Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6873-2022
https://doi.org/10.5194/gmd-15-6873-2022
Model evaluation paper
 | 
09 Sep 2022
Model evaluation paper |  | 09 Sep 2022

The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study

Giulia Bonino, Doroteaciro Iovino, Laurent Brodeau, and Simona Masina

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Cited articles

Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis, NOAA Technical Memorandum NESDIS NGDC-24, National Geophysical Data Center, NOAA [data set], https://doi.org/10.7289/V5C8276M, 2009. a
Barnier, B.: Forcing the Ocean, in: Ocean Modeling and Parameterization, edited by: Chassignet, E. P. and Verron, J., NATO Science Series, vol 516, Springer, 45–80, https://doi.org/10.1007/978-94-011-5096-5_2, 1998. a
Barnier, B., Madec, G., Penduff, T., Molines, J. M., Treguier, A. M., Le Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J., and De Cuevas, B.: Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution, Ocean Dynam., 56, 543–567, https://doi.org/10.1007/s10236-006-0082-1, 2006. a
Blanke, B. and Delecluse, P.: Variability of the tropical Atlantic Ocean simulated by a general circulation model with two different mixed-layer physics, J. Phys. Oceanogr., 23, 1363–1388, 1993. a
Bonino, G.: The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study, Zenodo [code and data set], https://doi.org/10.5281/zenodo.6258085, 2022. a, b
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Short summary
The sea surface temperature (SST) is highly influenced by the transfer of energy driven by turbulent air–sea fluxes (TASFs). In the NEMO ocean general circulation model, TASFs are computed by means of bulk formulas. Bulk formulas require the choice of a given bulk parameterization, which influences the magnitudes of the TASFs. Our results show that parameterization-related SST differences are primarily sensitive to the wind stress differences across parameterizations.