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RESEARCH ARTICLE
Contents Vol 15(2)

Evaluation of MM5 model resolution when applied to prediction of National Fire Danger Rating indexes

Jeanne L. Hoadley A F , Miriam L. Rorig A , Larry Bradshaw B , Sue A. Ferguson A , Kenneth J. Westrick C , Scott L. Goodrick D and Paul Werth E
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Pacific Northwest Research Station, 400 N 34th Street #201, Seattle, WA 98103, USA.

B USDA Forest Service, Pacific Northwest Research Station Fire Sciences Laboratory, 5775 US W Highway 10, Missoula, MT 59808-9361, USA.

C 3Tier Environmental Forecast Group, 2825 Eastlake Avenue E #301, Seattle, WA 98102, USA.

D USDA Forest Service, Southeast Research Station, 320 Green Street, Athens, GA 30602-2044, USA.

E US Department of Interior, Northwest Interagency Coordination Center, 5420 NE Marine Drive, Portland, OR 97218-1007, USA.

F Corresponding author. Email: jhoadley@fs.fed.us

International Journal of Wildland Fire 15(2) 147-154 https://doi.org/10.1071/WF05015
Submitted: 20 January 2005  Accepted: 25 October 2005   Published: 31 May 2006

Abstract

Weather predictions from the MM5 mesoscale model were used to compute gridded predictions of National Fire Danger Rating System (NFDRS) indexes. The model output was applied to a case study of the 2000 fire season in Northern Idaho and Western Montana to simulate an extreme event. To determine the preferred resolution for automating NFDRS predictions, model performance was evaluated at 36, 12, and 4 km. For those indexes evaluated, the best results were consistently obtained for the 4-km domain, whereas the 36-km domain had the largest mean absolute errors. Although model predictions of fire danger indexes are consistently lower than observed, analysis of time series results indicates that the model does well in capturing trends and extreme changes in NFDRS indexes.


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