@article{MaraunKurths2004,
  author    = {Maraun, Douglas and Kurths, J{\"u}rgen},
  title     = {Cross wavelet analysis: significance testing and pitfalls},
  issn      = {1023-5809},
  year      = {2004},
  abstract  = {In this paper, we present a detailed evaluation of cross wavelet analysis of bivariate time series. We develop a statistical test for zero wavelet coherency based on Monte Carlo simulations. If at least one of the two processes considered is Gaussian white noise, an approximative formula for the critical value can be utilized. In a second part, typical pitfalls of wavelet cross spectra and wavelet coherency are discussed. The wavelet cross spectrum appears to be not suitable for significance testing the interrelation between two processes. Instead, one should rather apply wavelet coherency. Furthermore we investigate problems due to multiple testing. Based on these results, we show that coherency between ENSO and NAO is an artefact for most of the time from 1900 to 1995. However, during a distinct period from around 1920 to 1940, significant coherency between the two phenomena occurs},
  language  = {en}
}
@article{MaraunKurths2005,
  author    = {Maraun, Douglas and Kurths, J{\"u}rgen},
  title     = {Epochs of phase coherence between El Nino/Southern Oscillation and Indian monsoon},
  issn      = {0094-8276},
  year      = {2005},
  abstract  = {We present a modern method used in nonlinear time series analysis to investigate the relation of two oscillating systems with respect to their phases, independently of their amplitudes. We study the difference of the phase dynamics between El Nino/Southern Oscillation (ENSO) and the Indian Monsoon on inter-annual time scales. We identify distinct epochs, especially two intervals of phase coherence, 1886 - 1908 and 1964 - 1980, corroborating earlier findings from a new point of view. A significance test shows that the coherence is very unlikely to be the result of stochastic fluctuations. We also detect so far unknown periods of coupling which are invisible to linear methods. These findings suggest that the decreasing correlation during the last decades might be a typical epoch of the ENSO/ Monsoon system having occurred repeatedly. The high time resolution of the method enables us to present an interpretation of how volcanic radiative forcing could cause the coupling},
  language  = {en}
}
@article{MaraunRustTimmer2004,
  author    = {Maraun, Douglas and Rust, H. W. and Timmer, Jens},
  title     = {Tempting long-memory : on the interpretation of DFA results},
  issn      = {1023-5809},
  year      = {2004},
  abstract  = {We study the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) and argue that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires the investigation of the local slopes. We account for the variability characteristic for stochastic processes by calculating empirical confidence regions. Comparing a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. We remark that scaling cannot be concluded from a straight line fit to the fluctuation function in a log-log representation. Furthermore, we show that a local slope larger than alpha=0.5 for large scales does not necessarily imply long memory. We also demonstrate, that it is not valid to conclude from a finite scaling region of the fluctuation function to an equivalent scaling region of the autocoffelation function. Finally, we review DFA results for the Prague temperature data set and show that long-range correlations cannot not be concluded unambiguously},
  language  = {en}
}
@article{MaraunRustOsborn2009,
  author    = {Maraun, Douglas and Rust, Henning W. and Osborn, Tim J.},
  title     = {The annual cycle of heavy precipitation across the United Kingdom : a model based on extreme value statistics},
  issn      = {0899-8418},
  doi       = {10.1002/Joc.1811},
  year      = {2009},
  abstract  = {The annual cycle of extreme I-day precipitation events across the UK is investigated by developing a statistical model and fitting it to data from 689 rain gauges A generalized extrerne-value distribution (GEV) is fit to the time series of monthly maxima, across all months of the year simultaneously, by approximating, the annual cycles of the location and scale parameters by harmonic functions, while keeping the shape parameter constant throughout the year We average the shape parameter of neighbouring rain gauges to decrease uncertainties. and also Interpolate values of all model parameters to give complete coverage of (lie UK. The model reveals distinct spatial patterns the estimated parameters The annual mean of the location and scale parameter is highly correlated with orography. The annual cycle of the location parameter is strong in the northwest UK (peaking in late autumn or winter) and in East Anglia (where it peaks HI late summer), and low in the Midlands The annual cycle of the scale parameter exhibits a similar pattern with strongest amplitudes in East Anglia The spatial patterns of the annual cycle phase suggest that they are linked to the dominance of frontal precipitation for generating extreme precipitation in the west and convective precipitation in the southeast of the UK The shape parameter shows a gradient from Positive Values in the east to negative values in some areas of the west We also estimate 10-year and 100-year return levels at each rain gauge, and interpolated across the UK.},
  language  = {en}
}