Impact model: LPJmL

LPJmL is one of the 14 models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a agricultural sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Agricultural Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.006

Sector
Agriculture
Region
global
Contact Person

Information for the model LPJmL 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.

Basic information
Reference Paper: Main Reference: BONDEAU A, SMITH P, ZAEHLE S, SCHAPHOFF S, LUCHT W, CRAMER W, GERTEN D, LOTZE-CAMPEN H, MÜLLER C, REICHSTEIN M, SMITH B et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology,13,679-706,2007
Reference Paper: Other References:
Output Data
Experiments: I, II, IIa, III
Climate Drivers: IPSL-CM5A-LR, HadGEM2-ES, GFDL-ESM2M, MIROC5
Date: 2017-07-07
Resolution
Spatial Aggregation: regular grid
Spatial 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: all crops everywhere
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Climate Variables: tas, rlds, rsds, pr
Additional Information About Input Variables: lwnet derived from tas and rlds
Additional Input Data Sets: GGCMI harmonized planting and maturity datasets
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: 200 year spinup for soil temperatures and soil moisture, recycling the first 30 years of the time series
Management & Adaptation Measures
Management: Planting dates are based on the data provided within the global gridded crop model inter-comparison project Elliott et al (2015); total heat units to reach maturity remain constant over time but vary spatially according to reported growing seasons for the recent historic period.
Key input and Management
Crops: whe(w,s), rice, mai, mill, sub, cass, fpea, soy, sunfl, rapes, gnut, suc
Land Cover: all land mass
Planting Date Decision: Planting dates are based on the data provided within the global gridded crop model inter-comparison project Elliott et al (2015)
Planting Density: planting density=1
Crop Cultivars: total heat units to reach maturity remain constant over time but vary spatially according to reported growing seasons for the recent historic period
Irrigation: no restriction on actual water availability, irrigated water applied when water stress
Crop Residue: Scenario
Initial Soil Water: 200 year spin up
Key model processes
Leaf Area Development: prescribed shape of LAI curve as function of phenology, modified by water stress & low productivity
Light Interception: Simple approach
Light Utilization: Detailed (explanatory) Gross photosynthesis – respiration, (for more details, see e.g. Adam et al. (2011))
Yield Formation: harvest index modified by water stress
Crop Phenology: temperature, vernalization
Root Distribution Over Depth: exponential
Stresses Involved: Water stress
Type Of Water Stress: ratio of supply to demand of water
Water Dynamics: soil water capacity with 5 soil layers
Evapo-Transpiration: Priestley -Taylor
Co2 Effects: Leaf-level photosynthesis-rubisco or on QE and Amax
Methods for model calibration and validation
Parameters, Number And Description: 3: maximum LAI under unstressed conditions, harvest index, factor for scaling leaf-level photosynthesis to stand level
Calibrated Values: Specific for each crop and country
Output Variable And Dataset For Calibration Validation: Yield (FAO yield statistics)
Spatial Scale Of Calibration/Validation: National
Temporal Scale Of Calibration/Validation: Average for 1998-2003
Criteria For Evaluation (Validation): Wilmott
Basic information
Reference Paper: Main Reference: BONDEAU A, SMITH P, ZAEHLE S, SCHAPHOFF S, LUCHT W, CRAMER W, GERTEN D, LOTZE-CAMPEN H, MÜLLER C, REICHSTEIN M, SMITH B et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology,13,679-706,2007
Reference Paper: Other References:
Output Data
Experiments: historical
Climate Drivers: GSWP3, PGMFD v.2 (Princeton), WATCH (WFD), WATCH+WFDEI
Date: 2016-05-04
Resolution
Spatial Aggregation: regular grid
Spatial 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: all crops everywhere
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Observed Atmospheric Climate Data Sets Used: GSWP3, PGMFD v.2 (Princeton), WATCH (WFD), WATCH+WFDEI
Climate Variables: co2, tas, rlds, lwnet, pr
Additional Information About Input Variables: lwnet derived from tas and rlds
Additional Input Data Sets: GGCMI harmonized planting and maturity datasets (for a subset of simulations)
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: 200 year spinup for soil temperatures and soil moisture, recycling the first 30 years of the time series
Management & Adaptation Measures
Management: crop sowing dates computed internally but fixed after the first simulation year in DEFAULT crop simulations, fixed at prescribed dates for HARMNON crop simulations
Key input and Management
Crops: whe(w,s), rice, mai, mill, sub, cass, fpea, soy, sunfl, rapes, gnut, suc
Land Cover: all land mass
Planting Date Decision: Simulate planting dates according to climatic conditions (Waha et al. 2012) during spinup and fixed planting dates to those dates after spinup in DEFAULT sims, fixed planting dates in HARMNON sims
Planting Density: planting density=1
Crop Cultivars: Simulate crop Growing Degree Days (GDDs) requirement according to estimated annual GDDs from daily temperature and vernalization requirements computed based on past climate experience (whe, sunfl, rapes); basetemperature computed based on past climate (mai); static (others)
Irrigation: no restriction on actual water availability, irrigated water applied when water stress
Crop Residue: Scenario
Initial Soil Water: 200 year spin up
Key model processes
Leaf Area Development: prescribed shape of LAI curve as function of phenology, modified by water stress & low productivity
Light Interception: Simple approach
Light Utilization: Detailed (explanatory) Gross photosynthesis – respiration, (for more details, see e.g. Adam et al. (2011))
Yield Formation: harvest index modified by water stress
Crop Phenology: temperature, vernalization
Root Distribution Over Depth: exponential
Stresses Involved: Water stress
Type Of Water Stress: ratio of supply to demand of water
Water Dynamics: soil water capacity with 5 soil layers
Evapo-Transpiration: Priestley -Taylor
Co2 Effects: Leaf-level photosynthesis-rubisco or on QE and Amax
Methods for model calibration and validation
Parameters, Number And Description: 3: maximum LAI under unstressed conditions, harvest index, factor for scaling leaf-level photosynthesis to stand level
Calibrated Values: Specific for each crop and country
Output Variable And Dataset For Calibration Validation: Yield (FAO yield statistics)
Spatial Scale Of Calibration/Validation: National
Temporal Scale Of Calibration/Validation: Average for 1998-2003
Criteria For Evaluation (Validation): Wilmott