The estimation of persistence (or: self-correlation) is necessary to evaluate the effective degree of freedom (or: the number of statistically independent samples) of a geophysical time series. The application of textbook definitions may result in problems when the time series contains periodic signals. This is demonstrated with analytical solutions for a given auto-correlation function. On physical grounds, in this paper we estimate the persistence time as the integral over the absolute value of the auto-correlation function. This procedure has been proposed by Stratonovich and is shown to work for slow and fast oscillations involved. In the practical part of the paper, a 42-year long time series of phase height measurements at Kühlungsbor...
The statistical distribution of values in the signal and the autocorrelations (interpreted as the me...
Satellite-derived soil moisture (SM) products have become an important information source for the st...
This dissertation examines manifestations of persistent memory in climate data. Persistence is chara...
Time series in the Earth Sciences are often characterized as self-affine long-range persistent, wher...
A wide variety of processes are thought to show “long-range persistence”, specifically an autocorrel...
We re-analyze historical daily atmospheric temperature time series for investigating long-range corr...
We use several variants of the detrended fluctuation analysis to study the appearance of long-term p...
Although persistence in natural data is generally admitted, its effect on the significance of variou...
A review paper considering space-time variability of climate, sedimentation, and geomagnetism
<p>The long-term persistence (LTP), else known in hydrological science as the Hurst phenomenon, is a...
We used detrended methods for scaling analysis (DFA2 and DMA) and wavelet transform spectral analysi...
Mining-induced ground movement is a complicated nonlinear process and a regional geological hazard. ...
Today, hydrologic research and modeling depends largely on climatological inputs, whose physical and...
The long-range correlations associated with the presence of persistence are investigated by applying...
Abstract. The distribution of extreme event return times and their correlations are analyzed in obse...
The statistical distribution of values in the signal and the autocorrelations (interpreted as the me...
Satellite-derived soil moisture (SM) products have become an important information source for the st...
This dissertation examines manifestations of persistent memory in climate data. Persistence is chara...
Time series in the Earth Sciences are often characterized as self-affine long-range persistent, wher...
A wide variety of processes are thought to show “long-range persistence”, specifically an autocorrel...
We re-analyze historical daily atmospheric temperature time series for investigating long-range corr...
We use several variants of the detrended fluctuation analysis to study the appearance of long-term p...
Although persistence in natural data is generally admitted, its effect on the significance of variou...
A review paper considering space-time variability of climate, sedimentation, and geomagnetism
<p>The long-term persistence (LTP), else known in hydrological science as the Hurst phenomenon, is a...
We used detrended methods for scaling analysis (DFA2 and DMA) and wavelet transform spectral analysi...
Mining-induced ground movement is a complicated nonlinear process and a regional geological hazard. ...
Today, hydrologic research and modeling depends largely on climatological inputs, whose physical and...
The long-range correlations associated with the presence of persistence are investigated by applying...
Abstract. The distribution of extreme event return times and their correlations are analyzed in obse...
The statistical distribution of values in the signal and the autocorrelations (interpreted as the me...
Satellite-derived soil moisture (SM) products have become an important information source for the st...
This dissertation examines manifestations of persistent memory in climate data. Persistence is chara...