Terrestrial Water Cycle Seminar: Drs. Rasmus Houborg and John Bolten (GSFC)

Hosted by the GLDAS/GRACE group

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Impact of GRACE Data Assimilation on the Simulation of Hydrologic States Across North America

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The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield crucial information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (no better than ~500 km) and temporal (10 day - monthly) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS) aims to tackle the challenges of assimilating coarse temporal and spatial resolution GRACE observations within the Catchment land surface model that runs at significantly finer resolutions. GRACE-DAS enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. GRACE-DAS has been applied to North America in an effort to demonstrate that drought conditions can be identified more accurately and objectively by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Here we show the impact of the GRACE data assimilation on the simulation of hydrologic states across North America. An extensive dataset of groundwater storage from USGS monitoring wells in addition to Soil Climate Analysis Network (SCAN) observations of surface soil moisture are used to assess improvements in the hydrologic modeling skill resulting from the assimilation of GRACE TWS data. The potential value of GRACE assimilated moisture output for drought monitoring purposes across North America will also be discussed.

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The Middle East and North Africa Land Data Assimilation System: First Results

The Arab region of the Middle East and North Africa (MENA) is dominated by dry, warm deserts, areas of dense population, and inefficient use of fresh water resources. Due to the scarcity, high intensity, and short duration of rainfall in the MENA, the region is prone to hydroclimatic extremes that are realized by devastating floods and times of drought. However, even with its widespread water stress and the considerable demand for water, the MENA remains relatively poorly monitored. This is due in part to the shortage of meteorological observations and the lack of data sharing between nations. As a result, the accurate monitoring of the dynamics of the water cycle in the MENA is difficult. This presentation will cover early results from the Land Data Assimilation System for the MENA region (MENA LDAS) designed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. The MENA LDAS is envisaged to aid in the identification and evaluation of regional hydrological anomalies by synergistically combining the physically-based Catchment Land Surface Model (CLSM)  with observations from several independent data products including soil-water storage variations from the Gravity Recovery and Climate Experiment (GRACE). In this fashion, we estimate the mean and seasonal cycle of the water budget components across the MENA to be used for flood and drought assessment.