Preprints
https://doi.org/10.5194/essd-2021-436
https://doi.org/10.5194/essd-2021-436
 
28 Jan 2022
28 Jan 2022
Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

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

Hannah C. Bloomfield1,2, David J. Brayshaw1,3, Matthew Deakin4, and David Greenwood4 Hannah C. Bloomfield et al.
  • 1Department of Meteorology, University of Reading, UK
  • 2School of Geographical Sciences, University of Bristol, UK
  • 3National Centre for Atmospheric Science, Reading, UK
  • 4Newcastle University, Newcastle-upon-Tyne, UK

Abstract. Energy systems are becoming increasingly exposed to the impacts of weather and climate due to the uptake of renewable 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 2 m temperature, 10 m wind speed, 100 m 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/321 with 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 therefore 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.

Hannah C. Bloomfield et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-436', Anonymous Referee #1, 18 Mar 2022
    • AC1: 'Reply on RC1', Hannah Bloomfield, 11 Apr 2022
  • RC2: 'Comment on essd-2021-436', Anonymous Referee #2, 20 Mar 2022
    • AC2: 'Reply on RC2', Hannah Bloomfield, 11 Apr 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-436', Anonymous Referee #1, 18 Mar 2022
    • AC1: 'Reply on RC1', Hannah Bloomfield, 11 Apr 2022
  • RC2: 'Comment on essd-2021-436', Anonymous Referee #2, 20 Mar 2022
    • AC2: 'Reply on RC2', Hannah Bloomfield, 11 Apr 2022

Hannah C. Bloomfield et al.

Data sets

ERA5 derived time series of European aggregated surface weather variables, wind power, and solar power capacity factors: hourly data from 1950-2020. Bloomfield, H. C. and Brayshaw., D. J. https://researchdata.reading.ac.uk/id/eprint/321

Future climate projections of surface weather variables, wind power, and solar power capacity factors across North-West Europe Bloomfield., H. C., Brayshaw., D. J. https://researchdata.reading.ac.uk/id/eprint/331

Hannah C. Bloomfield et al.

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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 including the impacts of near-term climate change.