The Guinea Coast is the southern part of the West African continent. Its summer rainfall variability mostly occurs on interannual timescales and is highly influenced by the sea surface temperature (SST) variability in the eastern equatorial Atlantic, which is the centre of action of the Atlantic Niño mode. Using both historical and scenario (SSP5–8.5) simulations from 31 general circulation models (GCMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we first show that these models present a wet bias during boreal summer. This bias is associated with overly high mean boreal summer SSTs in the eastern equatorial and south Atlantic regions. Next, we analyse the near-term, mid-term and long-term changes of the Atlantic Niño relative to the present-day situation, in a climate with a high anthropogenic emission of greenhouse gases. We find a gradual decrease in the equatorial Atlantic SST anomalies associated with the Atlantic Niño in the future. This result reflects a possible reduction of the Atlantic Niño variability in the future due to a weakening of the Bjerknes feedback over the equatorial Atlantic. In a warmer climate, an anomalous higher sea level pressure in the western equatorial Atlantic relative to the eastern equatorial Atlantic weakens the climatological trade winds over the equatorial Atlantic. As a result, the eastern equatorial Atlantic thermocline is deeper and responds less to the Atlantic Niño events. Among the models that simulate a realistic rainfall pattern associated with the Atlantic Niño in the present-day climate, there are 12 GCMs which project a long-term decrease in the Guinea Coast rainfall response related to the Atlantic Niño. In these models, the zonal 850 hPa wind response to the Atlantic Niño over the equatorial Atlantic is strongly attenuated in the future climate. We also find that 12 other GCMs show no robust change in the patterns associated with the Atlantic Niño. There is a higher confidence in the mid-term and long-term reduction of the rainfall associated with the Atlantic Niño over the Atlantic Ocean than over the Guinea Coast. We also found a projected decrease in the convection associated with the Atlantic Niño in the majority of the models.
The West African Monsoon (WAM) generally begins in mid-June and is characterized by a rapid shift of the rain band from the coastal areas to the Sahel region
The general response of the atmosphere to Atlantic Niño positive phases is a modification of the Walker circulation, characterized by rising motion and upper-level divergence in the Atlantic region. In the central Pacific, a compensating upper-level convergence and sinking motion also triggers a Gill-type response in vorticity
Conversely,
Results from the general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP) show that from the fifth phase (CMIP5) to the sixth phase (CMIP6), the surface temperature biases have been reduced over the tropical Atlantic, as pointed out by
Rainfall changes over the Guinea Coast during recent decades follow the observed decrease in the AEM variability
In the present study, we provide a more detailed analysis of the future changes in the Atlantic Niño and their impact on the rainfall over the tropical Atlantic and land masses in the Guinea Coast by using results of GCMs obtained within CMIP6. The near-term, mid-term and long-term changes are analysed separately. In Sect. 2, we describe the data and analysis strategy used in our study. Section 3 focuses on the performance of the models in simulating the Guinea Coast rainfall and the SST in the eastern equatorial Atlantic regions, as well as the SST pattern associated with the Atlantic Niño. In Sect. 4, we evaluate the rainfall patterns associated with the Atlantic Niño in the CMIP6 models over the last 30 years of the historical simulations conducted with these models. We highlight the group of models that simulate a realistic rainfall pattern associated with AEM over the Guinea Coast. Section 5 discusses the modelled future changes of the Atlantic Niño and their impact on the rainfall over the tropical Atlantic and Guinea Coast, as well as the associated mechanisms. In the last section, we draw the main conclusions.
This study focusses on the July–August–September (JAS) season, during which the rainfall variability over the Guinea Coast and all of West Africa peaks
CMIP6 models and members of historical and SSP5–8.5 simulations. An asterisk (
The ERA5 dataset, a reanalysis product from the European Centre for Medium-Range Weather Forecasts
The evaluation of the present-day climate simulations is based on the last 30 years of the historical climate experiments (1985–2014). Three different periods are considered for the future climate analyses: the near-term (2015–2039), mid-term (2040–2069) and long-term (2070–2099) periods. Prior to any diagnostic over each period, the data are interpolated to the same grid of 1
Coordinates of different domains.
The difference of the wind divergence between 200 and 850 hPa levels (DIV
For a given period, when the regression patterns are averaged over some subsets of models, we determine the robustness of the result by adapting the method of
Moreover, we define different groups of models based on their rainfall SDA over a region. We aim to understand if different groups of models simulate the rainfall pattern related to the Atlantic Niño over the equatorial Atlantic and the Guinea Coast in different ways and in particular if a different simulation of the current state has some implications on the simulated future changes in rainfall patterns. We also aim to highlight the differences in the key physical mechanisms between the groups. Focusing on the Guinea Coast for example, we first identify the climate models which are able to realistically simulate the observed rainfall pattern related to the Atlantic Niño in the Guinea Coast over the past decades (the group GC
The observed Guinea Coast rainfall annual cycle is characterized by a bimodal structure with two maxima in June and September respectively. Many of the CMIP6 models overestimate the magnitude of the rainfall and rainfall standard deviation in this region during the boreal summer (Fig. S6). Unlike ERA5, the CMIP6 ensemble mean (EnsMean) depicts a plateau of 9 mm d
The CMIP5 models are also known to overestimate the rainfall in coastal areas of West Africa during the “little dry season”
Mean biases (relative to ERA5) of the ensemble mean of the 30 GCMs for the JAS SST (in colours), rainfall (in black contours) and 850 hPa wind (arrows) over 1985–2014. Boxes in black, white, yellow, blue, cyan and magenta correspond to the TAB1, TAB2, EAB, ATL3, GCB and WAB regions, respectively.
In general, the JAS spatial structure of the West African rainfall is well reproduced by the models (Fig. S8a). The spatial correlation between the mean JAS rainfall in the 30 GCMs and that of ERA5 lies between 0.68 and 0.96 (Fig. S8b). The multimodel ensemble mean of the JAS rainfall also shows a good performance, with a correlation of 0.92 with ERA5. Moreover, the standard deviation of the JAS West African rainfall ranges between 2.79 and 5.75 mm d
In ERA5, the annual cycle of the SST in the ATL3 area (Fig. S9a) shows a cold tongue which develops from April when the mean SST over the ATL3 region is about 29
The spatial SST pattern characteristic of the summer Atlantic Niño is derived by regressing the JAS SST anomalies onto the standardized JAS ATL3 SST index (Fig.
Regression maps of the JAS SST anomalies onto the standardized JAS ATL3 SST index. Stippling in the EnsMean indicates grid points where more than 50 % of the models show significant regression at 95 % confidence level and more than 80 % of the models agree on the sign of the regression coefficient. Stippling in each model and ERA5 indicates significant regression coefficients at 95 % level.
The CMIP6 models exhibit various SST imprints related to the Atlantic Niño over the tropical Atlantic (the TAB1 region; see Table
Taylor diagram of the JAS SST pattern in Fig.
Figure
Regression maps of the JAS rainfall anomalies onto the standardized JAS ATL3 SST index over 1985–2014. Stippling in the EnsMean indicates grid points where more than 50 % of the models show significant coefficients at 95 % level and more than 80 % of the models agree on the sign of the regression coefficient. Stippling in each model and ERA5 indicates significant regression coefficients at 95 % level.
Over the West African region, the latitudinal position of the maximum of the rainfall anomalies related to the AEM and averaged between 20
The sign-dependent average of the 1985–2014 rainfall anomalies related to the AEM over the Guinea Coast box is positive in the reanalysis ERA5 (Fig. S11a). Two groups of GCMs are considered, according to their sign-dependent average over the GCB. The first group is termed GC
Regression maps of the JAS rainfall
During positive phases of the Atlantic Niño, a warmer-than-normal sea surface temperature in the eastern equatorial Atlantic weakens the zonal surface pressure gradient over the equatorial Atlantic. This in turn weakens the prevailing trade winds. The regression of the low-level zonal component of the wind onto the ATL3 SST index is used to evaluate the first component of the Bjerknes feedback, which is the forcing of the surface wind in the western basin of the Atlantic Ocean by SST in the eastern basin
The JAS sea surface temperature and sea surface height imprints related to the standardized JAS ATL3 SST index are similar in the GC
Finally, during positive phases of the Atlantic Niño, over the Guinea Coast and the equatorial Atlantic, the atmospheric convection is more enhanced in the GC
In this section, the impact of the Atlantic Niño on the tropical Atlantic and Guinea Coast is evaluated in a climate with a high anthropogenic emission of greenhouse gases. The standard deviation of the Atlantic Niño index in the present-day climate simulations varies between 0.24 and 0.65
In the present-day climate, the multimodel mean of the JAS SST anomalies associated with the JAS ATL3 SST index and averaged over the equatorial Atlantic (the EAB region) is 0.33
Boxplots of the JAS regression coefficients of
Over the period 1985–2014, the JAS CMIP6 EnsMean rainfall anomalies related to 1 standard deviation of the JAS ATL3 SST index and averaged over the EAB is 0.62 mm d
Regarding the AEM-induced rainfall over the Guinea Coast, an overall reduction of the multimodel mean is projected (Figs.
The positive loop of the Bjerknes feedback requires first the forcing of the eastern equatorial Atlantic SST on the surface winds in the western basin. A warming in the eastern equatorial Atlantic gives rise to anomalous westerlies in the western basin. In turn, these weaker trade winds induce a deepening of the eastern equatorial Atlantic thermocline, which can be measured by a rising of the sea surface height. This is the second element of the Bjerknes feedback. The increased thermocline depth in the eastern equatorial Atlantic reduces the upwelling of cold water in that area and strengthens the initial warming. This third component of the Bjerknes is characterized by a positive correlation between the SST and SSH in the eastern equatorial Atlantic. In the future climate, following the SSP5–8.5 scenario, the variability of the trade winds associated with the Atlantic Niño decreases, as shown in Figs.
In response to weakened trade winds during a positive AEM phase, the upwelling of seawater in the east is reduced, leading to an anomalous rising of the SSH in the east, and an SSH fall in the west (Figs.
Part of the weakening of the equatorial Atlantic rainfall variability associated with the Atlantic Niño in a warmer climate has been attributed to a faster warming of the mid-tropical Atlantic troposphere compared to the surface, as pointed out by
Moreover, as the rainfall patterns related to the Atlantic Niño could be a mix from local and remote SST drivers, the monthly Niño3 indices (average of SST anomalies over 5
Throughout this section, we investigate the JAS rainfall, SST, 850 hPa zonal wind and moisture flux associated with the standardized JAS ATL3 SST index. To highlight the impact of some specific differences between the models in their way of representing the spatial characteristics related to AEM in response to climate change, six different subsets of the CMIP6 models are considered. They are also based on the sign-dependent average of the AEM-related rainfall pattern over, on the one hand, the Guinea Coast (the GCB area) and, on the other hand, the equatorial Atlantic region (the EAB area). First, the GC
Next, the 30 CMIP6 models are able to simulate a positive rainfall anomaly over the Atlantic Ocean in the area between the Equator and 5
Among the 24 models in the GC
Long-term changes of the JAS rainfall
Regarding the SST patterns related to the Atlantic Niño, the projected changes display a decrease in SST over the equatorial Atlantic and off the Angola–Benguela Coast in both GC
The SSH response to AEM in GC
From the six models in the GC
In a warmer climate, over the equatorial Atlantic, the models project an increase in the mean JAS sea level pressure which is greater in the western basin than in the eastern area. This zonal surface pressure gradient drives anomalous westerlies over the equatorial Atlantic (Fig. S19). As a consequence, the weakened trade winds cause a deeper mean thermocline in the eastern equatorial Atlantic. This is indicated by the increased oceanic mixed layer depth, here used as a proxy for the top of the thermocline depth. As the thermocline becomes deeper, it responds less to the SST changes at the surface during the Atlantic Niño phases and leads to a weakened Bjerknes feedback.
In this study, the JAS Atlantic Niño impact on the JAS rainfall in the Guinea Coast and over the tropical Atlantic has been evaluated. First, the 1985–2014 period of the historical simulations has been considered.
The spatial patterns of the JAS SST anomalies related to the standardized JAS ATL3 SST index in the GCMs show good correlations with the pattern in ERA5. However, the maximum rainfall position associated with the Atlantic Niño in the 30 GCMs' ensemble mean is displaced south of the observed position over the tropical Atlantic. All the models manifest an increased rainfall associated with positive AEM phases over the equatorial Atlantic. In the case of the Guinea Coast region, 24 models exhibit a realistic increased rainfall related to a warm phase of the Atlantic Niño, compared to 6 models which show a negative or weak rainfall response. In connection with the AEM, there is a weaker zonal wind response and a weaker zonal moisture flux toward the Guinea Coast, as well as a weaker deep convection in these 6 models (the GC
Secondly, the change of the Atlantic Niño and its impact on the rainfall over the equatorial Atlantic and the Guinea Coast in a climate with a high anthropogenic emission of greenhouse gases has been evaluated. Analyses of the Shared Socioeconomic Pathway 5–8.5 simulations demonstrate a gradual decrease in the SST anomalies associated with 1 standard deviation of the Atlantic Niño index for the near-term, mid-term and long-term periods, relative to the present-day climate. The ensemble mean change of the standard deviation of the ATL3 SST index relative to the present-day period is
More specifically, focusing on the Guinea Coast, among the 24 models which present a relatively good AEM-rainfall signal in the 1985–2014 period, there are 12 GCMs (the GC
In the GC
In the last part of this study, we linked the background JAS mean state change to the change of the Atlantic Niño variability. In a warmer climate, we found that over the equatorial Atlantic, the mean sea level pressure change is positive and presents an east–west gradient. This contributes to decreasing the intensity of the mean easterlies, thus limiting the equatorial upwelling. Subsequently, the thermocline becomes deeper along the Equator, and the deepening is more important in the eastern equatorial Atlantic. For this reason, the influence of the eastern equatorial Atlantic thermocline on the surface during the Atlantic Niño phases is weakened in the future. This explains the projected decreased variability of the Atlantic Niño in the SSP5–8.5 emission scenario.
Future studies are needed to assess the impact of the warm biases in the eastern equatorial Atlantic on the teleconnection patterns of the Atlantic Niño and could help to increase the reliability of the projected changes. Moreover, the reduction of these biases is crucial for the rainfall projections over West Africa. Further analyses are also needed to understand the multidecadal modulation of the Guinea Coast rainfall and extreme rainfall by oceanic internal modes of variability in climate models for both present-day and future climate conditions.
The code for the Taylor diagrams in this article is publicly available at
The CMIP6 data are available on the Earth System Grid Federation (ESGF) portals (e.g.
The content of the Appendix in the preprint was moved to the Supplement in the final revised paper. The supplement related to this article is available online at:
KW, HG and TF conceptualized the paper. KW performed the analyses and prepared the figures. FK participated in the discussions. KW, HG, TF and FK wrote the paper. All the co-authors provided scientific inputs and commented on the final draft.
The contact author has declared that neither they nor their co-authors have any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The authors would also like to thank the editor, Govindasamy Bala, and the five anonymous reviewers for their thoughtful and constructive comments. Koffi Worou would like to thank François Massonnet and Léandro Ponsoni for the useful discussions they had. Many thanks to Pierre-Yves Barriat and to the Copernicus Publications Editorial Support. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.
This paper was edited by Govindasamy Bala and reviewed by five anonymous referees.