Diurnal and Interannual Variability of Rainfall in Nigeria Climatic Zones as Seen from In-situ and Satellite Measurements

Aladodo, S. S, Mathew, D. E, Otu, J. O., Najib Y., Akoshile, C. O.

Abstract


Rainfall has been considered as a key indicator of changes in the climate and important factor of flood. Its measurements are important for climate change assessment on the water cycle and water balance of the world while her intensities monitoring are necessary for flood predictions. This study investigated the variation of Rainfall Intensity and Rainfall depth in Nigeria climatic zones and to predict the reoccurrence of such type of rainfall for planning purposes. The climatic zones of Nigeria were grouped into four; Coastal, Rain forest, Savannah and Sahel. The Rainfall data used in this study were collected in five minutes average for rainfall intensity for years 2007 to 2015 from Centre for Atmospheric Research (CAR-NASRDA) using Automatic Weather Stations and Tropical Rain Measuring Mission (TRMM) of NASA while monthly rainfall depth of 1980 to 2010 from Nigeria Meteorological Agency (NiMet). The Intensity was converted from mm/5mins to mm/h followed by diurnal values over the months and annual rainfall amounts were derived from the monthly rainfall depth for variability and probability analysis. Statistical analyses were performed using SPSS package to further ascertain the deviations from normal rainfall pattern. The Result shows that short and violent rain (> 50mm/h) are more frequent in the Savannah and Sahel zones compared to Rain forest and Coastal zones where prolonged and light rain (< 2.5mm/h) persist. The Coastal zone experience the highest precipitation of 2823.50 mm while the least precipitation of 925.70 mm occurred in the Sahel during the period considered with some fluctuations within the zones. The decadal wetter trend zone is the Sahel with an increment in rainy of more than 200mm and other zones rainfall increase by nothing less than 50mm of rain since 1980s. The occurrence of yearly rainfall like these could be predicted using the probability curve generated from the annual rainfall values.

Keywords: rainfall, climatic zones, intensity, depth, probability


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ISSN (Paper)2224-3216 ISSN (Online)2225-0948

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