Various trend-detection studies have been carried out in different parts of the world, mostly for the identification of climatic change, if any. Some of these cases have shown significant trend components, especially during the last 40 years (Karl et al., 1993). Different techniques, such as parametric and non-parametric tests, are used for testing whether there have been statistically significant trends. However, the physical interpretation has related, at times, to the greenhouse effect, global warming, urban heat islands, and to aerosols that exert cooling effects on our climate (Balling, 1992). The data are analyzed in order to identify meaningful long-term trends by making use of the sequential version of the Mann-Kendall rank statistics, the effective application of which includes the following steps in sequence:
(i) The values of xi of the original series are replaced by their ranks yi, arranged in ascending order.
(ii) The magnitudes of yi (i = 1,.. .,N are compared with yj (j = 1,..,,i-1). At each comparison, the number of cases yi > yj is counted and denoted by ni.
(iii) A statistic ti is, therefore, defined as follows:
(iv) The distribution of the test statistic ti has a mean and a variance as i(i -1)
(v) The sequential statistic U(ti) is then computed as follows:
Was this article helpful?