Climate Study of Owerri and Comparative Analysis of Different Methods of Base Factor Computation

Abstract

This study analyzed three decades of the temperature and rainfall data of Owerri, South Eastern Nigeria and in the process carried out a comparative analysis of using three different methods namely the mean, median and jackknife to derive the base data upon which the anomalies are computed with a view to ascertaining if any significant differences exist in the obtained results. And for rainfall which is seasonal, a further z-score method was employed to remove the effect of seasonality by dividing the anomalies with its standard deviation. Linear regression analysis was used to interpret the anomaly plots and the trend in climate from 1986 to 2015 in Owerri extracted. For the temperature analysis, the mean and median methods gave similar result which makes the mean method an acceptable method due to its simplicity, taking cognizance of the heavy computation in the other methods. Interestingly, for the rainfall analysis, the mean and jackknife methods gave the same result which also makes the mean method acceptable to avoid the heavy computations of the other two. ANOVA on the anomalies so derived showed no significant difference in their mean, thus underpinning the choice of the mean method. Using the outcome of the mean method therefore, the analyzed mean minimum temperature and mean maximum temperature indicate that the night time temperature has increased in Owerri within the period under consideration by 0.0186 &#176 C each year and the daytime temperature increased by 0.01 &#176 C per year respectively, thus indicating that a warming climate change has taken place in Owerri. Within the same period, the rate for rainfall on the other hand showed a decrease. In summary, the simple mean method of base computation suffices over the median and jackknife methods in climate studies for Owerri, a trend of warming climate has taken place in Owerri with increases in both daytime and night temperatures but with a reverse trend in rainfall which will require further inquiry.