Stratospheric Aerosol Injection (SAI), a proposed climate intervention, aims to reduce the amount of solar radiation reaching the Earth's surface by increasing the reflectivity of the atmosphere, thereby offsetting the warming effect of greenhouse gases. During the Harmattan season (December-February) in West Africa (WA), a natural meteorological phenomenon injects dust and sand particles into the atmosphere, leading to a cooling effect. In this study, we investigate the influence of SAI on West African surface temperature, dust, and other meteorological variables using the Whole Atmosphere Community Climate Model under the Shared Socioeconomic Pathway 2-4.5 scenario and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth system with SAI (ARISE-SAI) dataset. Our findings indicate that SAI intervention significantly impacts the projected surface temperatures, specific humidity, and wind speed changes during the Harmattan season. Compared to a future without SAI, the intervention shows a significant net cooling effect over most parts of WA during the mid-future period (2050-2069). Also, SAI intervention significantly decreases moisture content over southern and northern WA in the near-future (2035-2054), mainly due to the net cooling effects over WA, when compared to a future without SAI. This feature is enhanced in the mid-future period. The cooling effects of SAI are likely to reduce the air's capacity to hold moisture, leading to lower specific humidity levels relative to a future without SAI. It could also have negative implications, such as increased aridity compared to a future without SAI in the northern and central regions of WA. These findings also highlight the potential for SAI to improve air quality in certain areas but also underscore the need for careful consideration of implementation strategies and possible trade-offs. The changes from SAI observed are specific to the ARISE simulation and may differ from other SAI simulations.

This study investigates West Africa's climate vulnerability under stratospheric aerosol injection (SAI), using UKESM1 and CESM2 models. We analyzed temperature and precipitation responses for 2050-2069 relative to 2015-2034 under SSP2-4.5 and ARISE-SAI-1.5 scenarios. Our approach involved evaluating temperature and precipitation anomalies, applying signal-to-noise ratio (SNR) analysis-defined as the ratio of the forced climate response to internal variability-to assess signal robustness, and using cumulative distribution (CDF) and probability density (PDF) functions to explore shifts in precipitation extremes. Results indicate that under SSP2-4.5, both models project significant warming. UKESM1 simulates increases near 1.8 degrees C, while CESM2 projects between 1.0 degrees C and 1.2 degrees C. Under ARISE-SAI-1.5, UKESM1 shows pronounced cooling, with temperatures dropping up to 0.3 degrees C below the reference period at some latitudes. CESM2 shows a more uniform cooling, with temperatures between 0 degrees C and 0.3 degrees C above the reference. SNR analysis reveals robust, statistically significant temperature changes across the region, clearly emerging above natural variability by midcentury. Precipitation changes, however, show lower SNR values and greater spatial uncertainty, suggesting weaker and less predictable hydrological responses. CDF and PDF analyses highlight complex shifts in precipitation extremes, suggesting that while SAI could counteract warming trends, it may introduce additional variability and uncertainty in rainfall projections. These results emphasize the importance of multimodel comparisons in assessing geoengineering impacts on regional climates, as differing sensitivities to radiative forcing and feedback can produce divergent outcomes.

Mesoscale convective systems (MCSs) are frequently observed over southern West Africa (SWA) throughout most of the year. These MCS events are the dominant rain-bearing systems, contributing over 50 % of annual rainfall over SWA. However, it has not yet been identified what variations in typical large-scale environments of the seasonal cycle of the West African monsoon may favour MCS occurrence in this region. Here, nine distinct synoptic states are identified and are further associated with being a synoptic-circulation type of either a dry, transition, or monsoon season using self-organizing maps (SOMs) with inputs from reanalysis data. We identified a pronounced annual cycle of MCS numbers with frequency peaks in April and October that can be associated with the start of rainfall during the major rainy season and the maximum rainfall for the minor rainy season across SWA, respectively. Comparing daily MCS frequencies, MCSs are most likely to develop during transition conditions featuring a northward-displaced moisture anomaly (2.8 MCSs per day), which can be linked to strengthened low-level westerlies. Considering that these transition conditions occur predominantly during the pre- and post-monsoon period, these patterns may in some cases be representative of monsoon onset conditions or a delayed monsoon retreat. On the other hand, under monsoon conditions, we observe weakened low-level south-westerlies during MCS days, which reduce moisture content over the Sahel but introduce more moisture over the coast. Finally, we find a majority of MCS-day synoptic states exhibiting positive zonal wind shear anomalies. Seasons with the strongest zonal wind shear anomalies are associated with the strongest low-level temperature anomalies to the north of SWA, highlighting that a warmer Sahel can promote MCS-favourable conditions in SWA. Overall, the SOM-identified synoptic states converge towards high-moisture and high-shear conditions on MCS days in SWA, where the frequency at which these conditions occur depends on the synoptic state.

Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulate streamflow in the Ouémé river basin is assessed by forcing the model with operational analysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric and land surface processes are resolved at a spatial resolution of 5 km. The additional surface and subsurface water flow routing are computed at a resolution of 500 m. Key parameters of the hydrological module of WRF-Hydro are calibrated offline and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in the Ouémé river in offline and fully coupled modes with a Kling–Gupta efficiency (KGE) around 0.70 and 0.76, respectively. In the fully coupled mode, the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of ten members for three rain seasons shows that the coupled model performance in terms of KGE ranges from 0.14 to 0.79. Additionally, an assessment of the soil moisture has been developed. This ability to realistically reproduce observed discharge in the Ouémé river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.

Changes in rainfall onset and cessation dates are critical for improving decision making and adaptation strategies in numerous socio-economic sectors. An objective method of determining onset and cessation date is employed over Southern West Africa (SWA) in this study. The method is applied over 34 years of the quasi-global rainfall dataset from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and five High Resolution Model Intercomparison Project (HighResMIP) model datasets under the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment. Generally, a strong agreement exists between CHIRPS and the HighResMIP models in capturing the behaviour of seasonal rainfall over SWA, with models able to capture the bimodal rainfall season. The ability of models in capturing onset and cessation dates as observed in CHIRPS shows the strength of these models in representing the short break between the two wet seasons that is otherwise known as the ‘Little Dry Season’. Patterns observed in the onset and cessation dates over the SWA region are consistent with the northward and southward displacement of the Intertropical Convergence Zone (ITCZ). The seasonal timing of the models shows good agreement with observations such that most mean onset/cessation dates agree within 26 days. While IPSL-CM6A-ATM-HR, a model among the five HighResMIPs used in the study, best agrees with CHIRPS in representing onset and cessation dates during the unimodal rainfall season, no one model best agrees with CHIRPS during the bimodal season, with models outperforming each other in representing onset/cessation dates with little variation.

AbstractIt is commonly accepted that the Earth’s climate is changing and will continue to change in the future. Rising temperatures are one of the direct indicators of global climate change. To investigate how the rising global temperature will affect the spatial pattern of rainfall in West Africa, the precipitation and potential evapotranspiration variables from ten Global Climate Models (GCMs) under the RCP8.5 scenario were driven by the Rossby Centre regional atmospheric model (RCA4) from the COordinated Regional Climate Downscaling EXperiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the preindustrial level. This study utilized three indices, the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Besides, the analysis of the effect of the specified GWLs on the Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), and frequency of the intense rainfall events allowed to a better understanding of the spatial and temporal patterns of extreme precipitation in West Africa. Results reveal that, for the projections simulations and at each GWL, the rainfall onset starts one month earlier in the Gulf of Guinea in response to the control period. To encourage adaptation to the various changes in climate in general, and particularly in respect of rainfall, this study proposes several adaptation methods that can be implemented at the local (country) level, as well as some mitigation and adaptation strategies at the regional (West African) level.

It is well accepted that summer precipitation can be altered by soil moisture condition. Coupled land surface - atmospheric models have been routinely used to quantify soil moisture - precipitation feedback processes. However, most of the land surface models (LSMs) assume a vertical soil water transport and neglect lateral terrestrial water flow at the surface and in the subsurface, which potentially reduces the realism of the simulated soil moisture - precipitation feedback. In this study, the contribution of lateral terrestrial water flow to summer precipitation is assessed in two different climatic regions, Europe and West Africa, for the period June-September 2008. A version of the coupled atmospheric-hydrological model WRF-Hydro with an option to tag and trace land surface evaporation in the modelled atmosphere, named WRF-Hydro-tag, is employed. An ensemble of 30 simulations with terrestrial routing and 30 simulations without terrestrial routing is generated with random realizations of turbulent energy with the stochastic kinetic energy backscatter scheme, for both Europe and West Africa. The ensemble size allows to extract random noise from continental-scale averaged modelled precipitation. It is found that lateral terrestrial water flow increases the relative contribution of land surface evaporation to precipitation by 3.6% in Europe and 5.6% in West Africa, which enhances a positive soil moisture - precipitation feedback and generates more uncertainty in modelled precipitation, as diagnosed by a slight increase in normalized ensemble spread. This study demonstrates the small but non-negligible contribution of lateral terrestrial water flow to precipitation at continental scale.

Climate variability and change constitute major challenges for Africa, especially West Africa (WA), where an important increase in extreme climate events has been noticed. Therefore, it appears essential to analyze characteristics and trends of some key climatological parameters. Thus, this study addressed spatiotemporal variabilities and trends in regard to temperature and precipitation extremes by using 21 models of the Coupled Model Intercomparison Project version 6 (CMIP6) and 24 extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). First, the CMIP6 variables were evaluated with observations (CHIRPS, CHIRTS, and CRU) of the period 1983–2014; then, the extreme indices from 1950 to 2014 were computed. The innovative trend analysis (ITA), Sen’s slope, and Mann–Kendall tests were utilized to track down trends in the computed extreme climate indices. Increasing trends were observed for the maxima of daily maximum temperature (TXX) and daily minimum temperature (TXN) as well as the maximum and minimum of the minimum temperature (TNX and TNN). This upward trend of daily maximum temperature (Tmax) and daily minimum temperature (Tmin) was enhanced with a significant increase in warm days/nights (TX90p/TN90p) and a significantly decreasing trend in cool days/nights (TX10p/TN10p). The precipitation was widely variable over WA, with more than 85% of the total annual water in the study domain collected during the monsoon period. An upward trend in consecutive dry days (CDD) and a downward trend in consecutive wet days (CWD) influenced the annual total precipitation on wet days (PRCPTOT). The results also depicted an upward trend in SDII and R30mm, which, additionally to the trends of CDD and CWD, could be responsible for localized flood-like situations along the coastal areas. The study identified the 1970s dryness as well as the slight recovery of the 1990s, which it indicated occurred in 1992 over West Africa.

Since 2000s, most of West-African countries and particularly Benin have experienced an increased frequency of extreme flood events. In this study we focus on the case of the Ouémé-river basin in Benin for the period 2008-2010. To investigate on how to early warn flood events in this basin, the coupled atmosphere-hydrology model system WRF-Hydro is selected. Such a coupled model allows to explore the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro in correctly simulating streamflow in the Ouémé-river basin is assessed by forcing the model with operational analysis datasets from the ECMWF. Atmospheric and land surface processes are resolved at a spatial resolution of 5km. The additional surface and subsurface water flow routing is computed at a resolution 1:10. Key parameters of the hydrological module of WRF-Hydro are calibrated offline, and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic-energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in Ouémé river on offline and fully-coupled modes with a Kling-Gupta Efficiency (KGE) around 0.70 and 076 respectively. In fully-coupled mode the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of 10 members for three rain seasons shows that the coupled model performance in terms of KGE is from 0.14 to 0.79. This ability in realistically reproducing observed discharge in the Ouémé-river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.

The study investigates how the rising global temperature will affect the spatial pattern of rainfall and consequently drought in West Africa. The precipitation and potential evapotranspiration variables that are obtained from the Rossby Centre regional atmospheric model (RCA4) and driven by ten (10) global climate models under the RCP8.5 scenario were used. The model data were obtained from the Coordinated Regional Climate Downscaling Experiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level. This study utilized four (4) indices: the standardized precipitation index, the precipitation concentration index, the precipitation concentration degree, and the precipitation concentration period over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Additionally, studying the impact of the four GWLs on consecutive dry days, consecutive wet days, and frequency of the intense rainfall events led to a better understanding of the spatiotemporal pattern of extreme precipitation. The results show that, at each GWL studied, the onset of rainfall comes 1 month earlier in the Gulf of Guinea compared to the historical period (1971–2000) with increasing rainfall intensity in the whole study domain, and the northeastern part of the study area becomes wetter. The rainfall concentration is uniformly distributed over the Gulf of Guinea and the Savanna zone for both the historical period and RCP8.5 scenario, while the Sahel zone which has shown an irregular concentration of rainfall for the historical period shows a uniform concentration of rainfall under all four GWLs.