Climate Dynamics

, Volume 41, Issue 1, pp 155–172 | Cite as

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


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.


Indian summer monsoon SST bias Model systematic error Future projections Arabian Sea Climate model CMIP5 



The authors 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. ECMWF ERA-Interim data used in this study have been obtained from the ECMWF data server. RCL and GMM were supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the NERC Changing Water Cycle (CWC) SAPRISE project (reference NE/I022841/1) and the European Commission’s 7th Framework Programme, under Grant Agreement number 282672, EMBRACE project. AGT is funded by a NERC Fellowship (NE/H015655/1), SAPRISE project (NE/I022469/1), and the CWC Hydroflux-India project (NE/I022485/1). The authors thank two anonymous reviewers for suggestions which significantly helped to improve the manuscript.


  1. Adler RF et al (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrol 4:1147–1167. doi: 10.1175/15257541(2003)004<1147:TVGPCP>2.0.CO;2 Google Scholar
  2. Alory G, Wijffels S, Meyers G (2007) Observed temperature trends in the Indian Ocean over 1960–1999 and associated mechanisms. Geophys Res Lett 34:L02606. doi: 10.1029/2006GL028044 CrossRefGoogle Scholar
  3. Annamalai H, Liu P, Xie SP (2005) Southwest Indian Ocean SST variability: its local effect and remote influence on Asian monsoons. J Clim 18:4150–4167. doi: 10.1175/JCLI3533.1 CrossRefGoogle Scholar
  4. Annamalai H, Hamilton K, Sperber KR (2007) The South Asian summer monsoon and its relationship with ENSO in the IPCC AR4 simulations. J Clim 20:1071–1092. doi: 10.1175/JCLI4035.1 CrossRefGoogle Scholar
  5. Ashfaq M, Skinner CB, Diffenbaugh NS (2011) Influence of SST biases on future climate change projections. Clim Dyn 36:1303–1319. doi: 10.1007/s00382-010-0875-2 CrossRefGoogle Scholar
  6. Ashok K, Guan Z, Saji NH, Yamagata Y (2004) Individual and combined influences of ENSO and the Indian Ocean dipole on the Indian Summer Monsoon. J Clim 17:3141–3155. doi: 10.1175/1520-0442 CrossRefGoogle Scholar
  7. Bollasina M, Ming Y (2012) The general circulation model precipitation bias over the southwestern equatorial Indian Ocean and its implications for simulating the South Asian monsoon. Clim Dyn. doi: 10.1007/s00382-012-1347-7 (in press)
  8. Bollasina M, Nigam S (2009) Indian Ocean SST, evaporation, and precipitation during the South Asian summer monsoon in IPCC-AR4 coupled simulations. Clim Dyn 33:1017–1032. doi: 10.1007/s00382-008-0477-4 CrossRefGoogle Scholar
  9. CMIP5 (2011) WCRP coupled model intercomparison project—phase 5: special issue of the CLIVAR exchanges newsletter no. 56 (15–2)Google Scholar
  10. Dee DP et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  11. Gimeno L, Drumond A, Nieto R, Trigo RM, Stohl A (2010) On the origin of continental precipitation. Geophys Res Lett 37:L13804. doi: 10.1029/2010GL043712 CrossRefGoogle Scholar
  12. Graham NE, Barnett TP (1987) Sea surface temperature, surface wind divergence, and convection over tropical oceans. Science 238:657–659. doi: 10.1126/science.238.4827.657 CrossRefGoogle Scholar
  13. Ju J, Slingo JM (1995) The Asian summer monsoon and ENSO. Q J R Meteorol Soc 121:1133–1168CrossRefGoogle Scholar
  14. Kim HJ, Wang B, Ding Q (2008) The global monsoon variability simulated by CMIP3 coupled climate models. J Clim 21:5271–5294. doi: 10.1175/2008JCLI2041.1 CrossRefGoogle Scholar
  15. Kummerow C et al (2000) The status of the tropical rainfall measuring mission (TRMM) after two years in orbit. J Appl Meteorol 39:1965–1982. doi: 10.1175/15200450(2001)040<1965:TSOTTR>2.0.CO;2 CrossRefGoogle Scholar
  16. Levine RC, Turner AG (2012) Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases. Clim Dyn 38:2167–2190. doi: 10.1007/s00382-011-1096-z CrossRefGoogle Scholar
  17. Li C, Yanai M (1996) The onset and interannual variability of the asian summer monsoon in relation to land–sea thermal contrast. J Clim 9:358–375. doi: 10.1175/1520-0442(1996)009<0358:TOAIVO>2.0.CO;2 CrossRefGoogle Scholar
  18. Lin JL, Weickman KM, Kiladis GN, Mapes BE, Schubert SD, Suarez MJ, Bacmeister JT, Lee MI (2008) Subseasonal variability associated with asian summer monsoon simulated by 14 IPCC AR4 Coupled GCMs. J Clim 21:4541–4567. doi: 10.1175/2008JCLI1816.1 CrossRefGoogle Scholar
  19. Martin GM, The HadGEM2 development team (2011) The HadGEM2 family of Met office unified model climate configurations. Geosci Model Dev 4:723–757. doi: 10.5194/gmd-4-723-2011 CrossRefGoogle Scholar
  20. May W (2004) Potential future changes on the Indian summer monsoon due to greenhouse warming: analysis of mechanisms in a global timeslice experiment. Clim Dyn 22(4):389–414. doi: 10.1007/s00382-003-0389-2 CrossRefGoogle Scholar
  21. May W (2011) The sensitivity of the Indian summer monsoon to a global warming of 2°C with respect to pre-industrial times. Clim Dyn 37(9–10):1843–1868. doi: 10.1007/s00382-010-0942-8 CrossRefGoogle Scholar
  22. Meehl GA, Arblaster JM (2003) Mechanisms for projected future changes in south Asian monsoon precipitation. Clim Dyn 21:659–675. doi: 10.1007/s00382-003-0343-3 CrossRefGoogle Scholar
  23. Meehl GA, Washington WM, Arblaster JM, Bettge TW, Strand WG Jr (2000) Anthropogenic forcing and decadal climate variability in sensitivity experiments of twentieth- and twenty-first-century climate. J Clim 13:3728–3744CrossRefGoogle Scholar
  24. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007a) The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull Am Meteor Soc 88:1383–1394. doi: 10.1175/BAMS-88-9-1383 CrossRefGoogle Scholar
  25. Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A, Raper SCB, Watterson IG, Weaver AJ, Zhao ZC (2007b) Global climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor MMB, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate. Cambridge University Press, CambridgeGoogle Scholar
  26. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407–4435. doi: 10.1029/2002JD002670 CrossRefGoogle Scholar
  27. Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2012) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn. doi: 10.1007/s00382-012-1607-6 (in press)
  28. Sun Y, Ding Y, Dai A (2010) Changing links between South Asian summer monsoon circulation and tropospheric land-sea thermal contrasts under a warming scenario. Geophys Res Lett 37:L02704. doi: 10.1029/2009GL041662 Google Scholar
  29. Taylor KE, Williamson D, Zwiers F (2000) The sea surface temperature and sea-ice concentration boundary conditions for AMIP II simulations. PCMDI report 60, program for climate model diagnosis and intercomparison, Lawrence Livermore National Laboratory, Livermore, CaliforniaGoogle Scholar
  30. Taylor KE, Stouffer RJ, Meehl GA (2011) An overview of CMIP5 and the experiment design. Bull Am Meteor Soc 93(4):485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  31. Turner AG, Slingo JM (2009) Uncertainties in future projections of extreme precipitation in the Indian monsoon region. Atmos Sci Let 10:152–158. doi: 10.1002/asl.223 CrossRefGoogle Scholar
  32. Turner AG, Joshi M, Robertson ES, Woolnough SJ (2012) The effect of Arabian Sea optical properties on SST biases and the South Asian summer monsoon in a coupled GCM. Clim Dyn 39(3–4):811–826. doi: 10.1007/s00382-011-1254-3 CrossRefGoogle Scholar
  33. Ueda HA, Iwai A, Kuwako K, Hori ME (2006) Impact of anthropogenic forcing on the Asian summer monsoon as simulated by eight GCMs. Geophys Res Lett 33(L06703). doi: 10.1029/2005GL025336
  34. Webster PJ, Yang S (1992) Monsoon and ENSO: selectively interactive systems. Q J Roy Meteorol Soc 118:877–926CrossRefGoogle Scholar
  35. Xavier PX, Marzin C, Goswami BN (2007) An objective definition of the Indian summer monsoon season and a new perspective on the ENSO–monsoon relationship. Q J R Meteorol Soc 133(624):749–764. doi: 10.1002/qj.45 CrossRefGoogle Scholar
  36. Xie P, Arkin PA (1996) Analysis of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J Clim 9:840–858CrossRefGoogle Scholar

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

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