Evolution Des Indices Pluviométriques Extrêmes Par L'analyse De Modèles Climatiques Régionaux Du Programme CORDEX: Les Projections Climatiques Sur Le Sénégal

Sarr, Alioune Badara; Camara, Moctar

doi:10.19044/esj.2017.v13n17p206

Cited by 16 publications

(18 citation statements)

References 7 publications

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“…The second series of simulations (climate projections, period 2006-2100) aims to analyze the future evolution of the climate. In this context, several studies have been carried out (Sarr and Camara, 2017;Diallo et al, 2016;Sylla et al, 2016;Mariotti et al, 2014;Giorgi et al, 2014;Laprise et al, 2013) to identify the future evolution of the precipitation and the mean surface temperature. However, few research works have been devoted in studying the future evolution of extreme temperature events and its impact on human health in West Africa and particularly in Senegal.…”

Section: Introductionmentioning

confidence: 99%

Future evolution of surface temperature extremes and the potential impacts on the human health in Senegal

Sarr¹,

Diba²,

Basse³

et al. 2019

Afr. J. Environ. Sci. Technol.

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Climate change impacts negatively vulnerable regions such as West African countries like Senegal, through an increase of climate extremes. The objectives of this study is to analyze the future evolution of the extreme temperature events and their impacts on human health in Senegal during the cold (DJF), hot (MAM) and wet seasons (JAS) under the greenhouse gas scenarios RCP4.5 and RCP8.5 using Climate projections of five (5) regional climate models (RCMs) of the Coordinated Regional Climate Downscaling Experiment (CORDEX) program. The results show that the biases of the RCMs are globally low especially their ensemble mean of the RCMs. This ensemble mean was afterwards considered in the analysis of the climate extremes in the near (2021-2050) and far future (2071-2100). When considering the near future, the frequency of the hot nights (Tn90p) increases under the scenario RCP8.5 (up to 90%) during the rainy season in the south of the country. As for the percentage of the hot days (Tx90p), it may reach approximately 70% under the scenario RCP8.5 in DJF over the majority of the country. Moreover, a strong increase of Tn90p and Tx90p is also diagnosed during the far future with values exceeding 80% over most parts of the country. Concerning the evolution of the heat wave magnitude index-daily, the ensemble mean of all models shows that the heat waves are more severe in MAM and JAS under both scenarios during the near and the far future over most parts of the country. To estimate the potential impacts of this heat stress on the human health, the heat index and the humidex are used. The analysis of the heat index shows that the sanitary risks are more perceptible over the whole country during the rainy season with values reaching the symptom band II for both scenarios during the far future. As for the humidex, it is characterized by a gradual increase from the historical period to the far future. This analysis highlights the fact that appropriate adaptation measures should be considered to tackle efficiently the increase of temperature extremes which may impact negatively the human health.

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Section: Introductionmentioning

confidence: 99%

Future evolution of surface temperature extremes and the potential impacts on the human health in Senegal

Sarr¹,

Diba²,

Basse³

et al. 2019

Afr. J. Environ. Sci. Technol.

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“…The drawback of the above procedure of bias correction is the assumption of constant bias between the reference and future periods . However, we will accept this assumption as most of the recent studies did (Sarr and Camara, 2017) as mentioned earlier, bias correction and spatial disaggregation relies on finer-scale observation data and consists of the following steps: (1) aggregate finer-scale observed data to a RCM-specific scale; (2) correct the RCM's systematic biases through quantile mapping; and (3) disaggregate biascorrected outputs to a finer scale (Batablinlè et al, 2018). An equiratio cumulative distribution function matching (equiratio CDFm): The statistical transformation can be written as:…”

Section: Methodsmentioning

confidence: 89%

“…Pluviometric regimes will also be affected and may decrease of more than 20 % to 30 % compared to the reference (Bigot, 2003). Other studies indicated an increase in extreme rainfall events, particularly in Sahel (Nicholson and Webster, 2007) but also a decrease in Nigeria (Oguntundé et al, 2011) and (Easterling et al, 2000), Guinea Conakry (Aguilar et al, 2009), in eastern Niger (Ozer et al, 2009), in Ivory-Coast (Soro et al, 2014), in Benin (Yèkambèssoun et al, 2017) and in South Africa (Mason et al, 1999). In the northern part of Africa, there is a tendency towards wetter conditions; in contrast with the eastern part, experienced with more drying trends, although, these trends are of low significance.…”

Section: Introductionmentioning

confidence: 96%

Extreme Rainfall and Temperature Changes Assessment on late-twenty-first-century over the Mono River Basin, Togo (West-Africa)

et al. 2020

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Abstract. This study assessed the extreme rainfall and temperature changes over Mono river basin by the end of 21st century under the highest greenhouse gas emission scenario RCP8.5. Simulations of eight regional climate models (RCMs) provided by Africa-CORDEX program were considered. The maximum and minimum temperatures and rainfall were analyzed. Two groups of indices were analyzed. The first group consists of frequency indices: maximum number of consecutive dry days and wet days. The second group is intensity indices: five-day maximum rainfall and simple daily intensity index. These variables were calculated at annual and seasonal scales. Changes from the baseline period 1971–2000 were computed for far future 2071–2100. As result, almost all the RCMs considered predicted a decrease of the rainfall and increase of maximum and minimum temperatures over most parts of the Mono basin, particularly in the south. Declining mean monthly precipitation and irregular rainy seasons at all scales were exhibited by most of the models. Simple daily intensity and five-day maximum rainfall are projected to decrease by the majority of the used models. As for dry and wet sequences, the RCMs showed an increase of the consecutive dry days and a decrease of wet days.

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“…Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Sarr and Camara, 2017). Agriculture plays a significant role in the livelihood and economy growth of most African people (Kotir, 2010).…”

Section: Introductionmentioning

confidence: 91%

Simulation of the impact of climate change on peanut yield in Senegal

Sarr¹,

Camara²

2018

Int. J. Phys. Sci.

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This paper treats the impacts of climate change on peanut yield in Ziguinchor (Southwest of Senegal) during the near future (2021 to 2050) and the far future (2071 to 2100). The Decision Support System for Agrotechnology Transfer (DSSAT) crop model was run using daily weather data (maximum and minimum surface temperature, rainfall and solar radiation) of four (4) regional climate models (RCMs) of the Coordinated Regional Climate Downscaling Experiment (CORDEX). Two climate change scenarios (RCP4.5 and RCP8.5) are used to assess the climate change impact on peanut yield. First of all, the DSSAT crop model is calibrated and validated for peanut using relevant observed data: peanut yield and meteorological data. Compared to the reference period (1976 to 2005), the RCMs exhibit some disparities in the projected rainfall during the near and the far future. The ensemble mean of the models (Ens/RCMs) predict a strong decrease of rainfall under the RCP4.5 scenario and a slight decrease under the RCP8.5 scenario during both periods. A gradual increase in mean temperature is predicted by all models. However, this increase is stronger for the RCP8.5 scenario. Analysis of the yield change during the near future shows a decrease for all RCMs except RACMO22T model under the two considered scenarios. During the far future, all RCMs predict a decrease of the peanut yield. Moreover, this decrease is stronger for the RCP8.5 scenario. These results indicated that the peanut crop could be negatively affected by the climate change and adaptation strategies are needed to protect this sector.

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Evolution Des Indices Pluviométriques Extrêmes Par L'analyse De Modèles Climatiques Régionaux Du Programme CORDEX: Les Projections Climatiques Sur Le Sénégal

Cited by 16 publications

References 7 publications

Future evolution of surface temperature extremes and the potential impacts on the human health in Senegal

Future evolution of surface temperature extremes and the potential impacts on the human health in Senegal

Extreme Rainfall and Temperature Changes Assessment on late-twenty-first-century over the Mono River Basin, Togo (West-Africa)

Simulation of the impact of climate change on peanut yield in Senegal

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