ISSN:
1434-4483
Source:
Springer Online Journal Archives 1860-2000
Topics:
Geosciences
,
Physics
Notes:
Summary Investigations of the temporal change of the probability of defined sequences and dynamical entropy (Nicolis et al., 1997) are presented using the daily maximum and minimum of the air temperature of the Potsdam time series, which spans the 102 years from 1893–1994. To reduce the number of parameters a nonhierarchical cluster analysis algorithm (Steinhausen and Langer, 1977) was used. This algorithm assigns one of five clusters each day, classified as very cold, cold, temperate, warm or hot. According to the algorithm, each day is described by only one of the symbols vc, c, t, w or h. Subsequently a time series analysis on this series of symbols was performed. The basic analysis length was defined by a 30 year window, which was shifted over the entire time series thus yielding 73 analysis sections. The quantities vary from window to window. Their variations were used for the detection of climate change. One of the major findings was the increased persistence of typical temperature characteristics. Within the windows we investigate relatively long-term correlations which extend over many days. The results show the time series to be markedly non-Markov.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/s007040050078
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