Geographic segmentation, spatial dependencies, and evaluation of the relative position of rain-gauges based on gridded data of mean monthly precipitation: application in Nigeria

Abstract

Abstract The aim of the study is to present a combination of techniques for (a) the spatiotemporal analysis of mean monthly gridded precipitation datasets and (b) the evaluation of the relative position of the existing rain-gauge network. The mean monthly precipitation (P) patterns of Nigeria using ∼1 km2 grids for the period 1950–2000 were analyzed and the position of existing rain-gauges was evaluated. The analysis was performed through: (a) correlations of P versus elevation (H), latitude (Lat) and longitude (Lon); (b) principal component analysis (PCA); (c) Iso-Cluster and maximum likelihood classification (MLC) analysis for terrain segmentation to regions with similar temporal variability of mean monthly P; (d) use of MLC to create reliability classes of grid locations based on the mean clusters’ characteristics; and (e) analysis to evaluate the relative position of 33 rain-gauges based on the clusters and their reliability classes. The correlations of mean monthly P versus H, Lat, Lon, and PCA highlighted the spatiotemporal effects of the Inter Tropical Discontinuity phenomenon. The cluster analysis revealed 47 clusters, of which 22 do not have a rain-gauge while eight clusters have more than one rain-gauge. Thus, more rain-gauges and a better distribution are required to describe the spatiotemporal variability of P in Nigeria.