Impact model: LPJ-GUESS


Information for the model LPJ-GUESS is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Person responsible for model simulations in this simulation round
Matthew Forrest:, 0000-0003-1858-3489, Senckenberg Biodiversity and Climate Research Centre (BiK-F) (Germany)
Thomas Hickler:, 0000-0002-4668-7552, Senckenberg Biodiversity and Climate Research Centre (BiK-F) (Germany)
Jörg Steinkamp:, 0000-0002-7861-8789, Senckenberg Biodiversity and Climate Research Centre (BiK-F); now at: Data Center, Johannes Gutenberg-University Mainz (Germany)
Output Data
Experiments: I, II, IIa, III, IIIa (Hyytiälä, Peitz, Solling beech, Solling spruce, Sorø, Kroof, Collelongo, Bily Kriz)
Climate Drivers: None
Date: 2018-08-06
Basic information
Model Version: 3.1
Simulation Round Specific Description: * Data in embargo period, not yet publicly available
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Temporal resolution of input data: climate variables: daily
Temporal resolution of input data: co2: annual
Temporal resolution of input data: land use/land cover: annual
Temporal resolution of input data: soil: constant
Input data
Additional input data sets: Soiltypes:Haxeltine, A. and Prentice, I. C.: BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types, Global Biogeochemical Cycles, 10(4), 693–709, doi:10.1029/96GB02344, 1996.Nitrogen deposition:Lamarque, J.-F., Kyle, G. P., Meinshausen, M., Riahi, K., Smith, S. J., Vuuren, D. P. van, Conley, A. J. and Vitt, F.: Global and regional evolution of short-lived radiatively-active gases and aerosols in the Representative Concentration Pathways, Climatic Change, 109(1-2), 191–212, doi:10.1007/s10584-011-0155-0, 2011.Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R., Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G., Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell, D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M., Dahl-Jensen, D., Das, S., Fritzsche, D. and Nolan, M.: Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes, Atmos. Chem. Phys., 13(16), 7997–8018, doi:10.5194/acp-13-7997-2013, 2013.
Climate variables: tas, rsds, pr
Was a spin-up performed?: Yes
Spin-up design: 500 years, recycling detrended first 30 years; CO2 of first years
Natural Vegetation
Natural vegetation partition: dynamic vegetation distribution
Management & Adaptation Measures
Management: No forest cover in fraction of patches equivalent to crop/pasture fraction
Key model processes
Dynamic vegetation: yes
Nitrogen limitation: yes
Co2 effects: yes, Farquhar/Collatz photosynthesis
Light interception: big-leaf approach
Light utilization: Farquhar/Collatz photosynthesis
Phenology: differentiation between evergreen (constant leaf coverage over the year), raingreen (maximum leaf coverage until water stress threshold) and summergreen (budburst and senescence controlled by base temperature, leaf cover increases with accumulated heat sum) trees
Water stress: influence on photosynthesis, allocation (roots/leaf), triggers leaf abscission in raingreen trees
Heat stress: no
Evapo-transpiration approach: PET: Priestley-Taylor (modified for transpiration)
Differences in rooting depth: no
Root distribution over depth: trees and grasses differ
Closed energy balance: no
Coupling/feedback between soil moisture and surface temperature: no
Latent heat: no
Sensible heat: no
Causes of mortality in vegetation models
Age/senescence: yes
Fire: GlobFIRM (Thonicke et al 2001, GEB), the de facto fire model in LPJ-GUESS, uses soil moisture of the upper soil layer as a proxy for fuel moisture. Soil moisture is updated daily based on precipitation (excluding interception by the vegetation canopy); snow melt and evapotranspiration. The daily soil moisture values are used to calculate a daily fire probability using an empirical relationship; and these values are summed at the end of the year to calculate an annual fire season length. From this annual fire season length the annual area burnt is calculated using another empirical relationship. There is also a threshold amount of litter which is required for a gridcell to burn, providing a plant-productivity (and so further climatic) constraint on fire occurrance.
Drought: no
Insects: no
Storm: no
Stochastic random disturbance: yes
NBP components
Fire: 1) yes 2) burnt area fraction calculated at the end of each year, biomass C and above-ground litter C released to atmosphere
Land-use change: all biomass transferred to litter pools on land use change; no slash-and-burn or other treatment
Harvest: no
Species / Plant Functional Types (PFTs)
List of species / pfts: Boreal needleleaved evergreen (BNE); Boreal shade intolerant needleleaved evergreen (BINE); Boreal needleleved summergreen (BNS); Temperate broadleaved summergreen (TeBS); shade intolerant broadleaved summergreen (IBS); Temperate broadleved evergreen (TeBE); Tropical broadleaved evergreen (TrBE); Tropical shade intolerant broadleaved evergreen (TrIBE); Tropical broadleaved raingreen (TrBR); C3 grass (C3G); C4 grass (C4G);
Comments: Carbon pools: Vegetation (VegC); Litter (LitterC); Soil (SoilC); Total (Total); Carbon fluxes: Net primary production (Veg); Reproduction (Repr); Soil (Soil); Fire (Fire); Establishment (Est); Net ecosystem exchange (NEE);
Model output specifications
Output per pft?: Yes, grid-cell totals have to be calculated by hand by summing up the pfts; pft fraction not normalized, sum can be larger than 1, do not multiply with pft-fraction to calculate global totals
Considerations: consider all PFTs
Person responsible for model simulations in this simulation round
Matthew Forrest:, 0000-0003-1858-3489, Senckenberg Biodiversity and Climate Research Centre (BiK-F) (Germany)