An Approach for Assessing Misclassification of Tornado Characteristics using Damage

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Applied Meteorology and Climatology Pub Date : 2023-05-18 DOI:10.1175/jamc-d-22-0197.1
Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole
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引用次数: 1

Abstract

Tornado characteristics (e.g., frequency, intensity) are challenging to capture. Assessment of tornado characteristics typically requires damage as a proxy. The lack of validation in the Enhanced Fujita (EF) scale and the likelihood of rural tornadoes suggests that tornado characteristics are not accurately captured. This manuscript presents an approach to quantify the potential misclassification of tornado characteristics using Monte Carlo simulation for residential structures in rural areas. An analytical tornado wind field model coupled with fragility curves generates degrees of damage (i.e., DOD) from the EF scale in a wind speed to damage approach. The simulated DODs are then used to derive damage to wind speed relationships built from the National Weather Service Damage Assessment Toolkit (NWS DAT). Comparisons are then made between the simulated tornado characteristics and those derived from damage. Results from the simulations show a substantial proportion of tornadoes were ‘missed’ and path width and path length on average are underestimated. An EF4 rating based on damage is favored for EF3 to EF5 simulated tornadoes. A linear regression was utilized and determined damagebased wind speeds of different percentiles, damage length, damage width and the number of structures rated at a particular DOD were important for prediction. The distribution of DODs was also used to predict wind speed and the associated intensity rating. These methods were tested on actual tornado cases. Tornadoes that have the same damage-based peak wind speed can be objectively assessed to determine differences in overall intensity. The results also raise questions about the level of confidence when assessing wind speed based on damage.
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一种利用损伤评估龙卷风特征错误分类的方法
龙卷风的特征(如频率、强度)很难捕捉。龙卷风特征的评估通常需要以破坏为代表。增强藤田(EF)等级和农村龙卷风的可能性缺乏验证,这表明龙卷风特征没有被准确捕捉到。本文提出了一种使用蒙特卡洛模拟农村地区住宅结构来量化龙卷风特征潜在错误分类的方法。龙卷风风场分析模型与易损性曲线相结合,在风速-损伤方法中从EF尺度生成损伤程度(即DOD)。然后,模拟的DOD用于推导根据国家气象局损伤评估工具包(NWS DAT)建立的损伤-风速关系。然后将模拟的龙卷风特征与从破坏中得出的特征进行比较。模拟结果显示,相当大一部分龙卷风被“错过”,平均路径宽度和路径长度被低估。对于EF3至EF5模拟龙卷风,基于损失的EF4评级是有利的。利用线性回归确定了不同百分位数的基于损伤的风速、损伤长度、损伤宽度和特定DOD下的结构数量对预测很重要。DOD的分布也用于预测风速和相关的强度等级。这些方法在实际龙卷风案例中进行了测试。可以客观评估具有相同破坏性峰值风速的龙卷风,以确定总体强度的差异。这一结果也引发了人们对基于损伤评估风速时的置信水平的质疑。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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