Bachelery M. L., Illig Serena, Rouault M. (2020). Interannual coastal trapped waves in the Angola-Benguela Upwelling System and Benguela Nino and Nina events. Journal of Marine Systems, 203, p. art. 103262 [16 p.]. ISSN 0924-7963.
Titre du document
Interannual coastal trapped waves in the Angola-Benguela Upwelling System and Benguela Nino and Nina events
Journal of Marine Systems, 2020,
203, p. art. 103262 [16 p.] ISSN 0924-7963
We investigate the dynamics of the interannual Coastal Trapped Waves (CTW) propagations along the southwestern African coast and their role in triggering Benguela Nino and Nina events from 1958 to 2008. Using regional ocean model sensitivity experiments, we track equatorially-forced CTW down to the Southern Benguela Upwelling System (SBUS), where they account for 70% of the coastal sea level anomalies (SLA), temperature, and salinity variability. We then decompose the model coastal variability into individual CTW modal contributions and identify periods of energetic downwelling and upwelling propagations. A composite analysis allows for documenting and quantifying the oceanic response (circulation, temperature, and salinity) on the shelf during the passage of remotely-forced CTW. Results reveal that North of similar to 19 degrees S, the coastal interannual variability is dominated by the second and third CTW modes. In the BUS, their amplitudes decrease and the interannual fluctuations are largely explained ( > 70%) by the faster and weakly-dissipative first CTW mode. This dynamic explains the peculiar propagative pattern associated with SLA propagations, in which equatorially-forced fluctuations in the SBUS peak before the waves imprint the variability at similar to 19 degrees S. The impact of CTW on the temperature in the SBUS is drastically lower than in the NBUS and Angolan regions. At last, we show that 71% of the extreme Benguela Nino and Nina events, in the surface layer, are associated with remotely-forced CTW propagations. The coherence between our CTW index and these extreme events increases when detecting temperature anomalies in the sub-surface rather than at the sea surface.
