Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 17
Articles | Volume 16, issue 17
https://doi.org/10.5194/gmd-16-4977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-4977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 17
Model description paper
 | 
31 Aug 2023
Model description paper |  | 31 Aug 2023

Bidirectional coupling of the long-term integrated assessment model REgional Model of INvestments and Development (REMIND) v3.0.0 with the hourly power sector model Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) v1.0.2

Chen Chris Gong, Falko Ueckerdt, Robert Pietzcker, Adrian Odenweller, Wolf-Peter Schill, Martin Kittel, and Gunnar Luderer

Supplement

https://doi.org/10.5194/gmd-16-4977-2023-supplement

Model code and software

REMIND - REgional Model of INvestments and Development (3.0.0) Gunnar Luderer, Nico Bauer, Lavinia Baumstark, Christoph Bertram, Marian Leimbach, Robert Pietzcker, Jessica Strefler, Tino Aboumahboub, Gabriel Abrahão, Cornelia Auer, Falk Benke, Stephen Bi, Jan Dietrich, Alois Dirnaichner, Anastasis Giannousakis, Chen Chris Gong, Markus Haller, Robin Hasse, Jerome Hilaire, and Pascal Weigmann https://doi.org/10.5281/zenodo.6794920

REMIND - DIETER coupling (v1.1) Gunnar Luderer, Nico Bauer, Chen Chris Gong, Adrian Odenweller, Lavinia Baumstark, Christoph Bertram, Marian Leimbach, Robert Pietzcker, Jessica Strefler, Tino Aboumahboub, Gabriel Abrahão, Cornelia Auer, Falk Benke, Stephen Bi, Jan Dietrich, Alois Dirnaichner, Anastasis Giannousakis, Markus Haller, Robin Hasse, and Marianna Rottoli https://doi.org/10.5281/zenodo.7053246

REMIND-DIETER - code, reportings, scripts (v1.0) Chen Chris Gong https://doi.org/10.5281/zenodo.7072625

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Short summary
To mitigate climate change, the global economy must drastically reduce its greenhouse gas emissions, for which the power sector plays a key role. Until now, long-term models which simulate this transformation cannot always accurately depict the power sector due to a lack of resolution. Our work bridges this gap by linking a long-term model to an hourly model. The result is an almost full harmonization of the models in generating a power sector mix until 2100 with hourly resolution.
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