TY - JOUR
T1 - Assimilation of Gridded GRACE terrestrial water storage estimates in the North American land data assimilation system
AU - Kumar, Sujay V.
AU - Zaitchik, Benjamin F.
AU - Peters-Lidard, Christa D.
AU - Rodell, Matthew
AU - Reichle, Rolf
AU - Li, Bailing
AU - Jasinski, Michael
AU - Mocko, David
AU - Getirana, Augusto
AU - De Lannoy, Gabrielle
AU - Cosh, Michael H.
AU - Hain, Christopher R.
AU - Anderson, Martha
AU - Arsenault, Kristi R.
AU - Xia, Youlong
AU - Ek, Michael
N1 - Publisher Copyright:
© 2016 American Meteorological Society.
PY - 2016
Y1 - 2016
N2 - The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
AB - The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
KW - Data assimilation
KW - Hydrologic cycle
KW - Land surface model
KW - Models and modeling
KW - Observational techniques and algorithms
KW - Physical Meteorology and Climatology
KW - Remote sensing
KW - Satellite observations
KW - Water budget
UR - https://www.scopus.com/pages/publications/84976460584
U2 - 10.1175/JHM-D-15-0157.1
DO - 10.1175/JHM-D-15-0157.1
M3 - Article
AN - SCOPUS:84976460584
SN - 1525-755X
VL - 17
SP - 1951
EP - 1972
JO - Journal of Hydrometeorology
JF - Journal of Hydrometeorology
IS - 7
ER -