Analyse de la variabilité décennale et du changement climatique en Afrique de l'ouest à l'aide des produits CMIP5-Application à l'estimation des rendements agricoles à la fin du siècle.

The West African monsoon is characterized by high decadal and multi-decadal variability whose impacts can be catastrophic on local populations. The factors advanced to explain this variability put in competition the role of sea surface temperatures and atmospheric dynamics related in particular to Saharan Heat Low. In addition, the emergence of the climate change footprint on the West African Monsoon, linked to the increase in greenhouse gas emissions,involves regional effects (radiative forcing on the Saharan atmospheric circulation) and global effects (radiative forcing on sea temperatures). This thesis addresses these questions by comparing the sets of control and historical simulations of climate models carried out in the CMIP5 project with observational data from the 20th century.Through multivariate statistical analyses, it has been established that decadal modes of ocean variability (AMO, IPO and IDV) and decadal variability of Saharan atmospheric dynamics significantly influence the decadal variability of monsoon rainfall. These results also suggest the existence of an external anthropogenic forcing that is superimposed on the natural decadal variability inducing signal intensification in historical simulations compared to control simulations. In addition, we have shown that the decadal variability of rainfall in the Sahel, once the influence of oceanic modes has been eliminated, appears to be driven mainly by the activity of the Arabian Heat Low in the central Sahel and by the meridional temperature gradient structure in the western Sahel over the intertropical Atlantic.Moreover, the long-term evolution of the West African Monsoon over the period 1901-2099 is reflected in climate simulations by precipitation patterns over West Africa that are quite different from one model to another, which have been grouped into five categories, which may be very different from the multi-model average. We have also shown in these climate projections an increasing contribution of extreme daily rainfall to total rainfall accumulation, linked to anupward trend over the 21st century in the intensity of forcing factors such as vertical wind shear or the amount of precipitable water. Finally, bias corrections were applied to the daily climate model data and sensitivity to different reference data sets was demonstrated. Then the projections of the evolution of agricultural yields over the 21st century were made, showing a decline in yields in West Africa at the end of the century.La mousson ouest-africaine est caractérisée par une forte variabilité décennale et multidécennale dont les impacts peuvent être catastrophiques sur les populations locales. Les facteurs avancés pour expliquer cette variabilité mettent à contribution le rôle des températures de surface de mer et la dynamique atmosphérique liée en particulier à la dépression thermique saharienne. Par ailleurs, l’émergence de l’empreinte du changement climatique sur la mousson ouest-africaine, liée à l’augmentation des émissions de gaz à effet de serre, met en jeu des effets régionaux (forçage radiatif sur la circulation atmosphérique saharienne) et des effets globaux (forçage radiatif sur les températures de surface de mer). Cette thèse aborde ces questions en confrontant les ensembles de simulations de contrôle et historiques de modèles de climat réalisées dans le cadre du projet CMIP5 et les données d’observations sur le 20ème siècle.A travers des analyses statistiques multivariées, il a été établi que les modes décennaux de variabilité océaniques (AMO, IPO et IDV) et la variabilité décennale de la dynamique atmosphérique saharienne influencent de façon significative la variabilité décennale des précipitations de mousson. Ces résultats suggèrent aussi l’existence d’un forçage externe d’origine anthropique qui vient se superposer à la variabilité décennale naturelle induisant une intensification du signal dans les simulations historiques par rapport aux simulations de contrôle. De plus, nous avons montré que la variabilité décennale des pluies au Sahel, une fois l’influence des modes océaniques éliminés, apparaît pilotée principalement, sur le Sahel central par l’activité de la dépression thermique d’Arabie, et pour le Sahel ouest par la structure de gradient méridien de température sur l’Atlantique intertropical.Par ailleurs, l’évolution long-terme de la mousson ouest-africaine sur la période 1901-2099 se traduit dans les simulations climatiques par des structures de précipitations sur l’Afrique de l’ouest assez différentes d’un modèle à un autre, que l’on a regroupées en cinq catégories, pouvant être très différentes de la moyenne multi-modèle. Nous avons aussi montré dans ces projections climatiques une contribution de plus en plus accrue des pluies journalières extrêmes dans le cumul total des pluies, liée à une tendance à la hausse sur le 21ème siècle de l’intensité des facteurs de forçage comme le cisaillement vertical du vent ou la quantité d’eau précipitable. Enfin, des corrections de biais ont été appliquées aux données journalières des modèles de climat et la sensibilité à différents jeux de données de référence a été démontrée. Puis les projections sur le 21ème siècle de l’évolution des rendements agricoles ont été réalisées, montrant une baisse des rendements en Afrique de l’ouest à la fin du siècle

Reduction of CMIP5 models bias using Cumulative Distribution Function transform and impact on crops yields simulations across West Africa

International audienceDifferent CMIP exercises show that the simulations of the future/current temperature and precipitation are complex with a high uncertainty degree. For example, the African monsoon system is not correctly simulated and most of the CMIP5 models underestimate the precipitation. Therefore, Global Climate Models (GCMs) show significant systematic biases that require bias correction before it can be used in impacts studies. Several methods of bias corrections have been developed for several years and are increasingly using more complex statistical methods. The aims of this work is to show the interest of the CDFt (Cumulative Distribution Function transfom (Michelan-geli et al.,2009)) method to reduce the data bias from 29 CMIP5 GCMs over Africa and to assess the impact of bias corrected data on crop yields prediction by the end of the 21st century. In this work, we apply the CDFt to daily data covering the period from 1950 to 2099 (Historical and RCP8.5) and we correct the climate variables (temperature, precipitation, solar radiation, wind) by the use of the new daily database from the EU project WATer and global CHange (WATCH) available from 1979 to 2013 as reference data. The performance of the method is assessed in several cases. First, data are corrected based on different calibrations periods and are compared, on one hand, with observations to estimate the sensitivity of the method to the calibration period and, on other hand, with another bias-correction method used in the ISIMIP project. We find that, whatever the calibration period used, CDFt corrects well the mean state of variables and preserves their trend, as well as daily rainfall occurrence and intensity distributions. However, some differences appear when compared to the outputs obtained with the method used in ISIMIP and show that the quality of the correction is strongly related to the reference data. Secondly, we validate the bias correction method with the agronomic simulations (SARRA-H model (Kouressy et al., 2008)) by comparison with FAO crops yields estimations over West Africa. Impact simulations show that crop model is sensitive to input data. They show also decreasing in crop yields by the end of this century. Michelangeli, P. A., Vrac, M., & Loukos, H. (2009). Probabilistic downscaling approaches: Application to wind cumulative distribution functions. Geophysical Research Letters, 36(11). Kouressy M, Dingkuhn M, Vaksmann M and Heinemann A B 2008: Adaptation to diverse semi-arid environments of sorghum genotypes having different plant type and sensitivity to photoperiod. Agric. Forest Meteorol., http://dx

Impact of Climate Change in West Africa on Cereal Production Per Capita in 2050

International audienceFood security is a crucial issue in the Sahel and could be endangered by climate change and demographic pressure during the 21st century. Higher temperatures and changes in rainfall induced by global warming are threatening rainfed agriculture in this region while the population is expected to increase approximately three-fold until 2050. Our study quantifies the impact of climate change on food security by combining climate modelling (16 models from CMIP5), crop yield (simulated by agronomic model, SARRA-O) and demographic evolution (provided by UN projection) under two future climatic scenarios. We simulate yield for the main crops in five countries in West Africa and estimate the population pressure on crop production to assess the number of available cereal production per capita. We found that, although uncertain, the African monsoon evolution leads to an increase of rainfall in Eastern Sahel and a decrease in Western Sahel under the RCP8.5 (Representative Concentration Pathway) scenario from IPCC, leading to the higher temperature increase by the end of the 21st century. With regard to the abundance of food for the inhabitants, all the scenarios in each country show that in 2050, local agricultural production will be below 50 kg per capita. This situation can have impact on crop import and regional migratio

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

International audienceThe 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

A bias-corrected CMIP5 dataset for Africa using the CDF-t method : a contribution to agricultural impact studies

International audienceThe objective of this paper is to present a new dataset of bias-corrected CMIP5 global climatemodel (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950–2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to thedifferences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century

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

Heat waves in spring from Senegal to Sahel: Evolution under climate change

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Consequences of rapid ice sheet melting on the Sahelian population vulnerability

International audienceThe 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 agro-ecosystem. 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