Impact model: LPJ-GUESS

The model is the crop-enabled version of LPJ-GUESS, described in Lindeskog et al. (2013). It is loosely based on LPJmL as described in Bondeau et al. (2007), but differs in several important aspects, including not being calibrated to observed country-level yields, a new phenology scheme, and a dynamic calculation of the potential heat units (PHU) required for a crop to achieve maturity. Sowing dates are calculated dynamically following Waha et al. (2012). The PHU sum needed for full development of a crop in a particular grid cell is calculated using a 10-year running mean of heat unit sums accumulated from the sowing date to the end of a sampling period (ranging from 190 to 245 days) derived from default sowing and harvest limit dates (Lindeskog et al., 2013). Crops are harvested upon full development. This dynamic variation of PHU to climate effectively assumes a perfect adaptation of crop cultivar to the prevailing climate. N limitation is not explicitly accounted for in this version of the model. Bondeau, A. et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob. Change Biol. 13, 679-706, doi:10.1111/j.1365-2486.2006.01305.x (2007). Lindeskog, M. et al. Implications of accounting for land use in simulations of carbon cycling in Africa. Earth System Dynamics 4, 385-407, doi:10.5194/esd-4-385-2013 (2013). Waha, K., et al. Climate-driven simulation of global crop sowing dates. Global Ecology and Biogeography 21, 247-259 (2012).

Sector
Agriculture
Region
global
Contact Person

Information for the model LPJ-GUESS 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
Model Version: Version 4
Model output license: CC BY 4.0
Reference Paper: Main Reference: Olin, S. Lindeskog, M. Pugh, T. A.M. Schurgers, G. Wårlind, D. Mishurov, M. Zaehle, S. Stocker, B. D. Smith, B. Arneth, A. et al. Soil carbon management in large-scale Earth system modelling: Implications for crop yields and nitrogen leaching. Earth System Dynamics,6,475-768,2015
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
Input data sets used
Observed Atmospheric Climate Data Sets Used: GSWP3, WATCH (WFD), WATCH+WFDEI
Climate Variables: tas, rsds, pr
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: 30 year spinup, using climate and [CO2] from the first simulation year.
Management & Adaptation Measures
Management: With and without adapting growing periods.
Key input and Management
Crops: whe(w,s), rice, mai, mill, sub, cass, fpea, soy, sunfl, rapes, gnut, suc
Land Cover: potential suitable cropland area according to climatic conditions, current harvested areas (Hurtt et al. 2011/Portmann et al., 2010)
Planting Date Decision: Simulate planting dates according to climatic conditions (Waha et al. 2012) or planting dates fixed at present based on S.
Planting Density: planting density=1
Crop Cultivars: Simulate crop Growing Degree Days (GDDs) requirement according to estimated annual GDDs from daily temperature. Vernalization requirements computed based on past climate experience (whe, sunfl, rapes); BT (mai); static (others). No differentiation between varieties other than PHU, except for wheat, which automatically selects between spring and winter varieties according to prevailing climate.
Irrigation: No restriction on actual water availability, irrigated water applied whenever plants would otherwise enter water stress due to soil water limitations.
Crop Residue: N/A, as does not influence yields in this version of LPJ-GUESS.
Initial Soil Water: 30 year spin up
Initial Soil C And Om: Not initialised or spun-up, as they do not influence yields in this version of LPJ-GUESS.
Key model processes
Leaf Area Development: Dynamic simulation based on development and growth processes
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, heat unit index
Root Distribution Over Depth: linear
Stresses Involved: Water stress
Type Of Water Stress: ratio of supply to demand of water
Water Dynamics: soil water capacity approach with 2 soil layers
Evapo-Transpiration: Priestley -Taylor
Co2 Effects: Leaf-level photosynthesis-rubisco
Basic information
Reference Paper: Main Reference: Lindeskog, M. et al. et al. Implications of accounting for land use in simulations of carbon cycling in AfricaEarth System Dynamics,4,385-407,2013
Person Responsible For Model Simulations In This Simulation Round: Thomas Pugh
Output Data
Experiments: historical, rcp26, rcp45, rcp60, rcp85
Climate Drivers: GCM atmospheric climate data (Fast Track)
Date: 2013-12-13
Resolution
Spatial Aggregation: regular grid
Spatial Resolution: 0.5°x0.5°
Temporal Resolution Of Input Data: Climate Variables: annual
Temporal Resolution Of Input Data: Co2: annual
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Simulated Atmospheric Climate Data Sets Used: GCM atmospheric climate data (Fast Track)
Emissions Data Sets Used: CO2 concentration
Climate Variables: tas, rsds, pr
Spin-up
Was A Spin-Up Performed?: Yes
Spin-Up Design: 500 year spinup using 1850 atmospheric CO2 mixing ratio and the first 30 years of detrended climate as input.
Management & Adaptation Measures
Management: Sowing and harvest dates adapting to changes in climate. Number of potential heat units to maturity adapting to changes in climate such that growing season length is maintained with rising temperature.
Key input and Management
Crops: whe(w,s), rice, mai, mill, sub, cass, fpea, soy, sunfl, rapes, gnut, suc, mgr
Land Cover: All land mass
Planting Date Decision: Climate dependent
Planting Density: NA
Crop Cultivars: Adaptive to local climate
Fertilizer Application: NA
Irrigation: Yes, optimal
Crop Residue: 90% removed - but no feedback to yields.
Initial Soil Water: No
Initial Soil Nitrate And Ammonia: NA
Initial Soil C And Om: No
Initial Crop Residue: No
Key model processes
Leaf Area Development: Based on heat sum requirement and allocated carbon.
Light Interception: Simple approach
Yield Formation: Based on heat sum requirement
Crop Phenology: Based on heat sum requirement
Root Distribution Over Depth: Fixed
Stresses Involved: Water
Type Of Water Stress: Ratio of supply to demand of water
Water Dynamics: soil water capacity with 2 soil layers
Evapo-Transpiration: Priestley -Taylor
Soil Cn Modeling: NA
Co2 Effects: Leaf-level photosynthesis-rubisco