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http://dx.doi.org/10.3741/JKWRA.2020.53.4.285

Assessment of Noah land surface model-based soil moisture using GRACE-observed TWSA and TWSC  

Chun, Jong Ahn (Climate Analytics Department, Cliamte Services and Research Division, APEC Climate Center)
Kim, Seon Tae (Climate Analytics Department, Cliamte Services and Research Division, APEC Climate Center)
Lee, Woo-Seop (Climate Analytics Department, Cliamte Services and Research Division, APEC Climate Center)
Kim, Daeha (Climate Analytics Department, Cliamte Services and Research Division, APEC Climate Center)
Publication Information
Journal of Korea Water Resources Association / v.53, no.4, 2020 , pp. 285-291 More about this Journal
Abstract
The Noah 3.3 Land Surface Model (LSM) was used to estimate the global soil moisture in this study and these soil moisture datasets were assessed against satellite-based and reanalysis soil moisture products. The Noah 3.3 LSM simulated soil moistures in four soil layers and root-zone soil moistures defined as a depth-weighted average in the first three soil layers (i.e., up to 1.0 m deep). The Noah LSM soil moisture products were then compared with a satellite-based soil moisture dataset (European Space Agency Climate Change Initiatives (ESA CCI) SM v04.4) and reanalysis soil moisture datasets (ERA-interim). In addition, the five major basins (Yangtze, Mekong, Mississippi, Murray-Darling, Amazon) were selected for the assesment with the Gravity Recovery and Climate Experiment (GRACE)-based Total Water Storage Anomaly (TWSA) and TWS Change (TWSC). The results revealed that high anomaly correlations were found in most of the Asia-Pacific regions including East Asia, South Asia, Australia, and Noth and South America. While the anomaly correlations in the Murray-Darling basin were somewhat low, relatively higher anomaly correlations in the other basins were found. It is concluded that this study can be useful for the development of soil moisture based drought indices and subsequently can be helpful to reduce damages from drought by timely providing an efficacious strategy.
Keywords
Noah land surface model; Soil moisture; GRACE; TWSA; TWSC;
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1 Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., Van den Hurk, B.J.J.M., Hirschi, M., and Betts, A.K. (2009). "A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the integrated forecast system." Journal of Hydrometeorology, Vol. 10, No. 3, pp. 623-643.   DOI
2 Cammalleri, C., Micale, F., and Vogt, J. (2016). "A novel soil moisture-based Drought Severity Index (DSI) comining water deficit magnitude and frequency." Hydrological Processes, Vol. 30, pp. 289-301.   DOI
3 Csiszar, I., and Gutman, G. (1999). "Mapping global land surface albedo from NOAA AVHRR." Journal of Geophysical Research, Vol. 104, No. D6, pp. 6215-6228.   DOI
4 Dai, A. (2010). "Drought under global warming: A review." Wiley Interdisciplinary Reviews: Climate Change, Vol. 2, pp. 45-65.   DOI
5 Dai, A. (2011). "Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900-2008." Journal of Geophysical Research, Vol. 116, D12115.   DOI
6 Davis, T.W., Prentice, I.C., Stocker, B.D., Thomas, R.T., Whitley, R.J., Wang, H., Evans, B.J., Gallego-Sala, A.V., Sykes, M.T., and Cramer, W. (2017). "Simple processled algorithms for simulating habitats (splash v.1.0): Robust indices of radiation, evapotranspiration and plant-available moisture." Geoscientific Model Development, Vol. 10, pp. 689-708.   DOI
7 de Roo, A.P.J., Wesseling, C., and van Deusen, W. (2000). "Physically based river basin modelling within a GIS: The LISFLOOD model." Hydrological Processes, Vol. 14, pp. 1981-1992.   DOI
8 Dracup, J.A., Lee, K.S., and Paulson Jr., E.G. (1980). "On the definitions of droughts." Water Resources Research, Vol. 16 No. 2, pp. 297-302.
9 Ek, M.B., Mitchell, K.E., Lin, Y., Rogers, E., Grummann, P., Koren, V., Gayno, G., and Tarpley, J.D. (2003). "Implementation of Noah land surface model advances in the national centers for environmental prediction operational mesoscale Eta model." Journal of Geophysical Research, Vol. 108, p. 8851.
10 Gruber, A., Scanlon, T., van der Schalie, R., Wanger, W., and Dorigo, W. (2019). "Evolution of the ESA CCI soil moisture climate data records and their underlying merging methodology." Earth System Science Data, Vol. 11, pp. 717-739.   DOI
11 Gutman, G., and Ignatov, A. (1997). "The derivation of green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models." International Journal of Remote Sensing, Vol. 19, No. 8, pp. 1533-1543.   DOI
12 Heim, R.R.Jr. (2002). "A review of twentieth-century drought indices used in the United States." Bulletin of the American Meteorological Society, Vol. 83, pp. 1149-1165.   DOI
13 Long, D., Longuevergne, L., and Scanlon, B.R. (2014). "Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites." Water Resources Research, Vol. 50, pp. 1131-1151.   DOI
14 Kumar, S.V., Peters-Lidard, C.D., Tian, Y., Houser, P.R., Geiger, J., Olden, S., Lighty, L., Eastman, J.L., Doty, B., Dirmeyer, P., Adams, J., Mitchell, K., Wood, E.F., and Sheffield, J. (2006). "Land information system: An interoperable framework for high resolution land surface modeling." Environmental Modelling and Software, Vol. 21, pp. 1402-1415.   DOI
15 Kuria, D.N., Koike, T., Hui, L., Tsutsui, H., and Graf, T. (2007). "Field-supported verification and improvement of a passive microwave surface emission model for rough, bare, and wet soil surfaces by incorporating shadowing effects." IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 5, pp. 1207-1216.   DOI
16 Landerer, F.W., and Swenson, S.C. (2012). "Accuracy of scaled GRACE terrestrial water storage estimates." Water Resources Research, Vol. 48, W04531.
17 Miralles, D.G., Holmes, T.R.H., de Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., and Dolman, A.J. (2011). "Global land-surface evaporation estimated from satellite-based observations." Hydrology and Earth System Sciences, Vol. 15, pp. 453-469.   DOI
18 NASA Goddard Space Flight Center (GSFC) (2017). Land Information System (LIS) LIS 7.2 Users' Guide, accessed 11 January 2020, .
19 Perkins, S.E., Argueso, D., and White, C.J. (2015). "Relationships between climate variability, soil moisture, and Australian heatwaves." Journal of Geophysical Research: Atmospheres, Vol. 120, pp. 8144-8164.   DOI
20 Orth, R., and Seneviratne, S.I. (2015). "Introduction of a simple-model-based land surface dataset for Europe." Environmental Research Letter, Vol. 10, 044012.   DOI
21 Xia, Y., Cosgrove, B.A., Mitchell, K.E., Peters-Lidard, C.D., Ek, M.B., Kumar, S., Mocko, D., and Wei, H. (2016). "Basin-scale assessment of the land surface energy budget in the National Centers for Environmental Prediction operational and research NLDAS-2 systems." Journal of Geophysical Research: Atmospheres, Vol. 121, pp. 196-220.   DOI
22 Robinson, D.A., and Kukla, G. (1985). "Maximum surface albedo of seasonally snow-covered lands in the northern hemisphere." Journal of Climate and Applied Meteorology, Vol. 24, No. 5, pp. 402-411.   DOI
23 Rodell, M., Houser, P.R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J.K., Walker, J.P., Lohmann, D., and Toll, D. (2004). "The global land data assimilation system." Bulletin of the American Meteorological Society, Vol. 85, No. 3, pp. 381-394.   DOI
24 Tucker, J.J., and Choudhury, B.J. (1987). "Satellite remote sensing of drought conditions." Remote Sensing of Environment, Vol. 23, pp. 243-251.   DOI
25 Zobler, L. (1986). A world soil file for global climate modeling. NASA Technical Memorandum #87802, NASA Goddard Institute for Space Studies, N.Y., U.S.