Hourly historical and near-future weather and climate variables for energy system modelling

Bloomfield, H. C. ORCID: https://orcid.org/0000-0002-5616-1503, Brayshaw, D. J. ORCID: https://orcid.org/0000-0002-3927-4362, Deakin, M. and Greenwood, D. (2022) Hourly historical and near-future weather and climate variables for energy system modelling. Earth System Science Data, 14 (6). pp. 2749-2766. ISSN 1866-3516 doi: 10.5194/essd-14-2749-2022

Abstract/Summary

Energy systems are becoming increasingly exposed to the impacts of weather and climate due to the uptake of renew- able generation and the electrification of the heat and transport sectors. The need for high-quality meteorological data to manage present and near-future risks is urgent. This paper provides a comprehensive set of multi-decadal, time series of hourly meteorological variables and weather-dependent power systems components for use in the energy systems modelling community. Despite the growing interest in the impacts of climate variability and climate change on energy systems over the last decade, it remains rare for multi-decadal simulations of meteorological data to be used within detailed simulations. This is partly due to computational constraints, but also due to technical barriers limiting the use of meteorological data by non-specialists. This paper presents a new European level dataset which can be used to investigate the impacts of climate variability and climate change on multiple aspects of near-future energy systems. The datasets correspond to a suite of well-documented, easy-to-use, self-consistent hourly- nationally-aggregated and sub-national time series for 2m temperature, 10m wind speed, 100m wind speed, surface solar irradiance, wind power capacity factor, solar power factor and degree days spanning over 30 European countries. This dataset is available for the historical period (1950-2020), and is accessible from https://researchdata.reading.ac.uk/id/eprint/321with reserved DOI: http://dx.doi.org/10.17864/1947.000321 (Bloomfield and Brayshaw, 2021b). As well as this a companion dataset is created where the ERA5 reanalysis is adjusted to represent the impacts of near-term climate change (centred on the year 2035) based on five high resolution climate model simulations. This data is available for a 70 year period for central and Northern Europe. The data is accessible from https://researchdata.reading.ac.uk/id/eprint/331 with reserved DOI: http://dx.doi.org/10.17864/1947.000331 (Bloomfield and Brayshaw, 2021a). To the authors’ knowledge, this is the first time a comprehensive set of high quality hourly time series relating to future climate projections has been published, which is specifically designed to support the energy sector. The purpose of this paper is to detail the methods required for processing the climate model data and illustrate the importance of accounting for climate variability and climate change within energy system modelling from sub-national to European scale. While this study is there- fore not intended to be an exhaustive analysis of climate impacts, it is hoped that publishing this data will promote greater use of climate data within energy system modelling.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/105096
Item Type	Article
Refereed	Yes
Divisions	Interdisciplinary centres and themes > Energy Research Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Copernicus Publications
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