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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

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

Wenxian Zhang

School of Earth and Atmospheric Sciences

Georgia Institute of Technology

background
Background
  • Precipitation Land surface moisture
  • Numerical models

vs. observations

  • AGCMs
  • Model dependence
background1
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

motivations
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
experimental design
Three ensemble

- Write

- Read

- Subsurface

Sixteen members

1 June – 31 August 1994

The same SST

Experimental Design
diagnostic
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

diagnostic1
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
diagnostic2
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

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