What causes the spread of model projections of ocean dynamic sea-level change in response to greenhouse gas forcing?

Sea levels of different atmosphere–ocean general circulation models (AOGCMs) respond to climate change forcing in different ways, representing a crucial uncertainty in climate change research. We isolate the role of the ocean dynamics in setting the spatial pattern of dynamic sea-level (ζ) change by forcing several AOGCMs with prescribed identical heat, momentum (wind) and freshwater flux perturbations. This method produces a ζ projection spread comparable in magnitude to the spread that results from greenhouse gas forcing, indicating that the differences in ocean model formulation are the cause, rather than diversity in surface flux change. The heat flux change drives most of the global pattern of ζ change, while the momentum and water flux changes cause locally confined features. North Atlantic heat uptake causes large temperature and salinity driven density changes, altering local ocean transport and ζ. The spread between AOGCMs here is caused largely by differences in their regional transport adjustment, which redistributes heat that was already in the ocean prior to perturbation. The geographic details of the ζ change in the North Atlantic are diverse across models, but the underlying dynamic change is similar. In contrast, the heat absorbed by the Southern Ocean does not strongly alter the vertically coherent circulation. The Arctic ζ change is dissimilar across models, owing to differences in passive heat uptake and circulation change. Only the Arctic is strongly affected by nonlinear interactions between the three air-sea flux changes, and these are model specific.

     

Effectiveness of the Bjerknes stability index in representing ocean dynamics

The El Niño-Southern Oscillation (ENSO) is a naturally occurring coupled phenomenon originating in the tropical Pacific Ocean that relies on ocean–atmosphere feedbacks. The Bjerknes stability index (BJ index), derived from the mixed-layer heat budget, aims to quantify the ENSO feedback process in order to explore the linear stability properties of ENSO. More recently, the BJ index has been used for model intercomparisons, particularly for the CMIP3 and CMIP5 models. This study investigates the effectiveness of the BJ index in representing the key ENSO ocean feedbacks—namely the thermocline, zonal advective, and Ekman feedbacks—by evaluating the amplitudes and phases of the BJ index terms against the corresponding heat budget terms from which they were derived. The output from Australian Community Climate and Earth System Simulator Ocean Model (a global ocean/sea ice flux-forced model) is used to calculate the heat budget in the equatorial Pacific. Through the model evaluation process, the robustness of the BJ index terms are tested. We find that the BJ index overestimates the relative importance of the thermocline feedback to the zonal advective feedback when compared with the corresponding terms from the heat budget equation. The assumption of linearity between variables in the BJ index formulation is the primary reason for these differences. Our results imply that a model intercomparison relying on the BJ index to explain ENSO behavior is not necessarily an accurate quantification of dynamical differences between models that are inherently nonlinear. For these reasons, the BJ index may not fully explain underpinning changes in ENSO under global warming scenarios.