Search

The Sahelian Great Green Wall (SGGW) is an influential project to combat desertification and promote sustainable land management on a large scale, involving 11 countries in the Sahel region of Africa. The UNCCD's 2020 progress report showed a mixed picture concerning the meeting of the initial targets. At the One Planet Summit in 2021, announcements were made to consolidate the implementation of the SGGW, most notably with the creation of the Great Green Wall Accelerator. In this context, our paper sets out to review the scientific work conducted with regard to the SGGW. We have thus carried out a bibliometric analysis of the literature on SGGW. Although the initiative involves 11 countries and covers a large spectrum of scientific disciplines, our results show the predominance of ecological studies in the SGGW literature and a concentration of studies in certain geographies of interest, such as northern Senegal. Moreover, based on a secondary analysis of publications on land restoration and sustainable ecosystem management in Sahelian countries, we show that the literature relevant to SGGW topics is richer and fills in the information gaps we have identified at thematic and geographical levels. By showing that SGGW studies are overly focused on certain topics and geographical areas, our paper argues for a better interdisciplinary mobilization of researchers working on GGW-related topics. The scientific and operational success of the project depends on stronger networking between the different research teams and themes, both in Africa and internationally. [ABSTRACT FROM AUTHOR]

We applied two metrics, apparent temperature and humidex, to calculate heat stress in both present and future climates. We use an ensemble of CORDEX-Africa simulations to estimate heat stress during a baseline period and at two specific warming levels, 2 and 4 ∘C above pre-industrial. The increase in temperatures and changes to the precipitation distribution under climate change are projected to increase the intensity of heat stress events in Sahelian Africa and introduce new heat stress events in Northern and Central Africa. As the intensity of heat stress increases, it is expected that the use of energy-intensive cooling will increase. The energy system, therefore, will need to be able to supply more energy to power fans or air conditioning units. The cooling demand to turn a heat stress event into a non-heat stress event is computed. This value is then weighted by the population to find the total cooling required to prevent heat stress across the continent. Country-level results indicate that the greatest increases in cooling demand will occur in countries with densely populated regions, most notably Nigeria. Supplying this additional cooling demand will present the greatest challenge to less developed countries like Somalia. We find the least-cost future energy system that meets the projected increase in demand and derive the increase in energy system costs with the TIAM-UCL model. The total increase in energy costs to prevent heat stress is found to be $51bn by 2035 and $487bn by 2076. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present a new data set of bias-corrected CMIP5 global climate models (GCMs) daily data over Africa. This dataset was obtained in using the Cumulative Distribution Function Transform (CDF-t) method, a method that has been applied on several regions and contexts but never on Africa. Here CDF-t is used over the period 1950–2099 combining historical runs and climate change scenarios on 6 variables, precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface down-welling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. Evaluation of the results is carried out over West Africa on a list of priority users-based metrics that was discussed and selected with stakeholders and on simulated yield using a crop model simulating maize growth. Bias-corrected GCMs data are compared with another available dataset of bias-corrected GCMs, and the impact of three different reference datasets on bias-corrections is also examined in details. CDF-t is very effective in removing the biases and in reducing the high inter-GCMs scattering. Differences with other bias-corrected GCMs data are mainly due to the differences between the reference datasets. This is particular true for surface down-welling shortwave radiation, which has impacts in terms of simulated maize yields. Projections of future yields over West Africa have quite different levels, depending on bias-correction method used, but they all show a similar relative decreasing trend over the 21st century. [ABSTRACT FROM AUTHOR]

Highlights: [•] We simulate crop yield using state-of-the-art satellite rainfall estimates. [•] Satellite data use can introduce large biases in crop yield predictions. [•] Biases differ strongly among the four crops considered in two sites. [•] Biases are not simple extrapolation of each satellite product total rainfall biases. [•] A realistic distribution of rainfall can be very important for crop yield prediction. [Copyright &y& Elsevier]

This paper is part of a series of studies addressing the dynamics of the West African summer monsoon at intraseasonal time scales between 10 and 90 days. The dominant mode of 25–90-day convective variability in the African monsoon was investigated, starting from previous results involving the excitation of dry equatorial Kelvin and Rossby waves by a negative diabatic heat source located over the warm pool. This evolution is consistent with a significant contribution by a convectively coupled equatorial Rossby wave and the MJO. On the other hand, convectively coupled Kelvin waves as well as the dry Kelvin wave signal have a very weak impact. However, there is more to the global control of the African summer monsoon than convectively coupled wave dynamics. The active/break cycle of the Indian monsoon, controlled by a northward-moving dipole of diabatic heating in the Indian sector, can also influence the African monsoon through atmospheric teleconnections. Simulations performed with a dry primitive equation model show that this influence may be transferred through the northern Indian heat source, which excites a Rossby cyclonic circulation propagating westward over North Africa that is cut off by the northward arrival of the equatorial Indian heat source and the associated intrusion of an anticyclonic ridge. Low-level westerly winds and moisture advection within the ITCZ consequently increase over Africa. The mean time lag between an active phase over India and over Africa is about 15–20 days. [ABSTRACT FROM AUTHOR]

Background Every year West African countries within the Sahelo-Sudanian band are afflicted with major meningococcal meningitis (MCM) disease outbreaks, which affect up to 200,000 people, mainly young children, in one of the world's poorest regions. The timing of the epidemic year, which starts in February and ends in late May, and the spatial distribution of disease cases throughout the "Meningitis Belt" strongly indicate a close linkage between the life cycle of the causative agent of MCM and climate variability. However, mechanisms responsible for the observed patterns are still not clearly identified. Methods and Findings By comparing the information on cases and deaths of MCM from World Health Organization weekly reports with atmospheric datasets, we quantified the relationship between the seasonal occurrence of MCM in Mali, a West African country, and large-scale atmospheric circulation. Regional atmospheric indexes based on surface wind speed show a clear link between population dynamics of the disease and climate: the onset of epidemics and the winter maximum defined by the atmospheric index share the same mean week (sixth week of the year; standard deviation, 2 wk) and are highly correlated. Conclusions This study is the first that provides a clear, quantitative demonstration of the connections that exist between MCM epidemics and regional climate variability in Africa. Moreover, this statistically robust explanation of the MCM dynamics enables the development of an Early Warning Index for meningitis epidemic onset in West Africa. The development of such an index will undoubtedly help nationwide and international public health institutions and policy makers to better control MCM disease within the so-called westward--eastward pan-African Meningitis Belt. [ABSTRACT FROM AUTHOR]

Background: Meningococcal meningitis (MM) represents an important public health problem especially in the "meningitis belt" in Africa. Although seasonality of epidemics is well known with outbreaks usually starting in the dry season, pluri-annual cycles are still less understood and even studied. In this context, we aimed at study MM cases time series across 9 sahelo-sudanian countries to detect pluri-annual periodicity and determine or not synchrony between dynamics. This global and comparative approach allows a better understanding of MM evolution in time and space in the long-term., Results: We used the most adapted mathematical tool to time series analyses, the wavelet method. We showed that, despite a strong consensus on the existence of a global pluri-annual cycle of MM epidemics, it is not the case. Indeed, even if a clear cycle is detected in all countries, these cycles are not as permanent and regular as generally admitted since many years. Moreover, no global synchrony was detected although many countries seemed correlated., Conclusion: These results of the first large-scale study of MM dynamics highlight the strong interest and the necessity of a global survey of MM in order to be able to predict and prevent large epidemics by adapted vaccination strategy. International cooperation in Public Health and cross-disciplines studies are highly recommended to hope controlling this infectious disease.