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SECURES-Met: A European meteorological data set suitable for electricity modelling applications
The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is high...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484998/ https://www.ncbi.nlm.nih.gov/pubmed/37679367 http://dx.doi.org/10.1038/s41597-023-02494-4 |
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author | Formayer, Herbert Nadeem, Imran Leidinger, David Maier, Philipp Schöniger, Franziska Suna, Demet Resch, Gustav Totschnig, Gerhard Lehner, Fabian |
author_facet | Formayer, Herbert Nadeem, Imran Leidinger, David Maier, Philipp Schöniger, Franziska Suna, Demet Resch, Gustav Totschnig, Gerhard Lehner, Fabian |
author_sort | Formayer, Herbert |
collection | PubMed |
description | The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21(st) century. Thus, we have developed the aggregated European wide climate data set SECURES-Met that has a temporal resolution of one hour, covers the whole EU area and other selected European countries, has a reasonable size but considers the high spatial variability. |
format | Online Article Text |
id | pubmed-10484998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104849982023-09-09 SECURES-Met: A European meteorological data set suitable for electricity modelling applications Formayer, Herbert Nadeem, Imran Leidinger, David Maier, Philipp Schöniger, Franziska Suna, Demet Resch, Gustav Totschnig, Gerhard Lehner, Fabian Sci Data Data Descriptor The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21(st) century. Thus, we have developed the aggregated European wide climate data set SECURES-Met that has a temporal resolution of one hour, covers the whole EU area and other selected European countries, has a reasonable size but considers the high spatial variability. Nature Publishing Group UK 2023-09-07 /pmc/articles/PMC10484998/ /pubmed/37679367 http://dx.doi.org/10.1038/s41597-023-02494-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Formayer, Herbert Nadeem, Imran Leidinger, David Maier, Philipp Schöniger, Franziska Suna, Demet Resch, Gustav Totschnig, Gerhard Lehner, Fabian SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title | SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title_full | SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title_fullStr | SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title_full_unstemmed | SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title_short | SECURES-Met: A European meteorological data set suitable for electricity modelling applications |
title_sort | secures-met: a european meteorological data set suitable for electricity modelling applications |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484998/ https://www.ncbi.nlm.nih.gov/pubmed/37679367 http://dx.doi.org/10.1038/s41597-023-02494-4 |
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