Detection of Approximate Potential Trend Turning Points in Temperature Time Series (1941-2010) for Asansol Weather Observation Station, West Bengal, India

Abstract

Researches are being carried out world-wide to understand the nature of temperature change during recent past at different geographical scales so that comprehensive inferences can be drawn about recent temperature trend and future climate. Detection of turning points in time series of meteorological parameters puts challenges to the researches. In this work, the temperature time series from 1941 to 2010 for Asansol observatory, West Bengal, India, has been considered to understand the nature, trends and change points in the data set using sequential version of Mann-Kendall test statistic. Literatures suggest that use of this test statistic is the most appropriate for detecting climatic abrupt changes as compared to other statistical tests in use. This method has been employed upon monthly average temperatures recorded over the said 70 years for detection of abrupt changes in the average temperature of each of the months. The approximate potential trend turning points have been calculated separately for each month (January to December). Sequential version of Mann-Kendall test statistic values for the months of July and August is significant at 95% confidence level (p < 0.05). The average temperature for most of the other months ha s shown an increasing trend but more significant rise in July and August temperature has been recognized since 1960s.