Distinct Growth Rates of the Two ENSO Types
El Niño‐Southern Oscillation (ENSO) events can be grouped into two types based on their sea surface temperature anomaly spatial patterns, that is, eastern Pacific (EP) and central Pacific (CP) types. In this study, we propose a new method to empirically diagnose linear growth rates of the EP and CP...
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| Published in: | Geophysical research letters Vol. 47; no. 16 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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John Wiley & Sons, Inc
28.08.2020
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| ISSN: | 0094-8276, 1944-8007 |
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| Abstract | El Niño‐Southern Oscillation (ENSO) events can be grouped into two types based on their sea surface temperature anomaly spatial patterns, that is, eastern Pacific (EP) and central Pacific (CP) types. In this study, we propose a new method to empirically diagnose linear growth rates of the EP and CP ENSO types due to a limitation of applying the traditional Bjerknes stability index method simply to these two types. We spatially project the peak‐time symmetric component of the mixed‐layer oceanic heat budget terms onto the ENSO‐related sea surface temperature anomaly patterns to estimate the ENSO grow rate. After validating the method by comparing it with the Bjerknes stability index, we show that the growth rate is positive for the CP ENSO type and weakly negative for the EP ENSO type, contributed by different feedback terms. The Coupled Model Intercomparison Project Phase 5‐based multimodel ensemble mean shows similar characteristics as the reanalysis for the EP ENSO type rather than the CP ENSO type.
Key Points
A new method of empirically diagnosing the ENSO linear growth rate (GR) is proposed and validated by comparing it with the dynamical BJ index
The eastern Pacific ENSO has a weakly negative GR while the central Pacific one has a positive, where the thermocline feedback plays key roles
The GR of the eastern Pacific rather than central Pacific ENSO can be reasonably reproduced by the CMIP5 models with their ensemble mean |
|---|---|
| AbstractList | El Niño‐Southern Oscillation (ENSO) events can be grouped into two types based on their sea surface temperature anomaly spatial patterns, that is, eastern Pacific (EP) and central Pacific (CP) types. In this study, we propose a new method to empirically diagnose linear growth rates of the EP and CP ENSO types due to a limitation of applying the traditional Bjerknes stability index method simply to these two types. We spatially project the peak‐time symmetric component of the mixed‐layer oceanic heat budget terms onto the ENSO‐related sea surface temperature anomaly patterns to estimate the ENSO grow rate. After validating the method by comparing it with the Bjerknes stability index, we show that the growth rate is positive for the CP ENSO type and weakly negative for the EP ENSO type, contributed by different feedback terms. The Coupled Model Intercomparison Project Phase 5‐based multimodel ensemble mean shows similar characteristics as the reanalysis for the EP ENSO type rather than the CP ENSO type.
Key Points
A new method of empirically diagnosing the ENSO linear growth rate (GR) is proposed and validated by comparing it with the dynamical BJ index
The eastern Pacific ENSO has a weakly negative GR while the central Pacific one has a positive, where the thermocline feedback plays key roles
The GR of the eastern Pacific rather than central Pacific ENSO can be reasonably reproduced by the CMIP5 models with their ensemble mean El Niño‐Southern Oscillation (ENSO) events can be grouped into two types based on their sea surface temperature anomaly spatial patterns, that is, eastern Pacific (EP) and central Pacific (CP) types. In this study, we propose a new method to empirically diagnose linear growth rates of the EP and CP ENSO types due to a limitation of applying the traditional Bjerknes stability index method simply to these two types. We spatially project the peak‐time symmetric component of the mixed‐layer oceanic heat budget terms onto the ENSO‐related sea surface temperature anomaly patterns to estimate the ENSO grow rate. After validating the method by comparing it with the Bjerknes stability index, we show that the growth rate is positive for the CP ENSO type and weakly negative for the EP ENSO type, contributed by different feedback terms. The Coupled Model Intercomparison Project Phase 5‐based multimodel ensemble mean shows similar characteristics as the reanalysis for the EP ENSO type rather than the CP ENSO type. El Niño‐Southern Oscillation (ENSO) events can be grouped into two types based on their sea surface temperature anomaly spatial patterns, that is, eastern Pacific (EP) and central Pacific (CP) types. In this study, we propose a new method to empirically diagnose linear growth rates of the EP and CP ENSO types due to a limitation of applying the traditional Bjerknes stability index method simply to these two types. We spatially project the peak‐time symmetric component of the mixed‐layer oceanic heat budget terms onto the ENSO‐related sea surface temperature anomaly patterns to estimate the ENSO grow rate. After validating the method by comparing it with the Bjerknes stability index, we show that the growth rate is positive for the CP ENSO type and weakly negative for the EP ENSO type, contributed by different feedback terms. The Coupled Model Intercomparison Project Phase 5‐based multimodel ensemble mean shows similar characteristics as the reanalysis for the EP ENSO type rather than the CP ENSO type. A new method of empirically diagnosing the ENSO linear growth rate (GR) is proposed and validated by comparing it with the dynamical BJ index The eastern Pacific ENSO has a weakly negative GR while the central Pacific one has a positive, where the thermocline feedback plays key roles The GR of the eastern Pacific rather than central Pacific ENSO can be reasonably reproduced by the CMIP5 models with their ensemble mean |
| Author | Wang, Run Ren, Hong‐Li |
| Author_xml | – sequence: 1 givenname: Hong‐Li orcidid: 0000-0001-7194-0567 surname: Ren fullname: Ren, Hong‐Li email: renhl@cma.gov.cn organization: China University of Geoscience – sequence: 2 givenname: Run surname: Wang fullname: Wang, Run organization: China Meteorological Administration |
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| SubjectTerms | central Pacific (CP) ENSO eastern Pacific (EP) ENSO El Nino El Nino phenomena El Nino-Southern Oscillation event empirical method ENSO growth rate Growth rate Heat budget Intercomparison Oceanic heat budget Sea surface Sea surface temperature Sea surface temperature anomalies Southern Oscillation Stability Surface temperature Temperature anomalies |
| Title | Distinct Growth Rates of the Two ENSO Types |
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