Climate Dynamics

, Volume 50, Issue 3–4, pp 901–919 | Cite as

Seasonal ENSO phase locking in the Kiel Climate Model: The importance of the equatorial cold sea surface temperature bias

  • C. WengelEmail author
  • M. Latif
  • W. Park
  • J. Harlaß
  • T. Bayr


The El Niño/Southern Oscillation (ENSO) is characterized by a seasonal phase locking, with strongest eastern and central equatorial Pacific sea surface temperature (SST) anomalies during boreal winter and weakest SST anomalies during boreal spring. In this study, key feedbacks controlling seasonal ENSO phase locking in the Kiel Climate Model (KCM) are identified by employing Bjerknes index stability analysis. A large ensemble of simulations with the KCM is analyzed, where the individual runs differ in either the number of vertical atmospheric levels or coefficients used in selected atmospheric parameterizations. All integrations use the identical ocean model. The ensemble-mean features realistic seasonal ENSO phase locking. ENSO phase locking is very sensitive to changes in the mean-state realized by the modifications described above. An excessive equatorial cold tongue leads to weak phase locking by reducing the Ekman feedback and thermocline feedback in late boreal fall and early boreal winter. Seasonal ENSO phase locking also is sensitive to the shortwave feedback as part of the thermal damping in early boreal spring, which strongly depends on eastern and central equatorial Pacific SST. The results obtained from the KCM are consistent with those from models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5).


Seasonal ENSO phase locking SST bias Kiel Climate Model 



This study is supported by the SACCUS project of the German Ministry of Education and Research (BMBF), the European Union’s PREFACE project and the SFB754 “Climate-Biochemistry Interactions in the tropical Ocean”. The climate model integrations were performed at the Computing Centre of Kiel University. We thank Dietmar Dommenget and an anonymous reviewer for helpful comments and feedback on this work. We thank Zhaoyang Song for his help for the Bjerknes Stability Index calculation. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 2 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Supplementary material

382_2017_3648_MOESM1_ESM.docx (247 kb)
Supplementary material 1 (DOCX 247 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • C. Wengel
    • 1
    Email author
  • M. Latif
    • 1
    • 2
  • W. Park
    • 1
  • J. Harlaß
    • 1
  • T. Bayr
    • 1
  1. 1.GEOMAR Helmholtz Centre for Ocean Research KielKielGermany
  2. 2.University of KielKielGermany

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