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The frequency of flash floods resulting from heavy rainfall over West Africa has increased in recent years with serious socio‐economic consequences. Therefore, the need to utilize numerical weather prediction models to forecast heavy rainfall events reliably is also rising at many operational meteorological centres in West Africa. This paper evaluates the performance of the Consortium for Small‐scale Modelling (COSMO) model of the German Meteorological Services (DWD) in predicting rainfall over West Africa for high‐impact rainfall events that occurred between 19 and 26 August 2017. The paper aims to investigate the synoptic forcings modulating daily rainfall variability during that period. Results show that COSMO simulates adequately the spatio‐temporal variability of rainfall distribution over West Africa, though with inherent biases. COSMO displays a decreasing skill in producing spatial rainfall distribution as rainfall amounts tend to 30 mm and above. Additionally, areas of heavy rainfall, mostly about 100–300 km southwest of the core of the Africa Easterly Jet (AEJ), often coincide with areas of decreasing mean sea level pressure of at least 0.6 hPa and areas of increasing convective available potential energy of at least 500 J/kg. Although not in all cases, the trough of the Africa Easterly Wave (AEW) is always located to the east of these areas. We show that not every storm, especially east of the prime meridian, is associated with an AEW trough. COSMO is able to reproduce the atmospheric dynamics modulating the daily rainfall variability, in addition to capturing the daily propagation of the AEW trough, and the core of the AEJ. However, the reproducibility skill of the model in predicting atmospheric dynamics may not transform into the predictive skill of the model in producing rainfall. Nevertheless, operational forecasters may be able to determine likely areas of heavy rainfall by estimating the position of the AEJ core based on the position of areas of the least falling pressure from COSMO. Finally, the incorporation of the fractions skill score metric based on the neighbourhood approach could also assist operational forecasters to decide at which scale a severe weather alert can be issued. [ABSTRACT FROM AUTHOR]

Quantifying effective radiative forcing due to aerosol‐cloud interactions (EERFACI) remains a largely uncertain process, and the magnitude remains unconstrained in general circulation models. Previous studies focus on the magnitude of ERFACI arising from all cloud types, or examine it in the framework of dynamical regimes. Aerosol forcing due to aerosol‐cloud interactions in the HadGEM3‐GA7.1 global climate model is decomposed into several global observational cloud regimes. Regimes are assigned to model gridboxes and forcing due to aerosol‐cloud interactions is calculated on a regime‐by‐regime basis with a 20‐year averaging period. Patterns of regime occurrence are in good agreement with satellite observations. ERFACI is then further decomposed into three terms, representing radiative changes within a given regime, transitions between different cloud regimes, and nonlinear effects. The total global mean ERFACI is −1.03 Wm−2. When decomposed, simulated ERFACI is greatest in the thick stratocumulus regime (−0.51 Wm−2). Plain Language Summary: The effect of anthropogenic aerosol emissions on clouds is highly uncertain in climate models. Many previous attempts to reduce this uncertainty have focused on examining all cloud types as a whole. This work sets out a framework to examine one measure of aerosol‐cloud interactions when the effect is split by different cloud types. This framework is applied to the HadGEM3‐GA7.1 climate model. It is found that thick stratocumulus clouds exhibit the strongest aerosol‐cloud interactions, especially those found off the west coast of both North and South America, and West Africa. It is hoped that this will lead to a greater understanding of how these interactions manifest themselves in different cloud types, and that this methodology will promote the use of constraints on specific cloud types, to provide potentially greater reductions in the aforementioned uncertainty. Key Points: The majority of effective radiative forcing in HadGEM3‐GA7.1 comes from stratocumulus cloudsForcing from marine stratocumulus clouds is highly sensitive to aerosol perturbationsDecomposing radiative forcing by cloud regimes can be a useful technique to gain insights into climate model predictions [ABSTRACT FROM AUTHOR]

It is known that representing wetland dynamics in land surface modeling improves models' capacity to reproduce fluxes and land surface boundary conditions for atmospheric modeling in general circulation models. This study presents the development of the full coupling between the Noah‐MP land surface model (LSM) and the Hydrological Modeling and Analysis Platform (HyMAP) flood model in the NASA Land Information System and its application over the Inner Niger Delta (IND), a well‐known hot‐spot of strong land surface‐atmosphere interactions in West Africa. Here, we define two experiments at 0.02° spatial resolution over 2002–2018 to quantify the impacts of the proposed developments on simulating IND dynamics. One represents the one‐way approach for simulating land surface and flooding processes (1‐WAY), that is, Noah‐MP neglects surface water availability, and the proposed two‐way coupling (2‐WAY), where Noah‐MP takes surface water availability into account in the vertical water and energy balance. Results show that accounting for two‐way interactions between Noah‐MP and HyMAP over IND improves simulations of all selected hydrological variables. Compared to 1‐WAY, evapotranspiration derived from 2‐WAY over flooding zones doubles, increased by 0.8 mm/day, resulting in an additional water loss rate of ∼18,900 km3/year, ∼40% drop of wetland extent during wet seasons, and major improvement in simulated water level variability at multiple locations. Significant soil moisture increase and surface temperature drop were also observed. Wetland outflows decreased by 35%, resulting in a substantial Nash‐Sutcliffe coefficient improvement, from −0.73 to 0.79. It is anticipated that future developments in water monitoring and water‐related disaster warning systems will considerably benefit from these findings. Plain Language Summary: Many hydrological modeling systems are composed of land surface models (LSMs) capable of representing vertical land surface‐atmosphere interactions, and flood models capable of simulating the lateral redistribution of surface waters across a prescribed river network and floodplains. These models are oftentimes one‐way coupled, meaning that surface waters are neglected in the vertical water and energy balance. This study presents a generalized approach for the two‐way coupling (i.e., surface waters are taken into account in the vertical water and energy balance) between the Noah‐MP LSM and the HyMAP flood model. The proposed approach is tested over the Inner Niger Delta (IND), a well‐known hot‐spot of strong land surface‐atmosphere interactions in West Africa. To quantify the impact of the proposed development on the spatiotemporal variability of simulated hydrological variables, we performed two model experiments, one representing the one‐way approach, i.e., Noah‐MP neglects surface waters, and the proposed two‐way coupling, where surface water availability is taken into account. Results show that accounting for two‐way interactions between Noah‐MP and HyMAP over IND improves simulations of all selected hydrological variables. The generalized approach proposed here could be an asset to existing water monitoring systems and easily replicated over different domains or at the global scale. Key Points: The full coupling of land surface and flood models in NASA's Land Information System is described and evaluated over the Inner Niger DeltaIncreased evapotranspiration resulted in 18,900 km3/year water loss to the atmosphere, decreasing wetland outflows by 35% and extent by 40%Compared to an uncoupled system, the proposed implementation resulted in substantial improvements of all selected hydrological variables [ABSTRACT FROM AUTHOR]

It is well established that Africa is particularly exposed to climate extremes including heat waves, droughts, and intense rainfall events. How exposed Africa is to the co‐occurrence of these events is however virtually unknown. This study provides the first analysis of projected changes in the co‐occurrence of five such compound climate extremes in Africa, under a low (RCP2.6) and high (RCP8.5) emissions scenario. These changes are combined with population projections for a low (SSP1) and high (SSP3) population growth scenario, in order to provide estimates of the number of people that may be exposed to such events at the end of the 21st century. We make use of an ensemble of regional climate projections from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. This ensemble comprises five different Earth System Model/Regional Climate Model (ESM/RCM) combinations with three different ESMs and two RCMs. We show that all five compound climate extremes will increase in frequency, with changes being greater under RCP8.5 than RCP2.6. Moreover, populations exposed to these changes are greater under RCP8.5/SSP3, than RCP2.6/SSP1, increasing by 47‐ and 12‐fold, respectively, compared to the present‐day. Regions of Africa that are particularly exposed are West Africa, Central‐East Africa, and Northeast and Southeast Africa. Increased exposure is mainly driven by the interaction between climate and population growth, and the effect of population alone. This has important policy implications in relation to climate mitigation and adaptation. Plain Language Summary: It is well known that Africa is exposed to a range of different climate hazards including droughts, heat waves, and extreme rainfall events, which cause major social and economic suffering. It is, however, largely unknown how exposed the African population is to the co‐occurrence of such climate hazards. This is important because compound events will likely increase the suffering far and above that caused by individual climate hazards. In this study, we provide an analysis of potential changes in five different compound events, and the exposure of the African population to them, at the end of this century. Combining exposure to all compound events, the results show that compared to the present‐day, the exposure of the African population may increase by 12‐ and 47‐fold in the best‐ and worst‐case scenarios, respectively. The spatial distribution of changes shows that West Africa and central and eastern regions of Africa may be particularly exposed. Increased exposure is mainly caused by the interaction between climate and population growth, and the effect of population alone. These results imply that any policy response designed to reduce exposure needs to address both climatic and socioeconomic factors. Key Points: Five compound climate extremes are projected to be more frequent in Africa under both emission scenarios by the end of the centuryPopulations in West Africa, Central‐East Africa, and Northeast and Southeast Africa are projected to be particularly exposedIncreased exposure is mainly driven by the interaction between climate and population growth, and the effect of population alone [ABSTRACT FROM AUTHOR]

Representing the West African Monsoon is a major challenge in climate modeling because of complex mechanisms of interaction across scales. We study the monsoon precipitation response to a 4K increase in sea surface temperatures using an idealized meridional‐vertical (2D) model, which allows separating regional‐ and larger‐scale influences. The 2D simulations reproduce key features of Atmospheric Model Intercomparison Project simulations and indicate that, in response to sea surface temperature increase, large‐scale changes induce a decrease of Sahel precipitation, while regional‐scale mechanisms generate a southward shift of the rainband. Large‐scale changes moisten and warm the free troposphere, while regional circulation changes increase low‐level moisture. Precipitation in the control simulations accounts for much of the variance in precipitation change for both Atmospheric Model Intercomparison Project and 2D simulations. This response is strongly connected to the large‐scale drivers of temperature and moisture, with an additional spread associated with the formulation of the convective parameterization. Plain Language Summary: The Sahel region of West Africa receives most of its annual rainfall during the monsoon season. Projections of monsoon precipitation are important to the region's growing population, yet climate models disagree on the magnitude and direction of precipitation change in future climates. This study uses a simplified model of the West African monsoon, which we show behaves similarly to complex global climate simulations. Our model allows us to disentangle monsoon changes due to directly changing sea surface temperatures from changes due to the larger‐scale response to increased temperatures. We find that both play important roles in precipitation change, the direct forcing shifts the precipitation, while the large‐scale forcing produces drying. Processes that occur on small spatial scales play an important role in producing precipitation. We investigate how a few of these are represented in our model and discover that the change in precipitation is mostly dependent on how the large‐scale forcing produces precipitation in the current climate, with a spread that is connected to how these physical processes are represented. Our study shows the usefulness of a simplified monsoon model and increases understanding of how increasing sea surface temperatures alter the West African monsoon. Key Points: A 2D monsoon model produces similar changes to general circulation models in monsoon features when sea surface temperatures are increasedSouthward shift of the rainband is connected to regional forcing, while Sahel precipitation decrease is mainly driven by larger‐scale changePrecipitation change is strongly linked to large‐scale drivers of temperature and moisture with additional spread from parameterizations [ABSTRACT FROM AUTHOR]