Impact model: ELM-ECA

Sector
Biomes
Region
global

ELM is the land component of the earth system model (E3SM) from the US Department of Energy. ELM-ECA corresponds to one of the biogeochemistry configurations in the ELM model. It simulates carbon, nitrogen, phosphorus, water, and energy cycles at a 30-minute time step. Vegetations are prescribed with 17 different Plant Functional Types (PFT) with transient PFT fractional changes. Soils are resolved with 15 vertical layers.

Information for the model ELM-ECA 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
Qing Zhu: qzhu@lbl.gov, 0000-0003-2441-944X, Lawrence Berkeley National Lab (USA)
Basic information
Model Version: v1.0
Model Homepage: https://e3sm.org/
Model License: BSD 3-clause license
Reference Paper: Main Reference: Zhu Q, Riley W, Tang J, Collier N, Hoffman F, Yang X, Bisht G et al. Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking. Journal of Advances in Modeling Earth Systems,11,2238-2258,2019
Resolution
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Vertically resolved: Yes
Number of vertical layers: 15
Additional spatial aggregation & resolution information: N/A
Temporal resolution of input data: co2: annual
Temporal resolution of input data: land use/land cover: annual
Temporal resolution of input data: soil: constant
Additional temporal resolution information: N/A
Input data
Simulated atmospheric climate data sets used: GFDL-ESM4
Emissions data sets used: Atmospheric composition (ISIMIP3b)
Land use data sets used: Historical, gridded land use
Other human influences data sets used: N-deposition, N-Fertilizer (ISIMIP3b)
Additional input data sets: N/A
Climate variables: hurs, sfcWind, tas, rsds, ps, pr
Additional information about input variables: N/A
Person responsible for model simulations in this simulation round
Qing Zhu: qzhu@lbl.gov, 0000-0003-2441-944X, Lawrence Berkeley National Lab (USA)
Additional persons involved: N/A
Output Data
Experiments: obsclim_histsoc_default, obsclim_1901soc_default, counterclim_histsoc_obsco2, counterclim_histsoc_default, obsclim_histsoc_nofire, obsclim_histsoc_1901co2, counterclim_1901soc_default
Climate Drivers: GSWP3-W5E5
Date: 2023-11-17
Basic information
Model Version: v1.0
Model Output License: CC0
Model Homepage: https://e3sm.org/
Model License: BSD 3-clause license
Simulation Round Specific Description: N/A
Reference Paper: Main Reference: Zhu Q, Riley W, Tang J, Collier N, Hoffman F, Yang X, Bisht G et al. Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking. Journal of Advances in Modeling Earth Systems,11,2238-2258,2019
Resolution
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Vertically resolved: Yes
Number of vertical layers: 15
Additional spatial aggregation & resolution information: N/A
Temporal resolution of input data: co2: annual
Temporal resolution of input data: land use/land cover: annual
Temporal resolution of input data: soil: constant
Additional temporal resolution information: N/A
Input data
Observed atmospheric climate data sets used: GSWP3-W5E5 (ISIMIP3a)
Emissions data sets used: Atmospheric composition (ISIMIP3a)
Land use data sets used: Historical, gridded land use
Other human influences data sets used: N-deposition, N-Fertilizer (ISIMIP3a)
Additional input data sets: N/A
Climate variables: hurs, sfcWind, tas, rsds, ps, pr
Additional information about input variables: N/A
Exceptions to Protocol
Exceptions: N/A
Spin-up
Was a spin-up performed?: Yes
Spin-up design: 400 years of acclerated spinup followed by 200 years of regular spinup
Natural Vegetation
Natural vegetation partition: 17 Plant functional types
Natural vegetation dynamics: big leaf model to simulate vegetation dynamics
Natural vegetation cover dataset: LUH2
Soil layers: 15 layers
Management & Adaptation Measures
Management: N/A
Extreme Events & Disturbances
Key challenges: consider disturbance by wildfires
Additional comments: N/A
Model set-up specifications
How do you simulate bioenergy? i.e. what pft do you simulate on bioenergy land?: N/A
How do you simulate the transition from cropland to bioenergy?: N/A
How do you simulate pasture (which pft)?: N/A
Key model processes
Dynamic vegetation: Big leaf model to simulate photosynthesis rate, respiration, growth, litter fall, and mortality. Light, water, and nutrient limitations are considered.
Nitrogen limitation: Nitrogen (NH4 and NO3) competitions occur among roots, microbial immobilizers, nitrifier, denitrifier, and mineral surfacees. Nutrient limitation on vegetation activity depends on the consequence of such multi-consumer-multi-substrate competition network.
Co2 effects: Direct CO2 fertilization effect on photosynthesis as well as regulation effect on stomatal openness.
Light interception: One single canopy layer
Light utilization: Direct and diffusive lights are both utilized by canopy
Phenology: Use evergreen, stress deciduous, temperature deciduous phenology depending on which plant functional type
Water stress: Water stress is approximated with BTRAN factor, which is an integrated factor of soil water deficit across all soil layers.
Heat stress: Heat inhibition function is used in photosynthesis calculation.
Evapo-transpiration approach: Ball-Berry conductance model
Differences in rooting depth: Max rooting depth is prescribed with Jackson et al., 1999 dataset for different plant functional type
Root distribution over depth: vertical root distribution follows exponential decline function
Closed energy balance: closed
Coupling/feedback between soil moisture and surface temperature: coupled
Latent heat: Sensible heat from evaporation and vegetation transpiration.
Sensible heat: Consider bare ground, snow, and vegetated surface sensible heats
How do you compute soil organic carbon during land use (do you mix the previous pft soc into agricultural soc)?: 17 PFTs shared one soil column.
Do you separate soil organic carbon in pasture from natural grass?: N/A
Do you harvest npp of crops? do you including grazing? how does harvested npp decay?: N/A
How do you to treat biofuel npp and biofuel harvest?: N/A
Does non-harvested crop npp go to litter in your output?: N/A
Causes of mortality in vegetation models
Age/senescence: A background mortality rate is applied to mimic the natural senescence
Fire: Considered
Drought: N/A
Insects: N/A
Storm: N/A
Stochastic random disturbance: N/A
Other: N/A
Remarks: N/A
NBP components
Fire: Fire directly combusts vegetation and soil carbon and releases into the atmosphere.
Land-use change: Land use change induced fluxes directly goes into the atmosphere.
Harvest: N/A
Other processes: N/A
Comments: N/A
Species / Plant Functional Types (PFTs)
List of species / pfts: Temperate Needleleaf Evergreen Tree Boreal Needleleaf Evergreen Tree Boreal Needleleaf Deciduous Tree Tropical Broadleaf Evergreen Tree Temperate Broadleaf Evergreen Tree Tropical Broadleaf Deciduous Tree Temperate Broadleaf Deciduous Tree Boreal Broadleaf Deciduous Tree Temperate Broadleaf Evergreen Shrub Temperate Broadleaf Deciduous Shrub Boreal Broadleaf Deciduous Shrub C3 arctic grass C3 grass C4 grass Rain-fed crop Irrigated crop
Comments: N/A
Model output specifications
Output format: grid cell outputs, aggregated all PFT within each grid cell
Output per pft?: N/A
Considerations: N/A
Land-use change implementation
Is crop harvest included? if so, how?: N/A
Is cropland soil management included? if so, how?: N/A
Is grass harvest included? if so, how?: N/A
Is shifting cultivation included?: N/A
Is wood harvest included? if so, how?: N/A
Which transition rules are applied to decide where agriculture is conducted?: N/A
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
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): no
Fire modules
Aggregation of reported burnt area: simulated burned fraction multiple by grid cell area
Land-use classes allowed to burn: All
Included fire-ignition factors: both human and natural
Is fire ignition implemented as a random process?: fire ignition is a function of population density and lightning density
Is human influence on fire ignition and/or suppression included? how?: Both
How is fire spread/extent modelled?: Depends on wind speed and PFT
Are deforestation or land clearing fires included?: Yes
What is the minimum burned area fraction at grid level?: 0