Tolwinski-Ward S. E.

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Tolwinski-Ward
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S. E.
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  • Article
    Applications of proxy system modeling in high resolution paleoclimatology
    (Elsevier B.V., 2013-05-29) Evans, Michael N. ; Tolwinski-Ward, S. E. ; Thompson, D. M. ; Anchukaitis, Kevin J.
    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.
  • Article
    Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width
    (Copernicus Publications on behalf of the European Geosciences Union, 2013-07-15) Tolwinski-Ward, S. E. ; Anchukaitis, Kevin J. ; Evans, Michael N.
    We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization.