期刊
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷 113, 期 -, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2008JD010136
关键词
-
资金
- U. S. Department of Energy's Office of Science Biological and Environmental Research and the Climate Dynamics Division
- National Science Foundation
- Battelle Memorial Institute [DE-AC06-76RLO1830]
The Weather Research and Forecasting (WRF) model has been used to study the role of land-atmosphere coupling in influencing interannual summer climate variability over the contiguous United States. Two long-term climate simulations are performed: a control experiment (CTL) allows soil moisture to interact freely with the atmosphere, and an additional experiment uncouples the land surface from the atmosphere by replacing summer soil moisture at each time step with the climatology of CTL. The CTL simulation reproduces well the observed summer temperature and precipitation variability, despite some discrepancies in daily mean and maximum temperature variability in the midwest/Ohio Valley region and the adjacent areas, and precipitation variability in the Great Plains and some other areas. Strong coupling of soil moisture with daily mean temperature appears mainly over the zone from the southwest to the northern Great Plains to the southeast, contributing up to about 30-60% of the total interannual variance of temperature. There is a significantly different influence on daily maximum and minimum temperatures. Soil moisture plays a leading role in explaining the variability of maximum temperature over this zone whereas minimum temperature variability is highly constrained by external factors including atmospheric circulation and sea surface temperature almost everywhere over land. Soil moisture, mainly through its effects on convection, makes a dominant contribution to precipitation variability over about half of the northern United States. This result does not support the Global Land-Atmosphere Coupling Experiment (GLACE) hot spot hypothesis over the central United States, at least on the interannual timescale. The model's behavior agrees to a large extent with land-atmosphere relationships diagnosed using the observations.
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