Bias-Corrected CMIP5 Projections for Climate Change and Assessments of Impact on Malaria in Senegal under the VECTRI Model.

On the climate-health issue, studies have already attempted to understand the influence of climate change on the transmission of malaria. Extreme weather events such as floods, droughts, or heat waves can alter the course and distribution of malaria. This study aims to understand the impact of future climate change on malaria transmission using, for the first time in Senegal, the ICTP's community-based vector-borne disease model, TRIeste (VECTRI). This biological model is a dynamic mathematical model for the study of malaria transmission that considers the impact of climate and population variability. A new approach for VECTRI input parameters was also used. A bias correction technique, the cumulative distribution function transform (CDF-t) method, was applied to climate simulations to remove systematic biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) that could alter impact predictions. Beforehand, we use reference data for validation such as CPC global unified gauge-based analysis of daily precipitation (CPC for Climate Prediction Center), ERA5-land reanalysis, Climate Hazards InfraRed Precipitation with Station data (CHIRPS), and African Rainfall Climatology 2.0 (ARC2). The results were analyzed for two CMIP5 scenarios for the different time periods: assessment: 1983-2005; near future: 2006-2028; medium term: 2030-2052; and far future: 2077-2099). The validation results show that the models reproduce the annual cycle well. Except for the IPSL-CM5B model, which gives a peak in August, all the other models (ACCESS1-3, CanESM2, CSIRO, CMCC-CM, CMCC-CMS, CNRM-CM5, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, inmcm4, and IPSL-CM5B) agree with the validation data on a maximum peak in September with a period of strong transmission in August-October. With spatial variation, the CMIP5 model simulations show more of a difference in the number of malaria cases between the south and the north. Malaria transmission is much higher in the south than in the north. However, the results predicted by the models on the occurrence of malaria by 2100 show differences between the RCP8.5 scenario, considered a high emission scenario, and the RCP4.5 scenario, considered an intermediate mitigation scenario. The CanESM2, CMCC-CM, CMCC-CMS, inmcm4, and IPSL-CM5B models predict decreases with the RCP4.5 scenario. However, ACCESS1-3, CSIRO, NRCM-CM5, GFDL-CM3, GFDL-ESM2G, and GFDL-ESM2M predict increases in malaria under all scenarios (RCP4.5 and RCP8.5). The projected decrease in malaria in the future with these models is much more visible in the RCP8.5 scenario. The results of this study are of paramount importance in the climate-health field. These results will assist in decision-making and will allow for the establishment of preventive surveillance systems for local climate-sensitive diseases, including malaria, in the targeted regions of Senegal.

Livestock exposure to future cumulated climate-related stressors in West Africa.

A large range of climate change impacts is expected during the twenty-first century in vulnerable regions such as West Africa, where local populations largely rely on livestock systems as their main food production and income source. As climate change threatens livestock systems in various ways, here we assess how regional livestock could be exposed to cumulated climate-related stressors in the future. Using the world's largest multi-model climate impacts simulations database ISIMIP, we find that a large part of West Africa will experience at least 5-6 cumulated multiple climate stressors before the 2030s, including amplified severe heat stress conditions and flood risks. Consequently, about 30% of the current total regional livestock could be exposed to these cumulated stressors, with sheep and goat as the most affected species. This paper brings new quantifications that may help policy makers to prioritize decisions that could prepare local populations to face multiple climate-related impacts.

Pearl millet genomic vulnerability to climate change in West Africa highlights the need for regional collaboration.

Climate change is already affecting agro-ecosystems and threatening food security by reducing crop productivity and increasing harvest uncertainty. Mobilizing crop diversity could be an efficient way to mitigate its impact. We test this hypothesis in pearl millet, a nutritious staple cereal cultivated in arid and low-fertility soils in sub-Saharan Africa. We analyze the genomic diversity of 173 landraces collected in West Africa together with an extensive climate dataset composed of metrics of agronomic importance. Mapping the pearl millet genomic vulnerability at the 2050 horizon based on the current genomic-climate relationships, we identify the northern edge of the current areas of cultivation of both early and late flowering varieties as being the most vulnerable to climate change. We predict that the most vulnerable areas will benefit from using landraces that already grow in equivalent climate conditions today. However, such seed-exchange scenarios will require long distance and trans-frontier assisted migrations. Leveraging genetic diversity as a climate mitigation strategy in West Africa will thus require regional collaboration.

Robust assessment of the time of emergence of precipitation change in West Africa.

The time of emergence (TOE) of climate change is defined as the time when a new climate state emerges from a prior one. TOE assessment is particularly relevant in West Africa, a region highly threatened by climate change and urgently needing trustworthy climate predictions. In this paper, the TOE of precipitation change in West Africa is assessed for the first time, by analyzing 6 precipitation metrics (cumulated precipitation, number of wet and very wet days, onset and length of the rainy season) computed from the output of 29 state-of-the-art climate models. In West Sahel, climate conditions characterized by reduced occurrence of wet days are likely to emerge before 2036, leading to the possible emergence of a dryer climate in 2028-2052. In East Sahel, a wetter precipitation regime characterized by increased occurrence of very wet days is likely to emerge before 2054. Results do not provide a clear indication about a possible climate shift in the onset and length of the rainy season. Although uncertainty in climate model future projections still limits the robust determination of TOE locally, this study provides reliable time constraints to the expected climate shift in West Africa at the sub-regional scale, supporting adaptation measures to the future change in the precipitation regime.

Evidence of crop production losses in West Africa due to historical global warming in two crop models.

Achieving food security goals in West Africa will depend on the capacity of the agricultural sector to feed the rapidly growing population and to moderate the adverse impacts of climate change. Indeed, a number of studies anticipate a reduction of the crop yield of the main staple food crops in the region in the coming decades due to global warming. Here, we found that crop production might have already been affected by climate change, with significant yield losses estimated in the historical past. We used a large ensemble of historical climate simulations derived from an atmospheric general circulation model and two process-based crop models, SARRA-H and CYGMA, to evaluate the effects of historical climate change on crop production in West Africa. We generated two ensembles of 100 historical simulations of yields of sorghum and millet corresponding to two climate conditions for each crop model. One ensemble is based on a realistic simulation of the actual climate, while the other is based on a climate simulation that does not account for human influences on climate systems (that is, the non-warming counterfactual climate condition). We found that the last simulated decade, 2000-2009, is approximately 1 °C warmer in West Africa in the ensemble accounting for human influences on climate, with more frequent heat and rainfall extremes. These altered climate conditions have led to regional average yield reductions of 10-20% for millet and 5-15% for sorghum in the two crop models. We found that the average annual production losses across West Africa in 2000-2009 associated with historical climate change, relative to a non-warming counterfactual condition (that is, pre-industrial climate), accounted for 2.33-4.02 billion USD for millet and 0.73-2.17 billion USD for sorghum. The estimates of production losses presented here can be a basis for the loss and damage associated with climate change to date and useful in estimating the costs of the adaptation of crop production systems in the region.

Consequences of rapid ice sheet melting on the Sahelian population vulnerability.

The acceleration of ice sheet melting has been observed over the last few decades. Recent observations and modeling studies have suggested that the ice sheet contribution to future sea level rise could have been underestimated in the latest Intergovernmental Panel on Climate Change report. The ensuing freshwater discharge coming from ice sheets could have significant impacts on global climate, and especially on the vulnerable tropical areas. During the last glacial/deglacial period, megadrought episodes were observed in the Sahel region at the time of massive iceberg surges, leading to large freshwater discharges. In the future, such episodes have the potential to induce a drastic destabilization of the Sahelian agroecosystem. Using a climate modeling approach, we investigate this issue by superimposing on the Representative Concentration Pathways 8.5 (RCP8.5) baseline experiment a Greenland flash melting scenario corresponding to an additional sea level rise ranging from 0.5 m to 3 m. Our model response to freshwater discharge coming from Greenland melting reveals a significant decrease of the West African monsoon rainfall, leading to changes in agricultural practices. Combined with a strong population increase, described by different demography projections, important human migration flows could be potentially induced. We estimate that, without any adaptation measures, tens to hundreds million people could be forced to leave the Sahel by the end of this century. On top of this quantification, the sea level rise impact over coastal areas has to be superimposed, implying that the Sahel population could be strongly at threat in case of rapid Greenland melting.

Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance.

BACKGROUND: Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071-2100 is predicted to be 1-5.5 °C higher than that for 1971-2000. Climate change and elevated CO2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change. RESULTS: Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO2. The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C. CONCLUSIONS: This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers' ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation.

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation.

Potential escalation of heat-related working costs with climate and socioeconomic changes in China.

Global climate change will increase the frequency of hot temperatures, impairing health and productivity for millions of working people and raising labor costs. In mainland China, high-temperature subsidies (HTSs) are allocated to employees for each working day in extremely hot environments, but the potential heat-related increase in labor cost has not been evaluated so far. Here, we estimate the potential HTS cost in current and future climates under different scenarios of socioeconomic development and radiative forcing (Representative Concentration Pathway), taking uncertainties from the climate model structure and bias correction into account. On average, the total HTS in China is estimated at 38.6 billion yuan/y (US $6.22 billion/y) over the 1979-2005 period, which is equivalent to 0.2% of the gross domestic product (GDP). Assuming that the HTS standards (per employee per hot day) remain unchanged throughout the 21st century, the total HTS may reach 250 billion yuan/y in the 2030s and 1,000 billion yuan/y in 2100. We further show that, without specific adaptation, the increased HTS cost is mainly determined by population growth until the 2030s and climate change after the mid-21st century because of increasingly frequent hot weather. Accounting for the likely possibility that HTS standards follow the wages, the share of GDP devoted to HTS could become as high as 3% at the end of 21st century.

Effect of climate change, CO2 trends, nitrogen addition, and land-cover and management intensity changes on the carbon balance of European grasslands.

Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE-GM a process-based carbon cycle model that describes specific management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance [i.e., net biome production (NBP)] of European grasslands over 1991-2010 on a 25 km × 25 km grid. The modeled average trend in NBP is 1.8-2.0 g C m(-2)  yr(-2) during the past two decades. Attribution of this trend suggests management intensity as the dominant driver explaining NBP trends in the model (36-43% of the trend due to all drivers). A major change in grassland management intensity has occurred across Europe resulting from reduced livestock numbers. This change has 'inadvertently' enhanced soil C sequestration and reduced N2 O and CH4 emissions by 1.2-1.5 Gt CO2 -equivalent, offsetting more than 7% of greenhouse gas emissions in the whole European agricultural sector during the period 1991-2010. Land-cover change, climate change and rising CO2 also make positive and moderate contributions to the NBP trend (between 24% and 31% of the trend due to all drivers). Changes in nitrogen addition (including fertilization and atmospheric deposition) are found to have only marginal net effect on NBP trends. However, this may not reflect reality because our model has only a very simple parameterization of nitrogen effects on photosynthesis. The sum of NBP trends from each driver is larger than the trend obtained when all drivers are varied together, leaving a residual - nonattributed - term (22-26% of the trend due to all drivers) indicating negative interactions between drivers.

The greenhouse gas balance of European grasslands.

The greenhouse gas (GHG) balance of European grasslands (EU-28 plus Norway and Switzerland), including CO2 , CH4 and N2 O, is estimated using the new process-based biogeochemical model ORCHIDEE-GM over the period 1961-2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N2 O and CH4 emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land-use change, and variable CO2 and climate. The carbon balance of European grassland (NBP) is estimated to be a net sink of 15 ± 7 g C m(-2 ) year(-1) during 1961-2010, equivalent to a 50-year continental cumulative soil carbon sequestration of 1.0 ± 0.4 Pg C. At the farm scale, which includes both ecosystem CO2 fluxes and CO2 emissions from the digestion of harvested forage, the net C balance is roughly halved, down to a small sink, or nearly neutral flux of 8 g C m(-2 ) year(-1) . Adding CH4 and N2 O emissions to net ecosystem exchange to define the ecosystem-scale GHG balance, we found that grasslands remain a net GHG sink of 19 ± 10 g C-CO2 equiv. m(-2 ) year(-1) , because the CO2 sink offsets N2 O and grazing animal CH4 emissions. However, when considering the farm scale, the GHG balance (NGB) becomes a net GHG source of -50 g C-CO2 equiv. m(-2 ) year(-1) . ORCHIDEE-GM simulated an increase in European grassland NBP during the last five decades. This enhanced NBP reflects the combination of a positive trend of net primary production due to CO2 , climate and nitrogen fertilization and the diminishing requirement for grass forage due to the Europe-wide reduction in livestock numbers.

Meningococcal meningitis in Mali: a long-term study of persistence and spread.

OBJECTIVES: Meningococcal meningitis (MM) is still a huge threat in the African meningitis belt. To fight against epidemics, a strengthened health information system, based upon weekly collected data, was set up in Mali. We aimed to study the spatio-temporal dynamics of MM in this country between 1992 and 2003. METHODS: We were first interested in the impact of population size on the disease persistence. We then used cross-correlation analysis to study the spread of the disease on three different spatial scales, i.e., inter-region (global) and inter-district and intra-district (local) levels. RESULTS: We found no persistence of MM at district level in Mali during the whole of the study period. However, we found persistence on a nationwide scale after the 1997 big epidemics, as opposed to the 1992-1996 time periods. In terms of spread, two main regions seem to lead MM dynamics in Mali, even if on a local scale the 'cities-villages' diffusion pattern was not systematically observed. CONCLUSIONS: This study improves knowledge on the spread and persistence of MM in Mali in recent years. It constitutes a first spatial study describing persistence and spread of MM in an African meningitis belt country. The next step should be the integration of vaccination and genetic variability data to clarify the route of spread of the disease in the human population.

Relationships between climate and year-to-year variability in meningitis outbreaks: a case study in Burkina Faso and Niger.

BACKGROUND: Every year, West Africa is afflicted with Meningococcal Meningitis (MCM) disease outbreaks. Although the seasonal and spatial patterns of disease cases have been shown to be linked to climate, the mechanisms responsible for these patterns are still not well identified. RESULTS: A statistical analysis of annual incidence of MCM and climatic variables has been performed to highlight the relationships between climate and MCM for two highly afflicted countries: Niger and Burkina Faso. We found that disease resurgence in Niger and in Burkina Faso is likely to be partly controlled by the winter climate through enhanced Harmattan winds. Statistical models based only on climate indexes work well in Niger showing that 25% of the disease variance from year-to-year in this country can be explained by the winter climate but fail to represent accurately the disease dynamics in Burkina Faso. CONCLUSION: This study is an exploratory attempt to predict meningitis incidence by using only climate information. Although it points out significant statistical results it also stresses the difficulty of relating climate to interannual variability in meningitis outbreaks.

Comparative study of meningitis dynamics across nine African countries: a global perspective.

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.

Climate drives the meningitis epidemics onset in west Africa.

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.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact.

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10 degrees N-17 degrees N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel-Guillot-Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10-50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level.