Relative Strengths Recognition of Nine Mainstream Satellite-Based Soil Moisture Products at the Global Scale

Soil moisture (SM) is a crucial driving variable for the global land surface-atmosphere water and energy cycle. There are now many satellite-based SM products available internationally it necessary to consider all under same context comprehensive assessment inter-comparisons at scale. Moreover, product performances varying with dynamic environmental factors, especially those closely related retrieval algorithms, were less investigated. Therefore, this study evaluated identified relative strengths of nine mainstream derived from Advanced Microwave Scanning Radiometer 2 (AMSR2), Chinese Fengyun-3B (FY3B), Moisture Active Passive (SMAP), Ocean Salinity (SMOS), European Space Agency (ESA) Climate Change Initiative (CCI) by using Pearson correlation coefficient (R), R seasonal anomalies (Ranom), unbiased Root Mean Square Error (ubRMSE), bias metrics against ground observations International Network (ISMN), as well Global Land Data Assimilation System (GLDAS) Noah model simulations, overall three (Land Surface Temperature (LST), SM, Vegetation Optical Depth (VOD)) conditions. Results showed that SMOS-INRA-CESBIO (IC) outperformed SMOSL3 in most cases, Australia, but exhibited greater variability higher random errors Asia. ESA CCI other capturing spatial dynamics produced significantly high accuracy croplands. Although FY3B presented poor skills had good ability capture temporal original regions central Africa. Under various cover types, changes LST, VOD, different distinctly error characteristics. Generally, tended overestimate low in-situ content underestimate content. It expected these findings can provide guidance references improvement application promotions exchange surface