Simulating global fire regimes & biomass burning with vegetation-fire

models

Kirsten Thonicke1, Allan Spessa2 &

I. Colin Prentice1

1 2

Challenges

• to estimate global fire emissions: Wildfire emission modelsEx = 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

Vegetation-fire model:Our approach

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

• 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)

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

d

r

N

mmdifPdewd dTdTdTNNI

3maxmax

Litter moisture index = e(- *NI)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1000 2000 3000 4000 5000 6000 7000

Nesterov Index

1-hr fuel 10-hr fuel 100-hr fuel

(Nesterov 1949)

“Frame” for potential fires Fuel availability (as simulated by LPJ) Climate

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

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

a) Human-caused ignitions per region:- Intentional > negligence

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

b) Estimated for case study regions (grid cell)

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

Canada: LFDB

+ small fires+ grassland fires

Siberia

NorthernAustralia

• 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

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

Per PFT

Fuel class

• Human-dominated fire regimes (regional estimate) & constant wind speed

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

• Surface fire intensity

Isurface=H*ROS*(fuel consumed)

• Scorch height per PFT

• Crown scorch (CK) per PFT

SH of fire vs. tree height & crown length

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

3/2surface* IFSH

• Low intensities in savannahs• High intensities in forest ecosystems

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 l / critical time for cambial damage c

c = 2.9 * BT2 with BT- Bark thickness

– Biomass of killed trees to litter pool available for burning in the following year

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

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

• Carbon release to atmosphere– Surface fire

– Crown scorch

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

Fire Danger Index

No. ignitions

Spread

Effects

Emissions

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