Editing IPCC:AR6/WGI/Chapter-3 (section)

==== 3.5.1.2 Tropical Sea Surface Temperature Evaluation ====

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===== 3.5.1.2.1 Tropical Pacific Ocean =====

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In CMIP5, mean state biases in the tropical Pacific Ocean including the excessive equatorial cold tongue, erroneous mean thermocline depth and slope along the equator remained but were improved relative to CMIP3 ( [[#Flato--2013|Flato et al., 2013]] ). Misrepresentation of the interaction between the atmosphere and ocean via the Bjerknes feedback and vertical mixing parameterizations, and a bias in winds were among the suggested reasons for the persistent biases ( [[#Li--2014|Li et al., 2014]] ; [[#Zhu--2018|Zhu and Zhang, 2018]] ). Moving to CMIP6, a reduction of the cold bias in the equatorial cold tongue in the central Pacific is found on average in the CMIP6 models (Figure 3.24b; [[#Grose--2020|Grose et al., 2020]] ; [[#Planton--2021|Planton et al., 2021]] ), however, this reduced bias is not statistically significant when considered across the multi-model ensemble ( [[#Planton--2021|Planton et al., 2021]] ). It is also noteworthy that the longitude of the 28°C isotherm is closer to observed in CMIP6 than in CMIP5, with a coincident reduction in the CMIP6 inter-model standard deviation ( [[#Grose--2020|Grose et al., 2020]] ). The latter result implies that there is an improvement in the representation of the tropical Pacific mean state in CMIP6 models. Comparison of biases in individual HighResMIP models with biases in lower resolution versions of the same models indicates that there is no consistent improvement in SST biases in most of the equatorial Pacific with resolution (Figure 3.3e; [[#Bock--2020|Bock et al., 2020]] ).

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===== 3.5.1.2.2 Tropical Atlantic Ocean =====

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Fundamental features such as the mean zonal SST gradient in the tropical Atlantic were not reproduced in CMIP5 models. Studies have proposed that weaker than observed alongshore winds, underestimation of stratocumulus clouds, coarse model resolution, and insufficient oceanic cooling due to a deeper thermocline depth and weak vertical velocities at the base of the mixed layer in the eastern basin, underpinned these tropical Atlantic SST gradient biases ( [[#Hourdin--2015|Hourdin et al., 2015]] ; [[#Richter--2015|Richter, 2015]] ). The SST gradient biases still remain in CMIP6. On average the cold bias in the western part of the basin is reduced while the warm bias in the eastern part has slightly increased (Figure 3.24b,c; [[#Richter--2020|Richter and Tokinaga, 2020]] ). Several CMIP6 models, however, display large reductions in biases of the zonal SST gradient, such that the eastern equatorial Atlantic warm SST bias and associated westerly wind biases are mostly eliminated in these models ( [[#Richter--2020|Richter and Tokinaga, 2020]] ). The high resolution (HighResMIP) CMIP6 models show a better representation of the zonal SST gradient (Figure 3.24b,c), but some lower resolution models also perform well, suggesting that resolution is not the only factor responsible for biases in Tropical Atlantic SST ( [[#Richter--2020|Richter and Tokinaga, 2020]] ).

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===== 3.5.1.2.3 Tropical Indian Ocean =====

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The tropical Indian Ocean mean state is reasonably well simulated both in CMIP5 and CMIP6 (Figure 3.24b,c). However, CMIP5 models show a large spread in the thermocline depth, particularly in the equatorial part of the basin ( [[#Saji--2006|Saji et al., 2006]] ; [[#Fathrio--2017b|Fathrio et al., 2017b]] ), which has been linked to the parameterization of the vertical mixing and the wind structure, leading to a misrepresentation of the ventilation process in some models ( [[#Schott--2009|Schott et al., 2009]] ; [[#Richter--2015|Richter, 2015]] ; [[#Shikha--2018|Shikha and Valsala, 2018]] ). A common problem with the CMIP5 models is therefore a warm bias in the subsurface, mainly at depths around the thermocline, which is also apparent in the CMIP6 models (Figure 3.25g).

In the CMIP6 multi-model mean, the western tropical Indian Ocean shows a slightly larger warm bias compared to CMIP5 (Figure 3.24 b,c), which in part could be related to excessive supply of warm water from the Red Sea ( [[#Grose--2020|Grose et al., 2020]] ; [[#Semmler--2020|Semmler et al., 2020]] ). The HighResMIP models show decreases in SST bias across the Indian Ocean with increasing resolution (Figure 3.3e; [[#Bock--2020|Bock et al., 2020]] ), though as a group the SST biases in the HighResMIP models are no smaller than those of the full CMIP6 ensemble.

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===== 3.5.1.2.4 Summary =====

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In summary, the structure and magnitude of multi-model mean ocean temperature biases have not changed substantially between CMIP5 and CMIP6 ( ''medium confidence'' ). Although biases remain in the latest generation models, the broad consistency between the observed and simulated basin-scale ocean properties suggests that CMIP5 and CMIP6 models are appropriate tools for investigating ocean temperature and ocean heat content responses to forcing. This also provides ''high confidence'' in the utility of CMIP-class models for detection and attribution studies, for both ocean heat content ( [[#3.5.1.3|Section 3.5.1.3]] ) and thermosteric sea level applications ( [[#3.5.3.2|Section 3.5.3.2]] ).

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