Abstract
The added value of satellite‐based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely‐sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR‐E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system ‐ particularly in sparsely‐instrumented areas of the world where high‐quality rainfall observations are unavailable.
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