis data for Research and Applications，Version 2)simulated products.The evaluation was performed by adopting a classic statistical method (including Pearson correlation (R)for original SM data and anomalies，bias and unbiased root mean square root)and Triple Collocation (TC)approach based on the SMOS-L3 and AMSR-LPRM daily SM products during July 2012~July 2016.The results reveal that：(1)in space，the performance of SMOS-L3-SM is better than AMSR2-LPRM-SM both for the original SM data and anomalies.Because the SMOS-L3-SM performed consistent correlation over Asia and the smaller unbiased root mean squared difference (ubRMSD)of SMOS-L3-SM is found in most parts of Asia；(2)the correlation between satellite and simulated SM is better in the wet season than in the dry season.Additionally there is a quite high probability of a lack of value in high latitude (about >55°)areas in the dry season to appear；(3)SMOS-L3-SM and AMSR2-LPRM-SM have relatively similar TC errors distribution with a mean error of 0.076 m³/m³ for both of them.Overall，both SMOS-L3-SM and AMSR2-LPRM-SM give reasonable results on correlation and TC error，thus providing an additional reference for application of soil moisture in agriculture，meteorology，hydrology and other studies.