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Sonia I. Seneviratne
,
Randal D. Koster
,
Zhichang Guo
,
Paul A. Dirmeyer
,
Eva Kowalczyk
,
David Lawrence
,
Ping Liu
,
David Mocko
,
Cheng-Hsuan Lu
,
Keith W. Oleson
, and
Diana Verseghy

Abstract

Soil moisture memory is a key aspect of land–atmosphere interaction and has major implications for seasonal forecasting. Because of a severe lack of soil moisture observations on most continents, existing analyses of global-scale soil moisture memory have relied previously on atmospheric general circulation model (AGCM) experiments, with derived conclusions that are probably model dependent. The present study is the first survey examining and contrasting global-scale (near) monthly soil moisture memory characteristics across a broad range of AGCMs. The investigated simulations, performed with eight different AGCMs, were generated as part of the Global Land–Atmosphere Coupling Experiment.

Overall, the AGCMs present relatively similar global patterns of soil moisture memory. Outliers are generally characterized by anomalous water-holding capacity or biases in radiation forcing. Water-holding capacity is highly variable among the analyzed AGCMs and is the main factor responsible for intermodel differences in soil moisture memory. Therefore, further studies on this topic should focus on the accurate characterization of this parameter for present AGCMs. Despite the range in the AGCMs’ behavior, the average soil moisture memory characteristics of the models appear realistic when compared to available in situ soil moisture observations. An analysis of the processes controlling soil moisture memory in the AGCMs demonstrates that it is mostly controlled by two effects: evaporation’s sensitivity to soil moisture, which increases with decreasing soil moisture content, and runoff’s sensitivity to soil moisture, which increases with increasing soil moisture content. Soil moisture memory is highest in regions of medium soil moisture content, where both effects are small.

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Randal D. Koster
,
Y. C. Sud
,
Zhichang Guo
,
Paul A. Dirmeyer
,
Gordon Bonan
,
Keith W. Oleson
,
Edmond Chan
,
Diana Verseghy
,
Peter Cox
,
Harvey Davies
,
Eva Kowalczyk
,
C. T. Gordon
,
Shinjiro Kanae
,
David Lawrence
,
Ping Liu
,
David Mocko
,
Cheng-Hsuan Lu
,
Ken Mitchell
,
Sergey Malyshev
,
Bryant McAvaney
,
Taikan Oki
,
Tomohito Yamada
,
Andrew Pitman
,
Christopher M. Taylor
,
Ratko Vasic
, and
Yongkang Xue

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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Zhichang Guo
,
Paul A. Dirmeyer
,
Randal D. Koster
,
Y. C. Sud
,
Gordon Bonan
,
Keith W. Oleson
,
Edmond Chan
,
Diana Verseghy
,
Peter Cox
,
C. T. Gordon
,
J. L. McGregor
,
Shinjiro Kanae
,
Eva Kowalczyk
,
David Lawrence
,
Ping Liu
,
David Mocko
,
Cheng-Hsuan Lu
,
Ken Mitchell
,
Sergey Malyshev
,
Bryant McAvaney
,
Taikan Oki
,
Tomohito Yamada
,
Andrew Pitman
,
Christopher M. Taylor
,
Ratko Vasic
, and
Yongkang Xue

Abstract

The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

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