Abstract
Warm sea surface temperature (SST) biases in the tropical Atlantic Ocean form a longstanding problem in coupled general circulation models (CGCMs). Considerable efforts to understand the origins of these biases and alleviate them have been undertaken, but state-of-the-art CGCMs still suffer from biases that are very similar to those of the generation of models before. In this study, we use a powerful combination of in situ moored buoy observations and a new coupled ocean-atmosphere single-column model (SCM) with parameterization that is identical to that of a three-dimensional CGCM to investigate the SST bias. We place the SCM at the location of a Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) mooring in the southeastern tropical Atlantic, where large SST biases occur in CGCMs. The SCM version of the EC-Earth state-of-the-art coupled GCM performs well for the first five days of the simulation. Then, it develops an SST bias that is very similar to that of its three-dimensional counterpart. Through a series of sensitivity experiments we demonstrate that the SST bias can be reduced by 70%. We achieve this result by enhancing the turbulent vertical ocean mixing efficiency in the ocean parameterization scheme. The under-representation of vertical mixing in three-dimensional CGCMs is a candidate for causing the warm SST bias. We further show that surface shortwave radiation does not cause the SST bias at the location of the PIRATA mooring. Rather, a warm atmospheric near-surface temperature bias and a wet moisture bias contribute to it. Strongly nudging the atmosphere to profiles from reanalysis data reduces the SST bias by 40%.
Original language | English |
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Pages (from-to) | 6255-6271 |
Number of pages | 17 |
Journal | Journal of Climate |
Volume | 33 |
Issue number | 14 |
DOIs | |
Publication status | Published - 15 Jul 2020 |
Funding
Acknowledgments. This study was supported by the EU FP7/2007–2013 PREFACE Project under Grant Agreement 603521. We acknowledge the GTMBA Project Office of NOAA/PMEL for the freely available PIRATA mooring data used as model forcing and for comparison. We acknowledge Kerstin Hartung for valuable collaboration and for help with identifying optimal settings for the SCM at this location.