A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multi-channel collaborative algorithm

Soil moisture (SM) and vegetation optical depth (VOD) are essential variables in the terrestrial ecosystem. The multi-frequency radiometers AMSR-E AMSR2 provide >20 years of data records, enabling development long-term SM VOD products. Most current retrieval algorithms either only focus on or VOD, generally ignore polarization simplify frequency dependence effects for reducing unknowns facilitating process, limiting synergic applicability products soil-plant-atmosphere continuum. In this study, a new global frequency- polarization-dependent product from 2002 to 2021 was developed using multi-channel collaborative algorithm (MCCA), based inter-calibrated AMSR-E/2 passive microwave measurements. MCCA comprehensively considers physical relationship between multiple channels could retrieve while considering accuracy retrievals. overall comparison with other (AMSR-ANN, CCI-passive v07.1, LPRM-C/X, JAXA) over 25 dense networks, achieved best scores terms root mean square error (RMSE = 0.074 m3/m3), unbiased (ubRMSE 0.073 m3/m3) bias (0.007 presented slightly lower value Pearson's correlation coefficient (R 0.709) than LPRM-X 0.735). For indirect evaluation aboveground biomass (AGB) MODIS NDVI, showed performance comparable (LPRM-C/X, VODCA-C/X/Ku). MCCA-derived VODs, especially H-polarized exhibited smooth non-linear density distribution AGB high temporal correlations NDVI most regions globe. particular, VODs can physically present reasonable variations across spectrum (values increase frequency), which is superior LPRM VODCA It expected that be extended observations ongoing similar satellite missions capability, such as FY-3B/C/D/F/G upcoming AMSR3 CMIR missions.