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Sensitivity of systematic biases in South Asian summer monsoon simulations to regional climate model domain size and implications for downscaled regional process studies

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Abstract

Global climate models (GCMs) have good skill in simulating climate at the global scale yet they show significant systematic errors at regional scale. For example, many GCMs exhibit significant biases in South Asian summer monsoon (SASM) simulations. Those errors not only limit application of such GCM output in driving regional climate models (RCMs) over these regions but also raise questions on the usefulness of RCMs derived from those GCMs. We focus on process studies where the RCM is driven by realistic lateral boundary conditions from atmospheric re-analysis which prevents remote systematic errors from influencing the regional simulation. In this context it is pertinent to investigate whether RCMs also suffer from similar errors when run over regions where their parent models show large systematic errors. Furthermore, the general sensitivity of the RCM simulation to domain size is informative in understanding remote drivers of systematic errors in the GCM and in choosing a suitable RCM domain that minimizes those errors. We investigate Met Office Unified Model systematic errors in SASM by comparing global and regional model simulations with targeted changes to the domain and forced with atmospheric re-analysis. We show that excluding remote drivers of systematic errors from the direct area of interest allows the application of RCMs for process studies of the SASM, despite the large errors in the parent global model. The findings in this study are also relevant to other models, many of which suffer from a similar pattern of systematic errors in global model simulations of the SASM.

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Acknowledgments

First author thanks the Felix Scholarships for funding his DPhil. The model simulations were carried out at Met Office. Richard Jones and Richard Levine were supported by Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and Richard Levine by the NERC Changing Water Cycle project SAPRISE (NE/I022469/1). The authors would like to thank Gill Martin for comments on earlier drafts of the manuscripts, and two anonymous reviewers for comments which helped to significantly improve the manuscript. We also acknowledge use of the Ferret program, product of NOAA’s Pacific Marine Environmental Laboratory, for analysis and graphics in this paper.

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Authors and Affiliations

  1. School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, UK

    J. Karmacharya, R. Jones & M. New

  2. Department of Hydrology and Meteorology, Kathmandu, Nepal

    J. Karmacharya

  3. Met Office Hadley Centre, Exeter, UK

    R. C. Levine, R. Jones & W. Moufouma-Okia

  4. African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa

    M. New

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  1. J. Karmacharya
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Karmacharya, J., Levine, R.C., Jones, R. et al. Sensitivity of systematic biases in South Asian summer monsoon simulations to regional climate model domain size and implications for downscaled regional process studies. Clim Dyn 45, 213–231 (2015). https://doi.org/10.1007/s00382-015-2565-6

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