For historical droughts during major growing seasons in sub-Saharan Africa, we evaluate ETo and identify main drivers for drought cases--identified based on below-normal precipitation during the wettest three months of the growing season--and contrast these with the ETo drivers that dominate in wetter years (we also consider droughts triggered by above normal ETo). Our focus is on regions of Africa where adequate precipitation is important for productive agriculture and pastoral activities and where evaporative demand might exacerbate moisture limitations, e.g., the Sahel and semi-arid East and Southern Africa. It is expected that important ETo drivers are partly connected with precipitation-related processes (e.g., cloud cover and radiation, temperature, humidity) but that there are variations between regions and events. Factors less directly related to precipitation processes (e.g. wind speed) could also play an important role. The goal here is to provide a generalized understanding of what aspects of evaporative demand historically have posed an additional hazard to plant stress and how precipitation outcomes are responsible for the ETo drivers. In addition, we explore whether there have been discernible changes through time in regard to ETo drivers during below-normal precipitation seasons.
Upper and lower terciles of CHIRPS precipitation are used to identify anomalous dry and wet cases. The ETo dataset spans the 1980-near present period and is calculated following ASCE's formulation of Penman-Monteith method driven by daily temperature, humidity, wind speed, and solar radiation from NASA’s MERRA-2; this data is the basis for the Evaporative Demand Drought Index (EDDI). For this analysis, daily ETo and drivers are aggregated to monthly and seasonal time steps. ETo drivers are identified with the decomposition method from Hobbins et al. (2016), which considers the anomalies in meteorological variables and the sensitivity of ETo to each of them.
Hobbins, M. T., Wood, A., McEvoy, D. J., Huntington, J. L., Morton, C., Anderson, M., & Hain, C. (2016). The evaporative demand drought index. Part I: Linking drought evolution to variations in evaporative demand. Journal of Hydrometeorology, 17(6), 1745-1761.