Analysis of the in-situ and MODIS albedo variability at multiple time scales in the Sahel.

The variability of the Sahelian albedo is investigated through the combined analysis of five years of in situ radiation data from the AMMA northernmost sites (Agoufou 1°28'W, 15°20'N and Bamba 1°24'W, 17°06'N Mali) and remotely sensed albedo from seven years of MODIS data. Both datasets are found to be in good agreement in terms of correlation and bias. The drivers of albedo variability are identified by means of in situ measurements of biological and physical properties of the land surface collected over a network of 25 long-term survey sites. Short-term variability is dominated by changes in the spectral composition of incident radiation, which reflects aerosol optical depth and integrated water content, and changes in soil moisture, which have a short-lived effect (1 day). Bush fires cause a marked decrease of albedo of the order of 10 days, whereas a dry season storm event is suspected to have increased albedo through litter and soil surface abrasion. Seasonal plant growth causes the largest changes in rainy season albedo, and displays a large interannual variability: Because of the 2004 drought, albedo increases steadily from late 2003 toearly 2005 at latitude 15°N. Dry season albedo is controlled by the amount of litter and standing dead phytomass hiding the bright soils. Grazing pressure is found to impact albedo mostly in the dry season, through the pace of dry phytomass decay. EOF analysis and Hovmüller diagrams (10°W to 0°, 10°N to 20°N) show these effects to be present on a large scale. Above average rainfall thus have a direct effect on albedo through plant growth but also a lagged effect caused by above normal amounts of dry phytomass that can persist until the arrival of the next monsoon. This provides positive feedbacks at both the intra-seasonal and inter seasonal scales. Surface albedo in the Sahel exhibits a strong variability at different timescales caused by external forcing and internal dynamics of land surface, which should be included in climate models