Changes in Sahelian annual vegetation growth and phenology since 1960: A modeling approach

• Sahelian annual vegetation is simulated from 1960 to 2014
• Simulated vegetation captures phenology and spatial patterns as observed by satellite
• The present vegetation cover is still far below its pre-drought levels

In semi-arid areas like the Sahel, vegetation is particularly sensitive to climate variability and can play an important role in surface-atmosphere coupling. After a wet period extending from 1950 to 1970, the Sahel experienced a severe drought in the 1970s and 1980s, followed by a partial recovery of rainfall and a “re-greening” of vegetation beginning in the 1990s. This study explores how the multidecadal variability of Sahelian rainfall and particularly the drought period have affected vegetation phenology and growth since 1960.The STEP model, which is specifically designed to simulate the Sahelian annual vegetation, including the dry season processes, is run over an area extending from 13°N to 18°N and from 20°W to 20°E. Mean values, interannual variability and phenological characteristics of the Sahelian annual grasslands simulated by STEP are in good agreement with MODIS derived production and phenology over the 2001–2014 period, which demonstrates the skill of the model and allows the analysis of vegetation changes and variability over the last 50 years.It was found that droughts in the 1970s and 1980s shortened the mean vegetation cycle and reduced its amplitude and that, despite the rainfall recovery since the 1990s, the current conditions for green and dry vegetation are still below pre-drought conditions. While the decrease in vegetation production has been largely homogeneous during droughts, vegetation recovery has been heterogeneous over the Sahel since 1990, with specific changes near the western coast and at the eastern edge of the West African monsoon area. Since 1970, the Sahel also experienced an increased interannual variability in vegetation mass and phenology. In terms of phenology, region-averaged End and Length of Season are the most variable, while maximum date and Start of Season are the least variable, although the latter displays a high variability locally.