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Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble

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Abstract

Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m−2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.

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Acknowledgments

We are grateful to Paquita Zuidema and C. Roberto Mechoso for their insightful comments, which improved this paper significantly. This research is supported by the U.S. National Science Foundation Grants, OCE-1334707 and AGS-1067937, and Department of Energy Grant DE-SC0006824, as well as National Oceanic and Atmospheric Administration Grant NA11OAR4310154. PC acknowledges the support from the National Science Foundation of China (41028005, 40921004 and 40930844).

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Authors and Affiliations

  1. Physical Oceanography Laboratory, Ocean University of China, Qingdao, China

    Zhao Xu

  2. Department of Oceanography, Texas A&M University, 3146, College Station, TX, 77840-3146, USA

    Zhao Xu, Ping Chang & Who Kim

  3. Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA

    Ping Chang & Guanglin Tang

  4. Research Institute for Global Change, JAMSTEC, Yokohama, Japan

    Ingo Richter

  5. Application Laboratory, JAMSTEC, Yokohama, Japan

    Ingo Richter

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  1. Zhao Xu
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  2. Ping Chang
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  3. Ingo Richter
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  4. Who Kim
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  5. Guanglin Tang
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Correspondence to Ping Chang.

Additional information

This paper is a contribution to the special issue on tropical Atlantic variability and coupled model climate biases that have been the focus of the recently completed Tropical Atlantic Climate Experiment (TACE), an international CLIVAR program (http://www.clivar.org/organization/atlantic/tace). This special issue is coordinated by William Johns, Peter Brandt, and Ping Chang, representatives of the TACE Observations and TACE Modeling and Synthesis working groups.

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Xu, Z., Chang, P., Richter, I. et al. Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Clim Dyn 43, 3123–3145 (2014). https://doi.org/10.1007/s00382-014-2247-9

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