land cover & fire at high latitudes: model-data comparison and model modification nceo land...
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Land cover & fire at high latitudes:
model-data comparison and model modification
NCEO Land Science Meeting,28-29 February 2012, Sheffield, UK
E.Kantzas, M. Lomas, S.QueganNational Centre for Earth Observation-CTCDUniversity of Sheffield
•MONitoring and Assessing RegionalClimate change in High latitudes andthe Arctic.
•Generate an information package of multidisciplinary ECVs associated with terrestrial carbon and water fluxes at high latitudes.
Essential Climate Variables ConsideredVegetation Cover Ocean Color
Fire Sea Ice DriftRiver Discharge Surface Wind
Snow Cover PCO2, oceanPermafrost PCO2, atmosphere
Ice Sheets & Glaciers Sea Ice ExtentSea Level Sea Ice ThicknessCurrents Sea Surface Temperature
Goals:i) Synthesize available data setsii) Generation of time seriesiii) Interface ECVs with models
NBP
LEACHED
Litter Disturbance
ATMOSPHERICCO2
BIOPHYSICS
Soil
Photosynthesis
GROWTH
Biomass
GPP
NPP
Thinning
Mortality
Fire
Differences in Net Biome Production betweenthe 3 models in•Magnitude•Spatial distribution•Trend
N. AmericaN. America
GlobCoverGlobCover
GLC2000GLC2000
•Significant differences exist between data sets.
•Translating land classes into model PFTs is liable to user interpretation.
Driving model with different land cover data sets had the following carbon effects:•Up to 50% differences in fire emissions•Up to 20% differences in net carbon uptake
Models cannot capture the temporal and spatial variability of fire which leads to:
•Underestimation of inter-annual variability of land-atmosphere carbon exchange
•Inability of models to simulate the effects of fire disturbance on permafrost.
Method: By adding a probabilistic component to the algorithm which controls fire occurrence, simulated fire regime resembled GFED data.
Due to the lack of an energy balance modelno feedbacks of fire disturbance were observed on permafrost despite fire events removing up to 30% of cover.
Method: For each site the GFED data variance was added to model variance which lead to the model exhibiting similar variability to data.
Burned Area MhcBurned Area Mhc
Fire emissions variance increasedbutthe inter-annual variability of NBP remained largely unaffected.
LPJ-WM CLM4CN SDGVM
Fuel load AgB, BgB, litter AgB, BgB, litter AgB only
Combustion completeness
Biomass: 100%
Litter: 100%
Leaves and fine roots: 100%Stem, coarse roots: 20%
Litter: 100%Woody Debris: 40%
Biomass: 80%
Stocks (PgC) LPJ-WM CLM4CN
Biomass 93 75
Litter 100 21
Emissions (TgC y-1) LPJ-WM CLM4CN
Biomass 290 118
Litter 372 46
N. America
Eurasia
•Driving a model with different land cover significantly affects fire emissions and to some extent carbon uptake in boreal latitudes.
•The spatial and temporal variability in fire occurrence at high latitudes is not captured by C models so fire-permafrost interactions are not simulated.
•Different process representations lead to radically different total fire emissions and emissions per unit burnt area.
•Improve parameterization of the probabilistic component in the fire algorithm to better describe the inter-annual and spatial variability of fire emissions and land-atmosphere carbon exchange.
•Define first qualitatively and then quantitatively modelled fire emissions.
•After establishing a realistic fire disturbance framework, evaluate fire-permafrost interactions.
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