The standardized precipitation index (SPI) is computed and analyzed using 55 years of precipitation data recorded in 24 observation stations in Cameroon along with University of East Anglia Climate Research Unit (CRU) spatialized data. Four statistical distribution functions (gamma, exponential, Weibull, and lognormal) are first fitted to data accumulated for various time scales, and the appropriate functions are selected on the basis of the Anderson–Darling goodness-of-fit statistic. For short time scales (up to 6 months) and for stations above 10°N, the gamma distribution is the most frequent choice; below this belt, the Weibull distribution predominates. For longer than 6-month time scales, there are no consistent patterns of fitted distributions. After calculating the SPI in the usual way, operational drought thresholds that are based on an objective method are determined at each station. These thresholds are useful in drought-response decision making. From SPI time series, episodes of severe and extreme droughts are identified at many stations during the study period. Moderate/severe drought occurrences are intra-annual in short time scales and interannual for long time scales (greater than 9 months), usually spanning many years. The SPI calculated from CRU gridded precipitation shows similar results, with some discrepancies at longer scales. Thus, the spatialized dataset can be used to extend such studies to a larger region—especially data-scarce areas.
Discriminating climate impacts between 1.5 • C and 2 • C warming levels is particularly important for Central Africa, a vulnerable region where multiple biophysical, political, and socioeconomic stresses interact to constrain the region's adaptive capacity. This study uses an ensemble of 25 transient Regional Climate Model (RCM) simulations from the CORDEX initiative, forced with the Representative Concentration Pathway (RCP) 8.5, to investigate the potential temperature and precipitation changes in Central Africa corresponding to 1.5 • C and 2 • C global warming levels. Global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to drive the RCMs and determine timing of the targeted global warming levels. The regional warming differs over Central Africa between 1.5 • C and 2 • C global warming levels. Whilst there are large uncertainties associated with projections at 1.5 • C and 2 • C, the 0.5 • C increase in global temperature is associated with larger regional warming response. Compared to changes in temperature, changes in precipitation are more heterogeneous and climate model simulations indicate a lack of consensus across the region, though there is a tendency towards decreasing seasonal precipitation in March-May, and a reduction of consecutive wet days. As a drought indicator, a significant increase in consecutive dry days was found. Consistent changes of maximum 5 day rainfall are also detected between 1.5 • C vs. 2 • C global warming levels.
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