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ToolsBartók, Blanka, Tobin, Isabelle, Vautard, Robert, Vrac, Mathieu, Jin, Xia, Levavasseur, Guillaume, Denvil, Sébastien, Dubus, Laurent, Parey, Sylvie, Michelangeli, Paul-Antoine, Troccoli, Alberto and Saint-Drenan, Yves-Marie (2019) A climate projection dataset tailored for the European energy sector. Climate Services, 16. ISSN 2405-8807
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Abstract
Climate information is necessary for the energy sector. However, the use of climate projections has remained limited so far for a number of reasons such us the lack of consistency among climate projections, the inadequate temporal and spatial resolution, the climate model biases, the lack of guidance for users, and the size of data sets. In this work, we develop and assess a consistent ensemble of high time and space resolution climate projections that address these problems. First, a methodology for sub-ensemble selection is developed and proposed. Our ensemble dataset includes eleven 12 km-resolution EURO-CORDEX simulations of temperature, precipitation, wind speed and surface solar radiation on 3-hourly and daily time scales. These variables are bias-corrected for a more effective use into impact studies. The assessment of bias-corrected model simulations against observational data indicates reduced biases and increased coherence in projected changes among models compared to the raw climate projections. We provide a well-documented dataset for energy practitioners and decision-makers to facilitate the access and use of energy-relevant high-quality climate information in operation and planning. The new dataset is freely available via the Earth System Grid Federation (ESGF) platform.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | sdg 13 - climate action ,/dk/atira/pure/sustainabledevelopmentgoals/climate_action |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 04 Dec 2019 02:14 |
| Last Modified: | 22 Oct 2022 05:33 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/73262 |
| DOI: | 10.1016/j.cliser.2019.100138 |
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