Filling observational gaps with crowdsourced citizen science rainfall data from the Met Office Weather Observation Website

IF 2.7 4区 环境科学与生态学 Q2 Environmental Science Hydrology Research Pub Date : 2023-03-28 DOI:10.2166/nh.2023.136
Tess O'Hara, F. McClean, Roberto Villalobos Herrera, E. Lewis, H. Fowler
{"title":"Filling observational gaps with crowdsourced citizen science rainfall data from the Met Office Weather Observation Website","authors":"Tess O'Hara, F. McClean, Roberto Villalobos Herrera, E. Lewis, H. Fowler","doi":"10.2166/nh.2023.136","DOIUrl":null,"url":null,"abstract":"\n This paper demonstrates the potential for crowdsourced rainfall data to infill gaps in the official rain gauge network and to provide new datasets for use in research. We use data from the Met Office Weather Observation Website (WOW) over 10 years (2011–2020) to generate two open-source datasets for Britain; multi-parameter raw data in an easy-to-use format; and an hourly rainfall dataset. We have compiled and prepared the data and detail here station selection, rain depth calculation, and data resampling to hourly intervals to create a consistent dataset for further processing (including statistical quality control) and application. Mapping the new rainfall dataset establishes that WOW observations fill spatial gaps in the official ground-based rain gauge network over Britain, particularly in urban areas. This could be particularly useful for post-event analysis of rainfall that results in pluvial flash flooding. Here, we focus on Britain but due to agreements with meteorological services in Belgium, the Netherlands, Australia, New Zealand, Sweden, and the Republic of Ireland, plus many citizen scientists globally opting to share data via WOW there is potential for the development of similar datasets using these methods around the world.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/nh.2023.136","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 1

Abstract

This paper demonstrates the potential for crowdsourced rainfall data to infill gaps in the official rain gauge network and to provide new datasets for use in research. We use data from the Met Office Weather Observation Website (WOW) over 10 years (2011–2020) to generate two open-source datasets for Britain; multi-parameter raw data in an easy-to-use format; and an hourly rainfall dataset. We have compiled and prepared the data and detail here station selection, rain depth calculation, and data resampling to hourly intervals to create a consistent dataset for further processing (including statistical quality control) and application. Mapping the new rainfall dataset establishes that WOW observations fill spatial gaps in the official ground-based rain gauge network over Britain, particularly in urban areas. This could be particularly useful for post-event analysis of rainfall that results in pluvial flash flooding. Here, we focus on Britain but due to agreements with meteorological services in Belgium, the Netherlands, Australia, New Zealand, Sweden, and the Republic of Ireland, plus many citizen scientists globally opting to share data via WOW there is potential for the development of similar datasets using these methods around the world.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用来自英国气象局天气观测网站的众包公民科学降雨数据填补观测空白
本文展示了众包降雨数据的潜力,它可以填补官方雨量计网络的空白,并为研究提供新的数据集。我们使用英国气象局天气观测网站(WOW)超过10年(2011-2020年)的数据为英国生成两个开源数据集;多参数原始数据在一个易于使用的格式;以及每小时降雨量数据集。我们整理和准备了数据,并详细说明了这里的站点选择,雨深计算和数据重采样以每小时为间隔,以创建一个一致的数据集,以便进一步处理(包括统计质量控制)和应用。绘制新的降雨数据集表明,WOW观测结果填补了英国官方地面雨量计网络的空间空白,特别是在城市地区。这对于导致山洪暴发的降雨的事后分析尤其有用。在这里,我们关注的是英国,但由于与比利时、荷兰、澳大利亚、新西兰、瑞典和爱尔兰共和国的气象部门达成了协议,加上全球许多公民科学家选择通过WOW共享数据,因此有可能在世界各地使用这些方法开发类似的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Hydrology Research
Hydrology Research Environmental Science-Water Science and Technology
CiteScore
5.30
自引率
7.40%
发文量
70
审稿时长
17 weeks
期刊介绍: Hydrology Research provides international coverage on all aspects of hydrology in its widest sense, and welcomes the submission of papers from across the subject. While emphasis is placed on studies of the hydrological cycle, the Journal also covers the physics and chemistry of water. Hydrology Research is intended to be a link between basic hydrological research and the practical application of scientific results within the broad field of water management.
期刊最新文献
Prediction of flash flood peak discharge in hilly areas with ungauged basins based on machine learning Effects of tributary inflows on unsteady flow hysteresis and hydrodynamics in the mainstream Drought mitigation operation of water conservancy projects under severe droughts Water quality level estimation using IoT sensors and probabilistic machine learning model Design storm parameterisation for urban drainage studies derived from regional rainfall datasets: A case study in the Spanish Mediterranean region
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1