Articles | Volume 14, issue 6
https://doi.org/10.5194/essd-14-2749-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2749-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hourly historical and near-future weather and climate variables for energy system modelling
Hannah C. Bloomfield
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
School of Geographical Sciences, University of Bristol, Bristol, UK
David J. Brayshaw
Department of Meteorology, University of Reading, Reading, UK
National Centre for Atmospheric Science, Reading, UK
Matthew Deakin
School of Engineering, Newcastle University, Newcastle-upon-Tyne, UK
David Greenwood
School of Engineering, Newcastle University, Newcastle-upon-Tyne, UK
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Short summary
There is a global increase in renewable generation to meet carbon targets and reduce the impacts of climate change. Renewable generation and electricity demand depend on the weather. This means there is a need for high-quality weather data for energy system modelling. We present a new European-level, 70-year dataset which has been specifically designed to support the energy sector. We provide hourly, sub-national climate outputs and include the impacts of near-term climate change.
There is a global increase in renewable generation to meet carbon targets and reduce the impacts...
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