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| Titel |
An inverse modeling approach for tree-ring-based climate reconstructions under changing atmospheric CO2 concentrations |
| VerfasserIn |
É. Boucher, J. Guiot, C. Hatté, V. Daux, P.-A. Danis, P. Dussouillez |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 12 ; Nr. 11, no. 12 (2014-06-17), S.3245-3258 |
| Datensatznummer |
250117471
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| Publikation (Nr.) |
 copernicus.org/bg-11-3245-2014.pdf |
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| Zusammenfassung |
| Over the last decades, dendroclimatologists have relied upon linear transfer
functions to reconstruct historical climate. Transfer functions need to be
calibrated using recent data from periods where CO2 concentrations reached
unprecedented levels (near 400 ppm – parts per million). Based on these transfer functions,
dendroclimatologists must then reconstruct a different past, a past where
CO2 concentrations were far below 300 ppm. However, relying upon transfer
functions calibrated in this way may introduce an unanticipated bias in the
reconstruction of past climate, particularly if CO2 has had a noticeable
impact on tree growth and water use efficiency since the beginning of the
industrial era. As an alternative to the transfer function approach, we run
the MAIDENiso ecophysiological model in an inverse mode to link together
climatic variables, atmospheric CO2 concentrations and tree growth
parameters. Our approach endeavors to find the optimal combination of
meteorological conditions that best simulate observed tree ring patterns. We
test our approach in the Fontainebleau Forest (France). By comparing two
different CO2 scenarios, we present evidence that increasing CO2
concentrations have had a slight, yet significant, effect on the reconstruction
results. We demonstrate that realistic CO2 concentrations need to be
inputted in the inversion so that observed increasing trends in summer
temperature are adequately reconstructed. Fixing CO2 concentrations at
preindustrial levels (280 ppm) results in undesirable compensation effects
that force the inversion algorithm to propose climatic values that lie
outside from the bounds of observed climatic variability. Ultimately, the
inversion approach has several advantages over traditional transfer function
approaches, most notably its ability to separate climatic effects from CO2
imprints on tree growth. Therefore, our method produces reconstructions that
are less biased by anthropogenic greenhouse gas emissions and that are based
on sound ecophysiological knowledge. |
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