the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterization of Northwest African Coastal Upwelling Systems
Abstract. Coastal upwellings are critical for nutrient supply, biological productivity, socio-economic activities, local weather patterns and regional climate variability. This study investigated characteristics of the Northwest African coastal upwelling system, including the Senegal-Mauritania and Gulf of Guinea coastal upwelling regions. The spatial and temporal variability were analysed using physical and biogeochemical ocean variables from 1982 to 2022. The analysis focused on upwelling indices derived from sea surface temperatures (SSTs), wind stress and chlorophyll-a concentration during the boreal winterspring and summer, when upwelling peaks in the Senegal-Mauritania and Gulf of Guinea upwelling systems, respectively. Additional indicators such as the annual cycles of sea level anomaly, ocean surface current velocity, geostrophic balance, salinity, nitrate and dissolved oxygen in surface waters were also examined as upwelling indicators. Upwelling trends were investigated by comparing the results of different datasets. Results highlight the complex interplay of local and large-scale processes that influence the dynamics of coastal upwelling in Northwest Africa. The variability in these coastal upwelling regions was not only influenced by local and remote wind forcing, but also by large-scale climatic drivers such as El Niño Southern Oscillations (ENSO) and Atlantic Niño events. These climatic factors influence the intensity and frequency and duration of upwelling seasons. In the Senegal-Mauritania coastal upwelling, a strong relationship was observed between upwelling and the equatorial ENSO events from late winter to the early spring, with a notable reduction of upwelling intensity after the peak of El Niño in the equatorial Pacific. In the Gulf of Guinea, the summer upwelling intensity was affected by the equatorial Atlantic mode and often decoupled from local wind forcing, providing new insights into alternative upwelling drivers.
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RC1: 'Comment on egusphere-2024-4175', Anonymous Referee #1, 24 Feb 2025
Review of “Characterization of Northwest African coastal Upwelling Systems” by Yamaloula et at.
Summary
In this study the seasonal and interannual variability of upwelling in the Senegal-Mauritania and Gulf of Guinea regions are investigated. Using multiple datasets, the study analyzes different upwelling indices based on multiple variables like SST, wind, and chlorophyll concentration. The study analyzes spatiotemporal dynamics of these systems and their connections to large-scale climatic drivers.
The paper is well-written, presenting interesting analyses that have the potential to offer valuable insights into the Northwest African upwelling systems. However, some aspects of the analyses could be expanded and would benefit from a more thorough discussion, particularly in relation to existing studies. Additionally, I think the novelty of the paper’s findings is not always clear. A more explicit emphasis on what sets this work apart from previous studies would improve its overall contribution. Given these concerns, I recommend major revisions.
Major points
- In the study analyze different upwelling indices. I am missing a discussion about the advantages/disadvantages of using the respective indices. Why do we need different indices to characterize the upwelling? And what dynamics do the different indices represent? This would be also important to clarify in the context of the interannual variability.
- The study presents multiple datasets for the same variables, offering an interesting comparison. However, the discussion of differences between datasets is relatively brief. I suggest either expanding this discussion to better highlight the discrepancies and their implications or selecting the most representative dataset for the main text while moving the expanded dataset comparison and justification to the supplementary material. This would also allow more space for in-depth analysis elsewhere in the manuscript.
- In the analysis of the cumulative upwelling index (Figs. 9–10), the choice of regional separation is unclear to me. Previous studies have identified distinct subregions within these upwelling systems, such as the permanent upwelling in northern SMUS and seasonal upwelling in the south (Wooster et al., 1976; Mittelstaedt 1991; Lathuilière, 2008). Similarly, GGUS consists of two upwelling cells with different governing mechanisms (Wiafe and Nyadjro, 2015; Brandt et al., 2023). I recommend aligning the regional separation with these distinctions. Additionally, introducing these regional differences more thoroughly in the introduction would provide valuable context for the reader.
- In the composite maps (Figs. 11–12), the indication of significant correlations is missing. Without this, it is difficult to assess the reliability of the observed patterns. I recommend adding significance markers to improve interpretability.
- The discussion of interannual variability does not address potential underlying mechanisms. How do large-scale climate drivers influence Northwest African upwelling systems? While analyzing these mechanisms in detail may be beyond the study’s scope, referencing previous studies and discussing relevant processes for the teleconnections would provide valuable context. Additionally, Dakar Niños is not mentioned in the study but should be discussed or at least mentioned in my opinion.
- To strengthen the analysis of large-scale climate influences on upwelling variability, I suggest including time series of the upwelling indices alongside key interannual climate modes (ENSO, Atlantic Niños, Atlantic Meridional Mode, etc.). Lead-lag correlations between upwelling indices and climate indices could provide insights into potential drivers and their temporal relationships. These are just a few ideas you do not have to follow these exact ones. However, I do think including a more thorough view on the temporal evolution of the indices would give a better sense on the temporal variability. I think this could be a great base to deepen the understanding of large-scale influences on Northwest African coastal Upwelling Systems and show long term trends of these systems.
Minor points
- I recommend summarizing the different indices calculated in this study in a table. This would provide a clear overview of which data were used for each index and could also include the definitions of the respective variables for better clarity.
- Line 151: What is meant by drained by local wind? Do you mean driven by wind stress curl?
- Line 170: Maybe I missed it but how do you calculate SSHal and SSHon?
- The contour lines in Fig. 2 are hardly visible. I would suggests improving their visibility.
- Line 215: What do you mean with downwelling? Isn’t it rather a relaxation period?
- Line 232: What is meant with “This highest SST drive the weakening of the surface wind stress pattern”? Do you mean that the SST influences the wind pattern? Can you clarify this? Other studies discuss an influence of advection of warm water by the NECC (Faye et al., 2015). This could be mentioned while discussion this.
- 5a-b & Fig 8. a-b: I do not really understand what is presented here. What surface velocity is this? Is it the alongshore or the cross-shore velocity? And how does the surface velocities contribute to upwelling? There are also studies who describe that the poleward undercurrent or also called the Mauritanian Current surfaces during the relaxation part (e.g. Klenz et al. 2018). How does that relate to your analyses of surface velocities?
- In Fig. 8 a & b there is no geostrophic velocities at 0E. What is the reason for that? And what is the reason for the reversal in the sign of the geostrophic velocities east and west of 0E?
- Line 284: How does the SLA influence the productivity? Are you talking about the effect of CTWs? That section might benefit from some clarification.
- Related to the last point: The study primarily discusses coastal-trapped waves (CTWs) in terms of their role in geostrophic transport. However, CTWs can influence ecosystems through both advection and the deformation of the density field. A brief mention of these mechanism would be great.
- In Fig. 5 and Fig. 6 the oxygen concentration in October is much lower than during the rest of the year. What is the reason for this uniform signal in both Figures?
- Line 340: It is mentioned that the peak of sea surface salinity is driven by upwelling events. How would you explain this connection?
- In the Figure caption of Fig. 9-10 the black arrow and the magenta cross is not explained. However, a red vector is mentioned that I do not see in the figures. I would suggest clarifying the figure captions.
- Line 383: Do you have references for the trend being connected to anthropogenic climate change? There have been several studies who show weakened variability in the equatorial Atlantic (Prigent et al. 2020). Might this be connected to the reduction in the GGUS upwelling?
References
Brandt, Peter, et al. "Physical processes and biological productivity in the upwelling regions of the tropical Atlantic." Ocean science 19.3 (2023): 581-601.
Faye, Saliou, et al. "A model study of the seasonality of sea surface temperature and circulation in the Atlantic North-eastern Tropical Upwelling System." Frontiers in Physics 3 (2015): 76.
Klenz, Thilo, Marcus Dengler, and Peter Brandt. "Seasonal variability of the Mauritania Current and hydrography at 18 N." Journal of Geophysical Research: Oceans 123.11 (2018): 8122-8137.
Lathuiliere, Cyril, Vincent Echevin, and Marina Lévy. "Seasonal and intraseasonal surface chlorophyll‐a variability along the northwest African coast." Journal of Geophysical Research: Oceans 113.C5 (2008).
Mittelstaedt, Ekkehard. "The ocean boundary along the northwest African coast: Circulation and oceanographic properties at the sea surface." Progress in Oceanography 26.4 (1991): 307-355.
Prigent, Arthur, et al. "Weakened SST variability in the tropical Atlantic Ocean since 2000." Climate Dynamics 54.5 (2020): 2731-2744.
Wiafe, George, and Ebenezer S. Nyadjro. "Satellite observations of upwelling in the Gulf of Guinea." IEEE Geoscience and Remote Sensing Letters 12.5 (2015): 1066-1070.
Wooster, Warren S., Andrew Bakun, and Douglas R. McLain. "The seasonal upwelling cycle along the eastern boundary of the North Atlantic." (1976).
Citation: https://doi.org/10.5194/egusphere-2024-4175-RC1 -
RC2: 'Comment on egusphere-2024-4175', Anonymous Referee #2, 24 Mar 2025
This paper compares various indices of coastal upwelling in two different regions of the eastern Atlantic, the Senegalese-Mauritano Upwelling System (SMUS) and the Gulf of Guinea Upwelling System (GGUS). Indices are based on wind stress (coastal divergence and curl) and SST gradient. Other indices are based on surface currents and sea level. These indices are computed from two ocean reanalyses (GLORYS, ORAS5), an atmospheric reanalysis (ERA5), and two SST products with different spatial resolution (OSTIA, Hadl). The authors first study the seasonal variations of upwelling and the latitudinal changes in the two regions. In the second part of the paper they describe the interannual variations using cumulative indices, composite and correlation analyses.
I found the purpose of the paper interesting and the quality of the figures rather good. However the writing is often poor and there are many unclear sections. First, the authors do not seem to fully understand what they are comparing. The wind stress from an ocean reanalysis results from a bulk formulae using a atmospheric forcing (possibly an atmospheric reanalysis) and the ocean model SST as inputs. The ERA5 wind stress results from bulk formulae (possibly different than that used in the ocean reanalysis) using ERA5 atmospheric forcing and observed SST as input. The authors do not explain why they compare these products and what to conclude from the comparison is unclear. Another issue is the use of sea level in the analysis. The authors seem to have understood that cross-shore geostrophic transport impacts coastal upwelling, but they do not compute this index in the paper. Instead they use sea level anomaly, “ocean surface current” (it is unclear if the latter refers to current speed or to a particular component) and a unknown “geostrophic balance” index in the analysis. This makes the paper rather difficult to follow. In the study of interannual variability, they misinterpret their own figures, as El Nino events seem to enhance southward wind off the SMUS but tend to produce warm SST anomalies. Last the discussion of the results is poor, it merely summerizes the findings and does not provide any discussion of the mecanisms at stake to explain some of the differences that have been identified.
To conclude, I also have had to write a very long list of specific minor and not-so-minor comments that the authors need to address. As there is a lot of work to be done to improve the paper, my decision is reject. I encourage the authors to revise their work thoroughly before considering resubmission.
Specific comments:
L18 : « remote wind forcing » can not influence the region. It can influence the ocean remotely and then ocean waves may propagate to the region.
L38 : Bograd et al., 2022 would be a more suited reference here.
Bograd, et al. (2023). Climate change impacts on eastern boundary upwelling systems. Annual Review of Marine Science, 15(1), 303-328.
L46 : using a regional ocean model
L47 : coastline geometry
L49 : Recent upwelling indices take into account the cross-shore geostrophic current which can enhance or reduce coastal upwelling (see Jacox,et al. (2018). Coastal upwelling revisited: Ekman, Bakun, and improved upwelling indices for the U.S. West Coast. Journal of Geophysical Research: Oceans, 123, 7332–7350. https://doi.org/ 10.1029/2018JC014187). This needs to be accounted for in this study.
L52 : these are physical, not biophysical processes
L53 you mean « eastward propagation of equatorial Kelvin waves » and « poleward propagation of coastal trapped waves » ?
L61 : what do you mean by « coastal variability » ?
L66 : where does this influence take place more specifically ?
L68 : Using a regional model
L69 : « .. highlighted the Guinea current » : not clear what is meant here. Can you elaborate a little ?
L73-81 : I find this paragraph not really useful as the paper focuses on the past period. It could be useful if Bakun’s alleged dynamical processes driving upwelling variability were mentioned but it is not the case.
L86 : what remote forcing ? You mean equatorial Kelvin waves ? This is unclear.
L88-89 : the goals of the study need to be described more precisely in the introduction.
L94 : Refer to the spatial resolutions of ORAS5 and GLORYS in the Table here.
L105 : Should be Table « 1 ». GLORYS does not deliver oxygen and nitrate, there must be another product with another spatial resolution.
L127 : « corresponds also to the ... »
L129 : UI needs to be defined.
L130 : not clear what you mean here.
L153 : not clear what you mean by « drained by the local wind » : if there is no coast, there is no divergence of the Ekman current and no upwelling. Do you mean « by the wind stress curl » ?
L168 : you must mention this process before (see my comment line 49).
L174 : I do not understand the definition of Tg : to compute the onshore geostrophic transport, you must compute the gradient of sea level in the direction parallel to the coast. What are SSHal and SSHon ?
L176 : nitrate
L179 : before CUI can be defined, a clear definition of UI is needed somewhere.
L182-188 : a schematic is needed to explain how the indices are defined.
L190 : it should be an integral, not a sum ? What is the temporal resolution ?
L194 : « based on the gradient descent fit » , « Pettitt statistical test »: references are needed
L196 : a word is missing here.
L201 : analysing
Figure 2 : what are ORAS5 and GLORYS wind stress fields ? ORAS5 and GLORYS are ocean reanalyses, meaning that wind products or reanalyses were used to compuate wind stress and force the ocean surface. These winds are possibly from era5, jra-55 or another reanalysis. This should be clearly explained in the methodology section.
I am puzzled by Figure 2 because coastal upwelling is negative (upward) in Fig 2a-c .However you mention earlier that Tg is negative eastward, which can not be the case because an eastward (negative) Tg produces a (negative) downwelling at the coast. I think that upwelling should always be positive as a convention. I also find it very confusing to have a different sign convention for coastal upwelling and wind stress curl upwelling. This needs to be changed.
Last, it would be nice to relax the saturation of the colorbar for positive values to see if there is coastal downwelling during some time periods.
L214 : the start of the upwelling seasons depends on latitude, so what is the latitude here ?
L214-216 : this is not easy to see this in Figure 2 and 3. Another figure should be shown.
L225 : What about the geostrophic transport Tg ? It does not seem to be taken into account in this analysis. It should be added (or at least compared) to the zonal Ekman transport (with the correct sign).
L127 : why is the maximum SST gradient observed before the maximum Ekman transport ?
L232 : « the highest SST drive... » : unclear, I do not understand what you mean ? The SST forces the wind patterns ? This should be demonstrated.
Figure 3 : several issued with this figure : the « THETAO » (e) label is awkward : GLORYS is an ocean reanalysis, same as ORAS5, so the title should be GLORYS ; in a-e, the color scale indicates SST where ? In the coastal box ?; the definition of the green line is strange : you mean during the month of minimum SST ? « Minimum SST » where ?; I do not see the point of the orange line and its link with upwelling as it lies south of the upwelling region.
L242-243 : I don’t see how you reach that conclusion as these are 3 different estimates of wind stress and we do not know which one is closest to reality.
L244 : « the good SST index... » : OSTIA and Hadl provide the observed SST indexes, not the good ones. How is the Hadl index poor ? You can just hypothesize that the OSTIA index is better because this product is more precise near the coast.
L246 : this is getting more and more confusing : ERA5 is not an SST dataset, it is an atmospheric reanalysis which is forced by an SST product (possibly OSTIA , to be checked). This needs to be clarified. Apparently the authors do not known well enough what they are comparing.
L247 : what are the wind forcing used to force ORAS5 and GLORYS ? This needs to be added in the table.
L248-249 : « The maximum magnitude.. » of what ?
Figure 4 : why didn’t you sum Ekman divergence (Mx), wind stress curl upwelling and Tg ? Just looking at Ekman transport does not make sense. What is SLA ? Is it Tg ? This is getting more and more confusing.
L260 : « geostrophic ... » : which figure are you refering to ? In Figure 4 SLA is shown, not geostrophic current. This is difficult to follow.
L262 : « positive WSCD generally enhance upwelling » : no, they contribute positively to upwelling, which is the sum of coastal upwelling (divergence of Ekman transport) and wind stress curl upwelling which occurs offshore. The rest of the sentence («negative WSCD ..suppress coastal upwelling ») should therefore be clarified.
Figure 5 : Legend is unclear : what is « ocean velocity » ? zonal, meridional, total ? What is « geostrophic balance” ? You mean geostrophic transport ? It is not the ocean velocity that matters for coastal upwelling but the surface cross-shore geostrophic velocity. Apparently the authors used ORAS5 and GLORYS surface velocity, which is useless.
What are the isolines in figure (e) ?
L273-274 : these two lines are meaningless.
L274 : what is the « Rossby circulation » ?
L284 : correlation does not indicate causality : how would SLA influence productivity ? I do not believe it is the case, or it needs to be better explained.
L295 : you mean « meridional SST gradient » ?
L295 : « the upwelling waters were estimated... » : not clear what this means. Rephrase. What is the justification for this SST threshold?
L300 : « integrating...” in time and space? Otherwise, what is the longitude refered to here? This figure is not shown.
Figure 7: repetition of text in legend.
L302-303: this is the maximum magnitude of the integrated transport or the maximum in time and space?
Line 306 and Fig.8: as for Fig. 5, I do not understand what is plotted when geostrophic balance is mentioned. Moreover, surface velocity is different from meridional geostrophic velocity, which may impact the GGUS coastal upwelling. It is impossible to interpret Figure 8a,b.
Line 306: “ocean velocity (contours)”
L320: Fig. 7 must be Fig.6 here. Keep in mind that ERA5 is not an ocean reanalysis, its wind stress is computed using a particular bulk formulae and a particular SST product (possibly OSTIA, to be verified). In the case of ocean reanalyses, wind stress is computed using using bulk formulae and the ocean model SST. Thus the wind stress differences in the different products may originate from the SST products and differences in bulk formulae. This should be discussed.
L321: I do not really see the point in using Hadl product since it is obvious that this product is not adapted for the upwelling index due to its coarse spatial resolution. It could be suppressed from the study to shorten the paper.
L327: “This indicates ...”: I strongly disagree. Correlation is not causality.
L328: I do not see two cells in Fig.7f-j., just one.
L330: What do you mean by “the western cell is linked to the SLA”: what is the mechanism? Does the geostrophic current driven by a SSH gradient play a role?
L330-332: Citing papers is not sufficient, how Kelvin waves and CTW drive this upwelling needs to be explained.
Figure 8: it would help to represent Figure 8 with the horizontal axis for longitude and vertical axis for time.
L347: “the maximum concentration of Chlorophyll ...”: not at all. Oxygen concentration does not drive chlorophyll concentration. I think the figures and text about the Chl, Nitrate, Oxygen and surface salinity should be suppressed, they do not bring any useful information to the paper.
Figure 9: which wind stress and SST product are used here?
L370-372: what was used for the upwelling indices in the linear regression? The cumulative index? The maximum for each year? This lacks details and makes it very difficult to follow.
L382-383: “This decreasing trend...”: you can not prove that this is linked to anthropogenic climate change with this analysis, this could also be decadal variability.
L400: A table should be added to list the climate events used to compute the composite with time periods, SST anomalies in the Pacific, Atlantic, SMUS and GGUS. The SST product used to compute the composite is not indicated.
Figure 11: I do not see the point in showing the global ocean in this figure. You could show only the Atlantic and Pacific ocean between 30°S-30°N, thus it would be easier to visualize the SST and wind stress anomalies in the SMUS and in the GGUS (it is impossible to see anything about the GGUS in the present figure).
Figure 11: how do you know that the composite is significant? A statistical test is needed.
L402-403: “extremely warm SST anomalies”: 0.6°C is not extreme in my opinion. I think the arrows indicate that coastal upwelling in the south part of (entire) SMUS is enhanced in DJF (MAM) , but the SST increases. Coastal upwelling does not explain this SST increase, apparently.
L405: References are needed here, since the authors have not shown any of this.
L407-408: I can not see the positive anomalies in the Gulf of Guinea druing La Nina events.
Figure 12: same comment as for Figure 11: only the regions of interest (Equatorial Pacific, tropical Atlantic) should be shown.
L425: how was the correlation computed? What was the time series used? Over which time period?
L430: I think the authors misinterpreted the result of the correlation: the correlation between El Nino index and meridional wind stress off the SMUS is negative, meaning that when the El Nino index is high (strong El Nino conditions), the meridional wind stress anomaly is negative (southward) thus enhances coastal upwelling in the SMUS. This can also be seen in Figs 11a,c, wind stress anomalies appear to be southward in SMUS.
L452: how mesoscale variability impacts upwelling needs to be explained in the discussion.
L453: “weak upwelling trend..”: positive or negative?
L455: I think this needs to be refined, the trends are different in the north and south of the SMUS and this line is not consistent with Sylla et al. (2019) findings.
L470: I disagree with the statement. The wind-driven upwelling increases and the SST is warmer, meaning that another process explains the surface warming.
Citation: https://doi.org/10.5194/egusphere-2024-4175-RC2
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