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Publication Information

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Title: Feasibility of high-density climate reconstruction based on Forest Inventory and Analysis (FIA) collected tree-ring data

Author: DeRose, R. Justin; Wang, Shih-Yu; Shaw, John D.

Date: 2013

Source: Journal of Hydrometeorology. 14: 375-381.

Publication Series: Journal/Magazine Article (JRNL)

Description: This study introduces a novel tree-ring dataset, with unparalleled spatial density, for use as a climate proxy. Ancillary Douglas fir and pinyon pine tree-ring data collected by the U.S. Forest Service Forest Inventory and Analysis Program (FIA data) were subjected to a series of tests to determine their feasibility as climate proxies. First, temporal coherence between the FIA data and previously published tree-ring chronologies was found to be significant. Second, spatial and temporal coherence between the FIA data and water year precipitation was strong. Third, the FIA data captured the El Nino-Southern Oscillation dipole and revealed considerable latitudinal fluctuation over the past three centuries. Finally, the FIA data confirmed the quadrature-phase coupling between wet/dry cycles and Pacific decadal variability known to exist for the Intermountain West. The results highlight the possibility of further developing high-spatial-resolution climate proxy datasets for the western United States. (The preliminary FIA data are provided online at http://cliserv. jql.usu.edu/FIAdata/ in both station and gridded format.)

Keywords: tree-ring data, spatial density, climate proxy, Forest Inventory and Analysis Program (FIA) data

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

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Citation:


DeRose, R. Justin; Wang, Shih-Yu; Shaw, John D. 2013. Feasibility of high-density climate reconstruction based on Forest Inventory and Analysis (FIA) collected tree-ring data. Journal of Hydrometeorology. 14: 375-381.

 


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