Customized spatial climate models for North America

Daniel W. McKenney*, Michael F. Hutchinson, Pia Papadopol, Kevin Lawrence, John Pedlar, Kathy Campbell, Ewa Milewska, Ron F. Hopkinson, David Price, Tim Owen

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    352 Citations (Scopus)

    Abstract

    Natural Resources Canada, Canadian Forest Service, and their partners have developed customized spatial spline models and gridded datasets for North America for a wide variety of variables, time steps, and spatial resolutions. The initial motivation in developing the models was to address forestry-related issues, however, many agencies and researchers have since used them in a variety of applications. The parameters for the basic model, along with the amount of data smoothing, are usually estimated by minimizing a diagnostic called the generalized cross validation (GCV). Average withheld error estimates for temperature and precipitation models across spatially representative locations at the monthly normal, historical monthly, and historical daily time steps, show that errors associated with the normal surfaces are small, reflecting the greater spatial coherence of monthly normals.

    Original languageEnglish
    Pages (from-to)1611-1622
    Number of pages12
    JournalBulletin of the American Meteorological Society
    Volume92
    Issue number12
    DOIs
    Publication statusPublished - Dec 2011

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