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Revisiting ENSO Coupled Instability Theory and SST Error Growth in a Fully Coupled Model

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  • 1 Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida
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Abstract

A coupled model framework is presented to isolate coupled instability induced SST error growth in the ENSO region. The modeling framework using CCSM4 allows for seasonal ensembles of initialized simulations that are utilized to quantify the spatial and temporal behavior of coupled instabilities and the associated implications for ENSO predictability. The experimental design allows for unstable growth of initial perturbations that are not prescribed, and several cases exhibit sufficiently rapid growth to produce ENSO events that do not require a previous ENSO event, large-scale wind trigger, or subsurface heat content precursor. Without these precursors, however, ENSO amplitude is reduced.

The initial error growth exhibits strong seasonality with fastest growth during spring and summer and also dependence on the initialization month with the fastest growth occurring in the July ensemble. Peak growth precedes the peak error, and evidence suggests that the final state error may be sensitive to a slight temperature bias in the initialized SST. The error growth displays a well-defined seasonal limit, with ensembles initialized prior to fall exhibiting a clear seasonal halt in error growth around September, consistent with increased background stability typical during fall. Overall, coupled instability error growth in CCSM4 is deemed best characterized by strong seasonality, dependence on the initialization month, and nonlinearity. The results pose real implications for predictability because the final error structure is ENSO-like and occurs without a subsurface precursor, which studies have shown to be essential to ENSO predictability. Despite the large error growth induced by coupled instabilities, analysis reveals that ENSO predictability is retained for most seasonal ensembles.

Corresponding author address: Sarah M. Larson, Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149. E-mail: slarson@rsmas.miami.edu

Abstract

A coupled model framework is presented to isolate coupled instability induced SST error growth in the ENSO region. The modeling framework using CCSM4 allows for seasonal ensembles of initialized simulations that are utilized to quantify the spatial and temporal behavior of coupled instabilities and the associated implications for ENSO predictability. The experimental design allows for unstable growth of initial perturbations that are not prescribed, and several cases exhibit sufficiently rapid growth to produce ENSO events that do not require a previous ENSO event, large-scale wind trigger, or subsurface heat content precursor. Without these precursors, however, ENSO amplitude is reduced.

The initial error growth exhibits strong seasonality with fastest growth during spring and summer and also dependence on the initialization month with the fastest growth occurring in the July ensemble. Peak growth precedes the peak error, and evidence suggests that the final state error may be sensitive to a slight temperature bias in the initialized SST. The error growth displays a well-defined seasonal limit, with ensembles initialized prior to fall exhibiting a clear seasonal halt in error growth around September, consistent with increased background stability typical during fall. Overall, coupled instability error growth in CCSM4 is deemed best characterized by strong seasonality, dependence on the initialization month, and nonlinearity. The results pose real implications for predictability because the final error structure is ENSO-like and occurs without a subsurface precursor, which studies have shown to be essential to ENSO predictability. Despite the large error growth induced by coupled instabilities, analysis reveals that ENSO predictability is retained for most seasonal ensembles.

Corresponding author address: Sarah M. Larson, Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149. E-mail: slarson@rsmas.miami.edu
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