Abstract
Despite the efforts of the modelling community to improve the representation of the sea surface temperature (SST) over the South Eastern Tropical Atlantic, warm biases still persist. In this work we use four different configurations of the fully-coupled AWI Climate Model (AWI-CM) which allow us to gain physics-based insight into the role of the oceanic and atmospheric resolutions of the model in the regional distribution of the SST. Our results show that a sole refinement of the oceanic resolution reduces warm biases further than a single increase of the atmospheric component. An increased oceanic resolution is required (i) to simulate properly the Agulhas Current and its associated rings; (ii) to reinforce the northward-flowing Benguela Current and (iii) to intensify coastal upwelling. The best results are obtained when both resolutions are refined. However, even in that case, warm biases persist, reflecting that some processes and feedbacks are still not optimally resolved. Our results indicate that overheating is not due to insufficient upwelling, but rather due to upwelling of waters which are warmer than observations as a result of an erroneous representation of the vertical distribution of temperature. Errors in the representation of the vertical temperature profile are the consequence of a warm bias in the simulated climate state.
Highlights
Over the last decades, the ability of coupled atmosphere–ocean general circulation models (AOGCMs) to simulate the present climate and its variability has been significantly improved (e.g., Xu et al 2014)
Biases are large over the South Eastern Tropical Atlantic (SETA), where individual models participating in the 5th phase of the CMIP show values that reach even more than 5 °C (Zuidema et al 2016)
This indicates that drawbacks in the ocean model dynamics and vertical thermal structure of the ocean could play a partial role in the generation of these biases
Summary
The ability of coupled atmosphere–ocean general circulation models (AOGCMs) to simulate the present climate and its variability has been significantly improved (e.g., Xu et al 2014). A well-known problem is the underestimation of low marine stratiform clouds in the SETA region (Giese and Carton 1994; Tanimoto and Xie 2002; Huang et al 2007; Wahl et al 2011; Exarchou et al 2018) Another systematic shortcoming shared by most AOGCMs is the misrepresentation of surface evaporation over the eastern Tropical Oceans, which is often smaller than observational data (Zheng et al 2011; Hourdin et al 2015). A significant correlation between the latitudinal position of the ABFZ and the SST biases has been found in CMIP models (Xu et al 2014) This indicates that an accurate representation of these currents is a key element to reduce the warm biases. Another major source of biases is insufficient representation of upwelling of cold waters at Benguela, ABA1 and ABA2 regions, as defined in Sect. 4.2, are depicted. c, d Horizontal resolution, in km, of the low- and high-resolution unstructured oceanic grids used in the LR and HR configurations, respectively (see Sect. 2 for details about the construction of these grids)
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