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| Titel |
Evaluating climate field reconstruction techniques using improved emulations of real-world conditions |
| VerfasserIn |
J. Wang, J. Emile-Geay, D. Guillot, J. E. Smerdon, B. Rajaratnam |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1814-9324
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| Digitales Dokument |
URL |
| Erschienen |
In: Climate of the Past ; 10, no. 1 ; Nr. 10, no. 1 (2014-01-06), S.1-19 |
| Datensatznummer |
250116891
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| Publikation (Nr.) |
 copernicus.org/cp-10-1-2014.pdf |
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| Zusammenfassung |
Pseudoproxy experiments (PPEs) have become an important framework for
evaluating paleoclimate reconstruction methods. Most existing PPE studies
assume constant proxy availability through time and uniform proxy quality
across the pseudoproxy network. Real multiproxy networks are, however,
marked by pronounced disparities in proxy quality, and a steep decline in
proxy availability back in time, either of which may have large effects on
reconstruction skill. A suite of PPEs constructed from a millennium-length
general circulation model (GCM) simulation is thus designed to mimic these
various real-world characteristics. The new pseudoproxy network is used to
evaluate four climate field reconstruction (CFR) techniques: truncated total
least squares embedded within the regularized EM (expectation-maximization) algorithm (RegEM-TTLS), the
Mann et al. (2009) implementation of RegEM-TTLS (M09), canonical correlation
analysis (CCA), and Gaussian graphical models embedded within RegEM
(GraphEM). Each method's risk properties are also assessed via a 100-member
noise ensemble.
Contrary to expectation, it is found that reconstruction skill does not vary
monotonically with proxy availability, but also is a function of the type and
amplitude of climate variability (forced events vs. internal variability).
The use of realistic spatiotemporal pseudoproxy characteristics also exposes
large inter-method differences. Despite the comparable fidelity in
reconstructing the global mean temperature, spatial skill varies considerably
between CFR techniques. Both GraphEM and CCA efficiently exploit
teleconnections, and produce consistent reconstructions across the ensemble.
RegEM-TTLS and M09 appear advantageous for reconstructions on highly noisy
data, but are subject to larger stochastic variations across different
realizations of pseudoproxy noise. Results collectively highlight the
importance of designing realistic pseudoproxy networks and implementing
multiple noise realizations of PPEs. The results also underscore the
difficulty in finding the proper bias-variance tradeoff for jointly
optimizing the spatial skill of CFRs and the fidelity of the global mean
reconstructions. |
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