Paper Reviewed
Xu, Z., Chang, P., Richter, I., Kim, W. and Tang, G. 2014. Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Climate Dynamics 43: 3123-3145.

Introducing the lengthy abstract of their work published in Climate Dynamics, Xu et al. (2014) write that warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA) are "a common problem in many current and previous generation climate models," while noting that the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble "provides a useful framework to tackle the complex issues concerning causes of the SST bias." And in exploring this framework, they come to the following conclusions.

[1] "The multi-model mean shows a positive shortwave radiation bias of ~20 W/m², consistent with [2] the models' deficiency in simulating low-level clouds." However, they note that [3] this shortwave radiation error "is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in [4] excessive heat loss from the ocean," although they state that [5] "the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias."

Continuing, they write that [6] "the majority of CMIP5 models underestimate upwelling strength along the Benguela coast," which is linked to [7] "the unrealistically weak alongshore wind stress simulated by the models." But they say that [8] "the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection," noting that [9] "SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region," further suggesting that [10] "the equatorial temperature bias remotely contributes to the SETA SST bias."

Xu et al. additionally say they found that [11] "all CMIP5 models simulate a southward displaced Angola-Benguela front (ABF), which in many models is more than 10 degrees south of its observed location." And they also report that [12] "SETA SST biases are most significantly correlated with ABF latitude, which suggests that [13] the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias." And they thus state that [14] "even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF."

Last of all, Xu et al. say their results [15] "indicate a 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," in response to which we give a hearty God speed!