Causes of the large warm bias in the Angola–Benguela Frontal Zone in the Norwegian Earth System Model

Shunya Koseki*, Noel Keenlyside, Teferi Demissie, Thomas Toniazzo, Francois Counillon, Ingo Bethke, Mehmet Ilicak, Mao Lin Shen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

We have investigated the causes of the sea surface temperature (SST) bias in the Angola–Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model’s local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.

Original languageEnglish
Pages (from-to)4651-4670
Number of pages20
JournalClimate Dynamics
Volume50
Issue number11-12
DOIs
Publication statusPublished - 1 Jun 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017, The Author(s).

Funding

Acknowledgements The authors would express their appreciation to two anonymous reviewers for their helpful comments. The authors would like to appreciate Prof. C.R. Mechoso in University of California, Los Angelsm Prof. W. Cabos in University of Alcalá, and Prof. A. Timmerman in University of Hawaii for their constructive discussions. We utilized the version of 2012Ra of MATLAB software package provided by The MathWorks, Inc., (http://www.mathworks.com) and Grid Analysis and Display System (GrADS, http://www.iges.org/ grads/) to compute each dataset and create figures. The research leading o these results received funding from the EU FP7/2007–2013 under Grant agreement to no. 603521 (EU-PREFACE). Computing resources were provided by NTur (nn9039k, ns9039k).

FundersFunder number
EU FP7/2007603521
Horizon 2020 Framework Programme648982

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