Heterogeneity in Warm‐Season Land‐Atmosphere Coupling Over the U.S. Southern Great Plains. Issue 15 (3rd August 2018)

• Record Type: Journal Article
• Authors: Tang, Qi; Xie, Shaocheng; Zhang, Yunyan; Phillips, Thomas J.; Santanello, Joseph A.; Cook, David R.; Riihimaki, Laura D.; Gaustad, Krista L.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 15(2018)
• Page Start: 7867
• Page End: 7882
• Publication Date: 2018-08-03
• Subjects: land‐atmosphere coupling -- multiple linear regression -- evaporative fraction -- soil moisture -- leaf area index -- Southern Great Plains; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2018JD028463
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: 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 satellite remote sensing at the Southern Great Plains (SGP). We examine the coupling strength at seven 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. Key Points: Observations show moderate to weak terrestrial segment LA coupling with large heterogeneity across the ARM SGP site during the warm season Large spatial variabilities in the contributions from SM and LAI to the EF changes are also found by the multiple linear regression method The LAI exerts more influence on the EF than does the SM due to its overwhelming impacts on the latent heat flux