A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature

Sea surface temperature (SST) is a crucial parameter in climate, weather, and ocean sciences due to its decisive role in ocean–atmosphere interactions. Identifying errors in the prognostic scheme used by the current European Centre for Medium-range Weather Forecasts (ECMWF) model for predicting the...

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Published inGeoscientific Model Development Vol. 17; no. 23; pp. 8553 - 8568
Main Authors Kang, Eui-Jong, Sohn, Byung-Ju, Kim, Sang-Woo, Kim, Wonho, Kwon, Young-Cheol, Kim, Seung-Bum, Chun, Hyoung-Wook, Liu, Chao
Format Journal Article
LanguageEnglish
Published Katlenburg-Lindau Copernicus GmbH 02.12.2024
Copernicus Publications
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Summary:Sea surface temperature (SST) is a crucial parameter in climate, weather, and ocean sciences due to its decisive role in ocean–atmosphere interactions. Identifying errors in the prognostic scheme used by the current European Centre for Medium-range Weather Forecasts (ECMWF) model for predicting the diurnal variation in ocean skin temperature led to a revisit and revision of the ocean mixed layer (OML) model. Validation of the revised model was conducted by comparing simulated temperatures at the sub-skin level and 1 m depth with observations from shipborne infrared measurements and buoys. These comparisons revealed a strong correlation, with an absolute mean deviation of less than 0.1 K and a standard deviation under 0.5 K, which are found to be comparable to errors in satellite observations of SST. Given that these results are derived from the same model simulations, the error statistics for the simulated skin temperature and its diurnal variation should have the same degree of accuracy. Furthermore, the simulation results closely align with anticipated solar radiation distributions, whereas ERA5 ocean skin temperature shows a significant lack of alignment with solar radiation. Consequently, the revised OML model shows promising potential for improving the simulation of diurnal SST variations in weather and climate models.
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ISSN:1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
DOI:10.5194/gmd-17-8553-2024