Reference : Assimilation of GRACE terrestrial water storage into a land surface model: Evaluation...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/10993/444
Assimilation of GRACE terrestrial water storage into a land surface model: Evaluation and potential value for drought monitoring in western and central Europe
English
Li, B. [Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, United States, Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States]
Rodell, M. [Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States]
Zaitchik, B. F. [Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD 21218, United States]
Reichle, R. H. [Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States]
Koster, R. D. [Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States]
van Dam, Tonie mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
2012
Journal of Hydrology
Elsevier Science
446-447
103-115
Yes (verified by ORBilu)
0022-1694
[en] Data assimilation ; GRACE terrestrial water storage ; Groundwater ; Runoff ; Soil moisture ; Central Europe ; Drought monitoring ; Gravity recovery and climate experiment satellites ; In-situ data ; Kalman smoother ; Land surface models ; Mass imbalance ; Meteorological forcing ; Model physics ; Normalized difference vegetation index datum ; Potential values ; Root mean square errors ; Root zone ; Seasonality ; Significant impacts ; Space and time ; Temporal correlations ; Terrestrial water storage ; Warm seasons ; Catchments ; Data processing ; Drought ; Mean square error ; NASA ; Vegetation ; Geodetic satellites ; GRACE ; MODIS ; NDVI ; Central Europe ; Western Europe
[en] A land surface model's ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff estimates (in temporal correlation and root mean square error) in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. GRACE data assimilation also had significant impacts in groundwater estimates including trend and seasonality. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. The assimilation downscaled (in space and time) and disaggregated GRACE data into finer scale components of TWS which exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation. Mass imbalances associated with GRACE data assimilation and challenges of using GRACE data for drought monitoring are discussed. © 2012 Elsevier B.V..
http://hdl.handle.net/10993/444
10.1016/j.jhydrol.2012.04.035

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