Editorial Type:
Article
Article Type:
Research Article

Climate Model Forecast Experiments for TOGA COARE

J. Boyle Lawrence Livermore National Laboratory, Livermore, California

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S. Klein Lawrence Livermore National Laboratory, Livermore, California

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G. Zhang Scripps Institute of Oceanography, La Jolla, California

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S. Xie Lawrence Livermore National Laboratory, Livermore, California

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X. Wei University of Colorado and NOAA/Earth System Research Laboratory, Boulder, Colorado

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Print Publication:
01 Mar 2008
DOI:
https://doi.org/10.1175/2007MWR2145.1
Page(s):
808–832
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Abstract

Short-term (1–10 day) forecasts are made with climate models to assess the parameterizations of the physical processes. The time period for the integrations is that of the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The models used are the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3.1 (CAM3.1); CAM3.1 with a modified deep convection parameterization; and the Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model, version 2 (AM2). The models were initialized using the state variables from the 40-yr ECMWF Re-Analysis (ERA-40).

The CAM deep convective parameterization fails to demonstrate the sensitivity to the imposed forcing to simulate precipitation patterns associated with the Madden–Julian oscillations (MJOs) present during the period. AM2 and modified CAM3.1 exhibit greater correspondence to the observations at the TOGA COARE site, suggesting that convective parameterizations that have some type of limiter (as do AM2 and the modified CAM3.1) simulate the MJO rainfall with more fidelity than those without. None of the models are able to fully capture the correct phasing of westerly wind bursts with respect to precipitation in the eastward-moving MJO disturbance. Better representation of the diabatic heating and effective static stability profiles is associated with a better MJO simulation.

Because the models’ errors in the forecast mode bear a resemblance to the errors in the climate mode in simulating the MJO, the forecasts may allow for a better way to dissect the reasons for model error.

Corresponding author address: J. Boyle, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550. Email: boyle5@llnl.gov

Abstract

Short-term (1–10 day) forecasts are made with climate models to assess the parameterizations of the physical processes. The time period for the integrations is that of the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The models used are the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3.1 (CAM3.1); CAM3.1 with a modified deep convection parameterization; and the Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model, version 2 (AM2). The models were initialized using the state variables from the 40-yr ECMWF Re-Analysis (ERA-40).

The CAM deep convective parameterization fails to demonstrate the sensitivity to the imposed forcing to simulate precipitation patterns associated with the Madden–Julian oscillations (MJOs) present during the period. AM2 and modified CAM3.1 exhibit greater correspondence to the observations at the TOGA COARE site, suggesting that convective parameterizations that have some type of limiter (as do AM2 and the modified CAM3.1) simulate the MJO rainfall with more fidelity than those without. None of the models are able to fully capture the correct phasing of westerly wind bursts with respect to precipitation in the eastward-moving MJO disturbance. Better representation of the diabatic heating and effective static stability profiles is associated with a better MJO simulation.

Because the models’ errors in the forecast mode bear a resemblance to the errors in the climate mode in simulating the MJO, the forecasts may allow for a better way to dissect the reasons for model error.

Corresponding author address: J. Boyle, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550. Email: boyle5@llnl.gov

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