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

Author:

Koster R. D.1,Mahanama S. P. P.123,Yamada T. J.124,Balsamo Gianpaolo5,Berg A. A.6,Boisserie M.78,Dirmeyer P. A.9,Doblas-Reyes F. J.1011,Drewitt G.6,Gordon C. T.12,Guo Z.9,Jeong J.-H.13,Lee W.-S.14,Li Z.13,Luo L.1516,Malyshev S.16,Merryfield W. J.14,Seneviratne S. I.17,Stanelle T.17,van den Hurk B. J. J. M.18,Vitart F.5,Wood E. F.16

Affiliation:

1. GMAO, NASA Goddard Space Flight Center, Greenbelt, Maryland

2. UMBC/GEST, Baltimore, Maryland

3. SAIC, Beltsville, Maryland

4. Division of Field Engineering for Environment, Hokkaido University, Sapporo, Japan

5. ECMWF, Reading, United Kingdom

6. Department of Geography, University of Guelph, Guelph, Canada

7. Center for Ocean–Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida

8. Meteo-France, Toulouse, France

9. Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

10. Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

11. Institut Català de Ciències del Clima (IC3), Barcelona, Spain

12. NOAA/GFDL, Princeton, New Jersey

13. Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden

14. CCCMA, Environment Canada, Victoria, Canada

15. Department of Geography, Michigan State University, East Lansing, Michigan

16. Princeton University, Princeton, New Jersey

17. Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

18. KNMI, De Bilt, Netherlands

Abstract

AbstractThe 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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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