Impact model: CLASSIC

The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) simulates the exchanges of energy, water, carbon, and momentum at the earth's surface. CLASSIC is formed by the coupling of the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM). CLASS simulates the fluxes of energy, water, and momentum. CTEM simulates biogeochemical cycles including fluxes of carbon.

Sector
Biomes
Region
global

Information for the model CLASSIC 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
Sian Kou-Giesbrecht: Sian.KouGiesbrecht@ec.gc.ca, 0000-0002-4086-0561, Canadian Centre for Climate Modelling and Analysis (Canada)
Output Data
Experiments: ssp585_2015soc-from-histsoc_nondep, ssp585_2015soc_default, ssp126_2015soc-from-histsoc_default, picontrol_2015soc-from-histsoc_default, ssp126_2015soc_default, picontrol_2015soc_default, ssp585_2015soc-from-histsoc_2015co2, historical_histsoc_default, ssp585_2015soc-from-histsoc_nondep2015co2, ssp585_2015soc-from-histsoc_ssp585ndep, ssp370_2015soc-from-histsoc_default, historical_2015soc_default, ssp585_2015soc-from-histsoc_default, ssp370_2015soc_default, historical_histsoc_nondep, ssp585_2015soc_2015co2, picontrol_histsoc_default, picontrol_1850soc_default
Climate Drivers: GFDL-ESM4, UKESM1-0-LL
Date: 2022-10-25
Basic information
Model Version: v1.0
Model Output License: CC0
Model Homepage: https://cccma.gitlab.io/classic/
Simulation Round Specific Description: * Data in embargo period, not yet publicly available.
Reference Paper: Main Reference: Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup et al. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance. Geoscientific Model Development,13,2825–2850,2020
Reference Paper: Other References:
Resolution
Spatial Aggregation: variable grid
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 sets used
Simulated Atmospheric Climate Data Sets Used: MRI-ESM2-0, IPSL-CM6A-LR, MPI-ESM1-2-HR, UKESM1-0-LL, GFDL-ESM4
Climate Variables: huss, sfcWind, tas, rlds, rsds, ps, pr
Additional Input Data Sets: Atmospheric CH4 concentration from input4MIPs (https://doi.org/10.22033/ESGF/input4MIPs.1118).
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: The spin-up was 650 years. It used pre-industrial climate and atmospheric CO2 concentration at 1850 levels. For histsoc, DHF were fixed at 1850 levels. For 2015soc, DHF were fixed at 2015 levels.
Natural Vegetation
Natural Vegetation Partition: Land cover is from the European Space Agency (ESA) Climate Change Initiative (CCI), see https://doi.org/10.5194/essd-10-219-2018.
Natural Vegetation Dynamics: NA
Natural Vegetation Cover Dataset: https://doi.org/10.5194/essd-10-219-2018
Management & Adaptation Measures
Management: NA
Model set-up specifications
How Do You Simulate Bioenergy? I.E. What Pft Do You Simulate On Bioenergy Land?: NA
How Do You Simulate The Transition From Cropland To Bioenergy?: NA
How Do You Simulate Pasture (Which Pft)?: No
Species / Plant Functional Types (PFTs)
List Of Species / Pfts: Needleleaf evergreen tree (evgndltr) Needleleaf deciduous tree (dcdndltr) Broadleaf evergreen tree (evgbdltr) Broadleaf cold deciduous tree (dcdcldbdltr) Broadleaf drought deciduous tree (dcddrybdltr) C3 crop (c3crop) C4 crop (c4crop) C3 grass (c3grass) C4 grass (c4grass)
Model output specifications
Output Format: Output is written out per grid-cell area.
Output Per Pft?: Output per PFT is written out per unit area of that PFT.
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): CLASSIC reaches a steady state after spin up for each climate forcing. The following are NBP averaged over the final 20 years of the spin up for each climate forcing: GFDL: 0.05 Pg C y-1 IPSL: 0.08 Pg C y-1 MPI: -0.09 Pg C y-1 MRI: -0.17 Pg C y-1 UKESM: -0.002 Pg C y-1
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): CLASSIC estimates NBP within 1.2 +/- 0.8 GtC/yr for each climate forcing. The following are NBP averaged over 1990 to 1999 for each climate forcing: GFDL: 0.97984 GtC/yr IPSL: 1.7284 GtC/yr MPI: 0.74633 GtC/yr MRI: 0.90597 GtC/yr UKESM: 1.7613 GtC/yr
Person responsible for model simulations in this simulation round
Sian Kou-Giesbrecht: Sian.KouGiesbrecht@ec.gc.ca, 0000-0002-4086-0561, Canadian Centre for Climate Modelling and Analysis (Canada)
Output Data
Experiments: obsclim_2015soc_default, counterclim_histsoc_default, obsclim_histsoc_nofire, obsclim_histsoc_default, counterclim_2015soc_default
Climate Drivers: GSWP3-W5E5
Date: 2022-07-26
Basic information
Model Version: CLASSICv1.4
Model Output License: CC0
Model Homepage: https://cccma.gitlab.io/classic_pages/
Reference Paper: Main Reference: Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup et al. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance. Geoscientific Model Development,13,2825–2850,2020
Resolution
Spatial Aggregation: regular grid
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 sets used
Observed Atmospheric Climate Data Sets Used: GSWP3-W5E5 (ISIMIP3a)
Land Use Data Sets Used: Historical, gridded land use
Other Human Influences Data Sets Used: N-Fertilizer (ISIMIP3a)
Climate Variables: huss, tasmax, tas, tasmin, rlds, rsds, ps, pr
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: The spin up was 400 years.
Natural Vegetation
Natural Vegetation Partition: - Land cover is from the European Space Agency (ESA) Climate Change Initiative (CCI), see https://doi.org/10.5194/essd-10-219-2018. Crop area is set according to the 5 crop land use classes data provided and natural PFT area is proportionally scaled. As the fractional coverage of the crop PFTs changes in a grid cell, the fractional coverage of the non-crop PFTs in the grid cell is changed in proportion to their existing values. See Wang et al. (2022).
Natural Vegetation Dynamics: NA
Natural Vegetation Cover Dataset: - Land cover is from the European Space Agency (ESA) Climate Change Initiative (CCI), see https://doi.org/10.5194/essd-10-219-2018.
Soil Layers: There are 20 soil layers starting with 10 soil layers of 0.1 m thickness, gradually increasing to a 30 m thick soil layer for a total ground depth of over 61 m.
Management & Adaptation Measures
Management: N fertilisation.
Extreme Events & Disturbances
Key Challenges: NA
Model set-up specifications
How Do You Simulate Bioenergy? I.E. What Pft Do You Simulate On Bioenergy Land?: NA
How Do You Simulate The Transition From Cropland To Bioenergy?: NA
How Do You Simulate Pasture (Which Pft)?: NA
Key model processes
Dynamic Vegetation: No
Nitrogen Limitation: - Photosynthesis carboxylation capacity is dependent on leaf N such that, when leaf N is low, photosynthetic capacity is downregulated and, when leaf N is high, photosynthetic capacity is upregulated. Vegetation C:N ratio is flexible. Vegetation upregulates and downregulates symbiotic BNF in response to strong and weak N limitation respectively. See Asaadi and Arora (2021) and Kou-Giesbrecht and Arora (2022).
Co2 Effects: - The photosynthesis parametrization is based upon the approach of Farquhar et al. (1980) and Collatz et al. (1991, 1992) as described in Melton and Arora (2016). The gross leaf photosynthesis rate depends upon the maximum assimilation rate allowed by light, Rubisco, and transport capacity, and is dependent on the partial pressure of CO2 in the leaf interior.
Light Interception: - The photosynthesis parametrization is based upon the approach of Farquhar et al. (1980) and Collatz et al. (1991, 1992) as described in Melton and Arora (2016). The leaf-level gross photosynthesis rate is scaled up to the canopy-level gross primary productivity by considering the exponential vertical profile of photosynthetically absorbed radiation along the depth of the canopy and leaf area index.
Light Utilization: - The photosynthesis parametrization is based upon the approach of Farquhar et al. (1980) and Collatz et al. (1991, 1992) as described in Melton and Arora (2016). The gross leaf photosynthesis rate depends upon the maximum assimilation rate allowed by light, Rubisco, and transport capacity, and is dependent on the incident photosynthetically active radiation.
Phenology: - The leaf phenology parametrization is described in detail in Arora and Boer (2005). There are four different leaf phenological states in which vegetation can be at a given instant: (i) no leaves or dormant, (ii) maximum growth, (iii) normal growth and (iv) leaf fall or harvest. PFTs may go through only some, or all, of these phenological states depending on their deciduousness. A broadleaf cold deciduous tree, for example, transitions through all these four states in a year. In winter, the broadleaf cold deciduous trees are in the no leaves or dormant state; favourable climatic conditions in spring trigger leaf growth and the tree enters the maximum leaf growth state when all the NPP is allocated to leaves to accelerate leaf out; when the LAI reaches a threshold the tree enters the normal leaf growth state and NPP is also allocated to the stem and roots; finally the arrival of autumn triggers leaf fall / harvest and the trees go into the leaf fall / harvest state where no NPP is allocated to leaves (but it continues for the stem and roots). When all the leaves have been shed, the trees go into the no leaves or dormant state again and the cycle is repeated the next year. The evergreen tree PFTs and the grass PFTs do not enter the leaf fall / harvest state and maintain a leaf canopy as long as environmental conditions are favourable.
Water Stress: - Water stress causes a reduction in photosynthesis and accelerated leaf turnover compared to the normal leaf turnover. Water stress also causes reduced growth efficiency which increases mortality. See Melton and Arora (2016).
Heat Stress: - Photosynthesis stops at high and low temperatures because each PFT has specified lower and upper temperature thresholds for photosynthesis. Vapour pressure deficit and soil moisture regulate photosynthesis and are also affected by temperature. Cold stress causes accelerated leaf turnover compared to the normal leaf turnover. See Melton and Arora (2016).
Evapo-Transpiration Approach: - Total evapotranspiration is comprised of soil evaporation, evaporation of intercepted water and sublimation of intercepted snow from the canopy and plant transpiration. See Sun and Verseghy (2019).
Differences In Rooting Depth: - Rooting depth is calculated using a dynamic root distribution (as a function of root biomass) and is defined to be the depth containing 95% of the root biomass. See Arora and Boer (2003).
Root Distribution Over Depth: - Root distribution is calculated using a dynamic root distribution (as a function of root biomass). See Arora and Boer (2003).
Closed Energy Balance: - Yes, the energy balance is closed. Net radiation equals the sum of latent, sensible and ground heat fluxes.
Coupling/Feedback Between Soil Moisture And Surface Temperature: - All soil layers experience moisture phase change as well as internal energy change caused by soil heat conduction and/or soil water mass loss/gain. See Verseghy (2012).
Latent Heat: - The top soil layer absorbs solar energy and emits longwave radiation as well as exchanging energy with the overlying air through sensible and latent heat fluxes. See Verseghy (2012).
Sensible Heat: - The top soil layer absorbs solar energy and emits longwave radiation as well as exchanging energy with the overlying air through sensible and latent heat fluxes. See Verseghy (2012).
How Do You Compute Soil Organic Carbon During Land Use (Do You Mix The Previous Pft Soc Into Agricultural Soc)?: - When the fractional coverage of a PFT decreases, litter and soil C from the removed fractional coverage of the PFT is uniformly spread over the grid cell. See Arora and Boer (2010).
Do You Separate Soil Organic Carbon In Pasture From Natural Grass?: - No (pasture is not represented).
Do You Harvest Npp Of Crops? Do You Including Grazing? How Does Harvested Npp Decay?: - Crop harvesting is initiated when the daily mean air temperature remains below 8C for 5 consecutive days, or when the crop LAI reaches a threshold (3.5 m2 m−2 for C3 crops and 94.5 m2 m−2 for C4 crops) signifying that the crops have matured. Crop harvesting occurs over a period of 15 days. The harvested crop biomass C contributes to the litter pool. See Arora and Boer (2005). Grazing is not included.
How Do You To Treat Biofuel Npp And Biofuel Harvest?: - Not represented.
Does Non-Harvested Crop Npp Go To Litter In Your Output?: - Non-harvested crop biomass C remains as live biomass C.
Causes of mortality in vegetation models
Age/Senescence: - Vegetation dies due to reduced growth efficiency and aging. Growth efficiency-related mortality is calculated using growth efficiency of a PFT over the course of the previous year following Prentice et al. (1993) and Sitch et al. (2003). Aging-related mortality uses a PFT-specific maximum age to calculate an annual mortality rate such that only 1% of tree PFTs exceed this maximum age. Aging-related mortality accounts for processes, whose effect is not explicitly captured in CLASSIC including insect damage, hail, wind throw, etc.
Fire: - CLASSIC represents both natural and human-influenced fires. Fire is simulated using a process-based scheme of intermediate complexity that accounts for all elements of the fire triangle: fuel load, combustibility of fuel, and an ignition source. The probability of fire due to fuel load is dependent on the aboveground biomass C available for sustaining a fire. The probability of fire due to combustibility of fuel is dependent on soil moisture. The probability of fire due to the presence of an ignition source is influenced by both natural (lightning) and anthropogenic agents (either intentional or accidental, dependent on population density). Fire emits CO2, CH4, other trace gases, and aerosols while plant mortality and damage due to fire contribute to litter C. See Arora and Boer (2005) and Arora and Melton (2018).
Drought: - Water stress causes a reduction in photosynthesis and accelerated leaf turnover compared to the normal leaf turnover. Water stress also causes reduced growth efficiency which increases mortality. See Melton and Arora (2016).
Insects: - Insect-related mortality is accounted for in aging-related mortality (described above).
Storm: - Insect-related mortality is accounted for in aging-related mortality (described above).
Stochastic Random Disturbance: - Insect-related mortality is accounted for in aging-related mortality (described above).
NBP components
Fire: - Fire is described above.
Land-Use Change: - During land use change, biomass C from a PFT whose fractional coverage decreases is divided into three components: (i) the component that is combusted immediately and which contributes to atmospheric CO2, (ii) the component that is left as slash or used for pulp and paper products, and (iii) the component that is used for long-lasting wood products. To account for the timescales involved, the fraction allocated to (ii) is transferred to litter C and the fraction allocated to (iii) is allocated to soil C. While they are placed in litter and soil C, these land use change products are kept separate to allow accurate accounting. See Arora and Boer (2010).
Harvest: - Crop harvest is described above. Harvest from forest and grassland management is not represented.
Species / Plant Functional Types (PFTs)
List Of Species / Pfts: - Needleleaf evergreen tree (evgndltr) - Needleleaf deciduous tree (dcdndltr) - Broadleaf evergreen tree (evgbdltr) - Broadleaf cold deciduous tree (dcdcldbdltr) - Broadleaf drought deciduous tree (dcddrybdltr) - C3 crop (c3crop) - C4 crop (c4crop) - C3 grass (c3grass) - C4 grass (c4grass)
Model output specifications
Output Format: - Output is written out per grid-cell area.
Output Per Pft?: - Output per PFT is written out per unit area of that PFT.
Land-use change implementation
Is crop harvest included? If so, how?: Yes. Crops are harvested (described above).
Is cropland soil management included? If so, how?: No.
Is grass harvest included? If so, how?: Grass harvest is not included explicitly (although during land use change some biomass C from a PFT whose fractional coverage decreases is used for pulp products, paper products, and long-lasting wood products as described above).
Is shifting cultivation included?: No.
Is wood harvest included? If so, how?: Wood harvest is not included explicitly (although during land use change some biomass C from a PFT whose fractional coverage decreases is used for pulp products, paper products, and long-lasting wood products as described above).
Which transition rules are applied to decide where agriculture is conducted?: Crop area is based on land cover data (described above).
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): - CLASSIC reaches a steady state after spin up for each climate forcing. The following are NBP averaged over the final 20 years of the spin up for each climate forcing: o GSWP3: 0.16 Pg C y-1 o GFDL: 0.05 Pg C y-1 o IPSL: 0.08 Pg C y-1 o MPI: -0.09 Pg C y-1 o MRI: -0.17 Pg C y-1 o UKESM: -0.002 Pg C y-1
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): - CLASSIC estimates NBP within 1.2 +/- 0.8 GtC/yr for each climate forcing. The following are NBP averaged over 1990 to 1999 for each climate forcing: o GSWP3: 0.94 GtC / yr o GFDL: 0.98 GtC/yr o IPSL: 1.73 GtC/yr o MPI: 0.75 GtC/yr o MRI: 0.91 GtC/yr o UKESM: 1.76 GtC/yr
Fire modules
Aggregation of reported burnt area: - Daily burned area is assumed to be elliptical and is based on the fire spread rate (described below) and the properties of an ellipse. Daily burned area is calculated given fire ignition probability and fire extinguishing probability.
Land-use classes allowed to burn: - All natural vegetation PFTs are allowed to burn. Crops are not allowed to burn.
Included fire-ignition factors: - The probability of fire due to the presence of an ignition source is influenced by both natural (lightning) and anthropogenic agents (either intentional or accidental, dependent on population density).
Is fire ignition implemented as a random process?: - No.
Is human influence on fire ignition and/or suppression included? How?: - The probability of fire due to the presence of an ignition source is influenced by both natural (lightning) and anthropogenic agents (either intentional or accidental, dependent on population density). Fire suppression is also dependent on population density (which determines fire extinguishing probability).
How is fire spread/extent modelled?: - The fire spread rate in the downwind direction is dependent on wind speed and the effect of rooting zone and duff soil wetness.
Are deforestation or land clearing fires included?: - During land use change, deforested biomass is divided into three components: (i) the component that is combusted immediately and which contributes to atmospheric CO2, (ii) the component that is left as slash or used for pulp and paper products, and (iii) the component that is used for long-lasting wood products.
What is the minimum burned area fraction at grid level?: Zero.