Search

Climate finance stakeholders across Africa have long sought to understand the complex nature of the climate cash flow architecture. Distribution models are critical mathematical tools for generating the general characteristics of the cash flow that are used to inform policy decisions. In this paper, we undertake a comprehensive investigation of the climate funds flowing into sub-Saharan Africa (SSA) by suggesting candidate climate finance models that can be used by policy makers to design simulations that can aid in assessing climate risks, identify more efficient climate finance schemes, and obtain optimal control parameter settings under different scenarios. This is achieved by considering climate finance as a form of insurance. Different dimensions of the data are examined following four distinct groupings of the data set. This is to account for different views of risk by the various climate finance participants. The frequency and severity of the approved funds are analyzed with the aid of various mathematical distribution models and regression analyses. The dynamics of a given variable relative to varying scenarios are examined. The findings obtained confirm the presence of emerging risks induced by the nature of the flow. Central Africa for instance records the lowest theme-specific projects and mitigation finance accounts for more than half of all the climate funds while sectoral-wise, adaptation finance is majorly concentrated in the energy sector. The perpetuation of the observed inequalities across the themes, subregions and sector-specific climate-related projects portends grave consequences as these risks begin to accumulate over time. The Burr mixture model best fitted the approved projects' cost distribution and the factors driving the frequency and severity of approved projects ranged from Central Africa to projects in the general environment sector. One of the policy recommendations emphasized was the need to adopt a risk-adjusted distribution model for climate finance allocation in SSA. [ABSTRACT FROM AUTHOR]

Empirical evidence continues to show that climate change remains a threat to the stability of the hydrologic system. As the climate system interacts with the hydrologic cycle, one significant repercussion of global warming includes changes in water availability at both regional and local scales. Climate change adaptation is intrinsically difficult to attain due to the dynamic earth system and lack of a comprehensive understanding of future climate and its associated uncertainties. Mostly in developing countries, climate adaptation is hampered by scarcity of good quality and adequate hydro-meteorological data. This article provides a synopsis of the modelling chain applied to investigate the response of the hydrologic system under changing climate, which includes choosing the appropriate global climate models, downscaling techniques, emission scenarios, and the approach to be used in hydrologic modelling. The conventional criteria for choosing a suitable hydrological model are discussed. The advancement of emission scenarios including the latest Shared Socioeconomic Pathways and their role in climate modelling, impact assessment, and adaptation, are also highlighted. This paper also discusses the uncertainties associated with modelling the hydrological impacts of climate change and the plausible approaches for reducing such uncertainties. Among the outcomes of this review include highlights of studies on the commonly used hydrological models for assessing the impact of climate change particularly in the sub-Saharan Africa region and some specific reviews in southern Africa. Further, the reviews show that as human systems keep on dominating within the earth system in several ways, effective modelling should involve coupling earth and human systems models as these may truly represent the bidirectional feedback experienced in the modern world. The paper concludes that adequate hydro-meteorological data is key to having a robust model and effective climate adaptation measures, hence in poorly gauged basins use of artificial neural networks and satellite datasets have shown to be successful tools, including for model calibration and validation. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) concentrations in the troposphere are decreasing globally, with Africa as an exception. Yet, the region is understudied, with a deficit of ground-based observations and highly uncertain CO emission inventories. This paper reports multiyear observational CO data from the Mt. Kenya Global Atmosphere Watch (GAW) station, as well as summertime CO isotope observations from both Mt. Kenya and Nairobi, Kenya. The CO variability at Mt. Kenya is characterized by slightly increased concentrations during dry periods and a strong influence of short-term pollution events. While some data gaps and differences in instrumentation complicate decadal-scale trend analysis, a small long-term increase is resolved. High-pollution events are consistent with isotopic signal from downwind savanna fires. The isotope fingerprint of CO in Nairobi indicates an overwhelming dominance (near 100 %) of primary emissions from fossil fuel combustion with implications for air pollution policy. In contrast, the isotope signature of CO intercepted at the large-footprint Mt. Kenya region suggests that at least 70 % is primary sourced, with a predominance likely from savanna fires in Africa. Taken together, this study provides quantitative constraints of primary vs. secondary CO in the eastern Africa region and in urban Nairobi, with implications for satellite-based emission inventories as well as for chemical transport and climate modeling. [ABSTRACT FROM AUTHOR]

This paper assesses the performances of runoff (Ro) and runoff coefficient (α, the ratio of runoff to precipitation) simulations from 23 models during the historical period and then projects their future changes under the two emission scenarios (SSP1‐2.6 and SSP5‐8.5) in the Coupled Model Intercomparison Project. Compared with the UNH/GRDC Ro dataset (0.82 mm day−1), the multi‐model median (MME) Ro of 1995–2014 produces a comparable global mean magnitude (0.80 mm day−1), displays a similar spatial distribution of mean Ro, and also well captures the seasonal cycles at both global and basin scales. The global mean Ro of MME is projected to be increased by 0.01–0.02 mm day−1 (SSP1‐2.6) and 0.02–0.10 mm day−1 (SSP5‐8.5) during the twenty‐first century. Regional hotspots for strong increasing Ro appear across most areas of northern high latitudes, Africa, and southeastern Asia, with high inter‐model consistency. The global mean α is projected to be slightly decreased (−0.17 to −0.63%) except for the long‐term under the SSP5‐8.5 (0.26%). Although signs of changes in Ro vary with the river basins, periods, and scenarios, α in more than half (7 out of 12) river basins are projected to decrease. The uneven distributions of projected Ro changes over global land areas are related to the response of multiple hydroclimatic variables to the global warming. Given regions with inconstancy change signs of the projected precipitation, we speculate that changes in Ro are affected by more complicated hydroclimatic processes that warrant further investigations with physical‐based approaches. Plain Language Summary: Evidence has indicated that the terrestrial hydrology would be changed unevenly over global land areas under a warmer climate. Runoff (Ro) is one of the key components of the land water budget and it represents the natural freshwater resource on the earth. This study assesses the historical simulation performances and then projects future changes in Ro and α (the ratio of runoff to precipitation) under two emission scenarios (i.e., SSP1‐2.6 and SSP5‐8.5) based on the simulations from 23 CMIP6 models. The results show that the multi‐model median Ro during the historical period is highly consistent with the reference dataset and captures the seasonal variation in most river basins. During the twenty‐first century, the multi‐model median of global mean Ro is overall projected to increase in the future and the α would slightly decrease except for the long‐term under the SSP5‐8.5. While signs and magnitudes of projection changes depend on regions and basins, those changes are more evident under higher warming levels. The uneven distributions of projected changes of Ro over global land areas are related to the response of other land surface hydrological variables to the global warming induced by anthropogenic emissions in climate models. Key Points: The runoff (Ro) and runoff coefficient (α) in CMIP6 are assessed and their future changes are projected under two SSPs in global and basin scalesThe global mean magnitude, spatial pattern, and seasonal cycles over most river basins are well reproduced by multi‐model median RoThe global mean Ro (α) is projected to increase (decrease), but their projections vary with basins and scenarios [ABSTRACT FROM AUTHOR]

The role of climate change in future streamflow is still very uncertain, especially over semi-arid regions. However, part of this uncertainty can be offset by correcting systematic climate models' bias. This paper tries to assess how the choice of a bias correction method may impact future streamflow of the Cheliff-Mactaa-Tafna (CMT) rivers. First, three correction methods (quantile mapping (QM), quantile delta mapping (QDM), and scaled distribution mapping (SDM)) were applied to an ensemble of future precipitation and temperature coming from CORDEX-Africa, which uses two Representative Concentration Pathways: RCP4.5 and RCP8.5. Then, the Zygos model was used to convert the corrected time series into streamflow. Interestingly, the findings showed an agreement between the three methods that revealed a decline in future streamflow up to [−42 to −62%] in autumn, [+31% to −11%] in winter, [−23% to −39%] in spring, and [−23% to −41%] in summer. The rate of decrease was largest when using QM-corrected model outputs, followed by the raw model, the SDM-corrected model, and finally, the QDM-corrected model outputs. As expected, the RCP presents the largest decline especially by the end of the 21st Century. [ABSTRACT FROM AUTHOR]

The Nonhydrostatic ICosahedral Atmospheric Model (NICAM), a global model with an icosahedral grid system, has been under development for nearly two decades. This paper describes NICAM16-S, the latest stable version of NICAM (NICAM.16), modified for the Coupled Model Intercomparison Project Phase 6, High Resolution Model Intercomparison Project (HighResMIP). Major updates of NICAM.12, a previous version used for climate simulations, included updates of the cloud microphysics scheme and land surface model, introduction of natural and anthropogenic aerosols and a subgrid-scale orographic gravity wave drag scheme, and improvement of the coupling between the cloud microphysics and the radiation schemes. External forcings were updated to follow the protocol of the HighResMIP. A series of short-term sensitivity experiments were performed to determine and understand the impacts of these various model updates on the simulated mean states. The NICAM16-S simulations demonstrated improvements in the ice water content, high cloud amount, surface air temperature over the Arctic region, location and strength of zonal mean subtropical jet, and shortwave radiation over Africa and South Asia. Some long-standing biases, such as the double intertropical convergence zone and smaller low cloud amount, still exist or are even worse in some cases, suggesting further necessity for understanding their mechanisms, upgrading schemes and parameter settings, and enhancing horizontal and vertical resolutions. [ABSTRACT FROM AUTHOR]

In this paper, daily characteristics of the Central Africa rainfall are assessed using the regional model REMO in the framework of contributions to the CORDEX-Africa project. The model is used to dynamically downscale two global climate models (MPI-ESM-LR and EC-EARTH) for the present (1981–2005) and future (2041–2065, 2071–2095) climate under the Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5 emission scenarios. A substantial spatio-temporal variability of the daily precipitation characteristics is obtained, as well as varying inferences for individual indices. For the present days, both REMO's runs capture reasonably well the mean seasonal rainfall, the frequency of wet days, the threshold of extreme rainfall, and the cumulative frequency of daily rainfall. The model better simulates the frequency of rainy days than their intensity. It is found that origins of model biases differ as a function of regions. Over the continent, boundary conditions tend to influence the spatial distribution of rainfall whereas over oceanic and coastal regions, REMO's physics seems to dominate over the boundary forcing. The projected frequency of wet days shows a decrease along the twenty-first century over most part of the continent. Throughout the century, all scenarios of REMO decrease the rate of rainfall with increasing intensity, and which will be noticeable in the Sahelian region at late twenty-first century. Furthermore, the extreme event thresholds decrease over Sahelian regions and increase along the coastal regions. [ABSTRACT FROM AUTHOR]

In this paper in three parts, climate change is approached by dealing with the three sides from which the danger comes: (i) global warming, (ii) increasing climate variability, (iii) more (and possibly more severe) meteorological and climatological extreme events. These are the three panels of this triptych review and the right panel on climate extremes and society's responses, including mitigation attempts as part of preparedness of African farmers, is this part. The occurrence of more (and possibly more severe) extreme meteorological/climatological events, as another likely consequence of climate change, is discussed, reviewing the literature and dealing for Africa with recent droughts and famines. It appears that there is more than sufficient proof that the numbers of disasters have risen globally, and on average at an increasing rate, over the last half a century, with more evidence in the later decades. Extreme hazards have a shorter recurrence time but whether they also have become more severe cannot be easily determined. This is due to developments in observations, populations and vulnerabilities and lack of developments in climate models. Only for increased temperature related disasters, severity has clearly become larger. However, recent more realistic calculations appear to suggest that there has been little change in drought over the past 60 years. In physical terms, there is also little or no evidence of increased severity of floods over the past century. Increasing farmer preparedness will be an important part of better responses to these conditions. The traditional response farming as to droughts, floods (annual recession and recurrent occasional ones), strong winds and other serious disasters should be among starting points. At the end of this paper, the contributions that tropical agriculture can make to reduce greenhouse gases (GHGs) in win-win situations are also dealt with. Soil carbon sequestration has a higher mitigation potential than emission reductions in African agriculture, although both may be important. These are best achieved under management systems with higher carbon density, as well as improved soil conservation. Agroforestry, assisted natural regeneration, forest rehabilitation, forest gardens, and improved forest fallow projects should all be eligible under the Clean Development Mechanism. Throughout the paper text boxes are used that illustrate local conditions that must be taken into account to understand the impacts/consequences of climate change for African farmers and how they may cope with them. [ABSTRACT FROM AUTHOR]

In this paper in three parts, climate change is approached by dealing with the three sides from which the danger comes: (i) global warming, (ii) increasing climate variability, (iii) more (and possibly more severe) meteorological and climatological extreme events. These are the three panels of this triptych review and this left panel is about (ii). This second panel starts with a compelling review of the present situation of food security, referring to African examples to improve the situation. Then the influence is discussed that the El Niño Southern Oscillation (ENSO) has on increasing climate variability as a consequence of climate change. It is indicated that, to date, climate models have been developed with little knowledge of agricultural systems dynamics. On the other hand one can illustrate that agricultural policy analysis has been conducted with little knowledge of climate dynamics. As a direct consequence of capricious behaviour of particularly rainfall in West Africa, the adaptation of its farmers has lagged behind enormously. This statement is valid for most farmers in sub-Saharan Africa. Within the climate science community there is an emerging effort to make findings more suitable for decision making, but as yet there is little consensus as to how data may be relied upon for decision making. Then a lot of attention is paid to how response farming, that is thoroughly defined, can play an important role in coping with the consequences of climate variability. Response farming is often limited envisaging rainfall events, but coping with weather and climate (and often soil) disasters as well as using windows of weather and climate (and often soil) opportunities are other forms of responding to weather and climate (and often soil) realities. Services such as in advice on design rules on above and below ground microclimate management or manipulation, with respect to any appreciable microclimatic improvement: shading, wind protection, mulching, other surface modification, drying, storage, frost protection and so on belong to such "response farming" agrometeorological services. Ideally, to get optimal preparations, farmers get advisories/services through extension intermediaries, backed by scientists, to properly understand decision options through discussions supported by economic analyses. Throughout the paper text boxes are used that illustrate local conditions that must be taken into account if one wants to understand the impacts/consequences of climate change for African farmers and how they may cope with them. [ABSTRACT FROM AUTHOR]

There are increasing efforts to use climate model output for adaptation planning, but meanwhile there is often limited understanding of how models represent regional climate. Here we analyze the simulation in global coupled climate models of a key rainfall-generating mechanism over southern Africa: tropical temperate troughs (TTTs). An image-processing algorithm is applied to outgoing longwave radiation data from satellites and models to create TTT event sets. All models investigated produce TTTs with similar circulation features to observed. However, there are large differences among models in the number, intensity, and preferred longitude of events. Five groups of models are identified. The first group generates too few TTTs, and relatively dry conditions over southern Africa compared to other models.Asecond group generates more TTTs and wet biases. The contrast between these two groups suggests that the number of TTTs could explain intermodel variations in climatological rainfall. However, there is a third group of models that simulate up to 92% more TTTs than observed, but do not have large rainfall biases, as each TTT event is relatively weak. Finally, there are a further two groups that concentrate TTTs over the subcontinent or the ocean, respectively. These distinctions between models are associated with the amount of convective activity in the Congo Basin, the magnitude of moisture fluxes into southern Africa, and the degree of zonal asymmetry in upper-level westerly flow. Model development focused on tropical convection and the representation of orography is needed for improved simulation of TTTs, and therefore southern African rainfall. [ABSTRACT FROM AUTHOR]

NICAM, a nonhydrostatic global atmospheric model with an icosahedral grid system, has been developed for nearly two decades. This paper describes NICAM16-S, the latest stable version of NICAM (NICAM.16) modified for Coupled Model Intercomparison Project Phase 6 (CMIP6). Major updates from NICAM.12, a previous version used for climate simulations, include updates of a cloud microphysics scheme and a land model, an introduction of natural and anthropogenic aerosols and a subgrid-scale orographic gravity wave drag, and improvement of coupling between cloud microphysics and radiation schemes. External forcings were updated to follow a protocol of CMIP6 High Resolution Model Intercomparison Project (HighResMIP). A series of short-term sensitivity experiments were performed to check and understand impacts of the model updates on the simulated mean states. Improvements in the ice water content, the high cloud amounts, the surface air temperature over the Arctic region, the location and the strength of zonal mean subtropical jet, and shortwave radiation over the Africa and the South Asia were found in the NICAM16-S simulations. Some long-standing biases such as the double intertropical convergence zone and smaller low cloud amounts still exist or even worsen in some cases, suggesting further necessity for understanding their mechanisms and upgrading schemes and/or their parameter settings as well as for enhancing horizontal and vertical resolutions. [ABSTRACT FROM AUTHOR]

Convection over the western equatorial Indian Ocean (WEIO) is strongly linked to precipitation over Africa and Australia but is poorly represented in current climate models, and its observed seasonal cycle is poorly understood. This study investigates the seasonal cycle of convection in the WEIO through rainfall and cloud measurements. Rainfall shows a single annual peak in early austral summer, but cloud proxies identify convective activity maxima in both boreal and austral summer. These diverging measures of convection during boreal summer are indicative of a reduction in the intensity of precipitation associated with a given cloud regime or cloud-top height during this time of year but an increase in the overall occurrence of high-top clouds and convectively active cloud regimes. The change in precipitation intensity associated with regimes is found to explain most of the changes in total precipitation during the period from May to November, whereas changes in the occurrence of convective regimes explains most of the changes throughout the rest of the year. The reduction in precipitation intensities associated with cloud regimes over theWEIOduring boreal summer appears to be related to large-scale monsoon circulations, which suppress convection through forcing air descent in the midtroposphere and increase the apparent occurrence of convectively active cloud regimes through the advection of high-level cloud from monsoon-active areas toward the WEIO region. [ABSTRACT FROM AUTHOR]

Climate models are basic tools to obtain reliable estimates of future climate change and its effects on the water resources and agriculture in given basin. However, all climate models are not equally valuable for all areas. Therefore, determining the most appropriate climate model for a specific study area is essential. This study examines the performance of 10 CORDEX-AFRICA-220 Regional Climate Models (RCMs), three downscaling institutional based ensembles mean (Reg ensemble, CCLM ensemble and REMOO ensemble) and the multi-model ensemble mean. The models were evaluated based on their ability in replicating the seasonal and annual rainfall, minimum and maximum temperature and inter-annual variability for the period of 1986–2005 using statistical metrics such as BIAS, Root Mean Square Error (RMSE), Pearson correlation coefficient (r), coefficient of variation (CV), Kling Gupta Efficiency (KGE) and Taylor diagram. The findings indicated that HadREMOO, MPI-Reg4-7, HadReg4-7, Reg ensemble, and multi-model ensemble mean performed relatively better in representing the mean annual observed rainfall at the Adiramets, Debarik Ketema, Niguse Maystebri, and Zarima stations, respectively. Whereas, NorESM-CCLM, MPI-CCLM, NorESM-Reg4-7, and NorESM-REMOO exhibited a weak performance in reproducing the observed mean annual rainfall at the Adiramets, Debarik Ketema Niguse, Maystebri, and Zarima stations, respectively. Similarly, RCMs generally capture the mean annual maximum temperature of climatic stationsof Zarima subbasin well. Specifically, the MPI-Reg4-7 simulation performs well in representing the mean annual observed maximum temperature at Adiramets and Maytsebri stations, while the Debarik and Ketema Niguse stations exhibit superior performance in the HadReg4-7 simulation and the Zarima station shows better representation in the CCLM ensemble simulations. The majority of the model simulations exhibit good representation of mean annual minimum temperature at Adiramets, Debarik, and Zarima stations. Specifically, CanESM-RCM, HadReg4-7, REMOOensemble, multi-model ensemble, and Regensemble simulations perform better at Adiramets, Debarik, Ketema niguse, Maystebri and Zarima stations respectively. This suggests that these models may have biases or shortcomings in capturing the temperature values in the subbasin. Furthermore, NorESM-CCLM at Adiramets, Ketema niguse, and Zarima stations, NorESM-REMOO at Debarik station, and HadReg4-7 at Maystebri station demonstrate poor performance in representing the observed mean minimum temprature. Majority of the RCMs, all institutional based ensemble means and the multi-model ensemble mean simulations overestimate the observed mean annual rainfall of the Zarima subbasin with minimum bias of 0.02 mm at Ketema niguse HadReg4-7and maximum bias of 2.81 mm at Maytsebri MPI-CCLM simulation. Similarly, HadReg4-7 simulation of Ketama Niguse MPI-CCLM showed a minimum 0.02 mm and Maytsebri simulation kiremit season mean rainfall showed a maximum bias of and 2.99 mm. Regarding mean annual and kiremit season maximum and minimum temperature of the Zarima subbasin were overestimated by majority of the simulation and the ensemble means. The correlation (r) of observed and model simulated mean annual and kiremit season rainfall was strong (0.60–0.79) and very strong (0.80–0.99) in the majority of the simulations except Ketema niguse station mean annual and kiremit season rainfall simulations of MPI-REMOO, NorESM-Reg4-7; Debarik station kiremit season rainfall of NorESM-CCLM and NorESM-REMOO, MPI-Reg4-7 and MPI-REMOO, which showed moderate correlation. The performance of the RCMs, institutional based ensemble means and multi-model ensemble mean were different in statistical metrics (BIAS, RMSE, r, CV and KGE) and Taylor diagram. Among the simulations and ensemble means, the multi-model ensemble mean was superiors in two or more of statistical metrics at each station of the Zarima subbasin except Maytsebri station kiremit season rainfall, where the CCLM ensemble was better. Consistently, the Taylor diagram showed that the multi-model ensemble was better in the replication of the areal annual and kiremit season rainfall, maximum and minimum temperature of the subbasin. This finding evidenced that selecting the best RCMs and ensemble mean is necessary for climate projection and climate change impact assessment study. [ABSTRACT FROM AUTHOR]

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions. [ABSTRACT FROM AUTHOR]

Differences in within-species phenology and structure are controlled by genetic variation, as well as topography, edaphic properties, and climatic variables across the landscape, and present important challenges to species differentiation with remote sensing. The objectives of this paper are as follows: 1) to evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach in discriminating ten common African savanna tree species and 2) to compare the results with the traditional SAM classifier based on a single endmember per species. The canopy spectral reflectance of the tree species ( Acacia nigrescens, Combretum apiculatum , Combretum imberbe, Dichrostachys cinerea, Euclea natalensis, Gymnosporia buxifolia, Lonchocarpus capassa, Pterocarpus rotundifolius, Sclerocarya birrea, and Terminalia sericea) was extracted from airborne hyperspectral imagery that was acquired using the Carnegie Airborne Observatory system over Kruger National Park, South Africa, in May 2008. This study highlights three important phenomena: 1) Intraspecies spectral variability affected the discrimination of savanna tree species with the SAM classifier; 2) the effect of intraspecies spectral variability was minimized by adopting the multiple-endmember approach, e.g., the multiple-endmember approach produced a higher overall accuracy (mean of 54.5% for 20 bootstrapped replicates) when compared to the traditional SAM (\mean overall accuracy = 20.5\%); and 3) targeted band selection improved the classification of savanna tree species (the mean overall percent accuracy is 57% for 20 bootstrapped replicates). Higher overall classification accuracies were observed for evergreen trees than for deciduous trees. [ABSTRACT FROM AUTHOR]

The need for accurate characterization of the land surface as boundary conditions in climate models has been recognized widely in the climate modeling community. A large number of land-cover datasets are currently used in climate models either to better represent surface conditions or to study the impacts of surface changes. Deciding upon land-cover datasets can be challenging because the datasets are made with different sensors, ranging methodologies, and varying classification objectives. A new statistical measure Q was developed to evaluate land-cover datasets in land–climate interaction research. This measure calculates biophysical precision of land-cover datasets using 1-km monthly Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) product. This method aggregates within-class biophysical consistency, calculated as LAI variation, across a study domain and over multiple years into a single statistic. A smaller mean Q value for a land-cover product indicates more precise biophysical characterization within the classes. As an illustration, four land-cover products were assessed in the East Africa region: Global Land Cover 2000 (GLC2000), MODIS land cover, Olson Global Ecosystems (OGE), and Land Ecosystem–Atmosphere Feedback (LEAF) model. The evaluation was conducted at three different spatial scales corresponding to 30 × 30, 50 × 50, and 100 × 100 km quadrates. The Q measure found that GLC2000 ranked higher compared to the other three land-cover products for every quadrate size. For the 30 × 30 km quadrate size GLC2000 was significantly better than LEAF, which is currently used in the Regional Atmospheric Modeling System. The statistic ranks MODIS land cover above OGE, which is above LEAF. As quadrate size increases, differences between Q decrease indicating greater uncertainty at coarser resolution. The utility of the measure is that it can be applied to any continuous parameter over any scale (space or time) to evaluate the biophysical precision of any land-cover dataset. [ABSTRACT FROM AUTHOR]

This study explores coupled land–atmosphere data assimilation (DA) for improving weather and hydrological forecasts by assimilating soil moisture (SM) data. This study integrates a land DA component into a global atmospheric DA system of the Nonhydrostatic ICosahedral Atmospheric Model and the local ensemble transform Kalman filter (NICAM-LETKF) and performs both strongly and weakly coupled land–atmosphere DA experiments. We explore various types of coupled DA experiments by assimilating atmospheric observations and SM data simultaneously. The results show that analyzing atmospheric variables by assimilating SM data improves the SM analysis and forecasts and mitigates a warm bias in the lower troposphere where a dry SM bias exists. On the other hand, updating SM by assimilating atmospheric observations has detrimental impacts due to spurious error correlations between the atmospheric observations and land model variables. We also find that assimilating SM by strongly coupled DA is beneficial in the Sahel and equatorial Africa from May to October. These regions are characterized by seasonal variations in the precipitation patterns and benefit from updates in the atmospheric variables through SM DA during periods of increased precipitation. Additionally, these regions coincide with those identified in the previous studies, where a global initialization of SM would enhance the prediction skill of seasonal precipitation. [ABSTRACT FROM AUTHOR]

The seasonality of circumnavigation of Madden–Julian Oscillation (MJO) events is examined using 42 years of observations, reanalysis, and global model simulations. MJO events are most likely to propagate across the Atlantic Ocean, Africa and back to the equatorial Indian Ocean relatively unweakened during March–April–May and to a lesser extent during September–October–November. During these seasons, referred to as the "long‐rain" and "short‐rain" periods of East African Monsoon (EAM), precipitation is near the equator and extends farthest east toward the Indian Ocean. Moisture budget analysis of a circumnavigating MJO event under real and hypothetical seasonally varying background conditions indicates that the seasonal zonal movement of the zonal component of the background circulation regulates the moistening of MJO crossing from Eastern Africa to the Indian Ocean. Ensembles of Energy Exascale Earth System Model simulations of the MJO event under idealized seasonally varying background state confirm the observed drawbridge‐like role of the EAM in the propagation of MJO. Plain Language Summary: The Madden–Julian Oscillation (MJO) has been recognized as an important source of predictability in the tropics and globally. This is particularly true for strong and circumnavigating events that can initiate a subsequent MJO event cycle. In this work, we show that circumnavigation is regulated by the East African Monsoon. Through analysis of observations and global model simulations, we show circumnavigation is most likely in spring and fall seasons when precipitation associated with the East Africa Monsoon is near the equator and extends farthest east toward Indian Ocean. In other words, by creating favorable moisture and circulation conditions the monsoon serves as a drawbridge for the crossing of MJO events across Africa to Indian Ocean. Key Points: Circumnavigation of Madden–Julian Oscillation (MJO) is most likely in during spring and fall when East African Monsoon (EAM) is located near the equatorAnalysis of moisture budget indicates the zonal movement of the EAM favors the crossing of MJO events onto Indian OceanRealistic and idealized simulations using atmospheric model component of Exascale Earth System Model (E3SM) confirm this seasonality MJO precipitation [ABSTRACT FROM AUTHOR]

Africa is highly vulnerable to climate change but emits a small portion of global greenhouse gases. Additionally, decarbonization might lead to a 'climate penalty' whereby reductions in cooling aerosols offset temperature benefits from CO2 reductions for several decades. However, climate change impacts conditions other than temperatures, including precipitation. Using the NASA Goddard Institute for Space Studies climate model, we find that although African emissions cuts have weak impacts on projected African temperatures, they significantly impact rainfall. Whereas business-as-usual increasing emissions lead to substantial drying over tropical Northern Hemisphere Africa during local summer, that drying is essentially eliminated under a sustainable development pathway. The reduction in cooling aerosols is responsible for ~33–90% of the avoided drying in our model, with the remainder largely attributable to reduced absorbing aerosols. African policy choices may therefore greatly reduce regional African summer drying, giving parts of Africa substantial leverage over their own climate and air quality future. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SAF) is among the most exposed climate change hotspots and is projected to experience severe impacts across multiple economical and societal sectors. For this reason, producing reliable projections of the expected impacts of climate change is key for local communities. In this work we use an ensemble of 19 regional climate model (RCM) simulations performed in the context of the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa and a set of 10 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) that were used as the driving GCMs in the RCM simulations. We are concerned about the degree to which RCM simulations are influenced by their driving GCMs, with regards to monthly precipitation climatologies, precipitation biases and precipitation change signal, according to the Representative Concentration Pathway (RCP) 8.5 for the end of the 21st century. We investigate the degree to which RCMs and GCMs are able to reproduce specific climatic features over SAF and over three sub-regions, namely the greater Angola region, the greater Mozambique region, and the greater South Africa region. We identify that during the beginning of the rainy season, when regional processes are largely dependent on the coupling between the surface and the atmosphere, the impact of the driving GCMs on the RCMs is smaller compared to the core of the rainy season, when precipitation is mainly controlled by the large-scale circulation. In addition, we show that RCMs are able to counteract the bias received by their driving GCMs; hence, we claim that the cascade of uncertainty over SAF is not additive, but indeed the RCMs do provide improved precipitation climatologies. The fact that certain bias patterns during the historical period (1985–2005) identified in GCMs are resolved in RCMs provides evidence that RCMs are reliable tools for climate change impact studies over SAF. [ABSTRACT FROM AUTHOR]

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a multiple atmosphere multiple land (MAML) framework in the superparamaterized version of E3SM (SP‐E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud‐resolving scale and their interactions with atmosphere. Comparing to the standard SP‐E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., multiple atmosphere single land (MASL)), the impact of MAML on the strength of land‐atmosphere coupling is limited, partly because the current implementation mainly facilitates one‐way coupling between the cloud‐resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP‐E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (P‐E) is primarily driven by the change in large‐scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P‐E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P‐E by decreasing the NGMS. Finally, future development in the MAML framework is discussed. Plain Language Summary: Land‐atmosphere interactions such as soil moisture‐precipitation feedback occur at a wide range of spatial scales. For example, spatial variability of surface fluxes such as radiation and precipitation can influence surface latent and sensible heat fluxes, which further influence turbulent mixing processes in the boundary layer and cloud and precipitation. Current global climate models (GCMs) have difficulties in representing land‐atmosphere interactions at scales smaller than the GCM grid (subgrid scales). To meet this challenge, we employ a novel framework, called multiple atmosphere multiple land (MAML), in a superparamaterized version of E3SM (SP‐E3SM) in which a cloud resolving model is embedded within each GCM grid to better resolve clouds and convection. MAML explicitly simulates the subgrid variabilities of land states and fluxes at scale of ∼1 km and provides feedback to the atmosphere. The use of MAML is shown to have a limited effect on the strength of land‐atmosphere coupling due to the current one‐way subgrid land‐atmosphere interaction setup. Despite the limited effect, MAML increases the rainfall in India, Amazon, and Central Africa, which reduces the dry bias in the model. Key Points: A multiple atmosphere multiple land (MAML) framework of land‐atmosphere coupling is implemented in the super‐parameterized E3SM (SP‐E3SM)MAML increases precipitation in India, Central Africa, and Amazon by increasing water vapor and hence large‐scale moisture convergenceMAML's impact on land‐atmosphere interactions is limited by the current setup of one‐way coupling on cloud‐resolving scales [ABSTRACT FROM AUTHOR]

In boreal winter, strong upper‐level midlatitude troughs across the Atlantic–Africa–southwestern Asia sector generate substantial tropical–extratropical interaction and have become recognized as important factors in some extreme weather events. As such, they represent important dynamic features to understand and capture in weather forecasts, as well as in climate models for projections on longer timescales. Here, we empirically study the 20% of winter days with strongest trough signatures during 1982–2020 at each longitude across the sector, and show that the trough impact over northern Africa, most notably in central parts, is particularly strong in magnitude, low‐latitude extent and persistence, leading to the characterization of a northern Africa mode of several‐days weather fluctuation. Weather conditions that follow strong troughs from the eastern Atlantic to the Central Mediterranean include: (i) a warming tendency across much of northern Africa, generally of several Celsius magnitude ahead of the trough, and >1°C even extending to the south of 10° N in central parts and continuing eastward until the Ethiopian Highlands; (ii) precipitation development further north than normal across northern tropical Africa, especially strong over longitudes corresponding to a northward extension of the main Congo rain belt. The intertropical discontinuity and low‐level heat low are also shifted significantly north, with the complex of anomalies persisting for several days, beyond the timescale of the trough. For context, at all other trough longitudes across the sector, a warming signal does emerge (statistically significant), but with much shorter persistence (2–3 days), smaller magnitude and extending southward clearly only to 15–20° N. Mid‐level tropical plumes of moisture are also typically present for strong troughs from the eastern Atlantic to southwestern Asia, and these alone can lead to weather extremes. However, low‐level warming and mid‐level moistening are uniquely juxtaposed at low latitudes over central Africa, where a near‐equatorial signature develops. [ABSTRACT FROM AUTHOR]

The Paris Agreement of COP21 set a goal of holding global average temperature increases to below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C. This is particularly relevant for the African context where temperatures are likely to warm faster than the global average and where the magnitude of change will be regionally heterogeneous. Most studies that provide information over Africa under specific global warming levels have used data from global models, however global models poorly resolve local scale forcing (e.g. topography) nor the internal climate variability of a region. Although downscaling using regional climate models can address these issues, we found only one paper that had used downscaled data for GWL studies over Africa. During 2018 the CORDEX-Africa campaign investigated the impact of 1.5 and 2 degrees of global warming over many regions of sub-Saharan Africa and compiled the results for a special issue of nine papers in ERL. This paper reports on some of the key regional findings of the analysis of 25 CORDEX downscalings, including the impact of the extra 0.5 degrees of warming between 1.5 and 2 degrees on particular extremes and the differences noted between the driving GCMs and downscaled results. We also briefly discuss the impact of the papers in the IPCC SR15 and their contribution to the development of adaptation and mitigation policies. [ABSTRACT FROM AUTHOR]

Organic aerosols are predominantly emitted from biomass burning and biofuel use. The fraction of these aerosols that strongly absorbs ultraviolet and short visible light is referred to as brown carbon (BrC). The life cycle and the optical properties of BrC are still highly uncertain, thus contributing to the uncertainty of the total aerosol radiative effect. This study presents the implementation of BrC aerosols in the Tropospheric Aerosols for ClimaTe In CNRM (TACTIC) aerosol scheme of the atmospheric component of the Centre National de Recherches Météorologiques (CNRM) climate model. This implementation has been achieved using a BrC parameterization based on the optical properties of. Several simulations have been carried out with the CNRM global climate model, over the period of 2000–2014, to analyze the BrC radiative and climatic effects. Model evaluation has been carried out by comparing numerical results of single-scattering albedo (SSA), aerosol optical depth (AOD), and absorption aerosol optical depth (AAOD) to data provided by Aerosol Robotic Network (AERONET) stations, at the local scale, and by different satellite products, at the global scale. The implementation of BrC and its bleaching parameterization has resulted in an improvement of the estimation of the total SSA and AAOD at 350 and 440 nm. This improvement is observed at both the local scale, for several locations of AERONET stations, and the regional scale, over regions of Africa (AFR) and South America (AME), where large quantities of biomass burning aerosols are emitted. The annual global BrC effective radiative forcing (all-sky conditions) has been calculated in terms of both aerosol–radiation interactions (ERFari , 0.029 ± 0.006 W m -2) and aerosol–cloud interactions (ERFaci , - 0.024 ± 0.066 W m -2). This study shows, on an annual average, positive values of ERFari of 0.292 ± 0.034 and 0.085 ± 0.032 W m -2 over the AFR and AME regions, respectively, which is in accordance with the BrC radiative effect calculated in previous studies. This work also reveals that the inclusion of BrC in the TACTIC aerosol scheme causes a statistically significant low-level cloud fraction increase over the southeastern Atlantic Ocean during the burning season partially caused by a vertical velocity decrease at 700 hPa (semi-direct aerosol effect). Lastly, this study also highlights that the low-level cloud fraction changes, associated with more absorbing biomass burning aerosols, contribute to an increase in both solar heating rate and air temperature at 700 hPa over this region. [ABSTRACT FROM AUTHOR]

In developing countries with data scarcity challenges, an integrated approach is required to enhance the estimation of streamflow variability for the design of water supply systems, hydropower generation, environmental flows, water allocation and pollution studies. The Flow Duration Curve (FDC) was adopted as a tool that is influenced by topography, land use land cover, discharge and climate change. The data from Global Climate Model (GCM) projections, based on Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 climate scenarios, were used as input data for the SWAT model for the simulation of streamflow. The FDCs were then derived from the simulated streamflow. The FDC for RCP 4.5 showed insignificant differences, whilst for RCP 8.5 it showed an increase of 5–10% in FDC from the baseline period, which is likely to increase the hydropower generation potential with some considerable streamflow variability. The integrated approach of utilizing FDC, GIS and SWAT for the estimation of flow variability and hydropower generation potential could be useful in data scarce regions. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modeling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behavior of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (October–March), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensembles exhibited improved performance compared to their forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher-resolution regional climate simulations. The CMIP6 ensemble displayed a similar behavior to CMIP5, but reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angola Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic processes that take place. Improvements in observational networks (both in situ and satellite) as well as continued advancements in high-resolution modeling will be critical, in order to develop a robust assessment of climate change for southern Africa. [ABSTRACT FROM AUTHOR]

From June to October, southern Africa produces one-third of the global biomass burning (BB) emissions by widespread fires. BB aerosols are transported westward over the south-eastern Atlantic with the mid-tropospheric winds, resulting in significant radiative effects. Ascension Island (ASI) is located midway between Africa and South America. From June 2016 to October 2017, a 17-month in situ observation campaign on ASI found a low single-scattering albedo (SSA) as well as a high mass absorption cross-section of black carbon (MAC BC), demonstrating the strong absorbing marine boundary layer in the south-eastern Atlantic. Here we investigate the monthly variations of critical optical properties of BB aerosols, i.e. SSA and MAC BC , during the BB seasons and the driving factors behind these variations. Both SSA and MAC BC increase from June to August and decrease in September and October. The average SSA during the BB seasons is 0.81 at 529 nm wavelength, with the highest mean ∼ 0.85 in October and the lowest ∼ 0.78 in August. The absorption enhancement (Eabs) derived from the MAC BC shows similar trends with SSA, with the average during the whole of the BB seasons at ∼ 1.96 and ∼ 2.07 in 2016 and 2017, respectively. As the Eabs is higher than the ∼ 1.5 commonly adopted value by climate models, this result suggests the marine boundary layer in the south-eastern Atlantic is more absorbing than model simulations. We find the enhanced ratio of BC to CO (ΔBC/ΔCO , equal to BC/ΔCO as the BC background concentration is considered to be 0) is well correlated with SSA and MAC BC , providing a simple way to estimate the aerosol optical characteristics in the south-eastern Atlantic. The exponential function we proposed can approximate SSA and MAC BC with BC/ΔCO , and when BC/ΔCO is small it can capture the rapid growth of SSA as BC/ΔCO decreases. BC/ΔCO is influenced by combustion conditions and aerosol scavenging. From the analysis of the location of BB, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of the BB plume, we conclude that the increase in BC/ΔCO from June to August is likely to be caused by burning becoming more flaming. The reduction in the water content of fuels may be responsible for the change in the burning conditions from June to August. The decrease in BC/ΔCO in September and October may be caused by two factors, one being a lower proportion of flaming conditions, possibly associated with a decrease in mean surface wind speed in the burning area, and the other being an increase in precipitation in the BB transport pathway, leading to enhanced aerosol scavenging, which ultimately results in an increase in SSA and MAC BC. [ABSTRACT FROM AUTHOR]

Abstract: The role of ocean feedback on monsoon variations at 6 and 9.5kyr Before Present (BP) compared to present-day is investigated by using sets of simulations computed with the IPSL–CM4 ocean–atmosphere coupled model and simulations with the atmospheric model only with the SST prescribed to the present-day simulation for the coupled model. This work is complementary to the study by Marzin and Braconnot (2009) who have analyzed in detail the response of Indian and African monsoons to changes in insolation at 6 and 9.5kyr BP using the IPSL–CM4 coupled model. The monsoon rainfall was intensified at 6 and 9.5kyr BP compared to 0kyr BP as a result of the intensified seasonal cycle of insolation in the Northern Hemisphere. In this paper, the impact of the ocean feedback is analysed for the Indian, East-Asian and African monsoons. The response of the ocean to the 6 and 9.5kyr BP insolation forcing shares similarities between the two periods, but we highlight local differences and a delay in the response of the surface ocean between 6 and 9.5kyr BP. The ocean feedback is shown to be positive for the early stage of the African monsoon. A dipole of SST in the tropical Atlantic favouring the earlier build-up of the monsoon in the 6 and 9.5kyr BP coupled simulations. However, it is strongly negative for the Indian and East Asian monsoons, and of stronger amplitude at 9.5 than at 6kyr BP over India. In these Asian regions, the convection is more active over the ocean than over the continent during the late monsoon season due to the ocean feedback. The results are consistent with previous studies about 6kyr BP climate. In addition, it is shown that the ocean feedback is not sufficient to explain the relative amplifications of the different monsoon systems within the three periods of the Holocene, but that the mechanisms such as the effect of the precession on the seasonal cycle of monsoons as discussed in Marzin and Braconnot (2009) are more plausible. [Copyright &y& Elsevier]

The Botswana High is an important component of the regional atmospheric circulation during austral spring, summer and autumn. While the high tends to be stronger during El Niño and weaker during La Niña, its direct response to El Niño Southern Oscillation (ENSO) remains unknown. To that end, a variable resolution global climate model (Model Prediction Across Scales version 7, hereafter MPAS) is applied with relatively high resolution (48-km grid spacing) over Southern Africa and a coarser resolution (240-km grid spacing) over the rest of the globe for the study period 1980–2010. The first model experiment uses observed sea surface temperatures (SSTs) everywhere during the study period, while the second experiment uses observed SSTs everywhere except over the Pacific Ocean, where monthly climatological SSTs are imposed. The model results were validated against satellite data (Global Precipitation Climatology Project, GPCP) and reanalysis datasets (Climate Forecast System Reanalysis, CFSR; European Centre for Medium-Range Weather Forecasts version 5, ERA5). The results of the study show that the MPAS model gives a credible simulation of the temporal variability of the Botswana High, the seasonal rainfall and 500-hPa geopotential heights over Southern Africa. In the absence of ENSO forcing, the amplitude of the Botswana High variability reduces but the signal of the variability remains. Hence, this study shows that ENSO enhances the strength of the Botswana High but does not aid in the formation of the high. [ABSTRACT FROM AUTHOR]

Biocrust sustainability relies on dew and rain availability. A study of dew and rain resources in amplitude and frequency and their evolution is presented from year 2001 to 2020 in southern Africa (Namibia, Botswana, South Africa) where many biocrust sites have been identified. The evaluation of dew is made from a classical energy balance model using meteorological data collected in 18 stations, where are also collected rain data. One observes a strong correlation between the frequency of dew and rain and the corresponding amplitudes. There is a general tendency to see a decrease in dew yield and dew frequency with increasing distance from the oceans, located west, east and south, due to decreasing RH, with a relative minimum in the desert of Kalahari (Namibia). Rain amplitude and frequency decreases when going to west and north. Short-term dew/rain correlation shows that largest dew yields clearly occur during about three days after rainfall, particularly in the sites where humidity is less. The evolution in the period corresponds to a decrease of rain precipitations and frequency, chiefly after 2010, an effect which has been cyclic since now. The effect is more noticeable towards north. An increase of dew yield and frequency is observed, mainly in north and south-east. It results in an increase of the dew contribution with respect to rain, especially after 2010. As no drastic changes in the distribution of biomass of biocrusts have been reported in this period, it is likely that dew should compensate for the decrease in rain precipitation. Since the growth of biocrust is related to dew and rain amplitude and frequency, future evolution should be characterized by either the rain cycle or, due to global change, an acceleration of the present tendency, with more dew and less rainfalls. [ABSTRACT FROM AUTHOR]

The dual peak semidiurnal variation in surface rainfall rate over the tropics, simulated using a 3.5-km-mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for 26 - 31 December 2006, is analyzed and compared with data from the 17 year winter precipitation climatology of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Precipitation Radar (PR), and the same 6 day data of Global Satellite Mapping of Precipitation, as well as infrared data from geostationary satellites. We focus on land areas including southern Africa and the Amazon. Over these land areas, the NICAM simulation captures the primary peak in the afternoon and the secondary peak in the early morning, at similar times to those captured using TRMM data. In the PR observation, the primary peak of rainfall is mainly due to convective rain, whereas the secondary peak is due to stratiform rain. In the NICAM simulation, if a simple method is used for the classification of convective/stratiform rain, convective rain is dominant all day long, and the rainfall rate is generally higher than in the PR observation. Nevertheless, an analysis of deep convection (DC) areas indicates consistency between the observation and NICAM; the primary peak of rainfall rate occurs at the mature stage of the number of DC areas, whereas the secondary peak occurs when the mean size of DC areas is almost at its highest point. However, in the NICAM simulation, the relative magnitudes of the two peaks are not represented well, and the contribution of the stratiform rain is underestimated. The present study indicates that a high-resolution global nonhydrostatic model like NICAM has the potential to overcome the limitations of coarse-resolution general circulation models by reproducing the semidiurnal variation of DC, although there is room for improvement. [ABSTRACT FROM AUTHOR]

During strong El Niño events, below-average rainfall is expected in large parts of southern Africa. The 1992 El Niño season was associated with one of the worst drought episodes in large parts of South Africa. Using reanalysis data set from NCEP-NCAR, this study examined circulation types (CTs) in Africa south of the equator that are statistically related to the El Niño signal in the southwest Indian Ocean and the implication of this relationship during the 1992 drought episode in South Africa. A statistically significant correlation was found between the above-average Nino 3.4 index and a CT that features widespread cyclonic activity in the tropical southwest Indian Ocean, coupled with a weaker state of the south Indian Ocean high-pressure. During the analysis period, it was found that the El Niño signal enhanced the amplitude of the aforementioned CT. The impacts of the El Niño signal on CTs in southern Africa, which could have contributed to the 1992 severe drought episode in South Africa, were reflected in (i) robust decrease in the frequency of occurrence of the austral summer climatology pattern of atmospheric circulation that favors southeasterly moisture fluxes, advected by the South Indian Ocean high-pressure; (ii) modulation of easterly moisture fluxes, advected by the South Atlantic Ocean high-pressure, ridging south of South Africa; (iii) and enhancement of the amplitude of CTs that both enhances subsidence over South Africa, and associated with the dominance of westerlies across the Agulhas current. Under the ssp585 scenario, the analyzed climate models suggested that the impact of radiative heating on the CT significantly related to El Niño might result in an anomalous increase in surface pressure at the eastern parts of South Africa. [ABSTRACT FROM AUTHOR]

Rapid and uncontrolled urbanization in tropical Africa is increasingly leading to unprecedented socio-economical and environmental challenges in cities, particularly urban heat and climate change. The latter calls for a better representation of tropical African cities' properties relevant for urban climate studies. Here, we demonstrate the possibility of collecting urban canopy parameters during a field campaign in the boreal summer months of 2018 for deriving a Local Climate Zone (LCZ) map and for improving the physical representation of climate-relevant urban morphological, thermal and radiative characteristics. The comparison of the resulting field-derived LCZ map with an existing map obtained from the World Urban Data and Access Portal Tool framework shows large differences. In particular, our map results in more vegetated open low-rise classes. In addition, site-specific fieldwork-derived urban characteristics are compared against the LCZ universal parameters. The latter shows that our fieldwork adds important information to the universal parameters by more specifically considering the presence of corrugated metal in the city of Kampala. This material is a typical roofing material found in densely built environments and informal settlements. It leads to lower thermal emissivity but higher thermal conductivity and capacity of buildings. To illustrate the importance of site-specific urban parameters, the newly derived site-specific urban characteristics are used as input fields to an urban parametrization scheme embedded in the regional climate model COSMO-CLM. This implementations decreases the surface temperature bias from 5.34 to 3.97 K. Based on our results, we recommend future research on tropical African cities to focus on a detailed representation of cities, with particular attention to impervious surface fraction and building materials. [ABSTRACT FROM AUTHOR]

Water isotopologues, as natural tracers of the hydrological cycle on Earth, provide a unique way to assess the skill of climate models in representing realistic atmospheric‐terrestrial water pathways. This study presents the newly developed WRF‐Hydro‐iso, which is a version of the coupled atmospheric‐hydrological WRF‐Hydro model enhanced with a joint soil‐vegetation‐atmospheric description of water isotopologue motions. It allows the consideration of isotopic fractionation processes during water phase changes in the atmosphere, the land surface, and the subsurface. For validation, WRF‐Hydro‐iso is applied to two different climate zones, namely Europe and Southern Africa under the present climate conditions. Each case is modeled with a domain employing a 5 km grid‐spacing coupled with a terrestrial subgrid employing a 500 m grid‐spacing in order to represent lateral terrestrial water flow. A 10‐year slice is simulated for 2003–2012, using ERA5 reanalyses as driving data. The boundary condition of isotopic variables is prescribed with mean values from a 10‐year simulation with the Community Earth System Model Version 1. WRF‐Hydro‐iso realistically reproduces the climatological variations of the isotopic concentrations δPO18 and δPH2 from the Global Network of Isotopes in Precipitation. In a sensitivity analysis, it is found that land surface evaporation fractionation increases the isotopic concentrations in the rootzone soil moisture and slightly decreases the isotopic concentrations in precipitation. Lateral terrestrial water flow minorly affects these isotopic concentrations through changes in evaporation‐transpiration partitioning. Plain Language Summary: Global climate models are limited by their coarse resolution, which may reduce their meaningfulness. This problem can be circumvented for a specific region with regional climate models, which provide, for example, a detailed description of clouds and land‐atmosphere interactions. But it remains a question: How realistic is the model representation of water transport through the different compartments of the hydrological cycle, the atmosphere, the land, and the sea? A unique way to assess modeled water transport is the comparison to natural tracers, such as water isotopologues, which requires to include the fate of these water isotopologues in the model. This is what we pursue here with the newly developed WRF‐Hydro‐iso model. A model description and a proof of concept are provided for two climate zones, using the Global Network of Isotopes in Precipitation data set as reference. Key Points: A new coupled atmospheric‐hydrological regional modeling system of water isotopologues is presentedLand surface evaporation fractionation increases the isotopic concentrations in the rootzoneLateral terrestrial water flow has a minor effect on isotopic concentrations in the rootzone [ABSTRACT FROM AUTHOR]

Three 16-year simulations were conducted to investigate the potential influence of the vegetation cover changes (static versus interactive) alone and vegetation-runoff systems (CN-TOP versus CN-VIC) on the gross primary production (GPP) over tropical Africa using a regional climate model RegCM4-CLM45. CLM45 is the land surface model coupled to the RegCM4, CN is the carbon–nitrogen module, SIMTOP (TOP) is the default runoff scheme and Variable Infiltration Capacity (VIC) is the optional runoff scheme of the CLM45. The results showed that when the vegetation cover changes were considered alone, the RegCM4 model shows a low bias of GPP—relative to the static vegetation case—in comparison with the observation-based dataset (Machine Tree Ensemble (MTE)). On the other hand, when the effects of the soil moisture (as represented by the runoff scheme) and vegetation cover changes were combined together, the difference between the two vegetation-runoff systems was larger than when the vegetation cover changes were considered alone. This was evident as the CN-VIC severely underestimated the GPP with respect to the MTE; meanwhile the CN-TOP reversed this effect particularly over the Congo basin. Overall, GPP is more sensitive to vegetation-runoff systems than when the vegetation cover changes are only considered. In addition, the regional coupled RegCM4-CLM45-CN-VIC model can simulate the GPP with a reasonable bias as long as the four parameters of the VIC surface dataset are calibrated against in-situ observations of tropical Africa. [ABSTRACT FROM AUTHOR]

The Toba eruption ~74,000 y ago was the largest volcanic eruption since the start of the Pleistocene and represents an important test case for understanding the effects of large explosive eruptions on climate and ecosystems. However, the magnitude and repercussions of climatic changes driven by the eruption are strongly debated. High-resolution paleoclimate and archaeological records from Africa find little evidence for the disruption of climate or human activity in the wake of the eruption in contrast with a controversial link with a bottleneck in human evolution and climate model simulations predicting strong volcanic cooling for up to a decade after a Toba-scale eruption. Here, we use a large ensemble of high-resolution Community Earth System Model (CESM1.3) simulations to reconcile climate model predictions with paleoclimate records, accounting for uncertainties in the magnitude of Toba sulfur emissions with high and low emission scenarios. We find a near-zero probability of annual mean surface temperature anomalies exceeding 4 °C in most of Africa in contrast with near 100% probabilities of cooling this severe in Asia and North America for the high sulfur emission case. The likelihood of strong decreases in precipitation is low in most of Africa. Therefore, even Toba sulfur release at the upper range of plausible estimates remains consistent with the muted response in Africa indicated by paleoclimate proxies. Our results provide a probabilistic view of the uneven patterns of volcanic climate disruption during a crucial interval in human evolution, with implications for understanding the range of environmental impacts from past and future supereruptions. [ABSTRACT FROM AUTHOR]

Global climate models experience difficulties in simulating the northward extension of the monsoonal precipitation over north Africa during the mid-Holocene as revealed by proxy data. A common feature of these models is that they usually operate on grids that are too coarse to explicitly resolve convection, but convection is the most essential mechanism leading to precipitation in the West African Monsoon region. Here, we investigate how the representation of tropical deep convection in the ICOsahedral Nonhydrostatic (ICON) climate model affects the meridional distribution of monsoonal precipitation during the mid-Holocene by comparing regional simulations of the summer monsoon season (July to September; JAS) with parameterized and explicitly resolved convection. In the explicitly resolved convection simulation, the more localized nature of precipitation and the absence of permanent light precipitation as compared to the parameterized convection simulation is closer to expectations. However, in the JAS mean, the parameterized convection simulation produces more precipitation and extends further north than the explicitly resolved convection simulation, especially between 12 and 17 ∘ N. The higher precipitation rates in the parameterized convection simulation are consistent with a stronger monsoonal circulation over land. Furthermore, the atmosphere in the parameterized convection simulation is less stably stratified and notably moister. The differences in atmospheric water vapor are the result of substantial differences in the probability distribution function of precipitation and its resulting interactions with the land surface. The parametrization of convection produces light and large-scale precipitation, keeping the soils moist and supporting the development of convection. In contrast, less frequent but locally intense precipitation events lead to high amounts of runoff in the explicitly resolved convection simulations. The stronger runoff inhibits the moistening of the soil during the monsoon season and limits the amount of water available to evaporation in the explicitly resolved convection simulation. [ABSTRACT FROM AUTHOR]

This article describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products with one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or for regional domains. Simple-to-visualize "scorecards" allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher-resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic Ocean TC frequency. Upstream refinement over northern Africa offers little benefit in simulating storm occurrence, but spatial genesis patterns are improved. We also show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on the version of the Morrison-Gettelman microphysics package that is used. [ABSTRACT FROM AUTHOR]

The interannual variability, trends, and the mean climatology of East African long rains are difficult for models to simulate. This is in part because long rains do not respond in a simple way to large-scale modes of variability such as ENSO and because of interactions with complex topography. Here we focus on the Kenyan regional climate in the ERA-Interim dataset during the long rains to create a set of atmospheric diagnostics that can be applied to the evaluation of climate models. Subseasonal observed rainfall and reanalysis reveal that very wet seasons and very dry seasons develop differently at the beginning of the season. Subseasonal aggregation periods (days 60–80, 80–100, 90–120, 120–150) highlight local (e.g., midtropospheric ascent, moisture flux convergence in the lower to midtroposphere, and midtropospheric moisture) and large-scale (e.g., midtropospheric zonal winds over central Africa, upper-tropospheric velocity potential) diagnostics that are useful to evaluate model atmospheric circulation affecting Kenyan rainfall in mean and wet or dry extremes. [ABSTRACT FROM AUTHOR]

In this study we evaluate the reliability of the Regional Climate Model (RegCM4.6) by performing several sensitivity tests at 50 km horizontal resolution using 10 convection schemes or combination of convection schemes. Emphasis on model output is made for the September-October--November 2017-2019 seasonal period. Part of the Central African region, five sub-regions, was identified. The simulated temperatures are compared to the daily climatology of near-surface temperature of the European Centre for Medium-Range Weather Forecasts Reanalysis fifthgeneration and the National Center for Environmental Prediction datasets, while the simulated precipitations are compared to the precipitation of the Global Precipitation Climatology Project and Climate Hazards Group Infrared Precipitation with Stations datasets. In most analyses, the Grell scheme with Arakawa--Schubert closure assumption tends to have the best index of agreement but its spatial distribution shows underestimation of rainfall. Generally, the Emanuel convection scheme is more suitable to represent rainfall and temperature over Central Africa. Compared to our previous study (Komkoua Mbienda et al., International Journal of Climatology, 2017, 37, 328-342), the present study shows that we have to pay attention to the choice of convective scheme when using any version of RegCM4 released for climate study over Central Africa. This choice is strictly related to the RegCM version released, the study years and the season. It is important to note, however, that the results presented are a preliminary study of the response to the selected convection schemes. The analysis uses a limited sample of climate model simulation (three model years for each convection scheme). Follow-up work, featuring longer duration climate simulations and a full assessment of statistical significance, is therefore required to confirm the robustness of the analysis presented. [ABSTRACT FROM AUTHOR]

Uncertainty in the future evolution of tropical rainfall is linked to circulation changes under warming. In Africa, a key barrier to interpreting rainfall changes is our limited understanding of water vapor transport across the continent. Here, we show that a series of nocturnal easterly Low‐Level Jets (LLJs), which form in the valleys punctuating the East African rift system, transport the majority of water vapor to central Africa from the Indian Ocean. There is a robust connection between strengthened LLJs and drought in eastern and southern Africa at interannual timescales, mediated by an increase in low‐level divergence and water vapor export. Analysis of climate model simulations at a wide range of resolutions (250–4.5 km) suggests that grid lengths <60 km are needed to simulate the salient structures of LLJs. The failure of coarse resolution models to capture LLJs is linked with biases in rainfall climatology and variability across the continent. Plain Language Summary: Africa is one of the continents least responsible for climate change but will bear a disproportionate share of its impact, particularly through changes to droughts and floods. An important task for climate scientists is therefore to understand possible future changes to African rainfall. Unfortunately, this task is made difficult by large gaps in our knowledge of the basic mechanics of the climate system over Africa. One of these gaps is in our understanding of how water vapor—which is a key ingredient for rainfall—travels from the Indian Ocean into the African interior. Here, we show that over 200,000 tonnes of water vapor are transported each second through a series of invisible rivers, which flow through the atmosphere in valleys interrupting the high mountains of the East African Rift System. The models that we use to project rainfall change can capture the structure of these invisible rivers, but only if they represent the mountains of tropical Africa realistically. Key Points: Topographically constrained nocturnal low‐level jets dominate water vapor transport from the Indian Ocean to the African interiorDrought is prevalent in the jet entrance regions across eastern and southern Africa during years with strong jetsCoarse resolution climate models do not simulate key low‐level jets: A failure which contributes to errors in simulated rainfall [ABSTRACT FROM AUTHOR]

The south-eastern Atlantic Ocean (SEA) is semi-permanently covered by one of the most extensive stratocumulus cloud decks on the planet and experiences about one-third of the global biomass burning emissions from the southern Africa savannah region during the fire season. To get a better understanding of the impact of these biomass burning aerosols on clouds and the radiation balance over the SEA, the latest generation of the UK Earth System Model (UKESM1) is employed. Measurements from the CLARIFY and ORACLES flight campaigns are used to evaluate the model, demonstrating that the model has good skill in reproducing the biomass burning plume. To investigate the underlying mechanisms in detail, the effects of biomass burning aerosols on the clouds are decomposed into radiative effects (via absorption and scattering) and microphysical effects (via perturbation of cloud condensation nuclei – CCN – and cloud microphysical processes). July–August means are used to characterize aerosols, clouds, and the radiation balance during the fire season. Results show that around 65 % of CCN at 0.2 % supersaturation in the SEA can be attributed to biomass burning. The absorption effect of biomass burning aerosols is the most significant on clouds and radiation. Near the continent, it increases the supersaturation diagnosed by the activation scheme, while further from the continent it reduces the altitude of the supersaturation. As a result, the cloud droplet number concentration responds with a similar pattern to the absorption effect of biomass burning aerosols. The microphysical effect, however, decreases the supersaturation and increases the cloud droplet concentration over the ocean, although this change is relatively small. The liquid water path is also significantly increased over the SEA (mainly caused by the absorption effect of biomass burning aerosols) when biomass burning aerosols are above the stratocumulus cloud deck. The microphysical pathways lead to a slight increase in the liquid water path over the ocean. These changes in cloud properties indicate the significant role of biomass burning aerosols for clouds in this region. Among the effects of biomass burning aerosols on the radiation balance, the semi-direct radiative effects (rapid adjustments induced by the radiative effects of biomass burning aerosols) have a dominant cooling impact over the SEA, which offset the warming direct radiative effect (radiative forcing from biomass burning aerosol–radiation interactions) and lead to an overall net cooling radiative effect in the SEA. However, the magnitude and the sign of the semi-direct effects are sensitive to the relative location of biomass burning aerosols and clouds, reflecting the critical task of the accurate modelling of the biomass burning plume and clouds in this region. [ABSTRACT FROM AUTHOR]

Global climate models (GCMs) are critical tools for understanding and projecting climate variability and change, yet the performance of these models is notoriously weak over much of tropical Africa. To improve this situation, process-based studies of African climate dynamics and their representation in GCMs are required. Here, we focus on summer rainfall of eastern Africa (SREA), which is crucial to the Ethiopian Highlands and feeds the flow of the Blue Nile River. The SREA region is highly vulnerable to droughts, with El Niño–Southern Oscillation (ENSO) being a leading cause of interannual rainfall variability. Adequate understanding and accurate representation of climate features that influence regional variability is an important but often neglected issue when evaluating models. We perform a process-based evaluation of GCMs, focusing on the upper-troposphere tropical easterly jet (TEJ), which has been hypothesized to link ENSO to SREA. We find that most models have an ENSO–TEJ coupling similar to observed, but the models diverge in their representation of TEJ–SREA coupling. Differences in the latter explain the majority (80%) of variability in ENSO teleconnection simulation across the models. This is higher than the variance explained by rainfall coupling with the Somali jet (44%) and African easterly jet (55%). However, our diagnostics of the leading hypothesized mechanism in the models—variability in divergence in the TEJ exit region—are not consistent across models and suggest that a deeper understanding of the mechanisms of TEJ–precipitation coupling should be a priority for studies of climate variability and change in the region. [ABSTRACT FROM AUTHOR]

Global climate models struggle to simulate both the convection and cloud ice fundamental to lightning formation. We use the first convection‐permitting, future climate simulations for the lightning hot spot of Africa, at the same time utilizing an ice‐based lightning parametrization. Both the model and observations show that lightning over Africa's drier areas, as well as the moist Congo, have more lightning per rainfall than other regions. Contrary to results in the literature, the future projection shows little increase in total lightning (~107 flashes (or 2%) per degree warming). This is a consequence of increased stability reducing the number of lightning days, largely offsetting the increased graupel and updraft velocity driving an increase in lightning per lightning day. The next step is to establish if these results are robust across other models and, if combined with parametrized‐convection models, whether ensemble‐based information on the possible responses of lightning to climate change can be investigated. Plain Language Summary: Lightning depends on ascending air in thunderstorms and the collision of cloud ice particles, which charge the thundercloud. Many climate models have too coarse a resolution to reliably capture these processes. We focus on Africa, which has some of the most frequent lightning in the world. We use a model that is much higher resolution than usual, and this allows us to explicitly simulate the deep convection associated with thunderstorms as well as provide more detailed representation of the distribution of cloud ice particles. Our results show that in drier regions, as well as the much wetter Congo, there is relatively more lightning per kilogram of surface rainfall than there is in other parts of the continent. Lightning does increase across the continent under climate change, but by a relatively small amount. This is despite the number of days with lightning decreasing as the lower atmosphere becomes more stable. On days with lightning, there are more lightning flashes because there is an increase in cloud ice and intensity of convection. This study gives much more detailed information about African lightning than previous work. However, it is a single simulation. Future research should look at these results across other climate models. Key Points: Lightning and its relationship to rainfall vary considerably across Africa, with indication of dry lightning in arid regionsOpposite changes in lightning days and intensity lead to little change in total flashes under climate change, unlike many past studiesGraupel increases are smaller than column water increases, and therefore, lightning intensity mostly increases less than rain intensity [ABSTRACT FROM AUTHOR]

The Hadley circulation and tropical rain belt are dominant features of African climate. Moist convection provides ascent within the rain belt, but must be parameterized in climate models, limiting predictions. Here, we use a pan-African convection-permitting model (CPM), alongside a parameterized convection model (PCM), to analyze how explicit convection affects the rain belt under climate change. Regarding changes in mean climate, both models project an increase in total column water (TCW), a widespread increase in rainfall, and slowdown of subtropical descent. Regional climate changes are similar for annual mean rainfall but regional changes of ascent typically strengthen less or weaken more in the CPM. Over a land-only meridional transect of the rain belt, the CPM mean rainfall increases less than in the PCM (5%vs 14%) but mean vertical velocity at 500 hPa weakens more (17% vs 10%). These changes mask more fundamental changes in underlying distributions. The decrease in 3-hourly rain frequency and shift from lighter to heavier rainfall are more pronounced in the CPM and accompanied by a shift from weak to strong updrafts with the enhancement of heavy rainfall largely due to these dynamic changes. The CPM has stronger coupling between intense rainfall and higher TCW. This yields a greater increase in rainfall contribution from events with greater TCW, with more rainfall for a given large-scale ascent, and so favors slowing of that ascent. These findings highlight connections between the convective-scale and larger-scale flows and emphasize that limitations of parameterized convection have major implications for planning adaptation to climate change. [ABSTRACT FROM AUTHOR]

In this study, nine global climate models (GCMs) and corresponding downscaled runs by means of the regional climate model (RCM) RCA4 are used to investigate added value (AV) in precipitation and its some drivers over Central Africa (CA). By employing a process‐based analysis approach, we intercompare abilities of RCM to those of driving GCMs in representing the total atmospheric moisture flux convergence (TMFC), moisture transport, and African Easterly Jets (AEJs). Results indicate that simulations with highest AVs in the precipitation climatology also show improvements in the representation of the TMFC and AEJs. Degraded precipitation due to the downscaling is associated with deterioration of at least two of three analyzed mechanisms, and sometimes there is inconsistent AVs between precipitation and related drivers. This sustains that a realistic representation of the moisture transport and atmospheric circulation is of great importance for the correct simulation of present (and, consequently, future) precipitation over CA. Plain Language Summary: Although the downscaling is proved beneficial for the African Coordinated Regional‐climate Downscaling Experiment domain, meaningful climate uncertainties persist; the origins of many biases/deficiencies in RCM results often remain unexplained, in a context where there is a requirement to ensure the fitness for purpose of the models used to generate climate information for decision‐makers. The added value is a statistical metric frequently used to judge whether an RCM has improved the results of the driving GCM or no. Most of the previous studies which have investigated added value over Africa have used the performance‐based evaluation method and are focused only on the diagnostic variables precipitation and temperature and therefore did not investigate reasons behind the RCM's amelioration or degradation. By the means of a process‐based analysis, this work shows that added value from the downscaling must be interpreted with a certain caution over Central Africa, as improvements in the representation of precipitation climatology are not always associated with improvements in related processes. Key Points: Experiments which feature clear improvement in precipitation also show improved moisture fluxes and AEJsDownscaled GCMs showing deteriorated precipitation also show deterioration in at least two of the analyzed processesThere is doubtful added value in some runs, highlighted through the process‐based analysis [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]

Recent studies have investigated past and future changes in the intensity and sinking branch of the global zonally averaged Hadley circulation (ZAHC), and discrepancies were found between climate models and reanalyses. However, studies concerning the regional Hadley circulation (HC), especially based on model simulations, are relatively rare. Here, using reanalyses and CMIP5 simulation datasets, we study the long-term changes in regional HCs over Africa (AFHC), the Indian Ocean (IOHC), the western Pacific (WPHC), the eastern Pacific (EPHC), South America (SAHC), and the Atlantic (ATHC). The results obtained from the reanalyses show that during the historical period, the intensification of the WPHC, EPHC, SAHC, and ATHC in the Northern Hemisphere (NH) may contribute to the strengthening of the ZAHC in the NH, while the contributions of the NH AFHC and IOHC are relatively small. The intensification of the IOHC, EPHC, SAHC, and ATHC in the Southern Hemisphere (SH) may contribute to the strengthening of the ZAHC in the SH, while the contributions of the SH AFHC and WPHC are negative. Regarding the poleward edge, the NH HCs have generally shifted poleward in recent decades, while trends in the SH HCs are nonsignificantly greater than zero in most cases. As reanalysis trends in the HC fall within the range of the model trends, we do not find sufficient evidence to demonstrate a discrepancy in the long-term changes in the HC between the CMIP5 models and reanalyses. The correlations of the HC intensities (poleward edges) among different regions obtained from the reanalysis data are generally different than (similar to) those obtained from the CMIP5 historical simulations, and the difference (similarity) may be caused by the difference (similarity) in the internal variabilities between the reanalyses and CMIP5 preindustrial control simulations. The changes in these HCs under global warming conditions are also investigated in this study. [ABSTRACT FROM AUTHOR]

Background: Malaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability will occur, which will require changes in the types and amounts of resources. Methods: The shifting geographic risk of malaria transmission was mapped, in context of changing seasonality (i.e. endemic to epidemic, and vice versa), and the number of people affected. A published temperature-dependent model of malaria transmission suitability was applied to continental gridded climate data for multiple future AR5 climate model projections. The resulting outcomes were aligned with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5). Results: Estimated geographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change predicted an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people is predicted be put at some level of risk in Western Africa by midcentury. Conclusions: This study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision-makers. In describing shifting seasonality, it was possible to capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations. [ABSTRACT FROM AUTHOR]