Parameterizing the Sea Surface Drag Coefficient over Aiyetoro in Ilaje Local Government Area, Ondo State, Southwestern Nigeria
Marine Science and Technology Department, Federal University of Technology Akure.
Department of Engineering, University of Campania Luigi Vanvitelli, Aversa, Italy
Department of Engineering, University of Campania Luigi Vanvitelli, Aversa, Italy
Segun Ohunayo Ekudehinwa
Nigerian Maritime University, Delta State, Nigeria
Gideon Efeoghene Ovwuwonye
Department of Marine Science and Technology, Federal University of Technology, Akure, Nigeria.
DOI: https://doi.org/10.36956/sms.v7i3.1989
Received: 11 April 2025; Published: 21 July 2025
Copyright © 2025 Adekunle Osinowo, Lateef Adesola Afolabi, Pasquale Contestabile, Segun Ohunayo Ekudehinwa, Gideon Efeoghene Ovwuwonye. Published by Nan Yang Academy of Sciences Pte. Ltd..
Abstract
Ocean surface waves and upper sea circulation are primarily propelled by wind force and are usually expressed in terms of sea surface drag coefficient (cd) that increases with sea surface roughness and wind speed. This work discussed the cd parameterization at Aiyetoro, Ilaje Local Government Area, Ondo State, Southwestern Nigeria, to quantify the exchange of momentum in this region, The dependence of cd on some one hourly averaged variables sourced from ERA5 Reanalysis over a 71 year period (1950–2020) was clearly analysed. Results of the monthly mean and variability of cd and u10 over the study area showed that November had the lowest monthly mean cd and u10, with values of 0.000825 and 3.38 m/s, respectively, and August had the highest values of 0.001031 and 5.66 m/s, respectively. Furthermore, the cd variability is lowest (63.24%) in November and highest (106.35%) in August. The variability for u10 is lowest in March (198.18%) and greatest in October (304.37%). For the study location, five parameterizations, were statistically evaluated for the predictive power of cd on an annual, seasonal and monthly basis. Furthermore, the cd showed improved performance when using monthly values than when using annual and seasonal values. The equations yielded better performance in the wet season than in the dry season.
Keywords: Era5 Reanalysis Data, Sea Surface Drag, Parameterization, Wind-Sea Interaction, Wave Dynamics, Momentum