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Trend Analysis of Air Temperature Time Series by Mann Kendall Test - A Case Study of Upper Ganga Canal Command (1901-2002)

Nitin Mishra, Deepak Khare, Rituraj Shukla, Kalyani Kumar

Current Journal of Applied Science and Technology · pp. 4066–4082 · Published 30 Jul 2014

10.9734/BJAST/2014/8650

Abstract

Worldwide climatologists are investigating to find a possible relation of climate change with anthropogenic behavior by studying trends in different climatic parameters. However, the changes in temperature are not equal for all regions especially in India and have localized intensity and must be quantified locally to manage the natural resources. Aim of the study is to determine trend in annual mean and monthly Temperature time series using nonparametric methods (i.e. the Mann–Kendall and Sen’s T tests). The magnitudes of trend in a Temperature time series have been estimated by Sen’s estimator method. Auto correlation effect is reduced from the Temperature series before applying the Mann–Kendall test. In the present study, an investigation has been made to study the spatial and temporal variability in the maximum, the minimum and the mean air temperatures of Upper Ganga Canal Command located in Uttar Pradesh and Uttarakhand on monthly, annual and seasonal series from 1901 to 2002. The annual mean, maximum and minimum temperatures have increased by 0.60ºC, 0.60ºC and 0.62ºC, respectively, over the past 101 years. On a seasonal basis, the winters are warmer than summers. The temperature decreased during the less urbanized period of 1901 to 1951 and increased during the more urbanized period of 1961 to 2002. It is also found that the minimum temperature increased at higher rate (0.42ºC) followed by the mean (0.36ºC) and the maximum (0.32ºC) air temperatures, during the more urbanized period.  

Air temperature non-parametric tests trend analysis auto correlation mann–kendall and sen’s t tests

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