Following the methodology developed in Imbol Koungue et al. (2017), 21 (13 warm and 8 cold) extreme coastal events are selected over the period 1958 to 2015. Three newly identified warm interannual coastal events are documented, namely, the extreme warm events 1958/1959 (December–July), 1960/1961 (September–April), and 1974 (April–July). Similarly, undocumented extreme cold events are identified in 1965 (September–December), 1980/1981 (October–April), and 1985 (March–June). Five out of 21 of these new extreme events occur before the satellite era (before 1982). Note that little differences are observed in the timing of the events (start and end) compared to the identified events in the recent study by Imbol Koungue et al. (2017) carried out over the PIRATA period from 1998 to 2012. For example, Imbol Koungue et al. (2017) and Rouault et al. (2018) identified the 2010/2011 extreme warm event between November and April while it is recorded between September 2010 and April 2011 using the OGCM over 1958 to 2015. Difference in timing of the event can be attributed to the difference in length of the time series which yields different monthly climatology, standard deviations, and then different normalized anomalies and thresholds. Also, the fact that the OGCM does not perfectly agree with observations and the presence of warm bias in the Angola-Benguela upwelling system (Figure 2b at 23°S) could impact the time series by increasing or reducing the duration of a coastal event. This could also justify the fact that some anomalous coastal events identified by Imbol Koungue et al. (2017) are missing in this study, for instance, coastal warm events 2003 (July–December) and 2008/2009 (November–January) which do not fulfill the criterion over the 1958–2015 period. Another source of discrepancies between coastal events duration or intensities of simulated and observed events is the fact that the interannual variability of river runoff is not taken into account in the OGCM. For instance, Lübbecke et al. (2019) recently suggested that the interannual variability of precipitation over Southern Africa leading to a freshwater anomaly off Angola via runoff of Congo and possibly other small rivers could have played a role in forcing the 2016 warm event.

FMA averages (Figures 4 and 8) of all the extreme coastal events show warming or cooling pattern along the southwestern African coast. The strongest warming occurs in FMA 1963 (1962/1963 event) and the strongest cooling in FMA 1997 (1996/1997 event). Over the 1958 to 2015 period, most of the anomalous coastal warm or cold events including the newly identified ones are linked to downwelling or upwelling IEKW mode 2 propagations in agreement with previous studies (Imbol Koungue et al., 2017). There is a one-month lag when detrended anomalies of IEKW mode 2 lead surface temperature anomalies in Southern Angola and the ABF domain. This finding agrees with the recent study of Imbol Koungue et al. (2017).

In the tropical Atlantic Ocean, extreme coastal events that peak in March–April show a warming or cooling pattern that is observed up to ~25°S along the Namibian coastline. This latitude corresponds to the southernmost latitude where the CTW propagations can be detected on the surface temperature signal anomalous coastal events. This is consistent with the work of Bachlery et al. (2016). We observe an asymmetry of Benguela Niño/Niña events. First, Benguela Niña events last longer than Benguela Niño events which agree with the finding of Florenchie et al. (2004). Second, we have observed that the spatial area of cold DT10A during a Benguela Niña event is broader than the one of warm DT10A during a Benguela Niño, occasionally covering the whole south Atlantic (Figures 8d and 11d). Third, the WES feedback seems to be more active during a Benguela Niño than a Benguela Niña from Figures 10c and 11c. More analyses are necessary to investigate the role of this feedback in more details. Lastly, the meridional dipole observed on the Benguela Niño composite maps is not observed on the Benguela Niña composite maps. This means that March–April Benguela Niña events appear to be independent of other air-sea interactions in the tropical North Atlantic. A tendency of Atlantic Niño to follow Benguela Niño with a lag of about two months is observed, which is consistent with the previous findings (Lübbecke et al., 2010; Richter et al., 2010; Rouault et al., 2009). Both forcings (local and remote) are found as part of basin-scale weakening or strengthening of the SAA and associated wind stress during Benguela Niño or Niña, respectively. This is consistent with the 1958–2000 modeling study of Lübbecke et al. (2010) in which correlation map between April SST and February wind stress revealed that the whole SAA partly formed of weak trade winds along the equator and weak coastal winds, weakened prior to the warming in the BUS.

We suggest that the WES feedback is at work one month before the peak and during the peak of the event, as northwesterly or southeasterly wind stress anomalies are present over the warming or cooling area south of the equator, respectively (Figures 10c, 10d, 11c, and 11d). Similar assumptions have been made in the study of Lübbecke et al. (2010) for the tropical Atlantic. Moreover, there could be a possibility that the ocean-
Following the methodology developed in Imbol Koungue et al. (2017), 21 (13 warm and 8 cold) extreme coastal events are selected over the period 1958 to 2015. Three newly identified warm interannual coastal events are documented, namely, the extreme warm events 1958/1959 (December–July), 1960/1961 (September–April), and 1974 (April–July). Similarly, undocumented extreme cold events are identified in 1965 (September–December), 1980/1981 (October–April), and 1985 (March–June). Five out of 21 of these new extreme events occur before the satellite era (before 1982). Note that little differences are observed in the timing of the events (start and end) compared to the identified events in the recent study by Imbol Koungue et al. (2017) carried out over the PIRATA period from 1998 to 2012. For example, Imbol Koungue et al. (2017) and Rouault et al. (2018) identified the 2010/2011 extreme warm event between November and April while it is recorded between September 2010 and April 2011 using the OGCM over 1958 to 2015. Difference in timing of the event can be attributed to the difference in length of the time series which yields different monthly climatology, standard deviations, and then different normalized anomalies and thresholds. Also, the fact that the OGCM does not perfectly agree with observations and the presence of warm bias in the Angola-Benguela upwelling system (Figure 2b at 23°S) could impact the time series by increasing or reducing the duration of a coastal event. This could also justify the fact that some anomalous coastal events identified by Imbol Koungue et al. (2017) are missing in this study, for instance, coastal warm events 2003 (July–December) and 2008/2009 (November–January) which do not fulfill the criterion over the 1958–2015 period. Another source of discrepancies between coastal events duration or intensities of simulated and observed events is the fact that the interannual variability of river runoff is not taken into account in the OGCM. For instance, Lübbecke et al. (2019) recently suggested that the interannual variability of precipitation over Southern Africa leading to a freshwater anomaly off Angola via runoff of Congo and possibly other small rivers could have played a role in forcing the 2016 warm event.

FMA averages (Figures 4 and 8) of all the extreme coastal events show warming or cooling pattern along the southwestern African coast. The strongest warming occurs in FMA 1963 (1962/1963 event) and the strongest cooling in FMA 1997 (1996/1997 event). Over the 1958 to 2015 period, most of the anomalous coastal warm or cold events including the newly identified ones are linked to downwelling or upwelling IEKW mode 2 propagations in agreement with previous studies (Imbol Koungue et al., 2017). There is a one-month lag when detrended anomalies of IEKW mode 2 lead surface temperature anomalies in Southern Angola and the ABF domain. This finding agrees with the recent study of Imbol Koungue et al. (2017).

In the tropical Atlantic Ocean, extreme coastal events that peak in March–April show a warming or cooling pattern that is observed up to ~25°S along the Namibian coastline. This latitude corresponds to the southernmost latitude where the CTW propagations can be detected on the surface temperature signal anomalous coastal events. This is consistent with the work of Bachèlery et al. (2016). We observe an asymmetry of Benguela Niño/Niña events. First, Benguela Niña events last longer than Benguela Niño events which agree with the finding of Florenchie et al. (2004). Second, we have observed that the spatial area of cold DT10A during a Benguela Niña event is broader than the one of warm DT10A during a Benguela Niño, occasionally covering the whole south Atlantic (Figures 8d and 11d). Third, the WES feedback seems to be more active during a Benguela Niño than a Benguela Niña from Figures 10c and 11c. More analyses are necessary to investigate the role of this feedback in more details. Lastly, the meridional dipole observed on the Benguela Niño composite maps is not observed on the Benguela Niña composite maps. This means that March–April Benguela Niña events appear to be independent of other air-sea interactions in the tropical North Atlantic. A tendency of Atlantic Niño to follow Benguela Niño with a lag of about two months is observed, which is consistent with the previous findings (Lübbecke et al., 2010; Richter et al., 2010; Rouault et al., 2009). Both forcings (local and remote) are found as part of basin-scale weakening or strengthening of the SAA and associated wind stress during Benguela Niño or Niña, respectively. This is consistent with the 1958–2000 modeling study of Lübbecke et al. (2010) in which correlation map between April SST and February wind stress revealed that the whole SAA partly formed of weak trade winds along the equator and weak coastal winds, weakened prior to the warming in the BUS.

We suggest that the WES feedback is at work one month before the peak and during the peak of the event, as northwesterly or southeasterly wind stress anomalies are present over the warming or cooling area south of the equator, respectively (Figures 10c, 10d, 11c, and 11d). Similar assumptions have been made in the study of Lübbecke et al. (2010) for the tropical Atlantic. Moreover, there could be a possibility that the ocean-
atmosphere coupling has impacted the local alongshore wind stress off Angola by weakening or strengthening them before the peak of the warm or cold coastal events, respectively, in Southern Angola. This could partly explain the high anticorrelation (~-0.5) between anomalies of T10 and meridional wind stress in Southern Angola compared to the other domains (Figure 7a and Table 1). However, there is a total absence of upwelling-favoring winds in Southern Angola (Ostrowski et al., 2009; Rouault, 2012). We have shown that the equatorial wind forcing resulting from the variations of zonal wind stress in the western/central (Illig et al., 2004; Florenchie et al., 2004; Lübbecke et al., 2010; Bachèlery et al., 2016; Imbol Koungue et al., 2017) and eastern equatorial Atlantic (Gulf of Guinea; Bachèlery et al., 2016) trigger IEKW which at the African coast initiate poleward propagating CTW which influence T10 along the southwestern African coast. We suggest that variations of meridional wind stress north of 15°S mainly in the Northern Angola domain (5°S-10°S, from the coast to 1° offshore) could also trigger local CTW which clearly influence T10 from Southern Angola to Northern Namibia (Figures 12c, 12f, and 12i). On top of that, weak (strong) cyclonic wind stress curl observed near the coast off Southern Angola could generate warm (cold) surface temperature anomalies by decreasing (increasing) the near-coastal upwelling. Weaker (stronger) wind could also lead to a warming (cooling) by reducing (enhancing) the turbulent latent heat flux at the sea surface (Lübbecke et al., 2019). Across the ABF, the poleward transport could be weakened by weak cyclonic wind stress curl (Junker et al., 2015) and surface temperature anomalies will be propagated poleward by downwelling CTW. At interannual time scales, meridional transport anomalies across the ABF might then contribute to the development of anomalous coastal events in Northern Namibia. A lag of one to two months (not shown) is found when detrended anomalies of net mass transport across the ABF lead surface temperature anomalies in the Northern Namibia domain which is consistent with the study of Rouault (2012), who reported a lag ranging between two and four months. The fact that maximum anticorrelation occurs at two-month lag (one month before the IEKW mode 2 forcing) could be due to the contribution of higher-order IEKW modes which propagate slower than IEKW mode 2 or to the effect of the large-scale wind stress forcing. Therefore, the advection of anomalous warm or cold waters across the ABF and its link to anomalous coastal events in Northern Namibia can be partly explained by the net mass transport across the ABF. We have shown that T10 in Northern Namibia is less influenced by equatorial dynamics compared to the two other domains further upstream (Rouault, 2012). Similar wind stress forcings as in the two other domains are observed except the zonal wind stress in the Gulf of Guinea which is weak. Due to the upwelling dynamics in Northern Namibia associated with a low local stratification depending on the season (Imbol Koungue et al., 2017), the imprint of CTW on at the ocean surface is not well observed. This could also justify the low correlation compared to other domains statistically significant at 95% observed between different parameters and DNT10A (Figures 6c, 12c, 12f, and 12i). Furthermore, we have shown that DNT10A are also impacted by local alongshore wind stress which is part of SAA. The recent study from Rouault et al. (2018) showed that during the onset of the 2010/2011 Benguela Niño, the southeasterly wind stress (upwelling-favoring wind) weakened off Namibia due to the equatorward shift of the SAA leading to above normal SST. They further claimed that these large-scale movements in the SAA involving wind stress in the tropical and South Atlantic are at the origin of many Benguela Niño and Atlantic Niño events as also proposed by Lübbecke et al. (2010, 2014). Weak (strong) local cyclonic wind stress curl observed near the Namibian coastline generate negative (positive) Ekman pumping and decrease (increase) the near-coastal upwelling leading to the apparition of positive (negative) surface temperature anomalies. A potential contribution of the local surface heat fluxes during the onset of the anomalous coastal events has not been thoroughly investigated in this study but is briefly discussed. Past studies (Bachèlery et al., 2016; Florenchie et al., 2004; Rouault et al., 2007) showed that local surface heat fluxes tend to damp the anomalous coastal events in the Angola-Benguela Area box, but they could also modulate their origin (Lübbecke et al., 2019).

In conclusion, an OLM can be a useful tool to investigate the IEKW propagations along the equatorial Atlantic which are linked to Benguela Niños or Niñas in the Angola-Benguela upwelling system as it was the case for the newly identified extreme coastal events that developed before 1982. The importance of the implementation of an early warning system using OLM forced with real-time satellite wind estimates or atmospheric model outputs in combination with real-time PIRATA buoy records and altimetry has already been mentioned in the recent study by Imbol Koungue et al. (2017). Tide gauge and current meter available in real time in Angola and Namibia would complete the system and are much needed. During the peak season of Benguela Niño and Niña (March-April), warming or cooling pattern is observed up to ~25°S along the
atmosphere coupling has impacted the local alongshore wind stress off Angola by weakening or strengthening them before the peak of the warm or cold coastal events, respectively, in Southern Angola. This could partly explain the high anticorrelation (~-0.5) between anomalies of T10 and meridional wind stress in Southern Angola compared to the other domains (Figure 7a and Table 1). However, there is a total absence of upwelling-favoring winds in Southern Angola (Ostrowski et al., 2009; Rouault, 2012). We have shown that the equatorial wind forcing resulting from the variations of zonal wind stress in the western/central (Illig et al., 2004; Florenchie et al., 2004; Lübbecke et al., 2010; Bachèlery et al., 2016; Imbol Koungue et al., 2017) and eastern equatorial Atlantic (Gulf of Guinea; Bachèlery et al., 2016) trigger IEKW which at the African coast initiate poleward propagating CTW which influence T10 along the southwestern African coast. We suggest that variations of meridional wind stress north of 15°S mainly in the Northern Angola domain (5°S-10°S, from the coast to 1° offshore) could also trigger local CTW which clearly influence T10 from Southern Angola to Northern Namibia (Figures 12c, 12f, and 12i). On top of that, weak (strong) cyclonic wind stress curl observed near the coast off Southern Angola could generate warm (cold) surface temperature anomalies by decreasing (increasing) the near-coastal upwelling. Weaker (stronger) wind could also lead to a warming (cooling) by reducing (enhancing) the turbulent latent heat flux at the sea surface (Lübbecke et al., 2019). Across the ABF, the poleward transport could be weakened by weak cyclonic wind stress curl (Junker et al., 2015) and surface temperature anomalies will be propagated poleward by downwelling CTW. At interannual time scales, meridional transport anomalies across the ABF might then contribute to the development of anomalous coastal events in Northern Namibia. A lag of one to two months (not shown) is found when detrended anomalies of net mass transport across the ABF lead surface temperature anomalies in the Northern Namibia domain which is consistent with the study of Rouault (2012), who reported a lag ranging between two and four months. The fact that maximum anticorrelation occurs at two-month lag (one month before the IEKW mode 2 forcing) could be due to the contribution of higher-order IEKW modes which propagate slower than IEKW mode 2 or to the effect of the large-scale wind stress forcing. Therefore, the advection of anomalous warm or cold waters across the ABF and its link to anomalous coastal events in Northern Namibia can be partly explained by the net mass transport across the ABF. We have shown that T10 in Northern Namibia is less influenced by equatorial dynamics compared to the two other domains further upstream (Rouault, 2012). Similar wind stress forcings as in the two other domains are observed except the zonal wind stress in the Gulf of Guinea which is weak. Due to the upwelling dynamics in Northern Namibia associated with a low local stratification depending on the season (Imbol Koungue et al., 2017), the imprint of CTW on at the ocean surface is not well observed. This could also justify the low correlation compared to other domains statistically significant at 95% observed between different parameters and DNT10A (Figures 6c, 12c, 12f, and 12i). Furthermore, we have shown that DNT10A are also impacted by local alongshore wind stress which is part of SAA. The recent study from Rouault et al. (2018) showed that during the onset of the 2010/2011 Benguela Niño, the southeasterly wind stress (upwelling-favoring wind) weakened off Namibia due to the equatorward shift of the SAA leading to above normal SST. They further claimed that these large-scale movements in the SAA involving wind stress in the tropical and South Atlantic are at the origin of many Benguela Niño and Atlantic Niño events as also proposed by Lübbecke et al. (2010, 2014). Weak (strong) local cyclonic wind stress curl observed near the Namibian coastline generate negative (positive) Ekman pumping and decrease (increase) the near-coastal upwelling leading to the apparition of positive (negative) surface temperature anomalies. A potential contribution of the local surface heat fluxes during the onset of the anomalous coastal events has not been thoroughly investigated in this study but is briefly discussed. Past studies (Bachèlery et al., 2016; Florenchie et al., 2004; Rouault et al., 2007) showed that local surface heat fluxes tend to damp the anomalous coastal events in the Angola-Benguela Area box, but they could also modulate their origin (Lübbecke et al., 2019).

In conclusion, an OLM can be a useful tool to investigate the IEKW propagations along the equatorial Atlantic which are linked to Benguela Niños or Niñas in the Angola-Benguela upwelling system as it was the case for the newly identified extreme coastal events that developed before 1982. The importance of the implementation of an early warning system using OLM forced with real-time satellite wind estimates or atmospheric model outputs in combination with real-time PIRATA buoy records and altimetry has already been mentioned in the recent study by Imbol Koungue et al. (2017). Tide gauge and current meter available in real time in Angola and Namibia would complete the system and are much needed. During the peak season of Benguela Niño and Niña (March-April), warming or cooling pattern is observed up to ~25°S along the
Namibian coastline. A tendency of Atlantic Niño or Niña to follow Benguela Niño or Niña has been observed, and a possible asymmetry of Benguela Niño/Niña was suggested in this study. Local and remote forcing which are part of basin-scale weakening or strengthening of the wind stress one to two months before the peak of Benguela Niño or Niña have been evidenced. Ocean-atmosphere coupling seems to be at work as northwesterly or southeasterly wind stress anomalies are observed over the warming or cooling area south of the equator east of 20°W. DT10A in Southern Angola and ABF domains have shown to be influenced by equatorial dynamics (CTW emanating from IEKW) via variations of zonal wind stress in the western and eastern equatorial Atlantic and CTW forced in the Northern/Southern Angola by meridional wind stress anomalies part of the large-scale wind stress forcing. However, DT10A in Northern Namibia is impacted by local southeasterly wind stress anomalies part of the SAA and CTW triggered by IEKW forced by variations of zonal wind stress anomalies in the western equatorial Atlantic and CTW forced by meridional wind stress anomalies in the Southern/Northern Angola. Across the ABF, the interaction between CTW and local currents leads to the advection of warm or cold waters into the Northern Benguela upwelling system which is a key factor for the development of anomalous coastal events.

Further work will involve a study of the role of local variability (strength of local stratification, cloud cover, Ekman transport, and turbulent fluxes) for each Benguela Niño and Benguela Niña event over 1958–2015. A high-resolution coupled ocean-atmosphere model could help to analyze the role of the local coupled feedback (WES feedback) in more details. Also, the role of the near coastal wind stress curl which drives the poleward boundary current needs to be better ascertained during the onset of these anomalous coastal events.

## Acknowledgments

The authors want to acknowledge ACCESS, NRF, DST, WRC, LMI ICEMASA, the SARCHI chair of Ocean Atmosphere Modelling, and the Nansen Tutu for Marine Environmental Research for funding. The research leading to these results received funding from the EU FP7/2007–2013 under grant agreement 603521 PREFACE project and from the EU H2020 under grant agreement 817578 TRIATLAS project. It was further supported by the German Federal Ministry of Education and Research as part of the SACUS II (03F0751A), BANINO (03F0795A) and RACE (03F0824C) projects. Model outputs used in this study are freely available at https://doi.org/10.6084/m9.figshare.8224394.v1.

## References

Bachlèry, M. L., Illig, S., & Dadou, I. (2016). Interannual variability in the South-East Atlantic Ocean, focusing on the Benguela Upwelling System: Remote versus local forcing. *Journal of Geophysical Research: Oceans*, 121, 284–310. https://doi.org/10.1002/2015JC011168

Bakun, A., & Nelson, C. S. (1991). The seasonal cycle of wind stress curl in subtropical eastern boundary current regions. *Journal of Physical Oceanography*, 21, 1815–1834.

Binet, D., Gobert, B., & Maloueki, L. (2001). El Niño-like warm events in the Eastern Atlantic (6°N, 20°S) and fish availability from Congo to Angola (1964–1999). *Aquatic Living Resources*, 14, 99–113.

Blamey, L. K., Shannon, L. J., Bolton, J. J., Crawford, R. J. M., Dufois, F., EversKing, H., et al. (2015). Ecosystem change in the southern Benguela and the underlying processes. *Journal of Marine Systems*, 144, 9–29. https://doi.org/10.1016/j.jmarsys.2014.11.006

Bourlès, B., Lumpkin, R., McPhaden, M. J., Hernandez, F., Nobre, P., Campos, E., et al. (2008). The PIRATA program: History, accomplishments, and future directions. *Bulletin of the American Meteorological Society*, 89(8), 1111–1126. https://doi.org/10.1175/2008BAMS2462.1

Boyer, D. C., Boyer, H. J., Fossen, I., & Kreiner, A. (2001). Changes in abundance of the northern Benguela sardine stock during the decade 1990–2000, with comments on the relative importance of fishing and the environment. *African Journal of Marine Science*, 23(1), 67–84. https://doi.org/10.2989/025776101784528854

Chavez, F. P., & Messié, M. (2009). A comparison of eastern boundary upwelling ecosystems. *Progress in Oceanography*, 83(1–4), 80–96. https://doi.org/10.1016/j.pocean.2009.07.032

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Colberg, F., & Reason, C. J. C. (2006). A model study of the Angola Benguela Frontal Zone: Sensitivity to atmospheric forcing. *Geophysical Research Letters*, 33, L19608. https://doi.org/10.1029/2006GL027463

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Namibian coastline. A tendency of Atlantic Niño or Niña to follow Benguela Niño or Niña has been observed, and a possible asymmetry of Benguela Niño/Niña was suggested in this study. Local and remote forcing which are part of basin-scale weakening or strengthening of the wind stress one to two months before the peak of Benguela Niño or Niña have been evidenced. Ocean-atmosphere coupling seems to be at work as northwesterly or southeasterly wind stress anomalies are observed over the warming or cooling area south of the equator east of 20°W. DT10A in Southern Angola and ABF domains have shown to be influenced by equatorial dynamics (CTW emanating from IEKW) via variations of zonal wind stress in the western and eastern equatorial Atlantic and CTW forced in the Northern/Southern Angola by meridional wind stress anomalies part of the large-scale wind stress forcing. However, DT10A in Northern Namibia is impacted by local southeasterly wind stress anomalies part of the SAA and CTW triggered by IEKW forced by variations of zonal wind stress anomalies in the western equatorial Atlantic and CTW forced by meridional wind stress anomalies in the Southern/Northern Angola. Across the ABF, the interaction between CTW and local currents leads to the advection of warm or cold waters into the Northern Benguela upwelling system which is a key factor for the development of anomalous coastal events.

Further work will involve a study of the role of local variability (strength of local stratification, cloud cover, Ekman transport, and turbulent fluxes) for each Benguela Niño and Benguela Niña event over 1958–2015. A high-resolution coupled ocean-atmosphere model could help to analyze the role of the local coupled feedback (WES feedback) in more details. Also, the role of the near coastal wind stress curl which drives the poleward boundary current needs to be better ascertained during the onset of these anomalous coastal events.

## Acknowledgments

The authors want to acknowledge ACCESS, NRF, DST, WRC, LMI ICEMASA, the SARCHI chair of Ocean Atmosphere Modelling, and the Nansen Tutu for Marine Environmental Research for funding. The research leading to these results received funding from the EU FP7/2007–2013 under grant agreement 603521 PREFACE project and from the EU H2020 under grant agreement 817578 TRIATLAS project. It was further supported by the German Federal Ministry of Education and Research as part of the SACUS II (03F0751A), BANINO (03F0795A) and RACE (03F0824C) projects. Model outputs used in this study are freely available at https://doi.org/10.6084/m9.figshare.8224394.v1.

## References

Bachlèry, M. L., Illig, S., & Dadou, I. (2016). Interannual variability in the South-East Atlantic Ocean, focusing on the Benguela Upwelling System: Remote versus local forcing. *Journal of Geophysical Research: Oceans, 121*, 284–310. https://doi.org/10.1002/2015JC011168

Bakun, A., & Nelson, C. S. (1991). The seasonal cycle of wind stress curl in subtropical eastern boundary current regions. *Journal of Physical Oceanography, 21*, 1815–1834.

Binet, D., Gobert, B., & Maloueki, L. (2001). El Niño-like warm events in the Eastern Atlantic (6°N, 20°S) and fish availability from Congo to Angola (1964–1999). *Aquatic Living Resources, 14*, 99–113.

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