(1) MODEL AND VERSION
Full model name: Lund Potsdam Jena Dynamic Global Vegetation Model
Host institutions: Potsdam Institute for Climate Impact Research, Germany
Department of Plant Ecology, Lund University, Sweden
Max Planck Institute for Biogeochemistry, Jena, Germany
Key references:
LPJ : a coupled model of vegetation dynamics and the terrestrial carbon cycle. S. Sitch, I.C. Prentice, B. Smith, J. Kaplan in preparation
BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types. 1996.
Haxeltine, I.C. Prentice. Global Biogeochemical Cycles, 10(4):693-709
Simulating fire disturbance within a Dynamic Global Vegetation Model: K. Thonicke, S. Venevsky, S. Sitch, W. Cramer in preparation
(2) MODEL TYPE (E.G. ECOSYSTEM, BIOGEOGRAPHY, DGVM)
DGVM
(3) PRIMARY MODEL PURPOSE
Understanding vegetation dynamics and the terrestrial carbon cycle.
(4) MODELING APPROACH
mechanistic, modular, vegetation is grouped into a set of Plant Functional Types.
(5) RESOLUTION (SPATIAL, TEMPORAL)
Spatial resolution: >0.5 degree with existing fire module, <0.5 when modified.
Temporal: the model is driven with monthly climatology, which is interpolated to daily values in subroutines in the model. The model can therefore be run with daily input forcing at a point.
(6) SPATIAL AND TWMPORAL SCALE(S) AT WHICH THE MODELS RESULTS SHOULD BE CONSIDERED:
As above the model can be run for several hundred years on a 0.5 degree Global Grid
(7) PROCESSES AND PROCESS COMPONENTS SIMULATED (E.G. CARBON: GPP, NPP, NEP)
Carbon: GPP, NPP, NEP, biomass burning
Water:
a) Soils (simple bucket, saturated/unsaturated flow, controls on water movement through the profile, etc.): Two layer bucket with active update by vegetation. Feedback between carbon and water update through canopy conductance.
b) Energy balance: (e.g. latent, sensible heat, aet, pet): aet & pet
c) Snow: Yes
d) 'Order' of water balance: (e.g. incoming water is first evaporated from plant/soil surface, then infiltration, transpiration, runoff) the minimum of a water supply and demand is used to calculate this days aet based on yesterday's water supply. The buckets are then updated for ppt, percolation, aet and runoff (mass balance).
Nitrogen: no explicit nitrogen cycle. Tissues assumed C:N ratios etc
(8) SIMULATED RESERVOIRS
Carbon:
a) vegetation: yes
b) litter: yes
c) SOC: yes
Nitrogen:
a) vegetation: implicitly using tissue C:N ratios
b) litter: no
c) SON: no
Soil water: yes
(9) CALIBRATION VARIABLE(S) AND METHOD:
Site, data, NPP, BIOMASS, NEP, Seasonal Carbon Cycle Compared Against Station Measurement, AET data.
(10) SCALING OF THE PROCESS TO THE GRID CELL
Optimization of leaf nitrogen in the canopy.
(11) DISTURBANCE: (FIRE, GRAZING, HARVEST, TREE REMOVAL, ETC.)
Fire and vegetation competition and mortality
(12) VEGETATION I/O: (E.G. POTENTIAL, ACTUAL):
Not prescribed, fractional PFT coverage is and output of the model
(13) INPUT DRIVERS (CLIATIC, SITE, VEG, SOILS) AND RESOLUTION (E.G. DAILY, MONTHLY) REQUIRED FOR MODEL INITIALIZATION:
Monthly(or daily): temperature, precipitation, % sunshine hours (or incoming solar radiation), soil texture class.
(14) ADDITIONAL COMMENTS: