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.