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

Abstract

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.