Trends and Geostatistical Interpolation of Spatio-Temporal Variability of Precipitation in Northern Cameroon

Abstract

This paper examines the spatial and temporal variability of the mean annual precipitation in the Northern Cameroon on the context of climate change during the time period 1950-2013. The study used homogeneous monthly and annual precipitations database of twenty-five stations located in the Northern Cameroon and Southern Chad Republic. Geostatisticals interpolation methods (Kriging and Inverse Distance Weighting method) associated with Digital Elevation Model were used to establish the spatial distribution of annuals precipitations. The non-parametric Mann-Kendall test and Sen's slope method were performed to determine respectively trend and magnitude. The result indicates a spatial distribution of precipitation mainly determined by the topography and the geography of the study area. The trend analysis shows a decrease of annual average precipitation across the Northern Cameroon at a rate of −0.568 mm/year over the time period 1950-2013. The magnitude of decreasing trends ranged between 0.11 and 3.92 mm/year. Statistically significant decreasing trends at the 95% level of confidence were noted at 10% while 5% of stations showed statistically significant increasing. However, 60% of stations indicate a decreasing trend. Monthly analysis of rainfall shows a decreasing trend during June and September while July and August present an increasing trend.

Simulated impact of global warming on extreme rainfall events over Cameroon during the 21st century

“…Note that, while all analyses on the spatial distributions of these indices are made for all seasons, that is, December–January–February (DJF), March–April–May (MAM), June–July–August (JJA) and September–October–November (SON), their inter‐annual variability is analysed over three zones (Zone 1: 9–12°N and 13–15°E; Zone 2: 4–6°N and 9–11°E; and Zone 3: 2–4°N and 12–16°E), selected on the basis of their high vulnerability and for their recurrent exposure to extreme events in recent years (Zogning et al, 2008; Dassou et al, 2016; Chouto and Wakponou, 2017; Tanessong et al, 2017; Saha and Tchindjan, 2017; Djuidje et al, 2019).…”

Assessment of agricultural drought during crop-growing season in the Sudano–Sahelian region of Cameroon

“…Kriging is a stochastic interpolation technique (Journel and Huijbregts 1978;Isaaks and Srivastava 1989) and is largely recognized as a standard approach for surface interpolation based on scalar measurements at different locations (Shahid and Behrawan 2008). Djoufack et al (2012) and Dassou et al (2016) showed that Kriging gives better global predictions than the Inverse Distance Weighting (IDW) in the current study domain.…”

“…Climatically, this study area falls within the Sudano-Sahelian domain that portrays a high inter-annual variability in its whole area, increasing from south to north. This may be attributed to the topography of the region (Dassou et al 2016), which features lowlands with altitudes within 95 and 795 m.…”

“…Few stations (less than 4%) have missing values. Dassou et al (2016), recently used most parts of this dataset. Our study focuses on the seasons of major crop cultivation in northern Cameroon, for the period 1980-2012 (from the sowing season to the harvesting season).…”

“…timescale) from 1980 to 2012. This method is widely applied in hydro climatic trend analysis(Dassou et al 2016;Shiru et al 2019;Ayugi and Tan 2018).The test statistic Z was computed as follows:…”