Download Simulating Climate-Vegetation-Fire Interactions & Emissions

Simulating Climate-Vegetation-Fire
Interactions & Emissions: Regional
Applications of the LPJ-SPITFIRE Model
Allan Spessa1,2, Kirsten Thonicke3,
Colin Prentice3
1.
2.
3.
4.
Max Planck Institute for Biogeochemistry, Jena, Germany
Hadley Centre (from 2006)
Marie Curie Fellow, Bristol University
QUEST & Bristol University
Key Research Questions
for LPJ-SPITFIRE
1. Assess long-term changes in vegetation composition
and above-ground carbon due to altered fire regimes,
at regional and global scales.
2. Quantify emissions of different trace gases from
biomass burning (CO2 etc), at regional and global
scales.
3. Examine effects of regional climate phenomona (e.g. El
Nino) on fire activity, vegetation, and emissions.
4. Investigate changes in human-caused ignition
patterns.
LPJ-DGVM
Fire in the Earth System
population
density
TrBlEg
TrBlRg
TeNlEg
TeBlEg
TeBlSg
BoNlEg
BoNlSg
BoBlSg
C3 grass
C4 grass
(Bare
Soil)
rainfall,
cloud,
temp.,
radiation
[CO2]
wind
speed
lightning
strike rate
texture
FIRE MODEL SIMULATES:
Regional fire model
(SPITFIRE)
Number of Fires, Area Burnt, Fire Intensity,
Crown Scorch, Plant Mortality, and
Emissions of CO2, CO, CH4, VOC, NOx & TPM.
Temporal scale = 1 day.
Spatial scale = 0.5 deg (flexible).
Key features of LPJ-SPITFIRE
1)
Human and lightning-caused ignition rates. Gridcell variable (calibration data
limited).
2)
Surface rate of spread based on Rothermel family of models. ROS is directly
proportional to energy produced by ignited fuel, and also wind. ROS is inversely
proportional to the amount of energy required to ignite fuels.
3)
Litter moisture = f (fire danger index);
4)
Grass phenology (‘green-up’ and curing);
5)
Raingreen tree phenology*;
6)
Fire intensity (independent of rate of spread);
7)
Fuel combustion (by fine and coarse fuel classes);
8)
Tree mortality & crown fires = f (scorch height, cambial kill; vegetation-specific
attributes);
9)
Land cover change*  adjust fire activity and emissions to natural vegetation
regions, and
10) Emission factors (CO2, CO, CH4, VOC, TPM, NOx)
 Emissions (tonnes/km2) × trace species × PFT × period (day, month or year).
* Not yet implemented
Progress to date on LPJ-SPITFIRE
• Beta version undergoing validation.
• Long-term validation data on fire activity collated from
several regions, covering most biomes (Iberian Peninsula, North
Germany, Russia and Central Asia, Africa, Australia, Western USA,
Canada, Borneo, Amazonia).
• Data from various sources: satellite and ground
observations, processed to a common format for model
checking.
• First simulation results:
 Global, 1960-2000;
 Australian Wet-Dry Tropics, 1997-2002; and
 Central Asia and Siberia, 1996-2002.
Northern Australia:
Structural Vegetation Cover (GLC 2000)
Northern Australia:
Observed Mean Annual Area Burnt, 1997-2002
(AVHRR FAA data, DOLA)
Northern Australia:
Simulated Mean Annual Area Burnt, 1997-2002
(LPJ-SPITFIRE)
Central
Transect
East
Transect
Northern Australia: Simulated Monthly Area Burnt,
1997-2002 (LPJ-SPITFIRE)
East Transect (North)
1000
monthly simulated area burnt
monthly observed area burnt
800
600
400
200
0
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Central Transect (middle)
mean area burnt per gridcell
[km²]
700
monthly simulated area burnt
600
monthly observed area burnt
500
400
300
200
100
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monthly simulated area burnt
monthly observed area burnt
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mean area burnt per gridcell [km²]
1200
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East Transect (middle)
mean area burnt per gridcell [km²]
mean area burnt per
gridcell [km²]
Central Transect (North)
4000
3500
monthly simulated area burn
monthly observed area burnt
3000
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Central Transect (South)
450
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monthly observed area burnt
350
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200
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100
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mean area burnt per gridcell [km²]
mean area burnt per gridcell
[km²]
East Transect (South)
monthly simulated area burnt
400
350
300
monthly simulated area burnt
monthly observed area burnt
250
200
150
100
50
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199 ul 1 99 n 199 ul 1 99 n 199 ul 1 99 n 200 ul 2 00 n 200 ul 2 00 n 200 ul 2 00
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Northern Australia:
Simulated C4 grass FPC, 2002
(LPJ-SPITFIRE)
Northern Australia:
Simulated Tropical Broadleaved Raingreen FPC, 2002
(LPJ-SPITFIRE)
Northern Australia:
Simulated Tropical Broadleaved Evergreen FPC, 2002
(LPJ-SPITFIRE)
Northern Australia:
Simulated Mean Annual CO2 Emissions
(tonnes per sqkm), 1960-2002 (LPJ-SPITFIRE)
Siberia xxxxxxx
& Central Asia:
Observed Mean Annual Area Burnt, 1996-2002
(AVHRR data, Suhkinin et al., 2004)
Siberia & Central Asia:
xxxxxxx
Simulated Mean Annual
Area Burnt, 1997-2002
(LPJ-SPITFIRE)
Siberia & Central Asia:
Simulated Meanxxxxxxx
Annual CO2 Emissions
(tonnes per sq km), 1960-2002 (LPJ-SPITFIRE)
Next Steps and Future Directions

Complete validation of simulated fire activity against
observed fire data from available regional sets.

Validate simulated patterns for Plant Functional Types, above-ground
carbon and emissions, where possible.

Account for discrepancies between simulated & observed!

Model Experiments. Address questions concerning climate-vegetationfire interactions and emission patterns.
----------------------wish list----------------------------

Simulate seasonal changes in ignition sources e.g. early- vs late- dry
season burning in tropical savannas.

Revisit calibration of population density with fire activity for humancaused ignitions. Consider joint effects of land use change. (Data
sources? GLC 2000, Ramankutty-Foley, Goldewijk HYDE 3.0)

Incorporate land use effects directly into the model e.g. grazing
(tropical savannas) or deforestation rates (humid tropical forests).

Simulate variability in lightning-caused fires (Data source? Optical
Transient Detector, Christian et al. 2003).
Linking LPJ-SPITFIRE to
Remote Sensing Studies of Emissions
Estimating Total Emissions
Total amount of Emissions (E) typically described by the
following equation (Seiler and Crutzen 1980),
M = ∑ ( [A]ijt x [B]ij x [C]ijt x [EF]k), where
• A is the monthly (t) burned area (km2) at location ij;
• B is the fuel load (tonnes/km2) expressed on
a dry weight (DM) basis;
• C is the fraction of available fuel which burns
(the combustion factor); and
• EF is the Emission Factor for the kth trace species (g/kg
or tonnes/km2).
Reducing uncertainty in emission estimates
• New long-term satellite products becoming available
(e.g. GLOBCARBON Plummer et al. in progress, Perriera et al.
in progress., Camaro et al. 2005 GCB + many others).
• Fine temporal &/or spatially resolved optical (e.g. LANDSATTM, MODIS ‘Terra’ & ‘Aqua’, Meteosat) for separate emission
calculations and testing above products.
But, large uncertainties remain with respect to…
• How much biomass is available for burning through space
and time. (Litter production, crown biomass.)
• Relative amount of fine fuels and coarse fuels. (Flaming vs
smouldering combustion.)
• Fuel moisture. (Flaming vs smouldering combustion.)
• What proportion of biomass is combusted. (Fire intensity.)
Thank you for your attention
Northern Australia:
Observed Number of Fires
(AVHRR FAA data, DOLA)
Northern Australia:
Simulated Number of Fires (LPJ-SPITFIRE)
Siberia & Central Asia:
xxxxxxx Evergreen FPC,
Simulated Boreal Needleaved
2000 (LPJ-SPITFIRE)
Siberia & Central Asia:
xxxxxxx
Simulated
C3 grass FPC,
2002 (LPJ-SPITFIRE)
Siberia & Central Asia:
xxxxxxx
Simulated Temperate Broadleaved
Summergreen FPC,
2002 (LPJ-SPITFIRE)
Siberia & Central Asia:
xxxxxxx Summergreen FPC,
Simulated Boreal Broadleaved
2002 (LPJ-SPITFIRE)
Siberia & Central Asia:
xxxxxxx Summergreen FPC,
Simulated Boreal Broadleaved
2002 (LPJ-SPITFIRE) expected