{"title":"1867-2024年大都柏林地区每月雪和雨夹雪系列","authors":"Csaba Horvath, Ciara Ryan, Conor Murphy","doi":"10.1002/gdj3.70022","DOIUrl":null,"url":null,"abstract":"<p>This paper details the compilation of data and application of quality assurance procedures for constructing a 157-year snow and sleet series for the Greater Dublin Area, Ireland. Snowfall is particularly sensitive to climate variability in temperate regions, and long-term records are essential for understanding changes in winter weather extremes over time. The dataset integrates observations from six sites and provides a regional snow and sleet frequency dataset at monthly, seasonal (October–May) and annual resolutions. Data sources include archived meteorological records, digitised station logs and synoptic weather reports. A brief analysis offers insights into long-term snowfall climatology in the Greater Dublin region from 1867 to 2024, revealing substantial interannual and decadal variability, as well as notable reductions in snow frequency in recent decades. This dataset provides a valuable baseline for assessing historical trends in snowfall and contributes to broader efforts in climate reconstruction and climate change impact studies in Ireland and beyond.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"12 4","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70022","citationCount":"0","resultStr":"{\"title\":\"A Monthly Snow and Sleet Series for the Greater Dublin Area 1867–2024\",\"authors\":\"Csaba Horvath, Ciara Ryan, Conor Murphy\",\"doi\":\"10.1002/gdj3.70022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper details the compilation of data and application of quality assurance procedures for constructing a 157-year snow and sleet series for the Greater Dublin Area, Ireland. Snowfall is particularly sensitive to climate variability in temperate regions, and long-term records are essential for understanding changes in winter weather extremes over time. The dataset integrates observations from six sites and provides a regional snow and sleet frequency dataset at monthly, seasonal (October–May) and annual resolutions. Data sources include archived meteorological records, digitised station logs and synoptic weather reports. A brief analysis offers insights into long-term snowfall climatology in the Greater Dublin region from 1867 to 2024, revealing substantial interannual and decadal variability, as well as notable reductions in snow frequency in recent decades. This dataset provides a valuable baseline for assessing historical trends in snowfall and contributes to broader efforts in climate reconstruction and climate change impact studies in Ireland and beyond.</p>\",\"PeriodicalId\":54351,\"journal\":{\"name\":\"Geoscience Data Journal\",\"volume\":\"12 4\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70022\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscience Data Journal\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://rmets.onlinelibrary.wiley.com/doi/10.1002/gdj3.70022\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience Data Journal","FirstCategoryId":"89","ListUrlMain":"https://rmets.onlinelibrary.wiley.com/doi/10.1002/gdj3.70022","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
A Monthly Snow and Sleet Series for the Greater Dublin Area 1867–2024
This paper details the compilation of data and application of quality assurance procedures for constructing a 157-year snow and sleet series for the Greater Dublin Area, Ireland. Snowfall is particularly sensitive to climate variability in temperate regions, and long-term records are essential for understanding changes in winter weather extremes over time. The dataset integrates observations from six sites and provides a regional snow and sleet frequency dataset at monthly, seasonal (October–May) and annual resolutions. Data sources include archived meteorological records, digitised station logs and synoptic weather reports. A brief analysis offers insights into long-term snowfall climatology in the Greater Dublin region from 1867 to 2024, revealing substantial interannual and decadal variability, as well as notable reductions in snow frequency in recent decades. This dataset provides a valuable baseline for assessing historical trends in snowfall and contributes to broader efforts in climate reconstruction and climate change impact studies in Ireland and beyond.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍:
Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered.
An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices.
Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.