92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 4:00 PM
Application of Long-Term NLDAS-2 Products: Hydroclimatic Trends Over the Continental United States From 1979 to 2009
Room 352 (New Orleans Convention Center )
Youlong Xia, IMSG at NOAA/NCEP Environmental Modeling Center, College Park, MD; and M. B. Ek, J. Sheffield, and E. F. Wood

Long-term hydrological products have been generated within the North American Land Data Assimilation System (NLDAS-2) through a long-term, multiple-institution collaboration. The quality of the products has been comprehensively evaluated against in-situ observations and satellite retrievals. The assessment shows that the products are close to observations when general features for large spatial and time scales are considered. In this study, trends in the hydroclimatic variables (i.e., precipitation, total runoff, evapotranspiration, total column soil moisture) over the Continental United States (CONUS) from 1979 to 2009 are investigated using the Mann-Kendall test and the NLDAS-2 products derived from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC) forced by North American Regional Reanalysis (NARR) products and PRISM corrected NCEP/CPC gauge precipitation. Trends in annual precipitation (P), evapotranspiration (ET), total runoff (R), and total column soil moisture (SM) are analyzed across various spatial scales within the CONUS with different confidence levels. The results generally show that annual P, ET, R, and SM have downward trends in the western and southeastern parts of CONUS, indicating drying and potential drought intensification for the past 30 years. In the Great Plains and northeastern part of the CONUS, the upward trends are increasing, indicating wetting and possible intensification of flood conditions. The spatial distribution of the trends is inhomogeneous, varying from state to state, and county to county. In addition, the trends depend on the hydroclimatic variables and the different models and we investigate these dependencies at various time and space scales.

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