{"title":"东南亚气象科学家用于划分影响严重程度的判断和决策策略","authors":"","doi":"10.1016/j.ijdrr.2024.104799","DOIUrl":null,"url":null,"abstract":"<div><div>Impact-based weather forecasting requires forecasters to predict what weather might <em>do</em> (impact information), rather than solely what weather might <em>be</em> (meteorological information). In a collaboration between the UK Met Office, UK psychologists, and weather scientists in Indonesia, Malaysia, the Philippines, and Vietnam, the present study employed Judgment Analysis and decision strategy comparisons to better understand weather scientists' impact severity judgments. In the Judgment Analysis Task, weather scientists (from Indonesia, Malaysia, the Philippines, and Vietnam) made numerical and categorical severity judgments for 70 hypothetical heavy rainfall events, each described via six impacts (e.g., number of deaths, number of people affected). The hypothetical impacts were generated from a multivariate distribution estimated from a distribution of real rainfall events. Subsequently, participants provided categorical severity classifications for a list of impact values for each type of impact (Threshold Identification Task) to aid the identification of decision strategies. In all four countries, weather scientists' severity judgments were best predicted by incorporating all six impacts via a compensatory judgment strategy. However, considerable individual differences were identified in the weights assigned to the different impacts and in the identified thresholds for each impact's categorical severity classification. To improve impact-based forecasting, meteorological agencies should seek to enhance consistency among forecasters.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Judgment and decision strategies used by weather scientists in southeast Asia to classify impact severity\",\"authors\":\"\",\"doi\":\"10.1016/j.ijdrr.2024.104799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Impact-based weather forecasting requires forecasters to predict what weather might <em>do</em> (impact information), rather than solely what weather might <em>be</em> (meteorological information). In a collaboration between the UK Met Office, UK psychologists, and weather scientists in Indonesia, Malaysia, the Philippines, and Vietnam, the present study employed Judgment Analysis and decision strategy comparisons to better understand weather scientists' impact severity judgments. In the Judgment Analysis Task, weather scientists (from Indonesia, Malaysia, the Philippines, and Vietnam) made numerical and categorical severity judgments for 70 hypothetical heavy rainfall events, each described via six impacts (e.g., number of deaths, number of people affected). The hypothetical impacts were generated from a multivariate distribution estimated from a distribution of real rainfall events. Subsequently, participants provided categorical severity classifications for a list of impact values for each type of impact (Threshold Identification Task) to aid the identification of decision strategies. In all four countries, weather scientists' severity judgments were best predicted by incorporating all six impacts via a compensatory judgment strategy. However, considerable individual differences were identified in the weights assigned to the different impacts and in the identified thresholds for each impact's categorical severity classification. To improve impact-based forecasting, meteorological agencies should seek to enhance consistency among forecasters.</div></div>\",\"PeriodicalId\":13915,\"journal\":{\"name\":\"International journal of disaster risk reduction\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of disaster risk reduction\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212420924005612\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of disaster risk reduction","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212420924005612","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Judgment and decision strategies used by weather scientists in southeast Asia to classify impact severity
Impact-based weather forecasting requires forecasters to predict what weather might do (impact information), rather than solely what weather might be (meteorological information). In a collaboration between the UK Met Office, UK psychologists, and weather scientists in Indonesia, Malaysia, the Philippines, and Vietnam, the present study employed Judgment Analysis and decision strategy comparisons to better understand weather scientists' impact severity judgments. In the Judgment Analysis Task, weather scientists (from Indonesia, Malaysia, the Philippines, and Vietnam) made numerical and categorical severity judgments for 70 hypothetical heavy rainfall events, each described via six impacts (e.g., number of deaths, number of people affected). The hypothetical impacts were generated from a multivariate distribution estimated from a distribution of real rainfall events. Subsequently, participants provided categorical severity classifications for a list of impact values for each type of impact (Threshold Identification Task) to aid the identification of decision strategies. In all four countries, weather scientists' severity judgments were best predicted by incorporating all six impacts via a compensatory judgment strategy. However, considerable individual differences were identified in the weights assigned to the different impacts and in the identified thresholds for each impact's categorical severity classification. To improve impact-based forecasting, meteorological agencies should seek to enhance consistency among forecasters.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.