The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Applications of proxy system modeling in high resolution paleoclimatology
Open accessAbstract
A proxy system model may be defined as the complete set of forward and mechanistic processes by which the response of a sensor to environmental forcing is recorded and subsequently observed in a material archive. Proxy system modeling complements and sharpens signal interpretations based solely on statistical analyses and transformations; provides the basis for observing network optimization, hypothesis testing, and data-model comparisons for uncertainty estimation; and may be incorporated as weak but mechanistically-plausible constraints into paleoclimatic reconstruction algorithms. Following a review illustrating these applications, we recommend future research pathways, including development of intermediate proxy system models for important sensors, archives, and observations; linking proxy system models to climate system models; hypothesis development and evaluation; more realistic multi-archive, multi-observation network design; examination of proxy system behavior under extreme conditions; and generalized modeling of the total uncertainty in paleoclimate reconstructions derived from paleo-observations.
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Cites
An Overview of CMIP5 and the Experiment Design
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Oxygen and carbon isotope fractionation in biogenic aragonite: Temperature effects
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“The thermodynamic influence (O’Neil et al., 1969) may be approximated (Grossman and Ku, 1986) as a linear function of sea surface temperature (SST) (Weber and Woodhead, 1972); the seawater isotopic composition influence may be approximated in terms of sea surface salinity (SSS), which (like…”
BackgroundD'Arrigo, R., Wilson, R., Liepert, B., & Cherubini, P. (2008) · Global and Planetary Change · doi:10.1016/j.gloplacha.2007.03.004 · Cited by 838 · cited 1×
“More generally, apparent nonstationarity in sensor, archive or observational proxy system models (D’Arrigo et al., 2008) e such as the so-called “divergence” problem in dendrochronology e which is potentially superimposed on nonstationarity in the climate itself (Cole and Cook, 1998), is a general…”
BackgroundTropical cloud forest climate variability and the demise of the Monteverde golden toad
Anchukaitis, K. J., & Evans, M. N. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908572107 · Cited by 101
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Cited by
Jungclaus, J. H., Bard, E., Baroni, M., Braconnot, P., Cao, J., Chini, L. P., Egorova, T., Evans, M., González-Rouco, J. F., Goosse, H., et al. (2017) · Geoscientific Model Development · doi:10.5194/gmd-10-4005-2017 · Cited by 320
“…et al., 2012, 2013; Atwood et al., 2016), there are discrepancies between model results and the observed climate evolution, in particular regarding the amplitude of the response to volcanic eruptions (e.g. Brohan et al., 2012; Evans et al., 2013; Wilson et al., 2016; Anchukaitis et al., 2010).”
ResultSelf-citation(2023) · Climate Change 2021 – The Physical Science Basis · doi:10.1017/9781009157896.003 · Cited by 298
The last millennium climate reanalysis project: Framework and first results
Hakim, G. J., Emile‐Geay, J., Steig, E. J., Noone, D., Anderson, D. M., Tardif, R., Steiger, N., & Perkins, W. A. (2016) · Journal of Geophysical Research: Atmospheres · doi:10.1002/2016jd024751 · Cited by 293
Initialized Earth System prediction from subseasonal to decadal timescales
Meehl, G. A., Richter, J. H., Teng, H., Capotondi, A., Cobb, K., Doblas-Reyes, F., Donat, M. G., England, M. H., Fyfe, J. C., Han, W., et al. (2021) · Nature Reviews Earth & Environment · doi:10.1038/s43017-021-00155-x · Cited by 231
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Metadata
- Authors
- Evans, M. N., Tolwinski-Ward, S. E., Thompson, D. M., & Anchukaitis, K. J.
- Venue
- Quaternary Science Reviews
- Publisher
- Elsevier BV
- Published
- 2013-09
- Volume
- 76
- Pages
- 16-28
- ISSN
- 0277-3791 (ISSN-L)
- OpenAlex
- W2174462014
- Cited by
- 342
- References
- 4
- FWCI
- 16.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Evans, M. N., Tolwinski-Ward, S. E., Thompson, D. M., & Anchukaitis, K. J. (2013). Applications of proxy system modeling in high resolution paleoclimatology. Quaternary Science Reviews. https://doi.org/10.1016/j.quascirev.2013.05.024
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
