We use two sets of sensitivity experiments, consisting of 10 year runs with global coupled models in which North Atlantic SSTs are constrained to follow a fixed, idealised anomalous pattern of the AMV in its positive (AMV+) and negative (AMV-) phases, respectively. The anomalous pattern (see Fig. S1 in the Supplement) is derived from an estimation of the internal component of the observed SST variability, following the procedure proposed by and using the ERSSTv4 dataset . The SST AMV signal is imposed in the North Atlantic, from 10–65° N, with an additional 8° buffer zone in which the amplitude of the AMV anomaly is reduced. Within this region, SSTs are constrained either through alteration of the surface fluxes or through a Newtonian SST nudging. Hereinafter, we will jointly refer to these adjustments as SST restoring. Further details on how the AMV pattern is obtained and on how the models' SST is constrained can be found in and in the technical notes for AMV simulations (https://www.wcrp-esmo.org/projects-and-panels/dcpp/dcpp-cmip6, last access: 17 July 2026). Four models follow the protocol of the Decadal Climate Prediction Project – Component C DCPP-C, while nine others follow the protocol proposed in the EU Horizon 2020 PRIMAVERA project . In both cases, for each model, multiple ensemble members are generated by slightly perturbing initial conditions. The protocols differ in the applied radiative forcing (pre-industrial conditions in the DCPP-C protocol and 1950s conditions in the PRIMAVERA protocol) and in the magnitude of the anomalous AMV pattern, which is twice as large in the PRIMAVERA runs. Changes associated with a positive AMV phase are estimated by subtracting the negative experiment from the positive one (AMV⁺ - AMV⁻). Since this estimation assumes linearity, changes associated with a negative AMV phase can be obtained by reversing the sign of the anomalies. To facilitate comparison between protocols, changes in the model driven by the PRIMAVERA protocol are halved. For each experiment, we first calculate the 10 year mean of the simulation, and then we average all ensemble members for each model. The climatology for a given model and field is computed as half the sum of the positive and negative experiments, after averaging across ensemble members and the ten simulated years. Although there could be non-linear effects in the AMV impacts e.g., the current protocol does not allow their estimation.

Table  lists the models analysed, including their atmospheric horizontal resolution, protocol followed, number of ensemble members, and main reference.

From the model's monthly mean outputs, we calculate the following derived variables:

Top-of-atmosphere radiative energy imbalance. The energy imbalance at the top of the atmosphere RTOA is calculated as the difference between net incoming shortwave radiation and outgoing longwave radiation (OLR), with positive values indicating net radiative energy gain for the atmosphere.

To highlight the average signals across models, the multimodel mean is calculated as the unweighted average across all available models (an equal weight “1 model, 1 vote” approach), without any special weighting for different versions of the same model. In this calculation, each model is represented by the average over all its ensemble members, which varies among models (Table ). Before averaging, all model outputs are regridded to a common horizontal grid of 1°×1° using a first-order conservative method. For the calculation of vertical profiles, outputs are first computed for each model, regridded linearly to a common 1° horizontal grid (vertical levels are standardised, except for EC-Earth3 in the DCPP-C protocol, which is excluded for profile calculations), and then averaged across the available models.

In maps and spatial plots, model consistency is evaluated by hatching the regions where less than 80 % of the models agree on the sign of the AMV+ minus AMV- changes in a given variable.

As is common in modelling studies, the intermodel spread is used as a measure of uncertainty. We assume the model values form a sample drawn from a normal distribution with unknown variance, and we use the sample variance as an estimate of the population variance. Confidence intervals are constructed using a two-tailed Student's t-test at a significance level of α=0.05.

We also evaluate the potential relation between the intermodel spread of Sahel rainfall and that of other variables using scatter plots, for which the linear regression and correlation are calculated. The statistical significance of the latter is assessed using a t-test at the same significance level of α=0.05.

Due to the interdependence among models, determining the number of degrees of freedom in our sample of models is not straightforward . Specifically, two elements are provided by the same model (CNRM-CM6-1) run under the two different protocols, while others represent a single model configuration run at different resolutions (for instance, MetUM-GOML2-HR and MetUM-GOML2-LR). Moreover, several models share components (e.g., atmospheric or oceanic), thus reducing overall diversity. Most results shown are based on a sample of 11 models, of which around 6 can be considered independent, although their components might not be completely independent. Therefore, we assess the statistical significance under two assumptions: (1) treating all models as independent realisations, and (2) assuming only 6 independent elements. This dual approach allows us to evaluate the sensitivity of our conclusions to model interdependence. These are indicated in the text and figures with one and two asterisks, respectively.

To quantify how much of a given change in a zonally averaged field can be interpreted as a latitudinal shift vs. an amplitude change, we decompose anomalies into symmetric and antisymmetric components relative to the location of the climatological peak. We restrict the analysis to zonally averaged (in the 10° W–10° E longitudinal sector) fields that exhibit a distinct extremum (maximum or minimum) as a function of latitude (e.g., rainfall or zonal wind at 600 hPa) and focus on a latitude window centred on this peak. For any latitude within this window, the symmetric (antisymmetric) component is defined as half the sum (difference) of the value at that latitude and the value at its mirror latitude relative to the peak. For a given latitude range to one side of the peak (for instance, Sahel latitudes for rainfall), we identify the shift with the antisymmetric component and the amplitude change with the symmetric component, both averaged over the latitude range. The total averaged change for that given latitude range is the sum of both components. Unless otherwise stated, the region taken for the averages is from the latitude of the maximum to the northern limit of the plot. For the multimodel mean, the calculation is performed after model averaging.

We evaluate potential drifts of the simulations by calculating the drift in the TOA energy imbalance RTOA over the simulated years (Fig. a). All models except for MPI-ESM-2-HR and MPI-ESM-2-XR show negative RTOA, indicating that the AMV+ experiment is losing energy at TOA relative to AMV-. Although the negative values tend to grow over time, the trends are not statistically significant. This weak negative RTOA and its trend in the difference between AMV+ and AMV- experiments are consistent with a positive value and trend in OLR (Fig. b) and in global mean surface temperatures (Fig. c). The SST restoring imposes warm anomalies over the North Atlantic in the AMV+ experiment relative to AMV-, resulting in a warmer global mean surface temperature anomaly (Fig. c). This initial anomaly tends to increase over time as regions remote from the North Atlantic begin warming up (Fig. c). Consequently, the warmer AMV+ experiment loses more OLR to space relative to the AMV- experiment (Fig. b), which explains the negative RTOA and its weak negative trend (Fig. a).

Conversely, MPI-ESM-2-HR and MPI-ESM-2-XR exhibit highly anomalous behaviour. In response to warm North Atlantic SST anomalies, these models cool over the simulated period, especially over the tropical ocean regions (Figs. d and S2). The reasons for this cooling remain unclear, and while we encourage further analysis, it is out of the scope of this study. This cooling causes a strong positive drift of RTOA (Fig. a) due to a corresponding negative drift in OLR (Fig. b). In addition, these models present a strong response in Sahel rainfall (see Fig. S3), characterised by a positive and statistically significant trend throughout the simulation (Fig. e). We consider this behaviour unrealistic and have therefore removed these two models from the analyses shown here. We caution against the inclusion of the PRIMAVERA AMV+ and AMV- simulations performed with these two models in multimodel means, as it can unrealistically distort results and increase intermodel spread as in. Nevertheless, our main conclusions regarding the mechanisms governing the Sahel rainfall response to the AMV SST pattern remain robust regardless of the exclusion of these two models.

In response to the imposed positive AMV pattern during boreal summer, there is a pronounced surface warming across continental regions poleward of 30° N, including eastern Asia. In the Southern Hemisphere, warm anomalies appear mainly over South America (Fig. a). This pattern is consistent with previous studies evaluating similar experiments . Elsewhere, models show weaker and less consistent temperature responses, with modest multimodel mean changes.

In agreement with earlier work e.g., over West Africa, the positive phase of the AMV leads to increased rainfall over the continent, strongest along the western coast, and over the Atlantic north of 5° N (Fig. b). Negative precipitation anomalies occur to the south of the main convective regions. Models show high consistency in the positive rainfall response over the Sahel but larger uncertainty over the Guinea Gulf coastal regions west of 0° E (Fig. b). On average, models suggest an increase of 0.10±0.02*/0.03**mmd-1 in JAS rainfall over the Sahel, corresponding to approximately 5 % of the climatological mean.

Increases in Sahel rainfall can arise from an intensification and/or a northward shift of the main rainband. The meridional dipole of precipitation anomalies in Fig. b is suggestive of a northward displacement of the ITCZ. Most models indeed show such a northward ITCZ shift over West Africa (Fig. c), with a multimodel mean estimate of 0.09±0.05*/0.08**°. Moreover, the intermodel spread in the magnitude of this shift is positively associated with the spread in Sahel rainfall changes, indicating that models simulating a stronger northward ITCZ shift tend to produce larger rainfall increases over the Sahel.

To further evaluate if the rainfall response is better interpreted as an intensification or a latitudinal shift, we decompose rainfall changes averaged in the 10° W–10° E longitude sector into symmetric and antisymmetric components relative to the latitude of maximum climatological rainfall (Fig. a). For the multimodel mean, 70 % of the changes in rainfall over Sahel latitudes are explained by the antisymmetric component (Fig. b), supporting a dominant contribution from a northward displacement of the precipitation pattern. At the individual model level, results are more disparate, with five models showing a dominance of the antisymmetric component and four a dominance of the symmetric component, consistent with an intensification of the mean precipitation pattern. The intermodel spread of changes over the Sahel is positively correlated with both components (Fig. c and d), which is expected since their sum represents the total change. However, the correlation with the symmetric component is weak and not statistically significant, while it is stronger and statistically significant for the antisymmetric one.

In summary, in response to the positive AVM phase, models simulate an enhancement of Sahel rainfall, arising from both an intensification and a northward shift of the main rainband. The northward displacement dominates the mean response and also helps explain the intermodel spread in total rainfall changes.

As shown above, the response of Sahel rainfall to a positive phase of the AMV is dominated by a northward shift of the ITCZ. The energetic framework has established a clear link between similar ITCZ shifts and changes in the cross-equatorial atmospheric energy transport, modulated by the inverse of the net energy input into the atmosphere (NEI) in the equatorial region . It is therefore of interest to investigate whether the identified rainfall changes at Sahel longitudes are related to corresponding changes in cross-equatorial energy transport and equatorial NEI modifications. To this aim, Fig. a shows NEI into the atmosphere and the divergent component of the column-integrated total MSE flux (〈uh〉+, arrows). In response to a positive AMV, changes in equatorial NEI at Sahel longitudes are small (Fig. a) and show no consistent alignment with Sahel rainfall changes (not shown). Conversely, a robust anomalous southward cross-equatorial column-integrated MSE flux develops in the Atlantic and along African longitudes (〈vh〉+, with meridional wind v, Fig. b), and is also observed at the global scale in the zonal mean (Fig. S4). Provided gross moist stability does not change , the zonally averaged southward energy transport is realised through a northward displacement of the ascending branch of the Hadley circulation . The simulated increase in Sahel rainfall and associated ITCZ northward shift together with the anomalous southward energy transport at the Sahel longitudes are consistent with the zonally averaged paradigm, suggesting sector-mean zonal energy fluxes are of second-order relevance .

At Sahel longitudes (10° W–10° E, yellow box in Fig. b), the multimodel mean response in the meridional component of the column-integrated divergent MSE flux across the equator is (-1.4±0.4*/0.6**)×106Wm-1. Combining this with our previous estimate of the mean ITCZ shift at these longitudes yields a displacement of (-6.2±4.2*)×10-8° per each Wm-1. When scaled to the entire latitude circle, this corresponds to (-1.6±1.0*) ° per PW, an estimate in close agreement with those reported by for the observed interannual variability of the zonally averaged ITCZ position.

The southward cross-equatorial energy transport arises as a response to the enhanced net input of energy into the atmosphere in the North Atlantic (Fig. a, shaded). This energy excess cannot be stored locally and results in large-scale atmospheric circulation adjustments that generate the divergent MSE flux seen in Fig. a. These adjustments also include changes in NEI in regions remote from the primary forcing, such as the Atlantic south of the equator, where negative NEI anomalies develop (Fig. a) and further strengthen the inter-hemispheric energy gradient. Decomposition of the NEI excess into individual contributions from TOA and surface energy imbalances (Fig. c and d) shows that the main contribution comes from the surface imbalance, which is in turn principally driven by the latent heat flux (Fig. e). The mean NEI anomaly in the North Atlantic (see box in Fig. c) is 1.5±0.1*/0.2**Wm-2, 85 % of which originates from latent heat flux changes. A notable exception to the dominance of latent heat fluxes in the NEI pattern is the northern flank of the tropical NEI maximum (approximately between 60–20° W and 10–20° N). In this specific region, the positive surface energy anomaly is primarily due to cloud-radiative feedbacks linked to the northward ITCZ shift (Fig. S5).

Regarding the intermodel spread, the scatterplot in Fig. f suggests that models with a stronger southward energy transport response also exhibit larger increases in Sahel precipitation. A similar relationship emerges when comparing Sahel rainfall changes with the NEI or surface energy imbalance averaged over the North Atlantic, where strong NEI anomalies develop (Fig. g and h): models with higher atmospheric energy input through surface fluxes tend to produce stronger southward cross-equatorial energy transport and greater Sahel rainfall anomalies. Note that both the tropical and extratropical portions contribute to the North Atlantic NEI, and their combination explains more inter-model spread of Sahel rainfall changes than either contributor separately (Fig. S6).

To further analyse the changes in surface latent heat flux, we apply the bulk aerodynamic formula , whereby the latent heat flux (LE) can be expressed as: LE=LvρCDEUrqs(1-RH) where ρ is the air density, CDE is the aerodynamic transfer coefficient for moisture, Ur is the mean wind speed at the standard height, qs is the saturation specific humidity, and RH is the relative humidity. To a first-order approximation, we expect the fractional change in latent heat flux (δLE/LE, with δLE denoting the AMV+ minus AMV- anomalies of latent heat flux and LE the estimated climatological value) to be linearly related to the fractional change in saturated specific humidity (δqs/qs), to the fractional change in mean wind speed (δUr/Ur), and to the negative fractional change in relative humidity (-δRH/(1-RH)). In Fig. , we present these terms for the surface, except for the wind speed, which is estimated from monthly mean zonal and meridional components at 1000 hPa, and RH, which is calculated as the ratio between near-surface specific humidity and saturation specific humidity at the surface. These represent approximations to near-surface wind speed and relative humidity.

In response to the imposed SST restoring, the warm SST anomalies over the North Atlantic (Fig. a) lead to an overall increase in saturation specific humidity (Fig. b). This would, in isolation, favour enhanced latent heat flux from the surface over the North Atlantic. However, the anomalous spatial patterns in Fig. a and b differ markedly. Over the tropical north Atlantic, between the equator and 20° N, where fractional changes in qs are nearly uniform (Fig. b), latent heat flux fractional anomalies show a dipole (Fig. a), with weak and negative values in the tropical Atlantic between 10 and 20° N and west of 30° W, and strong and positive values to the south of 10° N. These differences suggest the influence of feedbacks that modulate the initial response to the imposed SST anomalies . Because the atmosphere is decoupled from the ocean within the SST-restored region, such feedbacks must be of atmospheric origin. Specifically, the northward shift of the Atlantic ITCZ following the AMV+ forced energy surplus in the North Atlantic would reduce the northerly winds to the north of the climatological ITCZ (approximately located at 10° N) and enhance the southerly winds to the south. This yields a dipole in surface wind speed anomalies (negative north of 10° N, positive to the south; Fig. c), which in turn suppresses latent heat flux to the north and increases it to the south, consistent with the pattern in Fig. a. Note that in this region, the experimental setup prevents full atmosphere–ocean coupling, such that positive and negative Wind-Evaporation-SST feedbacks are hindered.

In addition, over the North Atlantic subpolar region, changes in relative humidity further enhance latent heat flux into the atmosphere (Fig. d). This contribution comes from a reduction in the northwestern Atlantic RH (note the negative sign of the RH term in the bulk formula), as the positive anomaly in near-surface specific humidity (not shown) is smaller than the saturated one. This likely reflects a circulation-driven export of moist air away from the North Atlantic subpolar region, redistributing the excess moisture generated by warmer SSTs.

In summary, our results show that in response to the positive AMV phase, enhanced turbulent latent heat fluxes from the North Atlantic increase the atmospheric energy input. The excess energy is then exported from the North Atlantic by anomalous atmospheric circulation patterns, which in turn feed back onto the surface fluxes. The resulting steady state is characterised by a southward cross-equatorial energy flux across the Atlantic and African longitudes. In the African sector, this flux is accomplished by a northward shift of the monsoonal Hadley-like circulation's ascending branch and is thus associated with a corresponding northward shift of the main rainfall band, ultimately leading to enhanced rainfall over the Sahel.

The large-scale responses to the imposed AMV SST anomalies in the North Atlantic indicate modifications of the West African monsoon that extend beyond changes in seasonal rainfall amounts. The main changes in the monsoon circulation are summarised in Fig. . Close to the surface, during the positive phase of the AMV, models consistently show a stronger low-level westerly flow that penetrates further north (Fig. a). The magnitude of these anomalies is weak, consistent with the models' general underestimation of the AMV’s impact on Sahel rainfall . Changes in the low-level meridional wind reveal a weakening of the southerly winds south of 13° N (Fig. b), which enhances low-level wind convergence south of 10° N (Fig. c), in the region of mean climatological ascent . Positive meridional wind anomalies peak between 15 and 20° N (Fig. b), altering the horizontal wind divergent field by weakening and shifting northward the lower branch of the shallow meridional circulation (SMC) (Fig. c).

In the upper troposphere, the Tropical Easterly Jet (TEJ) strengthens, accompanied by enhanced northerlies associated with the upper branch of the Hadley cell (Fig. a and b). The upper-level horizontal divergence is also enhanced, especially on its northern edge between 10 and 15° N (Fig. c), suggesting a strengthening and northward displacement of the main ascent region, consistent with the rainfall anomalies.

In the mid and lower troposphere, the low-level atmospheric thickness anomalies point to an enhanced and northward-shifted SHL , with positive anomalies north of 20° N and negative ones to the south (Figs. d, S7 and S8). These negative anomalies are linked to the evaporative cooling induced by increased soil moisture following increased precipitation (see Fig. S9). The resulting evaporative cooling modifies the meridional temperature gradients, reducing them south of the climatological maximum and strengthening them to the north, which favours a northward shift of the African Easterly Jet (AEJ), consistent with thermal wind balance . Indeed, between 800 and 500 hPa, cyclonic zonal wind anomalies south of 20° N indicate a northward shift of the AEJ (Fig. a). The AEJ also shows a slight weakening (see Fig. S10). At mid levels, the upper branch of the SMC, located between 15 and 20° N and 800–600 hPa (see climatological contours showing divergence in Fig. c), shows a consistent weakening across models (see Fig. S11). This is reflected in reduced mid-level divergence and a weaker return flow south of 15° N (orange boxes in Fig. b and c).

Regarding the intermodel spread, the scatter plots shown in Fig. e–g suggest that the changes at mid levels are strongly related to the changes in Sahel rainfall. Models with stronger rainfall change over the Sahel are also those that show a stronger northward shift of the AEJ (Fig. e). We speculate this link to be a consequence of the surface response to enhanced rainfall (see Fig. S8): increased soil moisture in the latitudinal band between 10 and 15° N following enhanced precipitation promotes evaporative cooling of the surface by changing the balance between latent and sensible heat fluxes, which alters the surface temperature latitudinal gradient and, through thermal wind balance , enhances the AEJ to the north and reduces it to the south. In addition, models that exhibit a weaker shallow meridional circulation, characterised by a weaker mid-level return flow and weaker mid-level divergence close to 15° N, tend to show a stronger rainfall change in the Sahel (Fig. g, f). Conversely, the intermodel spread of neither the strength nor of the shift of the SHL structure is related to change in Sahel rainfall (see Fig. S7 and S8). The intermodel spread in rainfall changes is also not related to the shift of the divergence by the SMC upper branch (see Fig. S11).

The preceding analysis suggests, consistent with , a strong coupling between enhanced Sahel rainfall and a weakened return flow of the SMC at mid-levels. Such a weakening reduces the intrusion of dry air into the Sahel, thereby modifying horizontal advection of moist static energy in the region. To further investigate this mechanism, we examine the column-integrated atmospheric energy balance (Eq. ). Taking time averages, again assuming negligible atmospheric energy storage (∂t〈e‾〉≈0) and decomposing the total transport in mean and eddy components, the energy budget can be written as: 2NEI‾-〈∇h⋅(u‾h‾)〉-〈∇h⋅(u′h′‾)〉=0 where overbars denote time averages, and primes denote deviations from the time averages. Together with the continuity equation (∂pω+∇hu‾=0, where ω is the vertical velocity in pressure coordinates), the second term on the left-hand side of Eq. () can be written as: 〈∇h⋅(u‾h‾)〉=〈u‾⋅∇hh‾〉-〈h‾∂pω‾〉=〈u‾⋅∇hh‾〉+〈ω‾∂ph‾〉 This provides the following expression for the column-integrated energy balance: NEI‾-〈u‾⋅∇hh‾〉-〈ω‾∂ph‾〉-〈∇h⋅(u′h′‾)〉=0 In most deep convective regions, including monsoon systems, the transient eddy term is small and the dominant balance is between positive NEI‾ and the MSE divergence by the vertical advection term (-〈ω‾∂ph‾〉<0) . In the Sahel monsoon, as shown by , the horizontal advection term (-〈u‾⋅∇hh‾〉<0) is non negligible and in fact partly balances the positive NEI‾ through import of dry, and hence, lower-MSE air in the upper branch of the SMC.

Building on these ideas, in Fig. , we examine changes in the MSE export by the time-mean horizontal flow (u‾⋅∇hh‾) over the Sahel. Climatologically, the export of MSE at mid-levels is dominated by the moisture advection term (u‾⋅∇hLvq‾, compare black and blue lines in Fig. a), due to northerly flow between 800 and 300 hPa (Fig. b) acting on a negative meridional moisture gradient (Fig. c, ∂yq‾, blue line and axis), that is, by dry air advection by the upper branch of the SMC, in agreement with . Temperature advection slightly counteracts this MSE export (Fig. a, u‾⋅∇hcpT‾, red line), since the same northerly flow also advects warmer air.

In response to a positive phase of the AMV, models consistently show a reduction in MSE export at mid-levels due to weaker time-mean horizontal advection (Fig. b, δ(u‾⋅∇hh‾), black line). Because changes in NEI over the Sahel are positive (Fig. a) and the transient eddy MSE flux divergence is small e.g., this reduced horizontal export must be compensated by enhanced export through the divergent circulation. Consequently the vertical advection term (-〈ω‾∂ph‾〉) becomes more negative. Given the tropical MSE vertical structure, this implies a change from a shallower convection regime to a deeper convection regime with a first-baroclinic mode structure (see Fig. S12). This interpretation agrees with the horizontal divergence anomalies in Fig. c, which show reduced divergence at mid levels and stronger divergence aloft.

A decomposition of the change in the time-mean horizontal MSE export in temperature (δ(u‾⋅∇hcpT‾)), geopotential height (δ(u‾⋅∇hz‾)) and moisture (δ(u‾⋅∇hLvq‾)) components shows that the moisture advection term dominates (compare black and blue solid lines in Fig. b). Part of the reduced dry-air advection, and therefore the weaker MSE export, stems from the weakening of the meridional flow in the upper branch of the SMC (Fig. b, δ(u‾)⋅∇hLvq‾, blue dotted line), as positive meridional wind anomalies (Fig. b) act on the climatological negative meridional moisture gradient (Fig. c, blue line and axis). However, and consistent with , the dominant contribution arises from thermodynamic changes (Fig. b, u‾⋅δ(∇hLvq‾), dashed blue line) linked to changes in the moisture field itself. Under a positive AMV phase, and consistent with a stronger and more northward location of the rainfall band, the tropospheric moisture content increases across West Africa, especially at Sahel latitudes, peaking slightly north of 15° N in the lower troposphere (not shown). This moistening induces an anomalous positive meridional gradient of moisture in the Sahel (Fig. c, δ(∂yq‾), orange line and axis). The climatological northerlies (contours in Fig. b) acting on this anomalous meridional gradient explain the negative values of the u‾⋅δ(∇hLvq‾) term in Fig. b (blue dashed line).

Regarding intermodel differences, the scatter plots in Fig. d–f suggest that changes in Sahel rainfall are strongly linked to mid-tropospheric MSE horizontal advection (δ(u‾⋅∇hh‾), Fig. d), mainly through the thermodynamic moisture advection component (u‾⋅∇hδ(Lvq‾), Fig. f). Models exhibiting a stronger reduction in MSE export, through a greater decrease in dry air intrusion at mid levels (mainly mediated by modifications in the moisture profile), also simulate larger increases in Sahel rainfall. This relationship is consistent with the models that show greater decreases in mid-tropospheric horizontal divergence (Fig. f) indicating a weakening of the shallow convection regime.

In summary, a positive phase of AMV promotes a northward shift of the main monsoon circulation features, particularly the SHL and the AEJ. It also enhances low-level convergence near 10° N and divergence aloft, reinforcing the deep convection branch of the monsoon. While also shifting northward, the shallow meridional circulation weakens, reducing the intrusion of dry air into the Sahel main convective region at mid levels. This weakening not only occurs consistently across models but also scales with the magnitude of rainfall increase. The reduced mid-tropospheric dry-air intrusion lowers the MSE export by horizontal advection, which is then compensated by enhanced MSE export through the divergent circulation , ultimately supporting stronger precipitation. The dominant driver of the reduced horizontal MSE export is the thermodynamic component of the moisture advection, highlighting a strong coupling between moisture and circulation changes in the West African monsoon response to AMV.