| Abstract: | African precipitation trends are commonly analyzed using short-term data observed over small areas. This study analyzed changes in long-term (1901–2015) annual and seasonal precipitation of high spatial (0.5°?×?0.5° grid) resolution covering the entire African continent. To assess an acceleration/deceleration of the precipitation increase/decrease, trend magnitude (mm/year) over the period 1991–2015 was subtracted from that of 1965–1990 to obtain Slope Difference (SD, mm/year). Co-variation of precipitation sub-trends with changes in large-scale ocean–atmosphere conditions was investigated. Regardless of the trend significance, in most parts of Africa, annual precipitation exhibited negative (positive) trends over the period 1965–1990 (1991–2015). Thus, the continent was, on average, recently (from 1991 to 2015) wetter than it was over the period 1965–1990. From 1901 to 2015, the null hypothesis H0 (no trend) was rejected (p < 0.05) for annual precipitation decrease over West Africa especially along the coastal areas near the Gulf of Guinea. The H0 was also rejected (p < 0.05) for the increase in annual and September–November precipitation of some areas along the Equatorial region (such as in Gabon and around Lake Victoria). For both annual and seasonal precipitation, the least SD values in the range ??1 to 1 mm/year were obtained in areas north of 10° N. The SD value went up to about 20 mm/year over the Sahel belt especially for the peak monsoon (June–August season). For the March–May precipitation, positive SD values were obtained in the Western part of Southern Africa. However, negative SD values (around ??5 mm/year) were obtained in the Horn of Africa. Variation in sub-trends of the East African precipitation was found to be driven by changes in Sea Surface Temperature (SST) of the Indian and Atlantic Oceans. Variability in sub-trends of the West African precipitation is linked to changes in SST of the Atlantic Ocean. Changes in sub-trends of the South African precipitation correspond to anomalies in SST from the Pacific and Indian Oceans. Knowledge of precipitation changes and possible drivers is vital for predictive adaptation regarding the impacts of climate variability on hydro- or agro-meteorology. |
