Modelling Monthly and Annual Trends of the Monthly Air Maximum Temperature in Ndjamena, Chad, Over the Climatic Period 1961-1990
Njipouakouyou Samuel *
Faculty of Sciences, University of Dschang, Cameroon.
Ali Mahamat Nour
Faculty of Sciences, University of Dschang, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
The present article models monthly and annual trends of the monthly air maximum temperature in Ndjamena over the climatic period from 1961 to 1990. Monthly mathematical mean values over the period of this parameter has been calculated with their corresponding standard deviations. High values were registered from March to June, the beginning of the rainy season in the locality, and low values – during the dry season, from December to February. Its interval of variation was from 32.3°C in January to 41.0°C in April. Concerning the standard deviation, its interval of variation was from 0.9°C in April to 1.8°C in January, February and December. Deviations of the monthly air maximum temperatures from their corresponding mathematical mean values were calculated for each month over the climatic period. Their time trends were modeled by the least squares method. Analysis of the configuration their clouds of points in rectangular coordinates systems has shown that all monthly trends were according to the linear relationship. The coefficients of the obtained regression lines were mostly 0.1. This low value indicates that the time trend of the air maximum temperature was not significant to produce notable impacts on the environment in the considered locality. Similar treatments were applied to annual trends. The results were qualitatively the same. Thus, it is obviously clear during this climatic period no thermal perturbations to bring significant impacts to the environment were observed. But the study has revealed a weak tendency to the rise of the maximum air temperature in Ndjamena, particularly by the end of the period.
Keywords: Air maximum temperature, climatic period, monthly and annual trends, mathematical mean values, standard deviations, deviations of the monthly air maximum temperature from their mathematical mean values, linear relationship, least squares method, linear regression