3.1. Comparison of Near Coastal Satellite Salinity Data with In-Situ Data
The CCI + SSS satellite SSS retrievals used here have been globally validated and their accuracy was stated to be better than 0.15 in most areas [
25]. However, uncertainties in the satellite-derived salinity data remain high near coastlines due to land contamination of the signal there [
24].
In
Figure 1, the CCI + SSS salinity data are compared with in situ salinity measurements. To this end pairs of data collected from both datasets were identified in 0.5° × 0.5° grid boxes over the study region, considering only data within a temporal time window of one week. As can be expected, maximum salinity differences between both datasets were found near the Congo River mouth, where the differences exceeded 1 in magnitude (
Figure 1a). Apart from the enhanced near-coast SSS errors mentioned above, differences can result from a physical mechanism, such as vertical salinity gradients off the river mouth. Satellite data represent the top centimeter of the water column, whereas in situ data are measured in 2 to 5 m depth of the water column. Moreover, the satellite-derived SSS maps represent space–time averages, whereas the in situ data are punctual measurements in space and time. We note that the Nansen data used for this coastal validation are truly independent, as these data were not used for the bias-correction process of the satellite-derived SSS data.
The root mean square differences (RMSD, shown in
Figure 1b) are high in the region of the Congo River plume and the GG, but decline toward the open ocean, and especially toward the south, where the RMSD does not exceed 0.5. Lines of constant SSS variability (STD) are overlayed as black contour lines in
Figure 1b. It can be seen that high SSS variability coincided with the area of high RMSD. In contrast, in the region south of 15° S, mean differences and RMSD values were lower. RMSD values were enhanced in the months from February to April and October (not shown), when the plume was present. The authors of [
16] attribute the higher RMSD during periods of low SSS to the inadequate sampling of the in situ measurements to capture the run-off-induced freshwater plume associated with stronger spatial and temporal variability following the high-discharge season. We conclude that the differences in in situ salinity are mainly due to the differences in sampling and vertical salinity gradients, but that, in general, CCI + SSS are trustworthy in the near-coastal areas.
3.2. Annual and Semi-Annual Salinity Variability
In this section, we summarize the main features of the seasonal salinity variability in comparison to its potential drivers. The amplitude of the annual and semiannual cycle, and phase of the salinity minimum in the CCI + SSS over the GG, are shown in
Figure 2. The lowest salinity occurred between November and March in the equatorial and south-equatorial regions off the tropical western African coast, mainly due to the river discharge, mainly from the Niger River located at 3° N into the eastern GG and the Congo River at 6.2° S. Enhanced tropical precipitation also contributed to the salinity minimum during this period. While the maximum discharge of the Niger River and the rivers in Cameroon and Gabon, as well as maximum precipitation, occurred in October [
11,
32], the maximum discharge of the Congo River (as measured at a station in Kinshasa) occurred in December. It is assumed that the phase shift in SSS, shown in
Figure 2b relative to the maximum freshwater sources, resulted from the fact that the drainage areas on the African continent are influenced by the seasonal march of the Intertropical Convergence Zone (ITCZ); nevertheless the authors of [
32] claimed that this ITCZ paradigm does not explain the seasonal cycle in this region, while other processes such as Madden Julian Oscillation and Indian Monsoon influence the variability in the equatorial, western African region. According to the authors of [
33] and [
10], precipitation at 6° S over the ocean is not of any relevance to the seasonal decrease in ocean salinity; instead, the CRD alone suffices to explain the observed SSS structure and variability. The observed spreading of the associated low-salinity plume across the eastern South Atlantic takes some weeks, meaning that time of minimum salinity propagates from November southward along the coast of the GG, reaching 15° S latitude in April/May. The Congo River freshwater plume also extends zonally along 6° S, showing minimum SSS near the coast in December and January, and at about 4° W in June/July.
Usually, high SSS and high nutrient levels correlate in areas of upwelling (off the Guinea and Namibian coasts and along the equator). In contrast, the correlation between the SSS and NPP anomalies is clearly negative but large in magnitude in the area off the Congo River mouth (
Figure 2c), due to the high nutrient riverine input associated with the freshwater inflow there. (Only significant values are plotted, using t-statistics and assuming a normal distribution.) The climatological time series of the two parameters also yields a high negative correlation off the Congo River mouth (not shown). In the open ocean south of the Angola Benguela Front, the NPP is generally low, and the correlation is negative, i.e., highest NPP occurs in the months of low SSS, which are from October to December (
Figure 2b). The area with a slightly positive correlation between the SSS anomaly and NPP anomaly may be a signal of the upwelling in the Angola dome (12° S/5° W to 18° S/6° E).
The large size of the Congo Basin beneath the migrating tropical rain belt produces flood waves on the various tributaries that reach the Congo River with different phases [
34], thereby modulating the variability of the CRD.
Figure 3 shows the respective time series of the CRD between 1980 and 2020 at Kinshasa/Brazzaville, showing a clear annual cycle and a small semiannual component. Maximum CRD occurs, on average, early in December, with an std of 9 days; the minimum occurs late in July with an std of 16 days. The maximum river discharge is 5.7·10
4 m
3/s and the minimum amounts to 2.82·10
4 m
3/s, with an interannual std of only 10 % (i.e., 0.55·10
4 m
3/s and 0.32·10
4 m
3/s, respectively) for these extreme daily river discharges. The annual mean and std of the total CRD are 3.94·10
4 m
3/s and 0.9·10
4 m
3/s, respectively; the interannual component comprises about 22% of the total variability. Assuming an average downstream flow speed of 0.1 m/s from Kinshasa/Brazzaville to the 400 km downstream river mouth at the Atlantic coast, the maximum discharge into the Atlantic Ocean occurs in January, the minimum during mid-August. Deriving a detailed arrival date of the maximum fresh-water discharge from the SSS time series is difficult, because the SSS near the Congo River mouth is continuously low, and the satellite SSS field is only spatially resolved on scales of 50 km, and temporarily resolved for 10 days. Furthermore, the SSS is also dependent on advection and mixing, as well as on the amount of river discharge. Most of the ocean salinity minimum spreads to the west; however, it partially also spreads southward, as revealed here for the first time by the southward progressing coastal SSS minimum.
We note that the average river discharge of about 4·10
4 m
3/s, as calculated here, is about 10% smaller than that provided by Reference [
35], a commonly used river discharge dataset. However, their discharge data represent the period from 1948 to 2000, whereas the present study uses data from 1980 to 2020. Whether this decrease is due to differing precipitation amounts or patterns or due to the different water use in the huge river catchment area over the decades is not a subject of the present study. The authors of [
34] state that the anthropogenic influence on the hydrology of the River Congo is small; nevertheless the authors of [
36] recently showed a decrease in precipitation until 2017; subsequently, precipitation in late 2019 was exceptionally high, resulting in the highest CRD since 1980.
Figure 3b shows an expansion of the CRD time series for the period 2010–2020, over which the satellite SSS data are available. The SSS, zonally averaged across a 150-km distance along the coast (
Figure 3c), shows a similar annual cycle corresponding to the evolution of the CRD, with a minimum salinity between 5° S and 10° S at the beginning of the year and a secondary but weaker minimum in October at these latitudes (the Congo River mouth is at 6.2° S). Another SSS minimum in the GG (north of the equator) occurs about 2 months earlier, according to the earlier maximum river discharge due to the earlier phase of rainfall. A secondary north equatorial salinity minimum is evident in April, in phase with the secondary minimum off the Angolan coast. The correlation between CRD and the salinity minimum off the Congo River mouth, averaged in the area 100 km of either side of the coast at 6.2° S (not shown), is significant but weak, at only R = −0.28. The low correlation is due to the high salinity variability of >1 and presumably due to the influence of mixing and advection.
As can be inferred from the slanted isohalines in
Figure 3c, the salinity minimum propagates southward along the coast south of 6°S, presumably by advection. The authors of [
37] reported a respective surface current along the coast from February to April and in October. This surface current is a consistent pattern of semiannual circulation initiated by the dynamics of the equatorial circulation, provoking the semiannual occurrence of Kelvin wave propagating as Coastal Trapped Waves (CTW) along the northern and southern African coast. The variability in the coastal current (AC) off Angola and Namibia is partly controlled by the passage of these CTW [
37,
38]. During Benguela Niños, the AC advects warm tropical waters poleward into the northern Benguela region, impacting the marine ecosystem but also rainfall anomalies [
39,
40,
41].
As surface velocities are difficult to derive from moorings and ship-borne observations, subsurface current information is mainly available from in situ measurements. The authors of [
42] inferred an associated mean southward transport near the shelf break at 11° S of only 0.32 Sv (1 Sv
10
6 m
3s
−1) from the moored time series available across the shelf and continental slope, which is lower than that estimated by synoptic measurements in older studies. The geostrophic currents derived from the SLA (the Oscar data) have uncertainties near to the coast due to aliasing problems. These data are used here for comparison with the estimates of surface current velocities deduced from the southward spreading of the low-salinity tongue along the Angolan coast. The salinity minimum is used as a tracer, which is considered quasi-conservative during the time in which it is advected southward. Mixing by lateral diffusion and vertical processes is assumed to be slow in comparison to the advection, because the flow is concentrated in the shelf region. Moreover, wind speed is very low, especially in October and February; therefore, wind stress is of minor relevance. Furthermore, the surface mixed layer is sharply separated by a strong vertical density gradient, and the atmospheric freshwater surface flux during these months is very small, and does not lead to any considerable alteration in salinity. With these assumptions, the progress of the low-salinity front can be inferred from the Hovmöller diagram from
Figure 3c. Single events of the southward spreading are used to estimate the mean velocity over the weeks.
The southward spreading of low-salinity surface waters from the Congo River plume usually occurred from around March to April, and again during October and November (
Figure 4). The chlorophyll content of the surface water along the coast was also elevated during these months, corroborating a fluvial origin and causing a high net primary production (not shown).
Figure 4 shows the respective yearly evolution of velocity and SSS along the African coast: two dominant periods of geostrophic southward flow (
Figure 4a) and low SSS (
Figure 4b, contours) can be identified from January to April and from September to November. These periods are associated with the southward advection of warm water and high sea-level anomaly (SLA, not shown), corresponding to phases of downwelling [
23]. The strongest upwelling, though weak at the latitudes off Angola, and northward flow, occurred between May and August, here associated with a high SSS of up to 36. The variability in the meridional flow is plotted as color shading in
Figure 4a and shows the highest variability in the onset of the southward flow over the years. Three patches of high std(V) > 5 cm s
−1 in southward flow can be seen in mid-January, the end of February and in April, indicating stronger variability due to coastal trapped waves, which influence the southward flow poleward to 15° S. These periods of high velocity variability are associated with high salinity variability (
Figure 4b). From September to December, the variability was not as high as in the first months of the year; however, mean southward flow in October reached at least 12° S. The mean low salinity (SSS < 35) derived from the satellite data was advected to at least 13° S in both periods and high values of variability with std(SSS) > 0.8 reached southward to 15° S (
Figure 4b). The CRD was at a maximum in January and minimum in August at the river mouth (
Figure 4c), and was the cause of the high salinity variability advected along the coast.
3.3. Interannual Variability of the Alongshore, Southward Spreading
The in situ data from the Nansen cruises confirm the low-salinity water in the upper surface layer, spreading southward along the coast. The authors of [
42] showed that very low surface salinity occurs along 11°S in February and March, and again in October. We extend this description to the occurrence of the low-salinity layer along the coast throughout the years based on the same in situ data; to this end
Figure 5a,b show monthly and zonal averages of the sections within a coastal distance of 150 km. The calendar date of each section varies through the years; most cruises took place around February and in August (
Figure 5d) to catch the main down- and upwelling seasons; however, from October to December, no Nansen cruise took place at all [
23]. The velocity contour of −5 cm/s extracted from the Oscar velocity dataset, zonally averaged in a 100 km band off the African coast, is superimposed onto the salinity averaged in the upper 10 m (
Figure 5a). The figure reveals that the cruises did not always catch the southward flow that eventually began in January, because the cruise took place one or two months later (e.g., in 2004 and 2005) and thus did not measure the very low salinity. A rapid decline in the low salinity is evident in cases when the sections were repeated some weeks later, e.g., in 2006 and 2009. Usually, the cruises in February and March showed patterns of low salinity with a varying southward extent, e.g., in 2001 it reached a latitude of 17° S and, in most cases, 13° S. Unfortunately, the cruises show gaps in measurements south of 13° S so that the exact maximum southward reach cannot always be determined from the present data set.
Figure 5b shows the continuation of
Figure 5a into the decade of the satellite-derived SSS, with an overlapping time-period of from 2010 to 2014. The blue shading of low SSS corresponds to the low in situ salinity and is associated with poleward meridional velocity from January to April or from October/November of each year.
Figure 5c, finally, shows a mean salinity section along the coast in the first months (January to April ) of the years from 1995 to 2014 from the in situ data.
To check the frequency of the occurrence of the southward coastal current at the surface, the Oscar velocities were examined. Although the near coastal velocities derived from geostrophy are highly uncertain, they were found to correspond quite well to the advection of the low-salinity water from the Congo River. However, the correspondence between the negative salinity anomaly and the southward flow is not significant.
Figure 6 shows the coastal salinity anomaly averaged between 6° S and 9° S, together with the CRD, the sea-level anomaly (SLA) and the meridional velocity (V), all averaged between 6° S and 10° S. V and SLA were band-pass filtered in the band of the coastal trapped waves from 20 to 130 days [
5] to highlight the role of the intraseasonal variability. The southward flow is usually associated with the high SLA, at least in the first 3 months of the year and in Oct/November. For a strong negative propagating coastal salinity anomaly to occur (2016 and 2018) it seems to be necessary that several circumstances coincide: a strong CRD in the preceding December, which was not the case in 2011, 2013, 2014, or 2017. The southward flow modulated by the occurrence of a CTW has to be in time to advect the relative freshwater of riverine origin, which was not the case in 2012, though there was a strong southward flow later that year and a strong CRD. In 2014, there was a southward flow on time, but a weaker CRD. The year of 2015 had a considerable CRD, a southward flow on time, and, thus, a weak negative salinity anomaly. In 2016, the strong CRD was some days later than usual, and a strong southward flow was able to advect the low-salinity water southward. The strongest CRD in the last 40 years occurred at the end of 2019 due to anomalous high precipitation in the Congo Basin over the African continent. However, the negative salinity anomaly was not advected southward; instead, it spread into the western direction, as will be presented in the following.
The secondary negative salinity anomaly in October was weaker; however, a southward flow usually also occurs in that month, advecting the low-salinity water southward (compare with
Figure 4). The period from 2011 to 2013 shows a very small CRD during the austral winter, weakening the salinity signal along the coast despite the potential advection by the southward flow. In late 2019, the negative salinity anomaly was stronger than in the years before, associated with a strong southward flow and a strong positive SLA, indicative of an anomalously warm season. After the work in Reference [
43], there was a pronounced relationship between the meridional transport in the AC and the negative WSC on a seasonal time scale in the northern BUS. We only found a negative WSC anomaly in the coastal region off the Angolan coast in 2016 and 2018 (not shown), explaining the stronger southward Angola Current. However, a southward flow also existed in other years, without a negative WSC anomaly.
To explain the existence of interannual anomalies of the Congo River freshwater plume (either to the west or the south) the precipitation, the CRD and the advection were inspected concerning their interannual variability: the CRD was found to exert the strongest contribution of the freshwater forcing in the study area. The seasonal evolution of the run-off correlates well with the seasonal occurrence of the freshwater plume (
Figure 3). The authors of [
10] attributed 50% of the decrease in salinity in a box off the Congo River mouth to the river runoff, which we can confirm. The interannual variability of local precipitation was analyzed here to rule out potential causes of a negative SSS anomaly due to anomalous strong precipitation. In the area off the Congo River mouth, a box between 10° S and 4° S, 5° E to the coast, we averaged the amount of precipitation from various datasets and computed the seasonal anomalies. The area receives precipitation in December to May, with the strongest rainfall usually occurring during March/April. The IMERG data showed a stronger precipitation than GPCP or Persiann data, with differences that may have also resulted from the differing spatial resolution. The monthly anomalies reflect the intermittency of stronger rainfall in weekly timescales. However, the maxima of unusually high precipitation was 250 mm per month (not shown). Using a gross estimation of the influence of 0.25 m freshwater on a column of a mixed layer with a depth of 15 m and a mixed-layer salinity of 34.5, the strongest potential decrease in salinity per month due to its precipitation was 0.23, which was too low for the precipitation to be responsible for the strong salinity anomaly.
The authors of [
10] showed that the advection’s contribution to the climatological salinity budget is subject to high uncertainties. Their arbitrary choice of the velocity dataset did not explain the reason for this uncertainty. However, it is impossible to establish the salinity budget in the box, due to the lack of available in situ data. Therefore, the authors of [
10] used a climatological setting to establish at least a gross estimate of the processes. The depth of the mixed-layer and the vertical processes are unknown, to close the budget. We limited our study of the processes leading to the change in salinity in a box, similar to the one chosen by [
10], to the terms of advection motivated by
Figure 6, which shows the strong interannual variability of the low-salinity plume and the alongshore currents. The mixed-layer salinity change in a box can be calculated following Reference [
10], with:
Here,
S is the salinity of the mixed layer and is assumed to be equal to the satellite-derived surface salinity.
SH is the salinity at the mixed-layer depth
H. In the absence of sufficient profile data to calculate the mixed-layer depth in each month, the mean mixed-layer of the available data in the box of
H = 16 m was used. We extracted the mean salinity at the depth of the mixed layer from the objectively analyzed EN4 dataset for each month. E is the mean evaporation, P the mean precipitation of the box and R the CRD averaged for the box. The
Residuals contain all physical processes, e.g., the vertical and horizontal diffusion, and other vertical processes, which we will not address. We derived the vertical velocity
W at the base of the mixed layer from the continuity equation, using the Oscar velocities representative of the velocity in the mixed layer, i.e.,
Only upward (entraining) velocities were used because a downward velocity would not contribute to a change in the mixed-layer salinity. We are aware of this budget being a very crude estimate; however, the aim here is not to close the budget, but to show the variability of the advection terms. The present exercise can be considered as an extension of the study of Reference [
10]. We separated the velocity and SSS data into low- and a high-frequency parts by low-pass filtering the data with a ninety-days Hamming window:
, with the overbar presenting the low-passed velocity and salinity, and the prime presenting the high-frequency component. We noted that the terms
and
are very small; only the terms
and
contributed to the advection term.
The advection term plays the dominant role in the budget, and the interannual variability is considerable. The external surface fluxes, precipitation and river runoff show a quite regular seasonally varying influence; however, the contribution of the CRD was highest at the end of 2016 and 2019, and lowest at the end of 2017. We noted that the precipitation was not as small as Berger et al. suggested; we found a contribution of up to 50% of the freshwater supply into the box considered in the precipitation months. The OAflux evaporation data were recalculated for recent years; we note that there is a stronger seasonal cycle after 2016 than before 2016; however, this was smaller than the seasonal cycle of precipitation. The CRD had its maximum in December, while the precipitation reached its maximum in January/February; therefore, both provided freshwater to the box from October to March.
Figure 7 shows the calculated terms during the decade of satellite salinity data. The salinity tendency is shown with the black curve, with a negative tendency in the months from September to February, caused by the surface fluxes and compensated by strong advection. The salinity tendency shows a strong peak in April. This maximum cannot be explained by the considered processes; neither horizontal advection nor mean vertical advection can explain this increase in salinity. The residuals in Reference [
10] are at their maximum in the months from April to June, showing that, using observational data, we miss the main processes involved, which we presume to be the vertical processes during the upwelling season. Our crude estimate of the vertical advection is maximum in the month of April, especially in 2011, but we were not able to capture the processes that reestablish the high subtropical salinity.
3.4. Interannual Variability of SSS and NPP Anomalies
The interannually varying extent of the Congo River plume is best identified during the months from January to April following the maximum discharge in December. To this end, we show 8 the deviations in SSS from the long-term mean in
Figure 8. The seasonal SSS anomalies used above reveal strong positive anomalies due to temporal and spatial variability, e.g., a year with a strong southward extent of a fresh anomaly in February would lead to a positive anomaly in February of other years. Positive seasonal SSS anomalies are misleading, because the regional SSS is not strongly increasing, but only decreasing less. The negative SSS deviations from the long-term mean (blue color in
Figure 8) are able to describe the spreading of the Congo River plume.
Figure 8 reveals two main directions of spreading: the westward, mostly along 6° S, and the coastal southward extension. A low-salinity tongue also occurs along the equator and 3° S; this might be associated with the advection of equatorial low-salinity water, which is sometimes very separated from the low-salinity Congo plume (in 2014, 2015 and 2018), and sometimes merges not only with the CRD plume but also with the low-salinity waters in the GG. The low-salinity plume of the Congo is associated with NPP-positive anomalies (presented as contour lines in
Figure 8), confirming its riverine origin. The spreading eventually only happens towards the west (in 2012, 2014 and 2017); in other years the plume is first advected southward along the coast and then veers westward (in 2011, 2016 and 2019), and follows both directions in 2015 and 2018. A fulminate spilling occurred all over the region in 2020 due to the exceptionally high CRD, caused by the strong precipitation at the end of 2019. The river plume seems to also partially extend to the north and joins the river runoff of the Ogooue from Gabun and the low-salinity water near the equator. Clear positive NPP anomalies also spread offshore the Angolan coast during the secondary maximum of CRD from October to November of the years 2014, 2015, 2017 and 2018, whereas, in the years 2010, 2016 and 2019, clear negative NPP anomalies occurred in the offshore region (not shown).
The black contours in
Figure 8 show the occurrence of a positive SST anomaly (only SST anomalies exceeding 1°C are shown), revealing the Atlantic or Benguela Niños in 2011 and 2016. Benguela Niños are defined by SST anomalies exceeding the STD(SST) in the area off the Angolan coast over 3 months [
44]. Therefore, the weak anomaly in 2018 is not considered a Benguela Niño. Benguela Niños mainly occur in the downwelling season from January to April [
45], although they may also occur in October/November. There was a Benguela Niño from October to December 2019 (not shown in this Figure, but analyzed in Reference [
46]). Positive NPP anomalies are associated with the negative SSS anomalies; however, we cannot associate specific patterns of the plume extent with the Benguela Niños. We merely state that there is stronger coastal poleward flow in the spring months of 2016 and 2011, which are both associated with the spread of the low-salinity water; however, the poleward flow in 2015 and 2018 is associated with a very weak advection of low-salinity water in 2015, and no positive temperature anomaly, and only a weak positive SST anomaly in 2018. The positive NPP anomalies in 2011, 2015, 2016 and 2018 do not survive into the following upwelling months of July and August; in contrast, the NPPs in the July and August of 2011, 2015, 2016 and 2018 were anomalously weak.
3.5. Hydrographical Consequences
The layer of low-salinity and high-temperature spilling from the Congo River mouth and spreading in the eastern tropical Atlantic is assumed to change the regional hydrography, i.e., influence the depth of the mixed layer and the stability of the water column, with consequences for the heat budget and mixing and entrainment from below. These processes are very difficult to observe and can only be deduced from enough in situ profiles. Some studies dealing with the freshwater budget have already been mentioned, e.g., Reference [
10]: they show that, in this coastal region, the contributions of mixing and entrainment cannot be accessed by the available in situ data. Indications of high stability due to the freshwater layering are given by the Brunt–Väisälä frequency
N2, with
(
ρ being density and
g the gravity acceleration). The in situ profiles of the Nansen cruises and all Argo profiles in the region were used to investigate the seasonal development of the water-column stability. Along the African coast, the Nansen expeditions provide a high data density, so the influence along the southward spreading of the river plume can be shown (
Figure 9): The stability is higher, i.e., the
N2 values were higher in the average March than in August, when taking all years of available data into account. The black contours in
Figure 9 show the same isopycnals in March (upper panel) and August (lower panel) and reveal the upwelling along the coast between 6° S and 10° S; further south, the upwelling phases seem to be very variable. An indication of the presence of upwelling can be seen in the
N2 maximum, which was slightly shallower in August than in March. The high potential available energy, due to the salinity stratification, can be illustrated by comparison with profiles with a constant salinity in the upper layer, which is relevant for the internal waves [
22].
The relation between the maximum
N2 and the low salinity at the surface is shown in
Figure 9, right panel. The significant and clear relationship underlines the effect of the low-salinity plume on increasing the stability of the water column.
The plume distribution strongly varied over the years, so that it was difficult to obtain enough profile data for a section in the open ocean. Instead, the development of the stratification is shown along the trajectory of an exemplary, selected Argo profiler. In
Figure 10, the salinity along the trajectory of an exemplary Argo profiler is shown, with the mixed-layer depth derived from the density (ML
r, blue) and temperature (ML
t, black) profile. The difference between both is the barrier layer (BL = ML
t − ML
r). Periods of low salinity (other than red) due to the Congo River plume are associated with the occurrence of a barrier layer; however, this only occurs eventually and is only thin (up to 10 m). Eventually, the BL becomes thicker, as in October 2015. The stratification becomes sharper with the low-salinity layer on top, and
N2 increases. It is notably higher in March than in October, confirming the result of
Figure 9. However, the existence of a higher BL can neither be clearly related to lower SSS nor to a stronger stratification (
N2 maximum).
Figure 11 shows the positions of all Argo profilers in the months from January to April in each year, as indicated by the grey dots. Interestingly, the profilers hardly exit the region, i.e., the ocean velocity at the drifting depth of 1000 m is very small. Drift presumably occurs presumably in the upper layers. This behavior allows the evolution of the hydrography during the spreading of the plume to be observed (indicated by the blue contour lines, corresponding to the blue anomalies in
Figure 8). Some cases of a barrier layer were found in the presence of the low-salinity plume, also evolving near to the plume. With the Nansen dataset near to the coast, many BL cases were detected. However, a thick BL of more than 6 m off the coast is rarely found and cannot always be associated with the presence of the low-salinity layer. Moreover, the hypothesis of the existence of a strong BL during the anomalously warm episodes in the case of a Benguela Niño, e.g., in 2011 or 2016, cannot be proven. There were some Argo profiles in these 2 years, but a BL thicker than 6 m was found only sporadically. The north- and eastward advection of the subsurface-salinity maximum (South Atlantic Central Water) in July/August, below the relatively low salinity on top, may also lead to the formation of a BL. A systematic approach to the existence of the BL associated with the low-salinity plume is not possible, due to the sparse measurements.
We conclude that the development of a barrier layer may influence the heat budget, as hypothesized in [
3]; however, the events are rare and observations are difficult and based on hazard, so this cannot be quantified or proven. The strength of the river plume impact on the potential BL thickness is also dependent on the direction of the precipitation–evaporation flux, rather than on the strength of the river flow [
46].
The Angola current carrying the equatorial warm water poleward along the southwestern African coast results in less cooling and even stronger heating due to the top fresh layer. All available profiles in the study region were examined relative to the modification to the stratification of the water column and, e.g., the existence and thickness of a barrier layer. There is evidence from the available in situ profiles that a barrier layer occasionally exists; however, the geographical distribution shows a minimum number of profiles with barrier layers in the latitudinal range of the Congo river’s freshwater plume. The existence of a barrier layer is not associated with a negative salinity anomaly (4% of the profile show a BL and a negative salinity anomaly; however, 4 % also show a positive salinity anomaly), or a positive temperature anomaly. However, it is more likely for barrier layers to occur in the plume area of low salinity in March and April than in other months of the year. This result depends on the distribution of the CTD profiles in the area, which itself is dependent on the season. The Nansen CTD sections were predominantly carried out from February to April, and June to August, seldom carried out in May or October and never carried out from November to January, so the annual cycle was not completely covered.
In summary, the evidence of the barrier layer occurrence due to the low-salinity water of the Congo River plume could not be proven; however, it also could not be excluded. This is mostly due to the lack of data. The mixed layer is very thin, and the barrier layer that was found is very thin, too. Profiles with a BL showed thicknesses from 1 to 3 m, and rarely exceeded 10 m, which can only be assessed with a high-vertical-resolution that has only become available in recent years.