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

Abstract

Food 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 migration.

High-resolution downscaled CMIP5 projections dataset of essential surface climate variables over the globe coherent with ERA5 reanalyses for climate change impact assessments

“…CDF-t was first developed for wind values and is now referenced in dozens of peer-reviewed publications to downscale different sets of data and variables (e.g. [10][11][12]). QM methods relate the cumulative distribution function of a climate variable at large scale (e.g., from the GCM) to the CDF of the same variable at a local scale (e.g., from the reanalyses) and are increasingly popular in climate applications although bias correction methods have received criticism (e.g.…”

A high-resolution downscaled CMIP6 projections dataset of essential surface climate variables over the globe coherent with the ERA5-Land reanalysis for climate change impact assessments

“…CDF-t was first developed for wind values and is now referenced in dozens of peer-reviewed publications to downscale different sets of data and variables (e.g. [10][11][12]). QM methods relate the cumulative distribution function of a climate variable at large scale (e.g., from the GCM) to the CDF of the same variable at a local scale (e.g., from the reanalysis).…”

High-resolution downscaled CMIP5 projections dataset of essential surface climate variables over Europe coherent with ERA5-Land reanalyses for climate change impact assessments

“…CDF-t was first developed for wind values and is now referenced in dozens of peer-reviewed publications to downscale different sets of data and variables (e.g. [9][10][11]). QM methods relate the cumulative distribution function of a climate variable at large scale (e.g., from the GCM) to the CDF of the same variable at a local scale (e.g., from the reanalyses) and are increasingly popular in climate applications although bias correction methods have received criticism (e.g.…”