FN Archimer Export Format PT J TI Air-Sea Turbulent Fluxes From a Wave-Following Platform During Six Experiments at Sea BT AF Bourras, Denis Cambra, Remi Marié, Louis Bouin, Marie-Noëlle Baggio, Lucio Branger, Hubert Beghoura, Houda Reverdin, Gilles Dewitte, Boris Paulmier, Aurélien Maes, Christophe ARDHUIN, Fabrice Pairaud, Ivane Fraunié, Philippe Luneau, Christopher Hauser, Danièle AS 1:1;2:2;3:3;4:4,16;5:5;6:6;7:17;8:7;9:8,9,10,11;10:12;11:15;12:16;13:13;14:1;15:14;16:5; FF 1:;2:;3:PDG-ODE-LOPS-OC;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:PDG-ODE-LITTORAL-LERPAC;14:;15:;16:; C1 Aix Marseille Univ., Université de Toulon, CNRS, IRD, MIO UM 110; Marseille, France France Énergies Marines, Bâtiment Cap Océan; Plouzané, France LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France Météo-France/CNRM; Plouzané, France LATMOS, Quartier des Garennes; Guyancourt Cedex, France Aix Marseille Université, CNRS, IRPHE, Ecole Centrale Marseille; Marseille ,France Sorbonne-Université, CNRS/IRD/DMNHN (LOCEAN); Paris ,France Centro de Estudios Avanzados en Zonas Áridas (CEAZA), Coquimbo, Chile Millennium Nucleus for Ecology and Sustainable Management of Oceanic Island (ESMOI), Coquimbo, Chile Departamento de Biología Marina, Universidad Católica del Norte (UCN), Coquimbo, Chile Laboratoire d'Etudes en Géophysique et Océanographie Spatiales (LEGOS), Toulouse, France LEGOS, IRD, CNRS, CNES, Université de Toulouse, 14 avenue Edouard Belin, 31400 Toulouse, France Ifremer Méditerranée LERPAC, ZP de Brégaillon CS 20330, 83507 La Seyne sur Mer, France OSU Institut Pythéas, CEREGE, Europôle Meìditerraneìe, Site de l’Arbois, 13545 Aix en Provence Cedex 4, France LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France LOPS, Plouzané IUEM Technopole Brest Iroise, rue Dumont d'Urville; Plouzané ,France C2 UNIV AIX MARSEILLE, FRANCE FRANCE ENERGIES MARINES, FRANCE IFREMER, FRANCE CNRM (METEO FRANCE), FRANCE LATMOS, FRANCE UNIV AIX MARSEILLE, FRANCE CNRS, FRANCE CEAZA, CHILE ESMOI, CHILE UNIV CAT NORTE COQUIMBO, CHILE LEGOS, FRANCE IRD, FRANCE IFREMER, FRANCE CEREGE, FRANCE IRD, FRANCE CNRS, FRANCE UBO, FRANCE SI BREST TOULON SE PDG-ODE-LOPS-OC PDG-ODE-LITTORAL-LERPAC UM LOPS IN WOS Ifremer UPR WOS Ifremer UMR WOS Cotutelle UMR copubli-france copubli-p187 copubli-univ-france copubli-int-hors-europe IF 3.559 TC 4 UR https://archimer.ifremer.fr/doc/00503/61436/65156.pdf LA English DT Article CR AMOP BBWAVES 2016 FROMVAR 2011 STRASSE UPCAST BO L'Atalante Thalia Côtes De La Manche Thalassa Téthys II AB 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. PY 2019 PD JUL SO Journal Of Geophysical Research-oceans SN 2169-9275 PU American Geophysical Union (AGU) VL 124 IS 6 UT 000477722200047 BP 4290 EP 4321 DI 10.1029/2018JC014803 ID 61436 ER EF