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GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview

GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview. Wenxian Zhang School of Earth and Atmospheric Sciences Georgia Institute of Technology. Background. Precipitation Land surface moisture Numerical models vs. observations AGCMs Model dependence. Background.

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GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview

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  1. GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview Wenxian Zhang School of Earth and Atmospheric Sciences Georgia Institute of Technology

  2. Background • Precipitation Land surface moisture • Numerical models vs. observations • AGCMs • Model dependence

  3. Background • Land-atmosphere coupling strength • K02: Four-model intercomparison (Koster et al., 2002) - Four independent AGCM modeling groups - One-month simulation - The same time series of surface prognostic variables - Quantification of the response of precipitation - A marked disparity in the coupling strength

  4. Motivations • To quantify the land-atmosphere coupling strength of the twelve AGCMs - Participation from a wider range of models - Separation of the effects of “fast” and “low” reservoirs - Effect on air temperature • To document the coupling strengths of the participating models for future study

  5. Three ensemble - Write - Read - Subsurface Sixteen members 1 June – 31 August 1994 The same SST Experimental Design

  6. Experimental Design

  7. Experimental Design

  8. Ω Diagnostic • Time series of six-day totals • P(t): 14 six-day totals for each simulation • :The ensemble mean time series • :The temporal standard deviation • :The standard deviation of the ensemble mean time series

  9. Ω Diagnostic • The degree to which the sixteen precipitation time series generated by the ensemble members are similar • The relative contributions of boundary forcing and internal chaotic variability to the generation of precipitation

  10. Ω Diagnostic Figure 2 of Koster et al., 2002: Time series of precipitation produced by NSIPP’s R ensemble. (top) Grid cell for which Ω is high. (bottom) Grid cell for which Ω is low

  11. Ω Diagnostic

  12. Precipitation

  13. Conclusions • The range of coupling strengths is large. • The multimodel “hot spots” of land-atmosphere coupling is determined.

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