Impact model: VEGAS

Sector
Biomes
Region
global

VEGAS is one of the 8 global models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a biome sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Biomes Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.002

Information for the model VEGAS 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
Min Chen: chenminbnu@gmail.com, University of Wisconsin-Madison (USA)
Fang Zhao: fangzhao@pik-potsdam.de, 0000-0002-4819-3724, Potsdam Institute for Climate Impacts Research (Germany)
Output Data
Experiments: I, II, IIa, III
Climate Drivers: None
Date: 2017-09-20
Basic information
Resolution
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: not used
Input data
Simulated atmospheric climate data sets used: IPSL-CM5A-LR
Emissions data sets used: Atmospheric CO2 concentration
Land use data sets used: Historical, gridded land use (HYDE 3.2)
Other data sets used: Land-sea mask
Climate variables: tas, rsds, pr
Spin-up
Was a spin-up performed?: Yes
Spin-up design: First 300 years (first 200-year accelerated) with detrended, randomized climate data (using ISI-MIP provided random serie of detrended 1901-1930 data) with natural vegetation, followed by 300 years of random climate and constant 1860 land use and CO2.
Natural Vegetation
Natural vegetation partition: dynamic vegetation distribution
Management & Adaptation Measures
Management: prognostic planting and harvesting, varying management intensity and harvest index to simulate the tripling of crop production since 1961 (See Zeng et al. 2014)
Extreme Events & Disturbances
Key challenges: No heat stress mechanism in model.
Key model processes
Dynamic vegetation: yes
Nitrogen limitation: implicitly considered in Javis/Collatz photosynthesis
Co2 effects: yes, Javis/Collatz pohotosynthesis
Light interception: vegetation height-dependend light extinction
Light utilization: Jarvis light use efficiency
Phenology: dynamic
Water stress: Influence on photosynthesis, carbon allocation, evapotranspiration, and soil biogeochemical processes
Heat stress: no
Evapo-transpiration approach: Stomatal resistance, linked to photosynthesis; bulk transfer formula
Differences in rooting depth: Vegetation type dependent; also topography
Closed energy balance: yes
Coupling/feedback between soil moisture and surface temperature: yes
Latent heat: yes
Sensible heat: yes
Causes of mortality in vegetation models
Age/senescence: background mortality
Fire: yes. Fire module includes the effects of moisture availability, temperature, soil fuel loading, and PFT dependent resistance and captures fire contribution to interannual CO2 variability.
Drought: yes
Insects: no
Storm: no
Stochastic random disturbance: yes (random cold temperature trigger leaf falling)
Other: light competition
NBP components
Fire: yes
Land-use change: yes
Harvest: Harvest from crops and forest. 1) total aboveground crop C * harvest index (fraction of edible parts) * fraction left after loss due to weeds, failed crop etc.; harvested crop C is transported horizontally (see Zeng et a. 2014), remaining biomass sent to metabolic ltter pool; 2) sustainable wood harvest
Other processes: RH
Species / Plant Functional Types (PFTs)
List of species / pfts: Broad-leaved tree; needleleaf tree; (Whether diciduous or evergreen is dynamically determined); cold grass; warm grass; generic crop
Comments: provided by Fang Zhao (with input from Ning Zeng) 2/16
Model output specifications
Output format: NetCDF
Output per pft?: Already averaged over the whole grid
Land-use change implementation
Is crop harvest included? if so, how?: yes. Harvest occurs when maximum LAI is reached.
Is cropland soil management included? if so, how?: Yes, irrigation is introduced to moderately increase soil moisture content for crop.
Is grass harvest included? if so, how?: no
Is shifting cultivation included?: Only a single crop type (average of maize, rice and wheat) is simulated.
Is wood harvest included? if so, how?: yes, harvested wood goes into medium and long term carbon storage.
Which transition rules are applied to decide where agriculture is conducted?: transition is assumed to occur at the edge of agricultural center (according to high spatial resolution HYDE data), such that the mature forest/most dense agricultural regions are often intact.
Carbon-cycle benchmarking
Does your model reach a (near) steady state after spin up (characterized by nbp of < 0.2 pgc y-1)? (yes/no, provide number): Yes after natural spin-up, no (0.3 PgC/yr) after constant 1860 land use spin up. Soil is losing carbon (thus reducing respiration and increasing NBP) due to agricultural activity that intensifies erosion. The soil erosion and subsequent transport/storage in river/marine systems cause a natural carbon sink estimated to be about 0.3 PgC y-1 that is considered to be part of the net land-atmo C flux.
What is your modeled nbp for the 1990-2000 decade? is it within 1.2 +/- 0.8 gtc/yr (1-sigma) of observed data from o2/n2 trends (keeling and manning 2014) for 1990-1999 (yes/no, provide number): NBP for 1990-2000 driven by daily GSWP3 forcing is 0.74 GtC/yr. (Note the model is sensitive to climate forcing and IPSL forcing with the same model version leads to a NBP of -0.1 GtC/yr for the same period.)
Person responsible for model simulations in this simulation round
Ghassem Asrar: ghassem.asrar@pnnl.gov, 0000-0002-1066-8384, Joint Global Change Research Institute, Pacific Northwest National Laborators (USA)
Min Chen: chenminbnu@gmail.com, University of Wisconsin-Madison (USA)
Rafique Rashid: rashidbao@gmail.com, 0000-0001-9591-6588, Joint Global Change Research Institute (USA)
Ning Zeng: zeng@umd.edu, University of Maryland (USA)
Fang Zhao: fangzhao@pik-potsdam.de, 0000-0002-4819-3724, Potsdam Institute for Climate Impacts Research (Germany)
Output Data
Experiments: historical
Climate Drivers: None
Date: 2016-01-21
Basic information
Resolution
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Temporal resolution of input data: climate variables: monthly, disaggragate to daily internally
Temporal resolution of input data: co2: annual
Temporal resolution of input data: land use/land cover: annual
Temporal resolution of input data: soil: not used
Input data
Observed atmospheric climate data sets used: GSWP3, WATCH (WFD), WATCH-WFDEI
Climate variables: tas, rsds, pr
Spin-up
Was a spin-up performed?: Yes
Spin-up design: 1. First 300 years (first 200-year accelerated) with detrended 1906 climate data (because 1701 data is 1906 detrended, and this prevents an artificial model jump), 278.72ppm CO2 (1765 level) and natural vegetation; 2. 1701-1900: randomized climate data (using ISI-MIP provided random serie of detrended 1901-1930 data), time-varying land use and co2; 3. 1901-, time varying climate, co2, land use
Natural Vegetation
Natural vegetation partition: dynamic vegetation distribution
Management & Adaptation Measures
Management: prognostic planting and harvesting, varying management intensity and harvest index to simulate the tripling of crop production since 1961 (See Zeng et al. 2014)
Key model processes
Dynamic vegetation: yes
Nitrogen limitation: implicitly considered in Javis/Collatz photosynthesis
Co2 effects: yes, Javis/Collatz pohotosynthesis
Light interception: vegetation height-dependend light extinction
Light utilization: Jarvis light use efficiency
Phenology: dynamic
Water stress: Influence on photosynthesis, carbon allocation, evapotranspiration, and soil biogeochemical processes
Heat stress: no
Evapo-transpiration approach: Stomatal resistance, linked to photosynthesis; bulk transfer formula
Differences in rooting depth: Vegetation type dependent; also topography
Closed energy balance: yes
Coupling/feedback between soil moisture and surface temperature: yes
Latent heat: yes
Sensible heat: yes
Causes of mortality in vegetation models
Age/senescence: background mortality
Fire: yes
Drought: yes
Insects: no
Storm: no
Stochastic random disturbance: yes (random cold temperature trigger leaf falling)
Other: light competition
NBP components
Fire: yes
Land-use change: yes
Harvest: Harvest from crops and forest. 1) total aboveground crop C * harvest index (fraction of edible parts) * fraction left after loss due to weeds, failed crop etc.; harvested crop C is transported horizontally (see Zeng et a. 2014), remaining biomass sent to metabolic ltter pool; 2) sustainable wood harvest
Other processes: RH
Species / Plant Functional Types (PFTs)
List of species / pfts: Broad-leaved tree; needleleaf tree; (Whether diciduous or evergreen is dynamically determined); cold grass; warm grass; generic crop
Comments: provided by Fang Zhao (with input from Ning Zeng) 2/16
Model output specifications
Output per pft?: Already averaged over the whole grid