ANALYSIS OF CLIMATE DATA USING SPATIAL TECHNIQUES TO ESTIMATE RAINFALL IN THE NORTH WEST OF NIGERIA (FUDMA JOURNAL OF SCIENCES, 2022)
The study inspect the spatial variation of Rainfall in different localities in the North West of Nigeria, Rainfall data present the basic metrological role in many field of geostatistical and practice, that is why it’s one of the major climate resources that can be used as a measuring tool of climate change. The aim was to analyzed the data of one decade for thirty sample locations from (2010 – 2019) obtained from NIMET using three different spatial models and compare the models performance in order to obtained the optimal model that can be used for rainfall prediction in the study Area. The assessment of the optimal model is based on the validation methods used in the research that is the method of RMSE and R2. The supportive auxiliary variables which have been used in estimating neighboring locations are Humidity, Temperature, Pressure and Wind speed. The predicted Rainfall in the models has proved the theory of ITCZ, and the locations with a higher predicted Rainfall are in the southern part while the locations with a lower predicted Rainfall are in the northern part of the study Area in all the models, regarding the validation methods used in the research, Geographically weighted Regression (GWR) outperform Ordinary Kring (O.K) and Inverse Distance Weighting (IDW) in terms of RMSE and R2.
Keywords: Geographically Weighted Regression, Inverse Distance Weighting, Ordinary Kriging, Rainfall