Effectiveness of the Bjerknes stability index in representing ocean dynamics

The El Nio-Southern Oscillation (ENSO) is a naturally occurring coupled phenomenon originating in the tropical Pacific Ocean that relies on oceanatmosphere feedbacks. The Bjerknes stability index (BJ index), derived from the mixed-layer heat budget, aims to quantify the ENSO feedback process in orde...

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Bibliographic Details
Published in:Climate Dynamics
Main Authors: Graham, FS, Brown, JN, Langlais, C, Marsland, SJ, Wittenberg, AT, Holbrook, NJ
Format: Article in Journal/Newspaper
Language:English
Published: Springer-Verlag 2014
Subjects:
Earth Sciences
Oceanography
Physical Oceanography
Pacific
Sea ice
Online Access:https://doi.org/10.1007/s00382-014-2062-3
http://ecite.utas.edu.au/88909
Description
Summary:The El Nio-Southern Oscillation (ENSO) is a naturally occurring coupled phenomenon originating in the tropical Pacific Ocean that relies on oceanatmosphere 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 feedbacksnamely the thermocline, zonal advective, and Ekman feedbacksby 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.

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