The variation of ENSO characteristics associated with atmospheric parameter perturbations in a coupled model
We analyse the differences in the properties of the El Niño Southern Oscillation (ENSO) in a set of 17 coupled integrations with the flux-adjusted, 19-level HadCM3 model with perturbed atmospheric parameters. Within this ensemble, the standard deviation of the NINO3.4 deseasonalised SSTs ranges from 0.6 to 1.3 K. The systematic changes in the properties of the ENSO with increasing amplitude confirm that ENSO in HadCM3 is prevalently a surface (or SST) mode. The tropical-Pacific SST variability in the ensemble of coupled integrations correlates positively with the SST variability in the corresponding ensemble of atmosphere models coupled with a static mixed-layer ocean (“slab” models) perturbed with the same changes in atmospheric parameters. Comparison with the respective coupled ENSO-neutral climatologies and with the slab-model climatologies indicates low-cloud cover to be an important controlling factor of the strength of the ENSO within the ensemble. Our analysis suggests that, in the HadCM3 model, increased SST variability localised in the south-east tropical Pacific, not originating from ENSO and associated with increased amounts of tropical stratocumulus cloud, causes increased ENSO variability via an atmospheric bridge mechanism. The relationship with cloud cover also results in a negative correlation between the ENSO activity and the model’s climate sensitivity to doubling CO2.
KeywordsEnsemble Member Flux Adjustment Thermocline Feedback
The authors wish to thank Ben Booth and Glen Harris for their help in making the ensemble data available to us. The model integrations were performed at the Hadley Centre by the QUMP team. This work was supported by the UK Department of the Environment, Food and Rural Affairs under Contract PECD 7/12/37, by the Government Meteorological Research Contract, by the National Centre for Atmospheric Sciences (NCAS-Climate), and by the EU DYNAMITE project (contract 003903-GOCE).
- Brown J, Collins M, Tudhope AW, Toniazzo T (2007) Modelling mid-Holocene tropical climate and ENSO variability: towards constraining predictions of future change with palaeo-data, 2007. Clim Dyn. doi: 10.1007/s00382-007-0270-9
- Coelho CAS, Stephenson DB, Doblas-Reyes FJ, Balmaseda M (2006) The skill of empirical and combined/calibrated coupled multi-model South American seasonal predictions during ENSO. Adv Geosci 6:51–55Google Scholar
- Collins M, Bhaskaran B, Booth B, Harris G, Murphy J, Sexton D, Webb M, Brierley C (2006b) Progress and plans for probabilistic climate prediction at the Hadley Centre. Geophys Res Abstracts, vol 8, 05738, 2006Google Scholar
- Rayner NA et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108 doi: 10.1029/2002JD002670
- Toniazzo T (2005) A study of the sensitivity of ENSO to the mean climate. Adv Geosci 6:111–118Google Scholar
- Webb MJ, Senior CA, Sexton DMH, Ingram WJ, Williams KD, Ringer MA, McAvaney BJ, Colman R, Soden BJ, Gudgel R, Knutson T, Emori S, Ogura T, Tsushima Y, Andronova N, Li B, Musat I, Bony S, Taylor KE (2006) On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim Dyn 27:17–38CrossRefGoogle Scholar