Impact model: CLM4.5


The Community Land Model is the land model for the Community Earth System Model (CESM). It examines the physical, chemical, and biological processes by which terrestrial ecosystems affect and are affected by climate across a variety of spatial and temporal scales. The central theme is that terrestrial ecosystems, through their cycling of energy, water, chemical elements, and trace gases, are important determinants of climate.

Model components consist of: biogeophysics, hydrologic cycle, biogeochemistry and dynamic vegetation.

The land surface is represented by 5 primary sub-grid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of plant functional types, each with its own leaf and stem area index and canopy height. Each subgrid land cover type and PFT patch is a separate column for energy and water calculations.

The current version of the Community Land Model is CLM4.5. Simulations for ISIMIP2b were conducted with CLM4.5, and include an interactive Carbon and Nitrogen cycle (CN) and a an interactive crop model (CROP). ISIMIP2a simulations were conducted either with CLM4.0 (global water) or CLM4.5post (agriculture, at 2° resolution).

Information for the model CLM4.5 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
Sonia Seneviratne:, 0000-0001-9528-2917, ETH Zurich (Switzerland)
Wim Thiery:, 0000-0002-5183-6145, Vrije Universiteit Brussel and ETH Zurich (Belgium)
Additional persons involved: Wim Thiery
Output Data
Experiments: I (no extended future), II, III, VIII
Climate Drivers: None
Date: 2020-06-18
Basic information
Model Version: 4.5
Model Output License: CC BY 4.0
Reference Paper: Main Reference: Thiery, W., et al. et al. Present-day irrigation mitigates heat extremes. J. Geophys. Res. Atm.,122,1403-1422,2017
Reference Paper: Other References:
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
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: ISIMIP daily atmospheric input data is temporally disaggregated to 6-hourly meteorological forcing fields for CLM (algorithm courtesy of Guoyong Leng, PNNL)
Input data
Simulated atmospheric climate data sets used: IPSL-CM5A-LR, HadGEM2-ES, GFDL-ESM2M, MIROC5
Land use data sets used: Historical, gridded land use (HYDE 3.2)
Climate variables: ta, huss, sfcWind, rlds, rsds, pr
Exceptions to Protocol
Exceptions: 1. Atmospheric CO2 concentrations are held constant at 284.7 ppm for picontrol runs (whereas the ISIMIP protocol prescribes 286.38 ppm). Note that this values is only used for the land carbon cycle, i.e. this difference does not affect the atmospheric forcing provided by ISIMIP. CO2 concentrations for the historical simulations follow observations and are consistent with the ISIMIP protocol. 2. Historical simulations are conducted with fixed, present-day land-use (2005soc), this due to the inability of CLM4.5 to account for transient irrigation extend. 3. 365_day calendar instead of proleptic_gregorian 4. For some pixels and time steps negative values were obtained for the variables 'tws', 'qtot', 'qr', 'maxdis', 'mindis', and 'dis'. In those cases, values were forced to be zero. We note however that the occurrence of negative values was very rare, and that values were small whenever they occurred.
Was a spin-up performed?: Yes
Spin-up design: picontrol simulations were branched from an existing picontrol spinup run which was run at 1.9° x 2.5° resolution and interpolated to 0.5° x 0.5° resolution using the CESM interpinic tool. Historical simulations were branched from the respective 0.5° x 0.5° ISIMIP picontrol run, scenario runs were branched from the respective 0.5° x 0.5° ISIMIP historical runs
Natural Vegetation
Natural vegetation partition: tile approach including 24 PFTs for the vegatated land unit.
Management & Adaptation Measures
Management: Irrigation (see Thiery et al., 2017 for a short description of the irrigation module)
Extreme Events & Disturbances
Key challenges: Representation of human water management (only irrigation is included in CLM4.5)
Additional comments: In total >450 variables are stored, additional variables are available upon request (
Key input and Management
Crops: yes The interactive crop management parameterizations from AgroIBIS (March 2003 version) were coupled as a proof-of-concept to the Community Land Model version 3 [CLM3.0, Oleson et al. (2004)] (not published), then coupled to the CLM3.5 (Levis et al. 2009) and later released to the community with CLM4CN (Levis et al. 2012).
Land cover: To allow crops to coexist with natural vegetation in a grid cell and be treated by separate models (i.e., CLM4.5CNcrop versus CLM4.5CNDV), we separate the vegetated land unit into a naturally vegetated land unit and a human managed land unit. Plant functional types in the naturally vegetated land unit share one soil column and compete for water (default CLM setting). Managed crop PFTs in the human managed land unit do not share soil columns and thus permit for differences in land management between crops.
Planting date decision: Corn and temperate cereals must meet the following requirements between April 1st and June 14th for planting in the northern hemisphere (NH): T 10 d > Tp T 10 min d > Tp min GDD 8 ≥ GDD min where T10d is the 10-day running mean of T2m, (the simulated 2-m air temperature at every model time step) and T 10d min is the 10-day running mean of T 2m min (the daily minimum of T2m). Tp and Tp min are crop-specific coldest planting temperatures (Table 20.1), GDD8 is the 20-year running mean growing degree-days (units are degree-days or °days) tracked from April through September (NH) base 8°C with maximum daily increments of 30°days (see Eq. (20.3)), and GDDmin is the minimum growing degree day requirement (Table 20.1). Soy must meet the same requirements but between May 1st and June 14th for planting. If the requirements in Eq. (20.1) are not met by June 14th , then corn, soybean, and temperate cereals are still planted on June 15th as long as GDD8>0. In the southern hemisphere (SH) the NH requirements apply 6 months later.
Planting density: tile approach
Crop cultivars: corn, soybean, winter cereals and temperate cereals
Fertilizer application: CLM adds nitrogen directly to the soil mineral nitrogen pool to meet crop nitrogen demands. CLM’s separate crop land unit ensures that natural vegetation will not access the fertilizer applied to crops. Fertilizer amounts are obtained from the Agro-IBIS model (Kucharik and Brye 2003), but can be modified in CLM’s pft-physiology input dataset. Fertilizer is reported in g N/m2 by plant functional type. Total nitrogen fertilizer amounts are 150 g N/m 2 for maize, 80 g N/m2 for temperate cereals, and 25 g N/m2 for soybean, representative of central U.S. annual fertilizer application amounts. Since CLM’s denitrification rate is high and results in a 50% loss of the unused available nitrogen each day, fertilizer is applied slowly to minimize the loss and maximize plant uptake. Fertilizer application begins during the emergence phase of crop development and continues for 20 days, which helps reduce large losses of nitrogen from leaching and denitrification during the early stage of crop development. The 20-day period is chosen as an optimization to limit fertilizer application to the emergence stage. A fertilizer counter in seconds, f, is set as soon as the onset growth for crops initiates: f = n * 86400 where n is set to 20 fertilizer application days. When the crop enters phase 2 (leaf emergence to the beginning of grain fill) of its growth cycle, fertilizer application begins by initializing fertilizer amount to the total fertilizer divided by the initialized f. Fertilizer is applied and f is decremented each time step until a zero balance on the counter is reached.
Irrigation: The CLM includes the option to irrigate cropland areas that are equipped for irrigation. The application of irrigation responds dynamically to the soil moisture conditions simulated by the CLM. This irrigation algorithm is based loosely on the implementation of Ozdogan et al. (2010). Irrigated and unirrigated crops are placed on separate soil columns, so that irrigation is only applied to the soil beneath irrigated crops. In irrigated croplands, a check is made once per day to determine whether irrigation is required on that day. This check is made in the first time step after 6 AM local time. Irrigation is required if (1) crop leaf area > 0, and (2) βt < 1, i.e., water is limiting for photosynthesis. If irrigation is required, the model computes the deficit between the current soil moisture content and a target soil moisture content; this deficit is the amount of water that will be added through irrigation. The target soil moisture content in each soil layer i (wtarget,i, kg m-2 ) is a weighted average of (1) the minimum soil moisture content that results in no water stress in that layer (wo,i, kg m-2) and (2) the soil moisture content at saturation in that layer (w sat,i, kg m-2): w target ,i = (1 − 0.7) ⋅ w o,i + 0.7 ⋅ wsat ,i w o,i is determined by inverting equation 8.19 in Oleson et al. (2010a) to solve for the value of si (soil wetness) that makes Ψi = Ψo (where Ψi is the soil water matric potential and Ψ o is the soil water potential when stomata are fully open), and then converting this value to units of kg m-2. wsat,i is calculated simply by converting effective porosity (section 7.4) to units of kg m-2. The value 0.7 was determined empirically, in order to give global, annual irrigation amounts that approximately match observed gross irrigation water use around the year 2000 (i.e., total water withdrawals for irrigation: ~ 2500 – 3000 km3 year-1 (Shiklomanov 2000)). The total water deficit (wdeficit, kg m-2) of the column is then determined by: w deficit = ∑ max ( w target ,i − w liq ,i , 0 ) where wliq,i (kg m-2) is the current soil water content of layer i (Chapter 7). The max function means that a surplus in one layer cannot make up for a deficit in another layer. The sum is taken only over soil layers that contain roots. In addition, if the temperature of any soil layer is below freezing, then the sum only includes layers above the top-most frozen soil layer. The amount of water added to this column through irrigation is then equal to wdeficit. This irrigation is applied at a constant rate over the following four hours. Irrigation water is applied directly to the ground surface, bypassing canopy interception (i.e., added to qgrnd,liq). Added irrigation is removed from total liquid runoff (Rliq), simulating removal from nearby rivers.
Crop residue: Post-grain fill C:N ratios are assigned the same as crop residue
Initial soil water: from initialisation (restart file)
Initial soil nitrate and ammonia: from initialisation (restart file)
Initial soil c and om: from initialisation (restart file)
Initial crop residue: from initialisation (restart file)
Key model processes
Leaf area development: According to AgroIBIS, leaves may emerge when the growing degree-days of soil temperature to 0.05 m depth tracked since planting ( GDD Tsoi ) reaches 3 to 5% of GDDmat (Table 20.1). GDD T soi is base 8, 0, and 10°C for corn, soybean, and temperate cereals. Leaf onset, as defined in the CN part of the model, occurs in the first time step of phase 2, at which moment all seed C is transferred to leaf C. Subsequently, the leaf area index generally increases and reaches a maximum value during phase 2.
Light utilization: For a given amount of photosynthetically active radiation absorbed by a leaf φ (W m-2), converted to photosynthetic photon flux density with 4.6 μmol J-1, the light utilized in electron transport is I PSII = 0.5 Φ PSII (4.6 φ ) where Φ PSII is the quantum yield of photosystem II, and the term 0.5 arises because one photon is absorbed by each of the two photosystems to move one electron. Parameter values are Θ PSII = 0.7 and Φ PSII = 0.85. The model uses co-limitation as described by Collatz et al. (1991, 1992).
Crop phenology: In CLM4.5CNcrop we have added the AgroIBIS crop phenology algorithm, consisting of three distinct phases. Phase 1 starts at planting and ends with leaf emergence, phase 2 continues from leaf emergence to the beginning of grain fill, and phase 3 starts from the beginning of grain fill and ends with physiological maturity and harvest.
Root distribution over depth: The root fraction r i in each soil layer depends on the plant functional type (eq. 8.30 Oleson et al., 2013). r a and r b are plant-dependent root distribution parameters adopted from Zeng (2001)
Stresses involved: water and cold stress
Type of heat stress: cold stress
Methods for model calibration and validation
Parameters, number and description: no calibration performed for ISIMIP2b