D. Hoffmann, Elizabeth Ebert, Carla J. Mooney, B. Golding, Sally Potter
{"title":"使用价值链方法评估端到端预警链","authors":"D. Hoffmann, Elizabeth Ebert, Carla J. Mooney, B. Golding, Sally Potter","doi":"10.5194/asr-20-73-2023","DOIUrl":null,"url":null,"abstract":"Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate\nwarning systems for high impact weather by integrating physical and social\nscience. It aims to create a framework with guidance and tools for using\nvalue chain approaches, and to develop a database of high impact weather\nwarning case studies for scientists and practitioners to review, analyse and\nlearn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study\ncollection that provides a tool for scientists and practitioners involved in\nresearching, designing and evaluating weather-related warning systems to\nreview previous experience of high impact weather events and assess their\nefficacy.\n","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"116 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using value chain approaches to evaluate the end-to-end warning chain\",\"authors\":\"D. Hoffmann, Elizabeth Ebert, Carla J. Mooney, B. Golding, Sally Potter\",\"doi\":\"10.5194/asr-20-73-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate\\nwarning systems for high impact weather by integrating physical and social\\nscience. It aims to create a framework with guidance and tools for using\\nvalue chain approaches, and to develop a database of high impact weather\\nwarning case studies for scientists and practitioners to review, analyse and\\nlearn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study\\ncollection that provides a tool for scientists and practitioners involved in\\nresearching, designing and evaluating weather-related warning systems to\\nreview previous experience of high impact weather events and assess their\\nefficacy.\\n\",\"PeriodicalId\":30081,\"journal\":{\"name\":\"Advances in Science and Research\",\"volume\":\"116 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Science and Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/asr-20-73-2023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/asr-20-73-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Using value chain approaches to evaluate the end-to-end warning chain
Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate
warning systems for high impact weather by integrating physical and social
science. It aims to create a framework with guidance and tools for using
value chain approaches, and to develop a database of high impact weather
warning case studies for scientists and practitioners to review, analyse and
learn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study
collection that provides a tool for scientists and practitioners involved in
researching, designing and evaluating weather-related warning systems to
review previous experience of high impact weather events and assess their
efficacy.