Heterogeneity in Warm-Season Land-Atmosphere Coupling over the U.S. Southern Great Plains

Tang, Qi ; Xie, Shaocheng ; Zhang, Yunyan ; Phillips, Thomas J ; Santanello, Joseph A [Point of Contact] ; Cook, David R ; Riihimaki, Laura D ; Gaustad, Krista L

关键词: ATMOSPHERES;    GREAT PLAINS CORRIDOR (NORTH AMERICA);    HETEROGENEITY;    INTERACTIONS;    LAND;    MODIS (RADIOMETRY);    PLANETARY BOUNDARY LAYER;    PRECIPITATION (METEOROLOGY);    SOIL MOISTURE;   

RP-ID  :  GSFC-E-DAA-TN60272

学科分类：地球科学(综合)

美国|英语

来源: NASA Technical Reports Server

【 摘 要 】

Heterogeneity in warm-season (May-August) land-atmosphere (LA) coupling is quantified with the long-time, multiple-station measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program and the moderate-resolution imaging spectroradiometer (MODIS) satellite remote sensing at the Southern Great Plains (SGP). We examine the coupling strength at 7 additional locations with the same surface type (i.e., pasture/grassland) as the ARM SGP central facility (CF). To simultaneously consider multiple factors and consistently quantify their relative contributions, we apply a multiple linear regression method to correlate the surface evaporative fraction (EF) with near-surface soil moisture (SM) and leaf area index (LAI). The observations show moderate to weak terrestrial segment LA coupling with large heterogeneity across the ARM SGP domain in warm-season. Large spatial variabilities in the contributions from SM and LAI to the EF changes are also found. The coupling heterogeneities appear to be associated with differences in land use, anthropogenic activities, rooting depth, and soil type at different stations. Therefore, the complex LA interactions at the SGP cannot be well represented by those at the CF/E13 based on the metrics applied here. Overall, the LAI exerts more influence on the EF than does the SM due to its overwhelming impacts on the latent heat flux. This study complements previous studies based on measurements only from the CF and has important implications for modeling LA coupling in weather and climate models. The multiple linear regression provides a more comprehensive measure of the integrated impacts on LA coupling from several different factors.