The southeastern tropical atlantic sst bias investigated with a coupled atmosphere-ocean single-column model at a pirata mooring site

Anna Lena Deppenmeier*, Rein J. Haarsma, Chiel van Heerwaarden, Wilco Hazeleger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

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 languageEnglish
Pages (from-to)6255-6271
Number of pages17
JournalJournal of Climate
Volume33
Issue number14
DOIs
Publication statusPublished - 15 Jul 2020

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