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Examination of Spatial Patterns in Fire Data for the western Great Basin John Nangle Applied...
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Transcript of Examination of Spatial Patterns in Fire Data for the western Great Basin John Nangle Applied...
Examination of Spatial Patterns in Fire Data for the western Great
Basin
John Nangle
Applied MathematicsPicture: http://www.turbosquid.com/FullPreview/Index.cfm/ID/237826
Outline
• Introduction
• Data and Data Sources
• Analysis Methods
• Results and Discussion
• Conclusions and Future Work
Introduction
• Preliminary at ISPE– Gregg Garfin– Don Falk
• Study potential interaction of climate and fire activity
• Better prediction capabilities
• Better able to focus resources
• Long-term analysis http://www.fs.fed.us/rm/boise/research/gis/maps.shtml
Data
• Two sets of fire data– Acres burned and number of fires started– 1º x 1º resolution over [-124.5:-101.5] and [31.5:48.5]– Compiled by Westerling .et .al
• Collected from 1980 to 2004– Bureau of Land Management– U.S. Forest Service– National Park Service– Bureau of Indian Affairs
• Season determined to be April – October in Westerling et. al.
Data, cont.
• Climate Data– 500mb heights
• NOAA Interactive Plotting and Analysis• http://www.cdc.noaa.gov• Download data in NetCDF format
– ENSO Index Values• NOAA Climate Prediction Center• http://www.cpc.ncep.noaa.gov
Analysis Methods
• Formatting of fire data– Format into data cube: (lat,lon,mon)– Multiply by cos(lat)– Normalize grid cells along time series:– Format into hypercube: (lat,lon,yr,mon)
• Create composite maps– High/Low area burned– High/Low number of starts
Analysis Methods
• Create ENSO maps for fire data composites
• Fire data maps created for ENSO composite years
• Create anomaly maps: – Season mean - long-term mean– Raw and normalized data
• PCA Analysis using SVD• Eyeball metric
Results and Discussion
Raw data anomaly map Normalized data anomaly map
• Raw data displays gross structure
• Normalized data contains more fine structure
Results and Discussion
• Plot burn years with ENSO
• Possible lag correlation• Pattern
– LN, EL, LN = High burn year
• Physical interpretation
Conclusion and Future Work
• Examining climate and fire interactivity
• Possible connection with ENSO
• Lag relationship with ENSO
• Correct for burnable area/grid cell
• Examine fire start data in more detail
References• A.L. Westerling, A. Gershunov, T.J. Brown, D.R. Cayan, M.D. Dettinger.
Climate and wildfire in the western united states. Journal of the American Meteorological Society, 84(5):595-604, 2005
• National Oceanic and Atmospheric Association. PSD interactive plotting and analysis page. Accessed Nov. 30, 2007. <http://www.cdc.noaa.gov/cig-bin/PublicData/getpage.pl>
• National Oceanic and Atmospheric Association. Climate prediction center – monitoring and data. Accessed Nov. 30, 2007. http://www.cpc.ncep.noaa.gov
• USDA. Office of Inspector General. Audit Report: Forest Service Large Fire Suppression Costs. (rept. 08601-44-SF). Washington: Government. Printing Office. 2006.