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3 results for “DGVM”
Simulations from the SEIB-DGVM dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the SEIB-DGVM dynamic global vegetation model. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for each individual turnover-causing process in the model were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Aerosol-light interactions reduce the carbon budget imbalance - DGVM output
<p>DGVM (JULES and ORCHIDEE_DF) output associated with the publication 'Aerosol-light interactions reduce the carbon budget imbalance' (O'Sullivan et al., 2021 - Environmental Research Letters).</p> <p>Files contain monthly data over the period 1901-2017. There are 7 simulations for each model, with varying surface solar radiation in each case. Atmospheric CO<sub>2</sub> and all climate variables (except for incoming short-wave radiation) vary throughout all simulations.</p> <p>Historical: total and diffuse shortwave radiation depend on the solar zenith angle, temporally varying cloud cover and aerosol optical depth of the whole atmospheric column.</p> <p>FixedAero: Time-invariant (1901-1920 cycle) tropospheric aerosol and no stratospheric aerosol influence on total and diffuse shortwave radiation</p> <p>FixedTropAero: Time-invariant (1901-1920 cycle) tropospheric aerosol influence on total and diffuse shortwave radiation</p> <p>FixedStratAero: no stratospheric aerosol influence on total and diffuse shortwave radiation</p> <p>FixedAero_DF: Time-invariant (1901-1920 cycle) tropospheric aerosol and no stratospheric aerosol influence on diffuse shortwave radiation</p> <p>FixedTropAero_DF: Time-invariant (1901-1920 cycle) tropospheric aerosol influence on diffuse shortwave radiation</p> <p>FixedStratAero_DF: no stratospheric aerosol influence on diffuse shortwave radiation</p> <p> </p>
TRENDYv10 DGVM output for: Process-oriented analysis of dominant sources of uncertainty in the land carbon sink
<p><strong>New datasets saved as NCDF files.</strong></p> <p><strong>Data</strong></p> <p>Post-processed TRENDYv10 DGVM data covering the period 1901-2020. Each file contains monthly/annual mean values for 19 models: CABLE-POP, CLASSIC, CLASSIC-N, CLM5.0, DLEM, IBIS, ISAM, ISBA-CTRIP, JSBACH, JULES-ES-1.1, LPJ-GUESS, LPJ, LPX-Bern, OCN, ORCHIDEE, ORCHIDEEv3, SDGVM, VISIT, YIBs. See https://blogs.exeter.ac.uk/trendy/</p> <p>List of variables can be found at https://blogs.exeter.ac.uk/trendy/documents/ . File name: 'trendy_listofvariables_GCP2021'.</p> <p>Data for three experiments (S1 - S3) is provided. For experiment details, see 'GlobalCarbonBudget-Protocol-2021-web' at https://blogs.exeter.ac.uk/trendy/documents/</p> <p><strong>Code</strong></p> <p>All data processing code is also provided. Files starting "raw#..." are run in order 1-4. Then the figure/manuscript files are executed, starting with "proc1.." - "proc3..". The remaining Figure scripts (Figures 1-5 and S1-S8) and "temp_changes.R" can be run in any order.</p> <p>Any enquiries, contact Mike O'Sullivan at m.osullivan@exeter.ac.uk</p>
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OpenNeuro
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