Examination of Spatial Patterns in Fire Data for the western Great Basin - PowerPoint PPT Presentation

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Examination of Spatial Patterns in Fire Data for the western Great Basin

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Title: Examination of Spatial Patterns in Fire Data for the western Great Basin


1
Examination of Spatial Patterns in Fire Data for
the western Great Basin
  • John Nangle
  • Applied Mathematics

Picture http//www.turbosquid.com/FullPreview/Ind
ex.cfm/ID/237826
2
Outline
  • Introduction
  • Data and Data Sources
  • Analysis Methods
  • Results and Discussion
  • Conclusions and Future Work

3
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.sh
tml
4
Data
  • Two sets of fire data
  • Acres burned and number of fires started
  • 1º x 1º resolution over -124.5-101.5 and
    31.548.5
  • 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.

5
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

6
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

7
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

8
Results and Discussion
  • Raw data displays gross structure
  • Normalized data contains more fine structure

9
Results and Discussion
  • Composite Difference Maps

10
Results and Discussion
  • PC plot and EOF maps

11
Results and Discussion
  • Plot burn years with ENSO
  • Possible lag correlation
  • Pattern
  • LN, EL, LN High burn year
  • Physical interpretation

12
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

13
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. lthttp//www.cdc.noaa.gov/cig-bin/P
    ublicData/getpage.plgt
  • 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.

14
Questions
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