{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T21:19:20Z","timestamp":1778793560774,"version":"3.51.4"},"reference-count":49,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T00:00:00Z","timestamp":1747353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science, Innovation and Universities","award":["FPU21\/03022"],"award-info":[{"award-number":["FPU21\/03022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>This data descriptor presents \u03b4-MedBioclim, a newly developed dataset for the Euro-Mediterranean region. This dataset applies the delta-change method by comparing the values of 25 General Circulation Models (GCMs) for the reference period (1981\u20132010) with their projections for future periods (2026\u20132050, 2051\u20132075, and 2076\u20132100) under the SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios. These anomalies are added to two pre-existing datasets, ERA5-Land and CHELSA, yielding resolutions of 0.1\u00b0 and 0.01\u00b0, respectively. Additionally, this manuscript provides a ranking of GCMs for each major river basin within the study area to guide model selection. \u03b4-MedBioclim includes, for all the aforementioned scenarios, monthly mean temperature, total monthly precipitation, and 23 bioclimatic variables, including 9 (biorm1 to biorm9) from the Worldwide Bioclimatic Classification System (WBCS) that are not available in other databases. It also provides two bioclimatic classifications: K\u00f6ppen\u2013Geiger and WBCS. This dataset is expected to be a valuable resource for modeling the distribution of Mediterranean species and habitats, which are highly affected by climate change.<\/jats:p>","DOI":"10.3390\/data10050078","type":"journal-article","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T06:57:28Z","timestamp":1747378648000},"page":"78","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["\u03b4-MedBioclim: A New Dataset Bridging Current and Projected Bioclimatic Variables for the Euro-Mediterranean Region"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1703-4616","authenticated-orcid":false,"given":"Giovanni-Breog\u00e1n","family":"Ferreiro-Lera","sequence":"first","affiliation":[{"name":"Department of Biodiversity and Environmental Management, Faculty of Biological and Environmental Sciences, University of Le\u00f3n, Campus de Vegazana s\/n, 24071 Leon, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5614-5378","authenticated-orcid":false,"given":"\u00c1ngel","family":"Penas","sequence":"additional","affiliation":[{"name":"Department of Biodiversity and Environmental Management, Faculty of Biological and Environmental Sciences, University of Le\u00f3n, Campus de Vegazana s\/n, 24071 Leon, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0733-2150","authenticated-orcid":false,"given":"Sara","family":"del R\u00edo","sequence":"additional","affiliation":[{"name":"Department of Biodiversity and Environmental Management, Faculty of Biological and Environmental Sciences, University of Le\u00f3n, Campus de Vegazana s\/n, 24071 Leon, Spain"},{"name":"Mountain Livestock Institute (CSIC-ULE), Le\u00f3n-Vega de Infanzones Road (Finca Marzanas-Grulleros), 24346 Leon, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"170122","DOI":"10.1038\/sdata.2017.122","article-title":"Climatologies at High Resolution for the Earth\u2019s Land Surface Areas","volume":"4","author":"Karger","year":"2017","journal-title":"Sci. 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Data"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1111\/j.2041-210X.2011.00134.x","article-title":"CliMond: Global High-Resolution Historical and Future Scenario Climate Surfaces for Bioclimatic Modelling","volume":"3","author":"Kriticos","year":"2012","journal-title":"Methods Ecol. Evol."},{"key":"ref_6","first-page":"1","article-title":"Worldwide Bioclimatic Classification System","volume":"1","author":"Penas","year":"2011","journal-title":"Glob. Geobot."},{"key":"ref_7","first-page":"5","article-title":"El Cambio Clim\u00e1tico y Su Influencia En La Vegetaci\u00f3n de Castilla y Le\u00f3n (Espa\u00f1a)","volume":"16","year":"2005","journal-title":"Itinera Geobot."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.gloplacha.2013.04.005","article-title":"Dangers of Using Global Bioclimatic Datasets for Ecological Niche Modeling. Limitations for Future Climate Projections","volume":"107","author":"Bedia","year":"2013","journal-title":"Glob. Planet. Change"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1719","DOI":"10.1007\/s00382-017-3717-7","article-title":"The Epistemological Status of General Circulation Models","volume":"50","author":"Loehle","year":"2018","journal-title":"Clim. Dyn."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.ecoinf.2011.01.004","article-title":"High-Resolution Bioclimatic Dataset Derived from Future Climate Projections for Plant Species Distribution Modeling","volume":"6","author":"Xiaojun","year":"2011","journal-title":"Ecol. Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108572","DOI":"10.1016\/j.dib.2022.108572","article-title":"Bioclimatic Variables Dataset for Baseline and Future Climate Scenarios for Climate Change Studies in Hawai\u2019i","volume":"45","author":"Kaiser","year":"2022","journal-title":"Data Brief"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"109354","DOI":"10.1016\/j.ecolmodel.2020.109354","article-title":"High Spatial Resolution Bioclimatic Variables to Support Ecological Modelling in a Mediterranean Biodiversity Hotspot","volume":"441","author":"Bazzato","year":"2021","journal-title":"Ecol. Model."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e31","DOI":"10.1017\/eds.2024.50","article-title":"Environmental and Bioclimatic Data for Epidemiological Analysis over French Mediterranean Areas","volume":"3","author":"Portes","year":"2024","journal-title":"Environ. Data Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1126\/science.1197869","article-title":"Climate Data Challenges in the 21st Century","volume":"331","author":"Overpeck","year":"2011","journal-title":"Science"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1038\/s41597-024-04134-x","article-title":"Bioclimatic Indicators Dataset for the Orographically Complex Canary Islands Archipelago","volume":"11","year":"2024","journal-title":"Sci. Data"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"164734","DOI":"10.1016\/j.scitotenv.2023.164734","article-title":"A Novel Artificial Neural Network Methodology to Produce High-Resolution Bioclimatic Maps Using Earth Observation Data: A Case Study for Cyprus","volume":"893","author":"Philippopoulos","year":"2023","journal-title":"Sci. Total Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1038\/s41597-025-04507-w","article-title":"BioVars\u2014A Bioclimatic Dataset for Europe Based on a Large Regional Climate Ensemble for Periods in 1971\u20132098","volume":"12","author":"Reichmuth","year":"2025","journal-title":"Sci. Data"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"167613","DOI":"10.1016\/j.scitotenv.2023.167613","article-title":"1 Km Monthly Precipitation and Temperatures Dataset for China from 1952 to 2019 Based on New Baseline Climatology Surfaces","volume":"906","author":"Gong","year":"2024","journal-title":"Sci. Total Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1016\/j.scitotenv.2017.12.258","article-title":"Enhancing the WorldClim Data Set for National and Regional Applications","volume":"625","author":"Poggio","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"457","DOI":"10.5194\/esd-14-457-2023","article-title":"Performance-Based Sub-Selection of CMIP6 Models for Impact Assessments in Europe","volume":"14","author":"Palmer","year":"2023","journal-title":"Earth Syst. Dyn."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4891","DOI":"10.1002\/joc.5705","article-title":"Using Multi-Model Ensembles of CMIP5 Global Climate Models to Reproduce Observed Monthly Rainfall and Temperature with Machine Learning Methods in Australia","volume":"38","author":"Wang","year":"2018","journal-title":"Int. J. Climatol."},{"key":"ref_22","unstructured":"Cramer, W., Guiot, J., and Marini, K. (2020). Climate and Environmental Change in the Mediterranean Basin\u2014Current Situation and Risks for the Future: First Mediterranean Assessment Report, MedECC."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1017\/S0376892924000067","article-title":"Integrative Research of Mediterranean Climate Regions: A Global Call to Action","volume":"51","author":"Arranz","year":"2024","journal-title":"Environ. Conserv."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2171","DOI":"10.1002\/hyp.9740","article-title":"Global River Hydrography and Network Routing: Baseline Data and New Approaches to Study the World\u2019s Large River Systems","volume":"27","author":"Lehner","year":"2013","journal-title":"Hydrol. Process"},{"key":"ref_25","unstructured":"(2024, July 11). ESRI ArcGIS Pro 3.2. Available online: https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-pro."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1007\/s41748-024-00408-x","article-title":"Multi-Model Ensemble Machine Learning Approaches to Project Climatic Scenarios in a River Basin in the Pyrenees","volume":"8","author":"Faria","year":"2024","journal-title":"Earth Syst. Environ."},{"key":"ref_27","first-page":"20532075","article-title":"The Use of the Multi-Model Ensemble in Probabilistic Climate Projections","volume":"365","author":"Tebaldi","year":"2007","journal-title":"Philos. Trans. R. Soc. A Math. Phys. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"104806","DOI":"10.1016\/j.atmosres.2019.104806","article-title":"Multi-Model Ensemble Predictions of Precipitation and Temperature Using Machine Learning Algorithms","volume":"236","author":"Ahmed","year":"2020","journal-title":"Atmos. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4803","DOI":"10.5194\/hess-23-4803-2019","article-title":"Selection of Multi-Model Ensemble of General Circulation Models for the Simulation of Precipitation and Maximum and Minimum Temperature Based on Spatial Assessment Metrics","volume":"23","author":"Ahmed","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"109190","DOI":"10.1016\/j.agwat.2024.109190","article-title":"CMIP6 Multi-Model Ensemble Projection of Reference Evapotranspiration Using Machine Learning Algorithms","volume":"306","author":"Nouri","year":"2024","journal-title":"Agric. Water Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.envsci.2010.04.004","article-title":"What Does It Mean When Climate Models Agree? A Case for Assessing Independence among General Circulation Models","volume":"13","author":"Pirtle","year":"2010","journal-title":"Environ. Sci. Policy"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1007\/s00382-014-2130-8","article-title":"Evaluation of Delta Change and Bias Correction Methods for Future Daily Precipitation: Intermodel Cross-Validation Using ENSEMBLES Simulations","volume":"42","year":"2014","journal-title":"Clim. Dyn."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1002\/2015JG003216","article-title":"Effect of Climate Data on Simulated Carbon and Nitrogen Balances for Europe","volume":"121","author":"Blanke","year":"2016","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1002\/joc.1839","article-title":"A Review of Climate Risk Information for Adaptation and Development Planning","volume":"29","author":"Wilby","year":"2009","journal-title":"Int. J. Climatol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4349","DOI":"10.5194\/essd-13-4349-2021","article-title":"ERA5-Land: A State-of-the-Art Global Reanalysis Dataset for Land Applications","volume":"13","author":"Dutra","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, T., Hamann, A., Spittlehouse, D., and Carroll, C. (2016). Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0156720"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1038\/s41597-019-0343-8","article-title":"High-Resolution and Bias-Corrected CMIP5 Projections for Climate Change Impact Assessments","volume":"7","author":"Tarapues","year":"2020","journal-title":"Sci. Data"},{"key":"ref_38","unstructured":"Ruiter, A. (2012). Delta-Change Approach for CMIP5 GCMs, Koninklijk Nederlands Meteorologisch Instituut."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2245405","DOI":"10.1080\/17445647.2023.2245405","article-title":"Landscape and Bioclimatic Regionalization of the Coast of Oaxaca (M\u00e9xico)","volume":"19","year":"2023","journal-title":"J. Maps"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1007\/s42965-023-00300-1","article-title":"Application of the Worldwide Bioclimatic Classification System to Determine Bioclimatic Features and Potential Natural Vegetation Distribution in Van Chan District, Vietnam","volume":"64","author":"Pham","year":"2023","journal-title":"Trop. Ecol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1080\/17445647.2017.1413017","article-title":"Bioclimates of Italy","volume":"13","author":"Pesaresi","year":"2017","journal-title":"J. Maps"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"105815","DOI":"10.1016\/j.dib.2020.105815","article-title":"Bioclimatic Dataset of Metropolitan France under Current Conditions Derived from the WorldClim Model","volume":"31","author":"Perrin","year":"2020","journal-title":"Data Brief"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"126391","DOI":"10.1016\/j.eja.2021.126391","article-title":"A New Integrated Methodology for Characterizing and Assessing Suitable Areas for Viticulture: A Case Study in Northwest Spain","volume":"131","author":"Hidalgo","year":"2021","journal-title":"Eur. J. Agron."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"108202","DOI":"10.1016\/j.ecolind.2021.108202","article-title":"Modelling the Impacts of Climate Change on Habitat Suitability and Vulnerability in Deciduous Forests in Spain","volume":"131","author":"Canas","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-P\u00e9rez, A., \u00c1lvarez-Esteban, R., Penas, \u00c1., and del R\u00edo, S. (2023). Bioclimatic Characterisation of Specific Native Californian Pinales and Their Future Suitability under Climate Change. Plants, 12.","DOI":"10.3390\/plants12101966"},{"key":"ref_46","first-page":"1205","article-title":"Potential Impacts of Climate Change on Habitat Suitability of Fagus Sylvatica L. Forests in Spain","volume":"152","author":"Cano","year":"2018","journal-title":"Plant Biosyst. Int. J. Deal. All Asp. Plant Biol."},{"key":"ref_47","unstructured":"K\u00f6ppen, W. (1936). Das Geographische System Der Klimate, Gebr\u00fcder Borntraeger."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Ferreiro-Lera, G.B., Penas, \u00c1., and del R\u00edo, S. (2024). Unveiling Deviations from IPCC Temperature Projections through Bayesian Downscaling and Assessment of CMIP6 General Circulation Models in a Climate-Vulnerable Region. Remote Sens., 16.","DOI":"10.2139\/ssrn.4905860"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"104725","DOI":"10.1016\/j.gloplacha.2025.104725","article-title":"Obtaining Refined Euro-Mediterranean Rainfall Projections through Regional Assessment of CMIP6 General Circulation Models","volume":"246","author":"Penas","year":"2025","journal-title":"Glob. Planet. Change"}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/5\/78\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:33:49Z","timestamp":1760031229000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/10\/5\/78"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,16]]},"references-count":49,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["data10050078"],"URL":"https:\/\/doi.org\/10.3390\/data10050078","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,16]]}}}