Abstract:
Anomalies in Terrestrial Water Storage (TWS) derived from the Gravity Recovery and Climate Experiment (GRACE) mission have been used effectively to study hydrologic variability and trends at basin scale across diverse climatic and geologic conditions. Many hydrology and water resources applications, however, require water storage estimates at higher spatial resolution, greater temporal frequency, and with greater physical specificity (e.g., groundwater versus soil moisture versus snow) than GRACE alone can offer. The GRACE Data Assimilation System (GRACE-DAS) was developed to merge GRACE information on large-scale TWS anomalies with physically-based advanced Land Surface Models in order to improve model simulation of water storage while disaggregating and downscaling the raw GRACE TWS estimate. The primary assimilation algorithm is a variant of the ensemble Kalman Smoother. In recent years the system has been applied to studies of water resources and drought monitoring over four different continents. These experiences have led to refinements in the assimilation system that include modifications to land surface model parameters and the treatment of irrigation withdrawals, adjustments in the assimilation algorithm for snow updates, and, most recently, the implementation of a gridded observation assimilation capability that allows for a more flexible application of the system. This presentation will provide an overview of current GRACE-DAS capabilities, report on recent innovations in the modeling system, and describe future directions in GRACE data assimilation research and applications.