BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098
Abstract Ongoing ecological research is concerned with analysing climate-induced changes in species distribution. For this purpose, the projection must have high-quality bioclimatic variables from historical and future climatic periods for the projection. To date, there are many global bioclimatic v...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04507-w |
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| author | Anne Reichmuth Oldrich Rakovec Friedrich Boeing Sebastian Müller Luis Samaniego Andreas Marx Hanna Komischke Andreas Schmidt Daniel Doktor |
| author_facet | Anne Reichmuth Oldrich Rakovec Friedrich Boeing Sebastian Müller Luis Samaniego Andreas Marx Hanna Komischke Andreas Schmidt Daniel Doktor |
| author_sort | Anne Reichmuth |
| collection | DOAJ |
| description | Abstract Ongoing ecological research is concerned with analysing climate-induced changes in species distribution. For this purpose, the projection must have high-quality bioclimatic variables from historical and future climatic periods for the projection. To date, there are many global bioclimatic variables on this topic. Nevertheless, a consistent dataset with identical model variables from historic and projected periods is rare. We present 26 bioclimatic variables that are calculated based on a large ensemble consisting of 70 bias-adjusted GCM-RCM simulations for 1971–2098. Both, the historic and the projection periods were calculated using the same models to ensure consistency between the periods. The variables are validated against E-OBS observations from which we calculated the same bioclimatic variables. For projection periods we chose 20 year ranges between 2021–2098. Here, we offer two versions of them: (1) variables separated into RCP 2.6, 4.5 and 8.5, including percentiles among the realisations and within the RCPs; and (2) variables per realisation separately. We then extracted the temporal 5th, 50th and 95th percentile per period as representing values. |
| format | Article |
| id | doaj-art-555bb8c9e0fa4a4f83ff9014ec4b3c78 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-555bb8c9e0fa4a4f83ff9014ec4b3c782025-02-09T12:11:48ZengNature PortfolioScientific Data2052-44632025-02-0112111610.1038/s41597-025-04507-wBioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098Anne Reichmuth0Oldrich Rakovec1Friedrich Boeing2Sebastian Müller3Luis Samaniego4Andreas Marx5Hanna Komischke6Andreas Schmidt7Daniel Doktor8Helmholtz-Centre for Environmental Research - UFZ, Department Remote SensingHelmholtz-Centre for Environmental Research - UFZ, Department Computational HydrosystemsHelmholtz-Centre for Environmental Research - UFZ, Department Computational HydrosystemsHelmholtz-Centre for Environmental Research - UFZ, Department Computational HydrosystemsHelmholtz-Centre for Environmental Research - UFZ, Department Computational HydrosystemsHelmholtz-Centre for Environmental Research - UFZ, Department Computational HydrosystemsHelmholtz-Centre for Environmental Research - UFZ, Department Remote SensingHelmholtz-Centre for Environmental Research - UFZ, Department Remote SensingHelmholtz-Centre for Environmental Research - UFZ, Department Remote SensingAbstract Ongoing ecological research is concerned with analysing climate-induced changes in species distribution. For this purpose, the projection must have high-quality bioclimatic variables from historical and future climatic periods for the projection. To date, there are many global bioclimatic variables on this topic. Nevertheless, a consistent dataset with identical model variables from historic and projected periods is rare. We present 26 bioclimatic variables that are calculated based on a large ensemble consisting of 70 bias-adjusted GCM-RCM simulations for 1971–2098. Both, the historic and the projection periods were calculated using the same models to ensure consistency between the periods. The variables are validated against E-OBS observations from which we calculated the same bioclimatic variables. For projection periods we chose 20 year ranges between 2021–2098. Here, we offer two versions of them: (1) variables separated into RCP 2.6, 4.5 and 8.5, including percentiles among the realisations and within the RCPs; and (2) variables per realisation separately. We then extracted the temporal 5th, 50th and 95th percentile per period as representing values.https://doi.org/10.1038/s41597-025-04507-w |
| spellingShingle | Anne Reichmuth Oldrich Rakovec Friedrich Boeing Sebastian Müller Luis Samaniego Andreas Marx Hanna Komischke Andreas Schmidt Daniel Doktor BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 Scientific Data |
| title | BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 |
| title_full | BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 |
| title_fullStr | BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 |
| title_full_unstemmed | BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 |
| title_short | BioVars - A bioclimatic dataset for Europe based on a large regional climate ensemble for periods in 1971–2098 |
| title_sort | biovars a bioclimatic dataset for europe based on a large regional climate ensemble for periods in 1971 2098 |
| url | https://doi.org/10.1038/s41597-025-04507-w |
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