Journal of Geography, Environment and Earth Science International

Abstract

The convective systems and maximum temperature are key weather parameters that affect various sectors of the Nigerian economy, especially Agriculture, health and transportation. Agriculture which is the mainstay of the economy of Nigeria is weather driven. A balanced weather condition brings about good crop yield which in turn have a positive impact on the economy. The aim of this study was to evaluate the relationship between rainfall, maximum temperature and convective activities over Ikeja, Abuja and Kano cities in Nigeria. Monthly weather data of squall, thunderstorms, maximum temperature and rainfall were obtained from the archives of the Nigeria Meteorological Agency for the period between 1985 and 2015 (30 years). Seasonal and inter-annual variations and relationships between the parameters were analyzed. Over Ikeja the result highlighted a gradual increase in these parameters from January to May/June, while the decrease began from October through to December. Further analysis revealed two separate peak periods for these parameters, with rainfall having its peaks in the months of June and September; Thunderstorm, June and October, and squall attaining its maxima in May and October. Over Kano, March, April and May (MAM) and September, October and November (SON) period indicated that the rain that fell during that period had positive correlation while December, January and February (DJF) and June, July and August (JJA) has a negative correlation. Over Abuja, DJF, MAM and SON showed positive while JJA shows a negative correlation. There will be a need for further studies which will consider the role(s) being played by the various triggering mechanisms and the extent to which the influence of the occurrence of these convective activities rainfall and maximum temperature. The utilization of modelling and mapping techniques may also give further insight into the variation of these systems and a clue to issuing more accurate forecasts and predictions.