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Simulating global fire regimes & biomass burning with vegetation-fire models

Simulating global fire regimes & biomass burning with vegetation-fire models. Kirsten Thonicke 1 , Allan Spessa 2 & I. Colin Prentice 1 1 2. to estimate global fire emissions: Wildfire emission models

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Simulating global fire regimes & biomass burning with vegetation-fire models

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  1. Simulating global fire regimes & biomass burning with vegetation-fire models Kirsten Thonicke1, Allan Spessa2 & I. Colin Prentice1 1 2

  2. to estimate global fire emissions: Wildfire emission models Ex = Area burnt*Fuel load*Combustion Efficiency*EFx to simulate vegetation - fire interactions: Mechanistic fire models in DGVMs Vegetation dynamics & composition on fuel characteristics Burning conditions (fire behaviour & intensity) determine biomass burnt, thus trace gas emissions Actual vs. potential vegetation (Human impact) • Reduce uncertainties • Inventory & satellite data • Inter-annual variability • Different climate conditions • Burning conditions • Affected vegetation Challenges

  3. Vegetation-fire model:Our approach

  4. SPread and IntensiTy of FIRE(SPITFIRE) • Embedded in Lund-Potsdam-Jena DGVM • litter carbon pool (leaves, sapwood, heartwood) reclassified into dead fuel classes (1, 10, 100, 1000-hr) • live grass (higher moisture content than dry fuel)  fire spread • Tree architecture  fire behaviour & post-fire mortality • Post-fire mortality  Vegetation composition & fuel availability • More fire processes = more PFT parameters  fuel characteristics & fire traits • Resolution: • 0.5° x 0.5° grid cell • Daily: fire processes • Monthly: calculating trace gas emissions • Annual: update of vegetation dynamics

  5. Fire Danger Index No. ignitions Spread Effects Emissions (Nesterov 1949) • Distribution of precipitation according to no. wet days (Gerten et al. J.Hydr. 2004)  daily estimation of fire danger • Fire danger index FDI = Probability that an ignition leads to a spreading fire • Litter moisture per fuel class = f(NI)

  6. Fire Danger Index No. ignitions Spread Effects Emissions “Frame” for potential fires • Fuel availability (as simulated by LPJ) • Climate

  7. Fire Danger Index No. ignitions Spread Effects Emissions • Expected number of fires E[nf]=E[Nig]*FDI with E[nig]=E[nl,ig]+E[nh,ig] • Lightning • Human-caused ignitions (after Venevsky et al. 2002) • Depending on human population density • Population growth 1950-2000: RIVM Database (NL) • Spatial: rural vs. urban lifestyle • Temporal: average no. ignitions per grid cell or region (intentional & negligence) • Minimum intensity to sustain a fire

  8. Fire Danger Index No. ignitions Spread Effects Emissions • Human-caused ignitions per region: - Intentional > negligence

  9. Canada: LFDB Siberia Fire Danger Index No. ignitions Northern Australia Spread Effects Emissions + small fires + grassland fires b) Estimated for case study regions (grid cell)

  10. Fire Danger Index Fuel class No. ignitions Spread Effects Emissions • Conditions of an average fire • Fire spread after Rothermel • Potential fuel load • Fuel characteristics • Litter moisture • Surface-area-to-volume ratio • Fuel bulk density • Wind speed (NCEP re-analysis data) • Fuel consumption after rate of spread • Litter moisture • Assume elliptical fire shape Per PFT

  11. Fire Danger Index No. ignitions Spread Effects Emissions • Human-dominated fire regimes (regional estimate) & constant wind speed

  12. Fire Danger Index No. ignitions Spread Effects Emissions • Surface fire intensity Isurface=H*ROS*S(fuel consumed) • Scorch height per PFT • Crown scorch (CK) per PFT SH of fire vs. tree height & crown length

  13. Fire Danger Index No. ignitions Spread Effects Emissions • Low intensities in savannahs • High intensities in forest ecosystems

  14. Fire Danger Index No. ignitions Spread Effects Emissions • Post-fire mortality Pm= Pm(CK) & Pm(cambial damage) • Mortality from crown scorch = r(CK)*CK3 • Cambial damage = residence time of fire tl / critical time for cambial damage tc • tc = 2.9 * BT2 with BT- Bark thickness • Biomass of killed trees to litter pool  available for burning in the following year

  15. Fire Danger Index No. ignitions Spread Effects Emissions • Carbon release to atmosphere • Surface fire • Crown scorch • Plant material from killed plants to respective dead fuel classes • Emission factor (Andreae & Merlet 2001, Andreae pers. comm. 2003) • CO2, CO, CH4, VOC, NOx, Total Particulate Matter

  16. Fire Danger Index No. ignitions Spread Effects Emissions • Carbon release to atmosphere • Surface fire • Crown scorch

  17. Fire Danger Index No. ignitions Spread Effects Emissions • Emission factor (Andreae & Merlet 2001, Andreae pers. Comm. 2003) • CO2, CO, CH4, VOC, NOx, Total Particulate Matter

  18. Next steps • Evaluation of interannual variability & seasonality • Variability in area burnt, fire intensity in relation to biomass burning • Comparison of biomass burning estimates • Methods • Uncertainties

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