Long-term memory: a natural mechanism for the clustering of extreme events and anomalous residual times in climate records.

By Armin Bunde, Jan F. Eichner, Jan W. Kantelhardt, Shlomo Havlin. Physical Review Letters, 2005

316 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b1f1922a88a6c655d21a51881b1c9d58ac3a58b6

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Citations in the corpus

Long‐term persistence in climate and the detection problem (2006, background): “Due to the persistence, warm years are more likely to be followed by warm years, and cold years by cold years, and the same holds for decades and centuries; it is this feature which leads to the pronounced mountainvalley structure we observe in Figures 3a and 3b and to the anomalous clustering of ex”
Trend evaluation in records with long‐term memory: Application to global warming (2009, background): “As a consequence of the long-term memory pronounced persistent positive and negative deviations from the mean temperature occur, which leads to a clustering of extreme events [Bunde et al., 2005].”
Beyond Word Frequency: Bursts, Lulls, and Scaling in the Temporal Distributions of Words (2009, background): “Distribution (2), also known as Weibull distribution, and similar stretched exponential distributions describe a variety of phenomena [6, 23, 33, 34, 35], including the recurrence time between extreme events in time series with long-term correlations [2, 36].”
Long memory of rivers from spatial aggregation (2007, unknown): “Likewise, statistical tests suffer from a reduced power compared to a situation without long memory [Cohn and Lins, 2005; Rybski et al., 2006].”
Scaling laws of human interaction activity (2009, background): “For example, the distribution of interevent times could be stretched exponential [see recent work on the study of extreme events of climatological records exhibiting long-term correlations (35)].”
Temporal correlations and clustering of landslides (2010, background): “In recent years, a number of authors (e.g. Nathenson, 2001; Altmann and Kantz, 2005; Bunde et al., 2005, 2008; Hainzl et al., 2006; Blender et al., 2008; Santhanam and Kantz, 2008) have proposed that the interextreme (interevent) occurrence times of extreme values in many environmental time series…”