Abstract

The impact of climate change on annual air temperature has received a great deal of attention from climatologists worldwide. Many studies have been conducted to illustrate that changes in temperature are becoming evident on a global scale. Air temperature, one of the most important components of climate parameters, has been widely measured as a starting point towards the apprehension of climate change and variability. The main objective of this study is to analyse the temporal variability of mean monthly temperature for the period of 1941 to 2010 (70 years). To detect the magnitude of trend in mean monthly temperature time series, we have used non-parametric test methods such as The Mann-Kendall test, often combined with the Theil-Sen’s robust estimate of linear trend. Whatever test is used, the user should understand the underlying assumptions of both the technique used to generate the estimates of a trend and the statistical methods used for testing. The results of this analysis reveal that four months – January, February, March and December – indicate a decreasing trend in average temperature, while the remaining eight months have an increasing trend. The magnitude of Mann-Kendall trend statistic Zc for this declining temperature and the magnitude of slope for the months of January, February and December are confirmed at the high significance levels of α = 0.001, 0.01 and 0.1 respectively. Though, the overall trend is positive for monthly as well as seasonally efficient time series.

Authors and Affiliations