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    Author(s): A.E. Daniels; J.F. Morrison; L.A. JoyceN.L. CrookstonS.C. ChenS.G. McNulty
    Date: 2012
    Source: Gen. Tech. Rep. RMRS-GTR-277WWW. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 32 p.
    Publication Series: General Technical Report (GTR)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (6.01 MB)


    Climate scenarios offer one way to identify and examine the land management challenges posed by climate change. Selecting projections, however, requires careful consideration of the natural resources under study, and where and how they are sensitive to climate. Selection also depends on the robustness of different projections for the resources and geographic area of interest, and possibly on what climate projections are available for a region. Rather than a misguided attempt to identify the "most accurate" climate scenario, managers are strongly encouraged to explore variability through the use of multiple climate scenarios. Considering a range of possible future climates facilitates the identification of management strategies to help ensure resilience of natural resource systems across a broad set of potential conditions. Downscaling climate projections increases the spatial resolution of climate information and can make projections more relevant to natural resource managers by allowing decision-makers to better visualize what these different futures imply locally and regionally. The following series of questions describes key concepts that end-users of climate projection products should understand to appropriately interpret downscaled climate projections, including various sources of uncertainty. The selection used for each component of a downscaled climate projection has implications for interpreting the resulting climate scenario. Understanding the merits and limitations of the downscaling method employed is also important since downscaling approaches vary in their dependence on observed data availability, computational requirements, and in resultant uncertainty owed to biases of the method or the spatial scale of the downscaling.

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    Daniels, A.E.; Morrison, J.F.; Joyce, L.A.; Crookston, N.L.; Chen, S.C.; McNulty, S.G. 2012. Climate projections FAQ. Gen. Tech. Rep. RMRS-GTR-277WWW. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 32 p.


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    climate change, climate projections, downscaling, general circulation models, vulnerability assessment

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