Robust estimation of background noise and signal detection in climatic time series

@article{Mann1996RobustEO,
  title={Robust estimation of background noise and signal detection in climatic time series},
  author={M. Mann and J. Lees},
  journal={Climatic Change},
  year={1996},
  volume={33},
  pages={409-445}
}
We present a new technique for isolating climate signals in time series with a characteristic ‘red’ noise background which arises from temporal persistence. This background is estimated by a ‘robust’ procedure that, unlike conventional techniques, is largely unbiased by the presence of signals immersed in the noise. Making use of multiple-taper spectral analysis methods, the technique further provides for a distinction between purely harmonic (periodic) signals, and broader-band (‘quasiperiodic… Expand

Figures and Tables from this paper

Oscillatory Spatiotemporal Signal Detection in Climate Studies: A Multiple-Taper Spectral Domain Approach
TLDR
Applied to observational climate data, the MTM–SVD analysis yields insight into secular trends, low-frequency, and high-frequency quasi-oscillatory variations in the climate system. Expand
Detecting cycles in stratigraphic data: Spectral analysis in the presence of red noise
[1] We discuss the detection of cyclic signals in stratigraphic ‘time series’ using spectral methods. The dominant source of variance in the stratigraphic record is red noise, which greatlyExpand
Spectral analysis of unevenly spaced climatic time series using CLEAN: signal recovery and derivation of significance levels using a Monte Carlo simulation
Abstract We present a Monte Carlo based method for the determination of errors associated with frequency spectra produced by the CLEAN transformation of Roberts et al. (1987) . The Monte CarloExpand
Seeing red in cyclic stratigraphy: Spectral noise estimation for astrochronology
[1] Fundamental to the development of astronomical time scales is the recognition of oscillatory variability within stratigraphic data and its evaluation relative to a null “noise” hypothesis. InExpand
Interannual Temperature Events and Shifts in Global Temperature: A ''Multiwavelet'' Correlation Approach
Abstract For the purpose of climate signal detection, we introduce a method for identifying significant episodes of large-scale oscillatory variability. The method is based on a multivariate waveletExpand
Resolving Milankovitch: Consideration of signal and noise
Milankovitch-climate theory provides a fundamental framework for the study of ancient climates. Although the identification and quantification of orbital rhythms are commonplace in paleoclimateExpand
Estimating red noise spectra of climatological time series
Spectral densities of climatological time series can be generally well approximated by red noise spectra. A common way of the spectral analysis is therefore based on a comparison of the periodogramExpand
Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise
Singular systems (or singular spectrum) analysis (SSA) was originally proposed for noise reduction in the analysis of experimental data and is now becoming widely used to identify intermittent orExpand
Evidence for periodicity and nonlinearity in a high-resolution fossil record of long-term evolution
The application of new signal analysis techniques provides increased insight into the study of the fossil record and processes of evolution. The fossil record of 622 planktic foraminifera containsExpand
Detection Test for Periodic Signals Revisited Against Various Stochastic Models
TLDR
This work improves the detection of periodic signals with the multitaper spectrum and wavelet spectrum by systematically taking into account a more appropriate null hypothesis (noise background) along with the multiple testing to test against. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 76 REFERENCES
Reshaping spectrum estimates by removing periodic noise: Application to seismic spectral ratios
An automated method for removing line spectrum elements embedded in colored spectra is presented. Since smooth spectrum estimates are desired, line spectra tend to smear out over an effectiveExpand
Time series analysis of Holocene climate data
  • D. Thomson
  • Mathematics
  • Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences
  • 1990
Holocene climate records are imperfect proxies for processes containing complicated mixtures of periodic and random signals. I summarize time series analysis methods for such data with emphasis onExpand
Investigating the origins and significance of low‐frequency modes of climate variability
An analysis of the 130-year record of the Earth's global mean temperature reveals a significant warming trend and a residual consistent with an auto-correlated (“red”) noise process whoseExpand
The Great Salt Lake: A Barometer of Low-Frequency Climatic Variability
Low-frequency (interannual or longer period) climatic variability is of interest because of its significance for the understanding and prediction of protracted climatic anomalies. Closed basin lakesExpand
Quadratic-inverse spectrum estimates: applications to palaeoclimatology
  • D. Thomson
  • Mathematics
  • Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences
  • 1990
This paper describes some new methods for the analysis of time series and their application to find new results in palaeoclimate. The new statistical theory includes a quadratic inverse theory forExpand
Climate spectra and detecting climate change
Part of the debate over possible climate changes centers on the possibility that the changes observed over the previous century are natural in origin. This raises the question of how large a changeExpand
Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series
We distinguish between two dimensions of a dynamical system given by experimental time series. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedomExpand
Singular-spectrum analysis: a toolkit for short, noisy chaotic signals
Abstract Singular-spectrum analysis (SSA) is developed further, based on experience with applications to geophysical time series. It is shown that SSA provides a crude but robust approximation ofExpand
Multitaper spectral analysis of high-frequency seismograms
Spectral estimation procedures which employ several prolate spheroidal sequences as tapers have been shown to yield better results than standard single-taper spectral analysis when used on a varietyExpand
Ocean variability and its influence on the detectability of greenhouse warming signals
Recent investigations have considered whether it is possible to achieve early detection of greenhouse-gas-induced climate change by observing changes in ocean variables. In this study we use modelExpand
...
1
2
3
4
5
...