Abstract
This article investigates the magnitude and significance of spatial-temporal trends of 37 years' time series of the gridded data for rainfall, maximum (Tmax) and minimum (Tmin) temperature for West Africa. A modified Mann-Kendall test and Theil-Sen's slope estimator were utilized to test the significance and the magnitude of trends, respectively. The magnitude of significant trends for three variables between six agroecological zones (AEZs) was compared. Gridded climate data represented gauge data with high accuracy and, therefore, can reliably complement the sparse observation network in West Africa. The three variables showed significant positive and negative trends of varying magnitude and spatial extent. June to September rainfall showed a positive increase (0.1-5 mm/month/year) that mostly occurred north of 11° latitude. October rainfall showed a positive trend across the region, but the magnitude was higher south of the same latitude. A widespread significant warming trend was observed across all AEZs and months. However, a localized cooling in August and September over the Sahel and Sudan Savanna was an exception. The cooling over the two AEZs coincided with a positive trend of rainfall. The zonal analysis revealed that the magnitude of the positive trend of June, September, and October rain increased following a North-South gradient from the Sahel to humid forest AEZs. Results provide spatial evidence of climate change in a limited data environment to guide the targeting of appropriate adaptation measures. The information generated from this article helps the design of early warning systems against droughts and floods.
Highlights
C LIMATE change and variability have significant positive or negative impacts on the productivity and resilience of agroecosystems across different regions [1]–[3]
climate hazards group infrared precipitation with stations (CHIRPS)-v2 and TC rainfall products, the underestimation bias of rainfall values above 100 mm was higher and more prevalent compared to the overestimation bias of low values
Recent evaluations of monthly gridded CHIRPS-v2 data against gauge station observations in West Africa reported a high correlation that is similar to the results reported in this study [15], [18], [28]
Summary
C LIMATE change and variability have significant positive or negative impacts on the productivity and resilience of agroecosystems across different regions [1]–[3]. These impacts are more severe in predominantly rain-fed agricultural systems in Africa, where they confound with extreme poverty and rapid population growth [4]. The fifth assessment report of the United Nations Intergovernmental Panel on Climate Change (IPCC) estimated increased warming and wet season rainfall.
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