Abstract

According to the ERA5 data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), the wind and wave fields in the Gulf of Guinea were very active in August. Then the Simulating Waves Nearshore (SWAN) model was applied to perform two-layer-nesting numerical simulations in this region. The wave propagation and distribution characteristics of the Gulf of Guinea in August are analyzed, especially its swell effect.

INTRODUCTION

The Gulf of Guinea (Fig.1) is located in western Africa. As an open gulf facing the Atlantic Ocean, it is vulnerable to the waves from the South Atlantic Ocean. Due to the lack of observational data and the characteristics of the unique waves in this region, it still needs more detailed mechanism and model research. Also, with the development of oil and gas exploitation, shipping, and coastal engineering, the research on the wave distribution and propagation characteristics in this region has great practical significance value.

The Gulf of Guinea is dominated by low tides and swells (Stive et al, 2002), the tidal range is from 0.3m to 1.8m (Almar et al, 2015; Melet et al, 2016). The swells propagating to the Gulf of Guinea mainly originate from the roaring forties in the 40°S–60°S region (Prevosto et al, 2013). Toualy et al. (2015) analyzed the wave data of AVISO and shown that the wave amplitude in the northwestern Gulf of Guinea varies greatly, and the large-amplitude, long-period waves also originated from the roaring forties in the South Atlantic.

There were few measured data in this area. Koffi et al. (1993) and Kadio et al. (2011) analyzed the daily wave data measured by oil companies in Côte d'Ivoire. However, these data cannot determine the origin and spatial variation of the waves in the Gulf of Guinea. The characteristics of waves in the Gulf of Guinea still needs further research. This paper established a two-layer-nesting SWAN model from the Atlantic Ocean to the Gulf of Guinea, studied its property under the typical sea conditions, and explored its distribution and propagation characteristics.

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