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| Titel |
Comparing Apples to Apples: Paleoclimate Model-Data comparison via Proxy System Modeling |
| VerfasserIn |
Sylvia Dee, Julien Emile-Geay, Michael Evans, David Noone |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250094236
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| Publikation (Nr.) |
 EGU/EGU2014-9636.pdf |
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| Zusammenfassung |
| The wealth of paleodata spanning the last millennium (hereinafter LM) provides an
invaluable testbed for CMIP5-class GCMs. However, comparing GCM output to paleodata is
non-trivial. High-resolution paleoclimate proxies generally contain a multivariate and
non-linear response to regional climate forcing. Disentangling the multivariate environmental
influences on proxies like corals, speleothems, and trees can be complex due to
spatiotemporal climate variability, non-stationarity, and threshold dependence. Given these
and other complications, many paleodata-GCM comparisons take a leap of faith, relating
climate fields (e.g. precipitation, temperature) to geochemical signals in proxy data (e.g. δ18O
in coral aragonite or ice cores) (e.g. Braconnot et al., 2012). Isotope-enabled GCMs are a step
in the right direction, with water isotopes providing a connector point between GCMs and
paleodata. However, such studies are still rare, and isotope fields are not archived as
part of LM PMIP3 simulations. More importantly, much of the complexity in how
proxy systems record and transduce environmental signals remains unaccounted
for.
In this study we use proxy system models (PSMs, Evans et al., 2013) to bridge this
conceptual gap. A PSM mathematically encodes the mechanistic understanding of the
physical, geochemical and, sometimes biological influences on each proxy. To translate GCM
output to proxy space, we have synthesized a comprehensive, consistently formatted package
of published PSMs, including δ18O in corals, tree ring cellulose, speleothems, and ice cores.
Each PSM is comprised of three sub-models: sensor, archive, and observation. For the first
time, these different components are coupled together for four major proxy types, allowing
uncertainties due to both dating and signal interpretation to be treated within a
self-consistent framework. The output of this process is an ensemble of many (say N =
1,000) realizations of the proxy network, all equally plausible under assumed dating
uncertainties.
We demonstrate the utility of the PSM framework with an integrative multi-PSM simulation.
An intermediate-complexity AGCM with isotope physics (SPEEDY-IER, (Molteni, 2003,
Dee et al., in prep)) is used to simulate the isotope hydrology and atmospheric response to
SSTs derived from the LM PMIP3 integration of the CCSM4 model (Landrum et al., 2012).
Relevant dynamical and isotope variables are then used to drive PSMs, emulating a realistic
multiproxy network (Emile-Geay et al., 2013). We then ask the following question: given our
best knowledge of proxy systems, what aspects of GCM behavior may be validated, and with
what uncertainties?
We approach this question via a three-tiered “perfect model” study. A random realization of
the simulated proxy data (hereafter “PaleoObs”) is used as a benchmark in the following
comparisons: (1) AGCM output (without isotopes) vs. PaleoObs; (2) AGCM output (with
isotopes) vs. PaleoObs; (3) coupled AGCM-PSM-simulated proxy ensemble vs. PaleoObs.
Enhancing model-data comparison using PSMs highlights uncertainties that may arise from
ignoring non-linearities in proxy-climate relationships, or the presence of age uncertainties
(as is most typically done is paleoclimate model-data intercomparison). Companion
experiments leveraging the 3 sub-model compartmentalization of PSMs allows us to quantify
the contribution of each sub-system to the observed model-data discrepancies. We discuss
potential repercussions for model-data comparison and implications for validating predictive
climate models using paleodata.
References
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