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The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall

Levine, R.C., Turner, A. ORCID: https://orcid.org/0000-0002-0642-6876, Marathayil, D. and Martin, G. (2013) The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall. Climate Dynamics, 41 (1). pp. 155-172. ISSN 1432-0894

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To link to this item DOI: 10.1007/s00382-012-1656-x

Abstract/Summary

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius-Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that, while such effects are likely small compared to other sources of uncertainty, models with large Arabian Sea cold SST biases suppress the range of potential outcomes for changes to future early monsoon rainfall.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:30496
Uncontrolled Keywords:Indian summer monsoon;SST bias;Model systematic error; Future projections;Arabian Sea;Climate model;CMIP5
Publisher:Springer

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