GLACE: the global land–atmosphere coupling experiment. Part I: overview
Koster, Randal D.; Guo, Zhichang; Dirmeyer, Paul A.; et al.Bonan, Gordon; Chan, Edmond; Cox, Peter M.; Davies, Harvey; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David; Liu, Ping; Lu, Cheng-Hsuan; Malyshev, Sergey; McAvaney, Bryant; Mitchell, Ken; Mocko, David; Oki, Taikan; Oleson, Keith W.; Pitman, Andrew; Sud, Y. C.; Taylor, Christopher M.; Verseghy, Diana; Vasic, Ratko; Xue, Yongkang; Yamada, Tomohito
Date: 1 August 2006
Journal
Journal of Hydrometeorology
Publisher
American Meteorological Society
Publisher DOI
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other ...
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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