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| Titel |
Comparison of Two Automatic Signal Correlation Methods to Align Relative Paleointensity Data |
| VerfasserIn |
D. B. Lee, J. E. T. Channell |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250058746
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| Zusammenfassung |
| Sedimentary relative paleointensity (RPI) data are often believed to represent a global signal
at >103 yr timescales. The development of chronologies independent of oxygen isotope data
(and orbital tuning) has important implications in paleoclimate science. Age models derived
from RPI data could ultimately be used to better understand the climate signal in
oxygen/carbon isotope data, the true link between orbital cycles and climate variations, and
test for leads and lags in the climate system. As a first step, a method of accurately and
reliably correlating RPI data from different sites must be developed. Automated correlations
using algorithms have great advantage over visual correlations as they are based
on firm criteria and repeatable, although a comparison of how various methods
perform when aligning RPI or δ18O data (or both signals in tandem) has not been
undertaken. Here we compare the performance of two automatic correlation techniques
when used to align RPI or δ18O data. One is the dynamic programming method
developed by Lisiecki and Lisiecki (2002) to align δ18O. records, the other is the
simulated annealing method proposed by Huybers and Wunsch (2004). RPI and δ18O
data collected from the North Atlantic are used to examine the differences in how
these algorithms cope with different levels of inter-site variation in both RPI and
δ18O data, and fluctuations in sedimentation rate. The algorithms are also evaluated
using synthetic datasets obtained using Monte Carlo simulations of RPI and δ18O
data. Multiple simulations are used to test the accuracy of the algorithms when
handling different levels of signal to noise, variations in sedimentation rate, and
differences in RPI resolution that are encountered when aligning RPI data collected
from sediments with variable or differing sedimentation rates. Once data from the
North Atlantic have been fully aligned using both methods, stacking techniques
are employed to develop stacks of RPI and δ18O data for each signal correlation
method. Finally, North Atlantic Quaternary age models, developed using both standard
insolation-forced ice-volume models, and “depth derived” methods, are applied to the stacks. |
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