Forestry - REMIND-MAgPIE: Difference between revisions
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m (Mathijs Harmsen moved page Forestry - REMIND to Forestry - REMIND-MAgPIE without leaving a redirect: Text replacement - "REMIND" to "REMIND-MAgPIE") |
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If run in stand-alone mode, REMIND relies on results from MAgPIE to account for CO<sub>2</sub> emissions from land use, land use change and forestry. Reduced emissions from deforestation and forest degradation (REDD) as a mitigation option is represented via a climate policy dependent marginal abatement cost curve | If run in stand-alone mode, REMIND-MAgPIE relies on results from MAgPIE to account for CO<sub>2</sub> emissions from land use, land use change and forestry. Reduced emissions from deforestation and forest degradation (REDD) as a mitigation option is represented via a climate policy dependent marginal abatement cost curve | ||
The coupled REMIND-MAgPIE system allows for a detailed analysis of forestry-based mitigation options in the context of an integrated climate change mitigation scenario. | The coupled REMIND-MAgPIE-MAgPIE system allows for a detailed analysis of forestry-based mitigation options in the context of an integrated climate change mitigation scenario. | ||
Revision as of 14:34, 21 November 2021
| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | Potsdam Institut für Klimafolgenforschung (PIK), Germany, https://www.pik-potsdam.de/research/sustainable-solutions/models/remind. |
| Solution concept | |
| Solution method | |
| Anticipation | |
If run in stand-alone mode, REMIND-MAgPIE relies on results from MAgPIE to account for CO2 emissions from land use, land use change and forestry. Reduced emissions from deforestation and forest degradation (REDD) as a mitigation option is represented via a climate policy dependent marginal abatement cost curve
The coupled REMIND-MAgPIE-MAgPIE system allows for a detailed analysis of forestry-based mitigation options in the context of an integrated climate change mitigation scenario.