Climate and Dynamics
Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data
Article first published online: 31 DEC 2005
Copyright 2005 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 110, Issue D24, 27 December 2005
How to Cite
2005), Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data, J. Geophys. Res., 110, D24115, doi:10.1029/2005JD006394., , , and (
- Issue published online: 31 DEC 2005
- Article first published online: 31 DEC 2005
- Manuscript Accepted: 20 OCT 2005
- Manuscript Revised: 19 SEP 2005
- Manuscript Received: 21 JUN 2005
- West Africa;
- soil moisture;
 The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation (CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document (1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and (2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed from July to October and when 1-month lag is considered between the parameters. This delay reflects the vegetation response time to the moisture pulses that follow precipitation events. The high correlation between NDVI and sigma_0 at interannual timescales confirms the importance of vegetation in the backscattering coefficient. However, sigma_0 shows stronger statistical links with precipitation, suggesting that this product contains additional useful information related in particular to upper soil moisture. Over Guinea, large differences are observed between the two remote sensing products, and their relationship with precipitation at interannual timescales is weaker. Sigma_0 is significantly linked to precipitation from July to November, whereas NDVI does not show any significant relationship with precipitation. NDVI and sigma_0 serial correlations over the Sahel and Guinea suggest that a 2-month memory usually characterizes vegetation photosynthetic activity and soil-vegetation water content anomalies. However, anomalies disappearance in winter then reappearance in the following spring also suggests an interseason memory held by deep soil moisture reservoirs and deep-rooted plants. A composite analysis reveals that the wettest Sahelian rainy seasons were preceded by positive anomalies of soil-vegetation water content over Guinea from winter to spring. Cross correlations and Granger causality analyses partly relate these winter to spring land surface anomalies to those recorded in precipitation during the previous autumn. Spring soil-vegetation water content anomalies strengthen the meridional gradient of soil-vegetation water content over the subcontinent. This gradient is thought to contribute to the gradient of entropy that drives the West African monsoon.