Global characterizations of drydown events from a long-term satellite soil moisture dataset

Soil moisture drydown plays an important role in many hydrometeorological processes such as regulating surface energy budget, evapotranspiration, and infiltration. In this study, we analyzed the spatial and temporal characteristics of global soil moisture drydown using the daily-scale long-term satellite soil moisture product NNSM. We find that the time-series of tau(S) and tau(L) remained stable over the years. The spatial distribution of global tau(S) and tau(L) shows an anti-spatial correlation pattern, implying that strong land-atmosphere interaction in the short and long term occurs in different regions. tau(S). of NNSM is closer to the observation measurement than SMAP. The results show that NNSM can provide a long-term global reference for global soil moisture memory characterization, and for improving land surface models.