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Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere PredictionAdvances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.
Document ID
20170006581
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Santanello, Joseph A., Jr. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Kumar, Sujay V. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Peters-Lidard, Christa D. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Lawston, P. (Delaware Univ. Newark, DE, United States)
Date Acquired
July 17, 2017
Publication Date
January 26, 2016
Publication Information
Publication: Journal of Hydrometeorology
Volume: 17
Issue: 2
ISSN: 1525-755X
Subject Category
Earth Resources and Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN44100
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
Distribution Limits
Public
Copyright
Other
Keywords
soil moisture
land surface model
downstream