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Cool Season Precipitation in the Southwestern United States since AD 1000: Comparison of Linear and Nonlinear Techniques for Reconstruction

Presented at the AMS Meeting, Albuquerque, NM, January 2001

Sumbitted to Int. J. of Climatology

Fenbiao Ni, Tereza Cavazos, Malcolm K. Hughes, Andrew, C. Comrie., and Gary Funkhouser

Univ. of Arizona, Tucson, AZ 85721.

ABSTRACT: A 1000-year reconstruction of cool-season (November-April) precipitation was developed for each climate division in Arizona and New Mexico from a network of 19 tree-ring chronologies in the Southwestern United States. Linear regression (LR) and artificial neural networks (NN) models were used to compare the response of tree growth to cool-season precipitation. The stepwise LR model was cross-validated with a leave-one-out procedure while the NN was validated with a bootstrap technique using 1931-1988 records. The final models were also independently validated using the 1896-1930 precipitation data. In most of the climate divisions both techniques can successfuly simulate dry and normal years, and the NN seems to better capture large precipitation events and more variability than the LR. In the 1000-year reconstructions the NN also produces more distinctive wet events and more variability, while the LR produces more distinctive dry events. The 1000-year reconstructed precipitation from the two models shows several sustained dry and wet periods comparable to the 1950s drought (e.g., 16th century megadrought) and the post-1976 wet periods (e.g., 1330s, 1610s).

The impact of extreme periods on the environment may be stronger during sudden reversals from dry to wet, which were not uncommon thorughout the millennium, such as the 1610s wet interval that followed the 16th century megadrought. The instrumental records suggest that strong dry to wet precipitation reversals in the past 1000 years might be linked to strong shifts from cold to warm El Nino/Southern Oscillation (ENSO) events and from negative to positive Pacific Decadal Oscillation (PDO).