Climate Dynamics

, Volume 36, Issue 11–12, pp 2419–2439 | Cite as

An efficient forward model of the climate controls on interannual variation in tree-ring width

  • Susan E. Tolwinski-WardEmail author
  • Michael N. Evans
  • Malcolm K. Hughes
  • Kevin J. Anchukaitis


We present a simple, efficient, process-based forward model of tree-ring growth, called Vaganov–Shashkin-Lite (VS-Lite), that requires as inputs only latitude and monthly temperature and precipitation. Simulations of six bristlecone pine ring-width chronologies demonstrate the interpretability of model output as an accurate representation of the climatic controls on growth. Ensemble simulations by VS-Lite of two networks of North American ring-width chronologies correlate with observations at higher significance levels on average than simulations formed by regression of ring width on the principal components of the same monthly climate data. VS-Lite retains more skill outside of calibration intervals than does the principal components regression approach. It captures the dominant low- and high-frequency spatiotemporal ring-width signals in the network with an inhomogeneous, multivariate relationship to climate. Because continuous meteorological data are most widely available at monthly temporal resolution, our model extends the set of sites at which forward-modeling studies are possible. Other potential uses of VS-Lite include generation of synthetic ring-width series for pseudo-proxy studies, as a data level model in data assimilation-based climate reconstructions, and for bias estimation in actual ring-width index series.


Paleoclimate proxy Forward modeling Tree-ring width Model validation Pseudo-proxy 



We thank Kurt Kipfmueller and Matt Salzer for providing data for the 5N network; the same two authors and Andy Bunn for sharing the bristlecone pine chronologies; contributors to the International Tree Ring Data Bank of the World Data Center for Paleoclimatology which was the source for the M08 network. We thank Connie Woodhouse for sharing her insights into regional climatic patterns captured by the 5N network, and Brooke Rabe for her input on writing statistical code. Thanks to the PRISM Climate Group at Oregon State University ( for making their product publicly available, and to Benno Blumenthal for making the gridded PRISM product available on the IRI/LDEO Data Catalog ( We are grateful to Martin Tingley and Joel Guiot for their thorough comments and feedback, which greatly improved the structure of the paper. Support for this work was provided by NSF/CMG grant 0724802, NOAA/CPO grant NA060AR4310115, NOAA grant NA07OAR4310060, and NOAA grant NA07OAR4310424.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Susan E. Tolwinski-Ward
    • 1
    Email author
  • Michael N. Evans
    • 2
  • Malcolm K. Hughes
    • 3
  • Kevin J. Anchukaitis
    • 4
  1. 1.Program in Applied MathematicsUniversity of ArizonaTucsonUSA
  2. 2.Department of GeologyUniversity of MarylandCollege ParkUSA
  3. 3.Laboratory of Tree Ring ResearchUniversity of ArizonaTucsonUSA
  4. 4.Lamont-Doherty Earth ObservatoryColumbia UniversityPallisadesUSA

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