Cargando…
ClimateEU, scale-free climate normals, historical time series, and future projections for Europe
Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decada...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719169/ https://www.ncbi.nlm.nih.gov/pubmed/33277489 http://dx.doi.org/10.1038/s41597-020-00763-0 |
_version_ | 1783619623752564736 |
---|---|
author | Marchi, Maurizio Castellanos-Acuña, Dante Hamann, Andreas Wang, Tongli Ray, Duncan Menzel, Annette |
author_facet | Marchi, Maurizio Castellanos-Acuña, Dante Hamann, Andreas Wang, Tongli Ray, Duncan Menzel, Annette |
author_sort | Marchi, Maurizio |
collection | PubMed |
description | Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21(st) century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database. |
format | Online Article Text |
id | pubmed-7719169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77191692020-12-11 ClimateEU, scale-free climate normals, historical time series, and future projections for Europe Marchi, Maurizio Castellanos-Acuña, Dante Hamann, Andreas Wang, Tongli Ray, Duncan Menzel, Annette Sci Data Data Descriptor Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21(st) century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database. Nature Publishing Group UK 2020-12-04 /pmc/articles/PMC7719169/ /pubmed/33277489 http://dx.doi.org/10.1038/s41597-020-00763-0 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Marchi, Maurizio Castellanos-Acuña, Dante Hamann, Andreas Wang, Tongli Ray, Duncan Menzel, Annette ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title | ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title_full | ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title_fullStr | ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title_full_unstemmed | ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title_short | ClimateEU, scale-free climate normals, historical time series, and future projections for Europe |
title_sort | climateeu, scale-free climate normals, historical time series, and future projections for europe |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719169/ https://www.ncbi.nlm.nih.gov/pubmed/33277489 http://dx.doi.org/10.1038/s41597-020-00763-0 |
work_keys_str_mv | AT marchimaurizio climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope AT castellanosacunadante climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope AT hamannandreas climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope AT wangtongli climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope AT rayduncan climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope AT menzelannette climateeuscalefreeclimatenormalshistoricaltimeseriesandfutureprojectionsforeurope |