Editorial Type:
Article
Article Type:
Research Article

The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill

R. D. Koster aGMAO, NASA Goddard Space Flight Center, Greenbelt, Maryland

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S. P. P. Mahanama aGMAO, NASA Goddard Space Flight Center, Greenbelt, Maryland
bUMBC/GEST, Baltimore, Maryland
cSAIC, Beltsville, Maryland

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T. J. Yamada aGMAO, NASA Goddard Space Flight Center, Greenbelt, Maryland
bUMBC/GEST, Baltimore, Maryland
dDivision of Field Engineering for Environment, Hokkaido University, Sapporo, Japan

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Gianpaolo Balsamo eECMWF, Reading, United Kingdom

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A. A. Berg fDepartment of Geography, University of Guelph, Guelph, Canada

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M. Boisserie gCenter for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida
hMeteo-France, Toulouse, France

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P. A. Dirmeyer iCenter for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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F. J. Doblas-Reyes jInstitució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
kInstitut Català de Ciències del Clima (IC3), Barcelona, Spain

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G. Drewitt fDepartment of Geography, University of Guelph, Guelph, Canada

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C. T. Gordon lNOAA/GFDL, Princeton, New Jersey

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Z. Guo iCenter for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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J.-H. Jeong mDepartment of Earth Sciences, University of Gothenburg, Gothenburg, Sweden

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W.-S. Lee nCCCMA, Environment Canada, Victoria, Canada

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Z. Li aGMAO, NASA Goddard Space Flight Center, Greenbelt, Maryland
cSAIC, Beltsville, Maryland

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L. Luo oDepartment of Geography, Michigan State University, East Lansing, Michigan
pPrinceton University, Princeton, New Jersey

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S. Malyshev pPrinceton University, Princeton, New Jersey

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W. J. Merryfield nCCCMA, Environment Canada, Victoria, Canada

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S. I. Seneviratne qInstitute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

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T. Stanelle qInstitute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

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B. J. J. M. van den Hurk rKNMI, De Bilt, Netherlands

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F. Vitart eECMWF, Reading, United Kingdom

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E. F. Wood pPrinceton University, Princeton, New Jersey

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Print Publication:
01 Oct 2011
DOI:
https://doi.org/10.1175/2011JHM1365.1
Page(s):
805–822
Restricted access

Abstract

The second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Corresponding author address: Randal Koster, Global Modeling and Assimilation Office, Code 610.1, NASA GSFC, Greenbelt, MD 20771. E-mail: randal.d.koster@nasa.gov

Abstract

The second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Corresponding author address: Randal Koster, Global Modeling and Assimilation Office, Code 610.1, NASA GSFC, Greenbelt, MD 20771. E-mail: randal.d.koster@nasa.gov
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