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

IF 4.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY International journal of disaster risk reduction Pub Date : 2024-10-15 DOI:10.1016/j.ijdrr.2024.104799
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引用次数: 0

摘要

基于影响的天气预报要求预报员预测天气可能造成的影响(影响信息),而不仅仅是天气可能是什么(气象信息)。在英国气象局、英国心理学家以及印度尼西亚、马来西亚、菲律宾和越南的气象科学家的合作下,本研究采用了判断分析和决策策略比较的方法,以更好地了解气象科学家对影响严重程度的判断。在 "判断分析任务 "中,来自印度尼西亚、马来西亚、菲律宾和越南的气象科学家对 70 个假设的强降雨事件进行了数字和分类严重性判断,每个事件通过六种影响(如死亡人数、受灾人数)进行描述。假设的影响是根据真实降雨事件分布估算出的多元分布生成的。随后,参与者对每类影响的影响值列表进行严重程度分类(阈值识别任务),以帮助确定决策策略。在所有四个国家中,气象科学家的严重性判断最好是通过补偿性判断策略纳入所有六种影响。然而,在不同影响的权重分配和每种影响严重程度分类的阈值确定方面,发现了相当大的个体差异。为了改进基于影响的预报,气象机构应努力提高预报员之间的一致性。
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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.
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来源期刊
International journal of disaster risk reduction
International journal of disaster risk reduction GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
8.70
自引率
18.00%
发文量
688
审稿时长
79 days
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.
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