Anikó Kern , Laura Dobor , Roland Hollós , Hrvoje Marjanović , Csaba Zsolt Torma , Anna Kis , Nándor Fodor , Zoltán Barcza
{"title":"无缝结合历史和预测日气象数据集,用于中欧影响研究:FORESEE v4.0 和 FORESEE-HUN v1.0","authors":"Anikó Kern , Laura Dobor , Roland Hollós , Hrvoje Marjanović , Csaba Zsolt Torma , Anna Kis , Nándor Fodor , Zoltán Barcza","doi":"10.1016/j.cliser.2023.100443","DOIUrl":null,"url":null,"abstract":"<div><p>The FORESEE is an open access, climatological database for Central Europe containing observed and projected meteorological data for the 1951–2100 period. As a climate service, FORESEE disseminates basic meteorological variables at a daily time step with a 0.1° × 0.1° spatial resolution including maximum/minimum temperature, precipitation, incoming shortwave solar radiation and daylight vapour pressure deficit. The future climate in FORESEE v4.0 and FORESEE-HUN v1.0 is projected by 14 regional climate models from the EURO-CORDEX database using the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Based on RCP4.5 the country-specific results indicate similar projected mean changes in annual mean temperature (1.5–1.7 °C) but considerable differences in precipitation (from −1.6 to 6.9%) in the region for 2071–2100 relative to 1991–2020. We present two case studies to demonstrate the applicability of FORESEE in climate change impact studies using the ensemble approach. Climate change induced negative weather effect (15.4% and 28.9% mean loss for 2071–2100 according to RCP4.5 and RCP8.5, respectively) might dominate the future winter wheat yields in Hungary that is superimposed to the overall trend determined by other factors. The projections provide consistent results about the mean advance in the start of the growing season for forests in Hungary up to 2100 with ensemble mean of 9.1 days (RCP4.5) and 19.8 days (RCP8.5). We also demonstrate that the representative model selection method might lead to misleading results in impact studies that should be considered. The updated FORESEE is a way forward in the dissemination of policy-relevant essential climate data in Central Europe.</p></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"33 ","pages":"Article 100443"},"PeriodicalIF":4.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S240588072300105X/pdfft?md5=a34d12845a9886670b99f87eb037f145&pid=1-s2.0-S240588072300105X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0\",\"authors\":\"Anikó Kern , Laura Dobor , Roland Hollós , Hrvoje Marjanović , Csaba Zsolt Torma , Anna Kis , Nándor Fodor , Zoltán Barcza\",\"doi\":\"10.1016/j.cliser.2023.100443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The FORESEE is an open access, climatological database for Central Europe containing observed and projected meteorological data for the 1951–2100 period. As a climate service, FORESEE disseminates basic meteorological variables at a daily time step with a 0.1° × 0.1° spatial resolution including maximum/minimum temperature, precipitation, incoming shortwave solar radiation and daylight vapour pressure deficit. The future climate in FORESEE v4.0 and FORESEE-HUN v1.0 is projected by 14 regional climate models from the EURO-CORDEX database using the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Based on RCP4.5 the country-specific results indicate similar projected mean changes in annual mean temperature (1.5–1.7 °C) but considerable differences in precipitation (from −1.6 to 6.9%) in the region for 2071–2100 relative to 1991–2020. We present two case studies to demonstrate the applicability of FORESEE in climate change impact studies using the ensemble approach. Climate change induced negative weather effect (15.4% and 28.9% mean loss for 2071–2100 according to RCP4.5 and RCP8.5, respectively) might dominate the future winter wheat yields in Hungary that is superimposed to the overall trend determined by other factors. The projections provide consistent results about the mean advance in the start of the growing season for forests in Hungary up to 2100 with ensemble mean of 9.1 days (RCP4.5) and 19.8 days (RCP8.5). We also demonstrate that the representative model selection method might lead to misleading results in impact studies that should be considered. The updated FORESEE is a way forward in the dissemination of policy-relevant essential climate data in Central Europe.</p></div>\",\"PeriodicalId\":51332,\"journal\":{\"name\":\"Climate Services\",\"volume\":\"33 \",\"pages\":\"Article 100443\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S240588072300105X/pdfft?md5=a34d12845a9886670b99f87eb037f145&pid=1-s2.0-S240588072300105X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Climate Services\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S240588072300105X\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate Services","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S240588072300105X","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0
The FORESEE is an open access, climatological database for Central Europe containing observed and projected meteorological data for the 1951–2100 period. As a climate service, FORESEE disseminates basic meteorological variables at a daily time step with a 0.1° × 0.1° spatial resolution including maximum/minimum temperature, precipitation, incoming shortwave solar radiation and daylight vapour pressure deficit. The future climate in FORESEE v4.0 and FORESEE-HUN v1.0 is projected by 14 regional climate models from the EURO-CORDEX database using the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Based on RCP4.5 the country-specific results indicate similar projected mean changes in annual mean temperature (1.5–1.7 °C) but considerable differences in precipitation (from −1.6 to 6.9%) in the region for 2071–2100 relative to 1991–2020. We present two case studies to demonstrate the applicability of FORESEE in climate change impact studies using the ensemble approach. Climate change induced negative weather effect (15.4% and 28.9% mean loss for 2071–2100 according to RCP4.5 and RCP8.5, respectively) might dominate the future winter wheat yields in Hungary that is superimposed to the overall trend determined by other factors. The projections provide consistent results about the mean advance in the start of the growing season for forests in Hungary up to 2100 with ensemble mean of 9.1 days (RCP4.5) and 19.8 days (RCP8.5). We also demonstrate that the representative model selection method might lead to misleading results in impact studies that should be considered. The updated FORESEE is a way forward in the dissemination of policy-relevant essential climate data in Central Europe.
期刊介绍:
The journal Climate Services publishes research with a focus on science-based and user-specific climate information underpinning climate services, ultimately to assist society to adapt to climate change. Climate Services brings science and practice closer together. The journal addresses both researchers in the field of climate service research, and stakeholders and practitioners interested in or already applying climate services. It serves as a means of communication, dialogue and exchange between researchers and stakeholders. Climate services pioneers novel research areas that directly refer to how climate information can be applied in methodologies and tools for adaptation to climate change. It publishes best practice examples, case studies as well as theories, methods and data analysis with a clear connection to climate services. The focus of the published work is often multi-disciplinary, case-specific, tailored to specific sectors and strongly application-oriented. To offer a suitable outlet for such studies, Climate Services journal introduced a new section in the research article type. The research article contains a classical scientific part as well as a section with easily understandable practical implications for policy makers and practitioners. The journal''s focus is on the use and usability of climate information for adaptation purposes underpinning climate services.