Hunting spectro-temporal information in unevenly spaced paleoclimate time series

18 p. Here we present some preliminary results of a statistical–computational implementation to estimate the wavelet spectrum of unevenly spaced paleoclimate time series by means of the Morlet Weighted Wavelet Z-Transform (MWWZ). A statistical significance test is performed against an ensemble of fi...

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Bibliographic Details
Main Author: Polanco, J.
Format: Report
Language:English
Published: Basque Centre for Climate Change/Klima Aldaketa Ikergai 2014
Subjects:
null
Greenland
ice core
Online Access:http://hdl.handle.net/10810/14274
Description
Summary:18 p. Here we present some preliminary results of a statistical–computational implementation to estimate the wavelet spectrum of unevenly spaced paleoclimate time series by means of the Morlet Weighted Wavelet Z-Transform (MWWZ). A statistical significance test is performed against an ensemble of first-order auto-regressive models (AR1) by means of Monte Carlo simulations. In order to demonstrate the capabilities of this implementation, we apply it to the oxygen isotope ratio (?18O) data of the GISP2 deep ice core (Greenland).

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