# Estimation of Long-Term Trends

Trends are determined using a nonparametric Mann-Kendall test to assess the probability that there is a trend statistically different from zero and to evaluate increasing or decreasing slope of trends in the time series of temperature and rainfall by using Sen’s method (Sen 1968). The Mann-Kendall test consists of comparing each value of the time series with the others remaining always in sequential order. The number of times that the remaining terms are greater than that under analysis is counted. The calculated TCC trends are tested for significance at the 95 % confidence level by Mann-Kendall and Sen’s method.

Temporal variations in annual and seasonal average TCC are shown in Fig. 2. Annual and seasonal spatial patterns of long-term mean TCC are shown in Fig. 3, where coefficient of variation (CV) is shown as contour lines in foreground and variations in mean TCC are shaded in colour in the background. Spatial distributions of annual and seasonal trends in TCC are shown in Fig. 4, where trends significant at 95 % level are marked by an outer circle in black. Scatter plot of India averaged TCC against DTR and NRD is shown in Figs. 5 and 7, respectively. Spatial patterns of correlation coefficients between TCC, DTR and NRD are shown in Figs. 6 and 8, respectively.