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 has shown
an increasing trend but more significant rise in July and August temperature
has been recognized since 1960s.
Cite this paper
S. Chatterjee, D. Bisai and A. Khan, "Detection of Approximate Potential Trend Turning Points in Temperature Time Series (1941-2010) for Asansol Weather Observation Station, West Bengal, India," Atmospheric and Climate Sciences
, Vol. 4 No. 1, 2014, pp. 64-69. doi: 10.4236/acs.2014.41009
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