Air-Sea Turbulent Fluxes From a Wave-Following Platform During Six Experiments at Sea
Type | Article | ||||||||
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Date | 2019-06 | ||||||||
Language | English | ||||||||
Author(s) | Bourras Denis1, Cambra Remi2, Marié Louis3, Bouin Marie-Noëlle4, 16, Baggio Lucio5, Branger Hubert6, Beghoura Houda17, Reverdin Gilles7, Dewitte Boris8, 9, 10, 11, Paulmier Aurélien12, Maes Christophe15, Ardhuin Fabrice![]() ![]() |
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Affiliation(s) | 1 : Aix Marseille Univ., Université de Toulon, CNRS, IRD, MIO UM 110; Marseille, France 2 : France Énergies Marines, Bâtiment Cap Océan; Plouzané, France 3 : LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France 4 : Météo-France/CNRM; Plouzané, France 5 : LATMOS, Quartier des Garennes; Guyancourt Cedex, France 6 : Aix Marseille Université, CNRS, IRPHE, Ecole Centrale Marseille; Marseille ,France 7 : Sorbonne-Université, CNRS/IRD/DMNHN (LOCEAN); Paris ,France 8 : Centro de Estudios Avanzados en Zonas Áridas (CEAZA), Coquimbo, Chile 9 : Millennium Nucleus for Ecology and Sustainable Management of Oceanic Island (ESMOI), Coquimbo, Chile 10 : Departamento de Biología Marina, Universidad Católica del Norte (UCN), Coquimbo, Chile 11 : Laboratoire d'Etudes en Géophysique et Océanographie Spatiales (LEGOS), Toulouse, France 12 : LEGOS, IRD, CNRS, CNES, Université de Toulouse, 14 avenue Edouard Belin, 31400 Toulouse, France 13 : Ifremer Méditerranée LERPAC, ZP de Brégaillon CS 20330, 83507 La Seyne sur Mer, France 14 : OSU Institut Pythéas, CEREGE, Europôle Meìditerraneìe, Site de l’Arbois, 13545 Aix en Provence Cedex 4, France 15 : LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France 16 : LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France 17 : LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France |
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Source | Journal Of Geophysical Research-oceans (2169-9275) (American Geophysical Union (AGU)), 2019-06 , Vol. 124 , N. 6 , P. 4290-4321 | ||||||||
DOI | 10.1029/2018JC014803 | ||||||||
WOS© Times Cited | 4 | ||||||||
Abstract | Turbulent fluxes at the air‐sea interface are estimated with data collected in 2011 to 2017 with a low‐profile platform during six experiments in four regions. The observations were carried out with moderate winds (2‐10 m s‐1) and averaged wave heights of 1.5 m. Most of the time, there was a swell, with an averaged wave age (the ratio between wave phase speed and wind speed) being equal to 2.8±1.6. Three flux calculation methods are used, namely the eddy‐covariance (EC), the inertial‐dissipation (ID), and the bulk methods. For the EC method, a spectral technique is proposed to correct wind data from platform motion. A mean bias affecting the friction velocity (u*) is then evaluated. The comparison between EC u* and ID u* estimates suggests that a constant imbalance term (ϕimb) equal to 0.4 is required in the ID method, possibly due to wave influence on our data. Overall, the confidence in the calculated u* estimates is found to be on the order of 10%. The values of the drag coefficient (CD) are in good agreement with the parameterizations of Smith (1988) in medium‐range winds and of Edson et al. (2013) in light winds. According to our data, the inverse wave age varies linearly with wind speed, as in Edson et al. (2013), but our estimates of the Charnock coefficient do not increase with wind speed, which is possibly related to sampling swell‐dominated seas. We find that the Stanton number is independent from wind speed. Plain language summary A small wave‐following platform was deployed in 2011‐2017 across four oceanic regions. The data are used to estimate turbulent fluxes, which are physical quantities that describe the exchanges of heat and momentum through the air‐sea interface. In weather models, simplified representations of the fluxes are used, which themselves depend on coefficients named drag coefficient for momentum exchange and Stanton number for temperature exchange, respectively. In this study, we evaluate these coefficients. First, we compare the flux estimates from the three main available methods. We adjust the parameters in the methods to reach the best possible agreement between the calculated fluxes. Two types of corrections are proposed, depending on the method considered, because turbulence data are modified by the motion of the platform and by the proximity of waves. Data are corrected by applying a mean bias to the fluxes and by accounting for a non‐measured term in the turbulence equations. Then, we analyze the wind dependence of the estimated drag coefficient and Stanton number. We find that drag is slowly increasing with wind speed, in agreement with existing models. Estimates of the Stanton number have biases, but which do not depend on wind speed. |
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