An evaluation of ENSO dynamics in CMIP simulations in the framework of the recharge oscillator model
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The CMIP model simulations show wide spread uncertainties in ENSO statistics and dynamics. In this study, we use the concept of the linear recharge oscillator (ReOsc) model to diagnose the ENSO-dynamics in CMIP3 and CMIP5 model simulations. The ReOsc model parameters allow us to quantify SST and thermocline damping, SST coupling to thermocline and vice-versa, sensitivity to wind stress and heat flux forcings and separate atmospheric from oceanic processes. Our results show that the ENSO-dynamics and their diversity within the CMIP ensemble can be well represented with the linear recharge oscillator model diagnostics. We also illustrate that the ENSO dynamics show larger biases relative to observations and spread within the models than simple large-scale statistics such as SST standard deviation would suggest. The CMIP models underestimate the atmospheric positive and negative feedbacks, they have compensating atmospheric and oceanic errors, the thermocline damping is too strong and stochastic noise forcings in models is too weak. The CMIP5 models show only marginal improvements relative to CMIP3. The results suggest that models can still be significantly improved and our analysis gives directions to what needs to be improved.
KeywordsEl Nino southern oscillation ENSO Ocean and atmospheric dynamics ENSO dyanmics El Nino dynamics Coupled general circulation models CGCM Model evaluation Recharge oscillator model Climate feedbacks CMIP simulations
We are grateful and thank Tobias Bayr, Shayne McGregor, Sarah Perry, Peter van Rensch and Christian Wengel for their suggestions and comments. This study was supported by the ARC project “Beyond the linear dynamics of the El Nino Southern Oscillation”, Australian Research Council (Grant no. DP120101442) and the ARC Centre of Excellence for Climate System Science, Australian Research Council (Grant no. CE110001028). The work presented here has a long history going back to 2007 with a number of people contributing to the analysis over time that we like to acknowledge here: Malte Jansen, Claudia Frauen, Simona Trefalt, Chevillard Jeanne and Payan Timothée and Yanshan Yu.
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