Earth and Atmospheric Sciences, Department of


Date of this Version



Environ. Res. Lett. 11 (2016) 095005


©2016 IOP Publishing Ltd

Open access



The Northern Sub-Saharan African (NSSA) region, which accounts for 20%–25%of the global carbon emissions from biomass burning, also suffers from frequent drought episodes and other disruptions to the hydrological cycle whose adverse societal impacts have been widely reported during the last several decades. This paper presents a conceptual framework of the NSSA regional climate system components that may be linked to biomass burning, as well as detailed analyses of a variety of satellite data for 2001–2014 in conjunction with relevant model-assimilated variables. Satellite fire detections in NSSA show that the vast majority (>75%) occurs in the savanna and woody savanna land-cover types. Starting in the 2006–2007 burning season through the end of the analyzed data in 2014, peak burning activity showed a net decrease of 2–7%/yr in different parts of NSSA, especially in the savanna regions. However, fire distribution shows appreciable coincidence with land-cover change. Although there is variable mutual exchange of different land cover types, during 2003–2013, cropland increased at an estimated rate of 0.28%/yr of the total NSSA land area,with most of it (0.18%/yr) coming from savanna.During the last decade, conversion to croplands increased in some areas classified as forests and wetlands, posing a threat to these vital and vulnerable ecosystems. Seasonal peak burning is anticorrelated with annual water-cycle indicators such as precipitation, soil moisture, vegetation greenness, and evapotranspiration, except in humid West Africa (5°–10° latitude),where this anti-correlation occurs exclusively in the dry season and burning virtually stops when monthly mean precipitation reaches 4 mm d−1. These results provide observational evidence of changes in land-cover and hydrological variables that are consistent with feedbacks from biomass burning in NSSA, and encourage more synergistic modeling and observational studies that can elaborate this feedback mechanism.