{"title":"Transnational Dialogues on Interdisciplinary Approaches for Advancing People-Centered Warning Systems","authors":"Victor Marchezini","doi":"10.1007/s13753-023-00511-z","DOIUrl":null,"url":null,"abstract":"Abstract The United Nations Office for Disaster Risk Reduction and the World Meteorological Organization launched in 2022 the executive plan of the world program “Early Warning Systems for All” to be implemented from 2023 to 2027. This program champions an investment of USD 3.1 billion into the four pillars of warning systems and calls for multi-hazard and people-centered warning systems (PCWS). However, there is a scientific gap concerning interdisciplinary approaches to promoting them. Motivated by the call for action of “Early Warning Systems for All” and warning research gaps on the lack of interdisciplinarity, a workshop series “Interdisciplinary Approaches for Advancing People-Centered Warning Systems” was held in early 2023. This short article shares the preliminary findings and recommendations of this research, which involved a transnational virtual dialogue between one scientific organization in Brazil and one from the United States. The findings and recommendations discussed in three virtual sessions and one collective working paper were centered on three aspects: promoting interdisciplinary integration in research; the need to discuss the characteristics of a PCWS; and promoting problem- and solution-based programs with people to integrate them at all phases of the warning system.","PeriodicalId":48740,"journal":{"name":"International Journal of Disaster Risk Science","volume":"210 1","pages":"0"},"PeriodicalIF":2.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Disaster Risk Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13753-023-00511-z","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The United Nations Office for Disaster Risk Reduction and the World Meteorological Organization launched in 2022 the executive plan of the world program “Early Warning Systems for All” to be implemented from 2023 to 2027. This program champions an investment of USD 3.1 billion into the four pillars of warning systems and calls for multi-hazard and people-centered warning systems (PCWS). However, there is a scientific gap concerning interdisciplinary approaches to promoting them. Motivated by the call for action of “Early Warning Systems for All” and warning research gaps on the lack of interdisciplinarity, a workshop series “Interdisciplinary Approaches for Advancing People-Centered Warning Systems” was held in early 2023. This short article shares the preliminary findings and recommendations of this research, which involved a transnational virtual dialogue between one scientific organization in Brazil and one from the United States. The findings and recommendations discussed in three virtual sessions and one collective working paper were centered on three aspects: promoting interdisciplinary integration in research; the need to discuss the characteristics of a PCWS; and promoting problem- and solution-based programs with people to integrate them at all phases of the warning system.
期刊介绍:
The International Journal of Disaster Risk Science (IJDRS) provides a pioneering platform for researchers and practitioners aiming at greater resilience and integrated risk governance in view of local, regional, and global disasters. IJDRS breaks new ground in research about disaster risks by connecting in-depth studies of actual disasters and of specific practices of disaster risk management with investigations of the global dynamics of disaster risks and theories and models relevant for advanced integrated risk governance.