Climate Dynamics

, Volume 41, Issue 1, pp 155–172

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

  • Richard C. Levine
  • Andrew G. Turner
  • Deepthi Marathayil
  • Gill M. Martin
Article

DOI: 10.1007/s00382-012-1656-x

Cite this article as:
Levine, R.C., Turner, A.G., Marathayil, D. et al. Clim Dyn (2013) 41: 155. doi:10.1007/s00382-012-1656-x

Abstract

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 such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall.

Keywords

Indian summer monsoonSST biasModel systematic errorFuture projectionsArabian SeaClimate modelCMIP5

Copyright information

© Crown Copyright 2013

Authors and Affiliations

  • Richard C. Levine
    • 1
  • Andrew G. Turner
    • 2
  • Deepthi Marathayil
    • 2
  • Gill M. Martin
    • 1
  1. 1.Met Office Hadley CentreExeterUK
  2. 2.Department of Meteorology, NCAS-ClimateUniversity of ReadingReadingUK