Statistical and Graphical Comparison of Relative Humidity in the Wet Zone of Sri Lanka

Abstract

Studying the trend analysis of climatic variables and evaluating their statistical significance in recent times is the greatest evidence about climate change. Climatic warming accompanied by atmospheric humidity is predicted to extend much faster than the entire precipitation amount. Atmospheric moisture is expected to rise with temperature. As a tropical country, Sri Lanka has a variety of different tropical climates. In this study, we received relative humidity data of selected stations in the past 27 years (1990-2017). Accordingly, to analyze the climate variation, we selected five main stations in the Wet Zone of Sri Lanka: Colombo, Katugastota, Bandarawela, Rathnapura, and Nuwara Eliya. To analyze relative humidity data collected over time (1990-2017) for consistently increasing or decreasing trends. The most popular non-parametric test the Mann-Kendall (MK) test was used to identify the trend variation and linear regression analysis was used to analyze statistically. For graphically analyze innovative trend analysis and continuous wavelet transformation methods were used. Data were selected as daytime and nighttime and trends were analyzed annually (1990-2017) using XLSTAT, Minitab, MATLAB, and Excel software. Other than Colombo, all four stations show positive trends in nighttime relative humidity, while the entire district shows a positive trend in daytime relative humidity. According to linear regression analysis, Bandarawela and Colombo show a negative trend in nighttime and only Colombo shows a negative in the daytime. Analyzing a Mann Kendal results shows RathnapuraKatugastota and Colombo shows a negative trend in the nighttime. In terms of CWT data analysis, in one district it shows at least three patterns during the day and four patterns at night.