严重程度影响分类概率通信:与东南亚天气预报人员的案例研究
Alice Liefgreen1,2, Sarah C Jenkins3,4,5, Sazali Osman6
1Department of Experimental Psychology, University College London, 26 Bedford Way, London, WCH1 0AP, UK.
Scientific reports
|June 25, 2024
概括
预报人员高估了严重天气影响的可能性,即使明确的概率是相同的. 这种"严重性效应"会影响天气预警和风险感知.
科学领域:
- 气象学 天气学
- 认知心理学 认知心理学
- 风险评估 风险评估
背景情况:
- 风险评估包括在各个领域评估事件的严重程度和可能性.
- 基于影响的天气预报 (IBF) 需要准确的风险沟通.
- 不对称的损失函数表明可能性和严重程度之间的潜在依赖.
研究的目的:
- 调查基于影响的天气预报中概率和严重程度之间的依赖.
- 为了确定预报者如何评估天气风险的认知偏见.
- 了解天气预警生成中的"严重性效应".
主要方法:
- 两项研究对363名来自东南亚气象组织的预报员进行了调查.
- 在不同的严重程度和可能性条件下,从预报者那里发出天气预警.
- 分析预测者如何将风险矩阵转化为数值概率的分析.
主要成果:
- 预测人员将高严重性影响的可能性高于低严重性影响的可能性,尽管具有相同的明确数值概率.
- 这种"严重性效应"是普遍存在的,即使有最新的预测信息,它仍然存在.
- 当将风险矩阵信息转换为数值概率时也观察到这种效应.
结论:
- 天气预报者表现出"严重性效应",在天气警告中优先考虑严重性而不是明确的可能性.
- 这种认知偏见可能会影响天气预报的准确性和解释.
- 了解"严重性效应"对于改善气象中的风险沟通至关重要.
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