Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

Author:

Lin Jia-Lin1,Kiladis George N.2,Mapes Brian E.3,Weickmann Klaus M.1,Sperber Kenneth R.4,Lin Wuyin5,Wheeler Matthew C.6,Schubert Siegfried D.7,Del Genio Anthony8,Donner Leo J.9,Emori Seita10,Gueremy Jean-Francois11,Hourdin Frederic12,Rasch Philip J.13,Roeckner Erich14,Scinocca John F.15

Affiliation:

1. NOAA–CIRES Climate Diagnostics Center, Boulder, Colorado

2. NOAA/Aeronomy Laboratory, Boulder, Colorado

3. Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

4. Program for Climate Model Diagnosis and Intercomparison (PCMDI), Lawrence Livermore National Laboratory, Livermore, California

5. State University of New York—Stony Brook, Stony Brook, New York

6. Bureau of Meteorlogy Research Centre, Melbourne, Australia

7. Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, Maryland

8. NASA Goddard Institute for Space Studies, New York, New York

9. NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

10. National Institute for Environmental Studies, Ibaraki, Japan

11. Météo-France, CNRM, Toulouse, France

12. Laboratoire de Météorologie Dynamique, Université de Paris, Paris, France

13. National Center for Atmospheric Research, Boulder, Colorado

14. Max Planck Institute for Meteorology, Hamburg, Germany

15. Canadian Centre for Climate Modelling and Analysis, Victoria, Canada

Abstract

Abstract This study evaluates the tropical intraseasonal variability, especially the fidelity of Madden–Julian oscillation (MJO) simulations, in 14 coupled general circulation models (GCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of daily precipitation from each model’s twentieth-century climate simulation are analyzed and compared with daily satellite-retrieved precipitation. Space–time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), and eastward inertio–gravity (EIG) and westward inertio–gravity (WIG) waves. The variance and propagation of the MJO, defined as the eastward wavenumbers 1–6, 30–70-day mode, are examined in detail. The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2–128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG–EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their “effective static stability” by diabatic heating. The MJO variance approaches the observed value in only 2 of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its westward counterpart is too small in most of the models, which is consistent with the lack of highly coherent eastward propagation of the MJO in many models. Moreover, the MJO variance in 13 of the 14 models does not come from a pronounced spectral peak, but usually comes from part of an overreddened spectrum, which in turn is associated with too strong persistence of equatorial precipitation. The two models that arguably do best at simulating the MJO are the only ones having convective closures/triggers linked in some way to moisture convergence.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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