Two coupled general circulation models, i.e., the Meteorological Research Institute (MRI) and Geophysical Fluid Dynamics Laboratory (GFDL) models, were chosen to examine changes in mixed layer depth (MLD) in the equatorial tropical Pacific and its relationship with ENSO under climate change projections. The control experiment used pre-industrial greenhouse gas concentrations whereas the 2 × CO2 experiment used doubled CO2 levels. In the control experiment, the MLD simulated in the MRI model was shallower than that in the GFDL model. This resulted in the tropical Pacific's mean sea surface temperature (SST) increasing at different rates under global warming in the two models. The deeper the mean MLD simulated in the control simulation, the lesser the warming rate of the mean SST simulated in the 2 × CO2 experiment. This demonstrates that the MLD is a key parameter for regulating the response of tropical mean SST to global warming. In particular, in the MRI model, increased stratification associated with global warming amplified wind-driven advection within the mixed layer, leading to greater ENSO variability. On the other hand, in the GFDL model, wind-driven currents were weak, which resulted in mixed-layer dynamics being less sensitive to global warming. The relationship between MLD and ENSO was also examined. Results indicated that the non-linearity between the MLD and ENSO is enhanced from the control run to the 2 × CO2 run in the MRI model, in contrast, the linear relationship between the MLD index and ENSO is unchanged despite an increase in CO2 concentrations in the GFDL model.
|Number of pages||15|
|Publication status||Published - 2009|
Bibliographical noteFunding Information:
The authors are grateful to two anonymous reviewers who provided many suggestions that have greatly improved this manuscript. S.-W. Yeh was supported by the KORDI (PP00720). B. Dewitte benefited from support of the Agency National de la Recherche (ANR) within the Peru Chile Climate Change (PCCC) project. This work was also supported by KRF Grant funded by MOEHRD, Basic Research Promotion Fund (KRF-2007-313-C0078). The authors acknowledge the international modeling groups for providing their data for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data, the JSC/CLIVAR Working Group on Coupled Modeling (WGCM) and their Coupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organizing the model data analysis activity, and the IPCC WG1 TSU for technical support. The IPCC Data Archive at Lawrence Livermore National Laboratory is supported by the Office of Science, US Department of Energy.
All Science Journal Classification (ASJC) codes
- Atmospheric Science