Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole
{"title":"一种利用损伤评估龙卷风特征错误分类的方法","authors":"Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole","doi":"10.1175/jamc-d-22-0197.1","DOIUrl":null,"url":null,"abstract":"\nTornado 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.\nResults 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.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Approach for Assessing Misclassification of Tornado Characteristics using Damage\",\"authors\":\"Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole\",\"doi\":\"10.1175/jamc-d-22-0197.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nTornado 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.\\nResults 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.\",\"PeriodicalId\":15027,\"journal\":{\"name\":\"Journal of Applied Meteorology and Climatology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Meteorology and Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/jamc-d-22-0197.1\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Meteorology and Climatology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jamc-d-22-0197.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
An Approach for Assessing Misclassification of Tornado Characteristics using Damage
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.
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.