Statistical Modelling of Intensity Modes of Rainfall Using Principal Component Itemization: A Case Study of Kano State

Abstract

Kano State is experiencing greater weather extremes, changes in rainfall patterns, analysis of heat and cold waves, and increasing droughts and floods (Kano meteorological agency). As a result, there is a need for the provision of the necessary weather advisories and early warnings to planners, decision-makers, and operators of the various rainfall-sensitive socio-economic sectors. However, this study is aiming to realize some hidden variables of Kano State total monthly rainfall dataset from the onset to cessation period of rain from the month of April to October over a 105 years (1911-2015) for classification into the intensity of the rain of the area under study, also to determine the linear model for the changing patterns of rainfall in Kano State and to identify some of the adverse impacts on socio-economic sectors and transport infrastructures. Thus, the appearances of the rainfall figure are established for the study region with the operation of Principal Component Analysis (PCA), application least square method. The leading three (3) PCs, gives account for about 61% of the entire disparity, is described. The revision displays and describe PC1 as associated with the heavy intensity rainfall, whereas PC2 is connected to the moderate-intensity rainfall and finally PC3 is linked to the light intensity rainfall of the region under study. By the scores of our PCs, uniform rainfall zones are established over the region of enquiring to which the yearly performance of rainfall is discussed. Statistically, all three models for the various mode of rainfall intensity are significant, which serves as the annual pattern of rainfall in the study area.