Applications of proxy system modeling in high resolution paleoclimatology

By M. Evans, S. Tolwinski-ward, D. Thompson, K. Anchukaitis. 2012

311 citations recorded by the source corpus.

Abstract 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.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/92b0962a7d0d5179fca9b5f7d5b1e713858d7d59

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Robert M. DeConto
2. Matthew Huber
3. S. Tolwinski-ward
4. M. Evans
5. K. Anchukaitis
6. B. Wade
7. Dan Lunt
8. S. Wing

In Global and Planetary Change

1. S. Tolwinski-ward
2. M. Evans
3. K. Anchukaitis
4. Robert M. DeConto
5. Matthew Huber
6. Dan Lunt
7. B. Wade
8. A. Winguth

Citations in the corpus

• Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width (2013, background): “Forward models of the physical or biological processes by which climate variability is imprinted on natural archives provide important tools for understanding such “proxies” as recorders of climate (Evans et al., 2013).”
• The DeepMIP contribution to PMIP4 (2017, methodology): “Climate proxy system modelling (Evans et al., 2013) coupled with Bayesian analysis (e.”