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Impact model: LPX-Bern

Sector
Peat
Region
global

LPX-Bern (“Land surface Processes and eXchanges” model of the University of Bern) is a Dynamic Global Vegetation Model (DGVM) of intermediate complexity. It simulates terrestrial vegetation dynamics and biogeochemical processes of various land surface covers, including representations of the area under human use and peatland, and is one of the few DGVMs with global peatland representation. It is constrained spatially and temporally by observational records from preindustrial era to present-day. LPX-Bern has fully coupled water, carbon, and nitrogen cycles and has the unique capacity to explicitly simulate multiple greenhouse gases and carbon isotopes.

Information for the model LPX-Bern 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 Sun: qing.sun@unibe.ch, 0000-0003-0767-4721, University of Bern (Switzerland)
Output Data
Experiments: (*) ssp585_2015soc-from-histsoc_2015co2, picontrol_2015soc-from-histsoc_default, ssp126_2015soc-from-histsoc_default, picontrol_histsoc_default, ssp370_2015soc-from-histsoc_default, ssp585_2015soc-from-histsoc_default, picontrol_1850soc_default, historical_histsoc_default
Climate Drivers: GFDL-ESM4
Date: 2024-09-03
Basic information
Model Version: v1.4.1
Model Output License: CC0
Model Homepage: https://lpx-bern.github.io/info/index.html
Model License: The code is not publicly licensed and is managed by the University of Bern (Climate and Environmental Physics). Access is restricted to internal collaborators and institutional use.
Reference Paper: Main Reference: Lienert S, Joos F et al. A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions. Biogeosciences,15,2909-2930,2018
Reference Paper: Other References:
Resolution
Horizontal resolution: 0.5°x0.5°
Vertically resolved: No
Temporal resolution of input data: climate variables: daily
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
Simulated atmospheric climate data sets: GFDL-ESM4
Which Direct Humam Forcings (DHF) did you use in the model simualtions?: Nitrogen deposition (ISIMIP3)
Emissions data sets: Atmospheric composition (ISIMIP3b)
Other human influences data sets: N-Fertilizer (ISIMIP3b)
Additional input data sets: For soil type, LPX-Bern used its default input: Harmonized World Soil Database, 2011 instead the dataset hwsd_soil_data_all_land.
Climate variables: tas, rsds, pr
Spin-up
Was a spin-up performed?: Yes
Spin-up design: 2500 years of spin-up following the protocol.
Natural Vegetation
Natural vegetation partition: The distribution of different plant functional types (PFT) is determined and regulated by bioclimatics. All the PFTs in the same grid cell compete for light, water, and nutrients (Strassmann et. al. 2018). Strassmann, K. M., Joos, F., & Fischer, G. (2008). Simulating effects of land use changes on carbon fluxes: past contributions to atmospheric CO2 increases and future commitments due to losses of terrestrial sink capacity. Tellus Series B-Chemical and Physical Meteorology, 60(4), 583-603. doi:10.1111/j.1600-0889.2008.00340.x
Natural vegetation dynamics: The distribution of different plant functional types (PFT) is determined and regulated by bioclimatics. All the PFTs in the same grid cell compete for light, water, and nutrients (Strassmann et. al. 2018). Strassmann, K. M., Joos, F., & Fischer, G. (2008). Simulating effects of land use changes on carbon fluxes: past contributions to atmospheric CO2 increases and future commitments due to losses of terrestrial sink capacity. Tellus Series B-Chemical and Physical Meteorology, 60(4), 583-603. doi:10.1111/j.1600-0889.2008.00340.x
Natural vegetation cover dataset: It is prescribed according to the protocol.
Management & Adaptation Measures
Management: Land use and land use change, fertilisation in croplands and pastures are prescribed according to the protocol.
MODEL OUTPUT SPECIFICATIONS
How to calculate global annual total outputs: Grid level variables: multiply 'pft-total' then sum over all the latitutudes and longitude. Land over level variables: multiply 'pft--total' then sum over all the latitutudes and longitude. PFT level variables: multiply 'pft--' then sum over all the latitutudes and longitude.
Person responsible for model simulations in this simulation round
Qing Sun: qing.sun@unibe.ch, 0000-0003-0767-4721, University of Bern (Switzerland)
Output Data
Experiments: (*) counterclim_histsoc_default, obsclim_histsoc_default, obsclim_histsoc_1901co2
Climate Drivers: GSWP3-W5E5
Date: 2025-08-13
Basic information
Model Version: 1.4.1
Model Output License: CC0
Model Homepage: https://lpx-bern.github.io/info/about
Model License: The code is not publicly licensed and is managed by the University of Bern (Climate and Environmental Physics). Access is restricted to internal collaborators and institutional use.
Reference Paper: Main Reference: Lienert S, Joos F et al. A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions. Biogeosciences,15,2909-2930,2018
Reference Paper: Other References:
Resolution
Horizontal resolution: 0.5°x0.5°
Vertically resolved: No
Temporal resolution of input data: climate variables: daily
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
Observed atmospheric climate data sets: GSWP3-W5E5 (ISIMIP3a)
Which Direct Humam Forcings (DHF) did you use in the model simualtions?: Nitrogen deposition (ISIMIP3)
Emissions data sets: Atmospheric composition (ISIMIP3a)
Land use data sets: Historical, gridded land use
Other human influences data sets: N-Fertilizer (ISIMIP3a)
Additional input data sets: For soil type, LPX-Bern used its default input: Harmonized World Soil Database, 2011 instead the dataset hwsd_soil_data_all_land.
Climate variables: tas, rsds, pr
Spin-up
Was a spin-up performed?: Yes
Spin-up design: 2500 years of spin-up following the protocol.
Natural Vegetation
Natural vegetation partition: The distribution of different plant functional types (PFT) is determined and regulated by bioclimatics. All the PFTs in the same grid cell compete for light, water, and nutrients (Strassmann et. al. 2018). Strassmann, K. M., Joos, F., & Fischer, G. (2008). Simulating effects of land use changes on carbon fluxes: past contributions to atmospheric CO2 increases and future commitments due to losses of terrestrial sink capacity. Tellus Series B-Chemical and Physical Meteorology, 60(4), 583-603. doi:10.1111/j.1600-0889.2008.00340.x
Natural vegetation dynamics: The distribution of different plant functional types (PFT) is determined and regulated by bioclimatics. All the PFTs in the same grid cell compete for light, water, and nutrients (Strassmann et. al. 2018). Strassmann, K. M., Joos, F., & Fischer, G. (2008). Simulating effects of land use changes on carbon fluxes: past contributions to atmospheric CO2 increases and future commitments due to losses of terrestrial sink capacity. Tellus Series B-Chemical and Physical Meteorology, 60(4), 583-603. doi:10.1111/j.1600-0889.2008.00340.x
Natural vegetation cover dataset: It is prescribed according to the protocol.
Management & Adaptation Measures
Management: Land use and land use change, fertilisation in croplands and pastures are prescribed according to the protocol.
MODEL OUTPUT SPECIFICATIONS
How to calculate global annual total outputs: Grid level variables: multiply 'pft-total' then sum over all the latitutudes and longitude. Land over level variables: multiply 'pft--total' then sum over all the latitutudes and longitude. PFT level variables: multiply 'pft--' then sum over all the latitutudes and longitude.




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