Journal of Hydrometeorology · 2006 · 792 citations · 49 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceClimate ScienceClimatologyClimate ModelingHydrometeorological ModelingLand Surface ModelingLand Surface ProcessesLand-atmosphere InteractionsPrecipitationCoupled Climate ModelsEarth System ModelsLand - Atmosphere CouplingLand Surface CouplingLand Surface ParameterizationModel Intercomparison StudiesMulti-model IntercomparisonSoil Moisture-atmosphere Coupling
GLACE is a model intercomparison study that quantifies how land surface anomalies, such as soil moisture, influence rainfall and other atmospheric processes. Twelve atmospheric general circulation model groups conducted simple numerical experiments over boreal summer, and the simulation design is fully documented to enable replication and comparison of coupling strengths. Coupling strengths differ markedly across models, yet consistent spatial hot spots appear for precipitation and temperature over large parts of Africa, central North America, India, and eastern China.
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 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.
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