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The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century

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Abstract

The boreal summer Asian monsoon has been evaluated in 25 Coupled Model Intercomparison Project-5 (CMIP5) and 22 CMIP3 GCM simulations of the late twentieth Century. Diagnostics and skill metrics have been calculated to assess the time-mean, climatological annual cycle, interannual variability, and intraseasonal variability. Progress has been made in modeling these aspects of the monsoon, though there is no single model that best represents all of these aspects of the monsoon. The CMIP5 multi-model mean (MMM) is more skillful than the CMIP3 MMM for all diagnostics in terms of the skill of simulating pattern correlations with respect to observations. Additionally, for rainfall/convection the MMM outperforms the individual models for the time mean, the interannual variability of the East Asian monsoon, and intraseasonal variability. The pattern correlation of the time (pentad) of monsoon peak and withdrawal is better simulated than that of monsoon onset. The onset of the monsoon over India is typically too late in the models. The extension of the monsoon over eastern China, Korea, and Japan is underestimated, while it is overestimated over the subtropical western/central Pacific Ocean. The anti-correlation between anomalies of all-India rainfall and Niño3.4 sea surface temperature is overly strong in CMIP3 and typically too weak in CMIP5. For both the ENSO-monsoon teleconnection and the East Asian zonal wind-rainfall teleconnection, the MMM interannual rainfall anomalies are weak compared to observations. Though simulation of intraseasonal variability remains problematic, several models show improved skill at representing the northward propagation of convection and the development of the tilted band of convection that extends from India to the equatorial west Pacific. The MMM also well represents the space–time evolution of intraseasonal outgoing longwave radiation anomalies. Caution is necessary when using GPCP and CMAP rainfall to validate (1) the time-mean rainfall, as there are systematic differences over ocean and land between these two data sets, and (2) the timing of monsoon withdrawal over India, where the smooth southward progression seen in India Meteorological Department data is better realized in CMAP data compared to GPCP data.

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Acknowledgments

We thank the CLIVAR AAMP and other invited experts for helpful comments and encouragement during the course of this work. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. K. R. Sperber was supported by the Office of Science (BER), U.S. Department of Energy through Lawrence Livermore National Laboratory contract DE-AC52-07NA27344. H. Annamalai was supported by the Office of Science (BER) U.S. Department of Energy, Grant DEFG02-07ER6445, and also by three institutional grants (JAMSTEC, NOAA and NASA) of the International Pacific Research Center. In-Sik Kang was supported by the National Research Foundation of Korea (NRF-2009-C1AAA001-2009-0093042). Aurel Moise was supported by the Australian Climate Change Science Program, funded jointly by the Department of Climate Change and Energy Efficiency, the Bureau of Meteorology and CSIRO. A. G. Turner is supported by a NERC Fellowship reference number NE/H015655/1. B. Wang was supported by US NSF award #AGS-1005599.

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Authors and Affiliations

  1. Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, P.O. Box 808, L-103, Livermore, CA, 94551, USA

    K. R. Sperber

  2. International Pacific Research Center, School of Ocean and Earth Science and Technology, University of Hawaii, 1680 East–West Road, Honolulu, HI, 96822, USA

    H. Annamalai & B. Wang

  3. School of Earth and Environmental Science (SEES), Seoul National University, Seoul, 151-742, Korea

    I.-S. Kang

  4. Meteorological Research Institute, 1-1 Nagamine, Tsukuba-shi, Ibaraki Prefecture, 305-0052, Japan

    A. Kitoh

  5. Climate Variability and Change Group, Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology, PO Box 1289, Melbourne, VIC, 3001, Australia

    A. Moise

  6. Department of Meteorology, National Centre for Atmospheric Science-Climate, University of Reading, Reading, RG6 6BB, UK

    A. Turner

  7. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing, 100029, China

    T. Zhou

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Sperber, K.R., Annamalai, H., Kang, IS. et al. The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41, 2711–2744 (2013). https://doi.org/10.1007/s00382-012-1607-6

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