Tornado climatology of China

2017 ◽  
Vol 38 (5) ◽  
pp. 2478-2489 ◽  
Author(s):  
Jiayi Chen ◽  
Xuhui Cai ◽  
Hongyu Wang ◽  
Ling Kang ◽  
Hongshen Zhang ◽  
...  
Keyword(s):  

Author(s):  
Kevin M. Simmons ◽  
Daniel Sutter
Keyword(s):  


2014 ◽  
Vol 18 (10) ◽  
pp. 1-32 ◽  
Author(s):  
Olivia Kellner ◽  
Dev Niyogi

Abstract Land surface heterogeneity affects mesoscale interactions, including the evolution of severe convection. However, its contribution to tornadogenesis is not well known. Indiana is selected as an example to present an assessment of documented tornadoes and land surface heterogeneity to better understand the spatial distribution of tornadoes. This assessment is developed using a GIS framework taking data from 1950 to 2012 and investigates the following topics: temporal analysis, effect of ENSO, antecedent rainfall linkages, population density, land use/land cover, and topography, placing them in the context of land surface heterogeneity. Spatial analysis of tornado touchdown locations reveals several spatial relationships with regard to cities, population density, land-use classification, and topography. A total of 61% of F0–F5 tornadoes and 43% of F0–F5 tornadoes in Indiana have touched down within 1 km of urban land use and land area classified as forest, respectively, suggesting the possible role of land-use surface roughness on tornado occurrences. The correlation of tornado touchdown points to population density suggests a moderate to strong relationship. A temporal analysis of tornado days shows favored time of day, months, seasons, and active tornado years. Tornado days for 1950–2012 are compared to antecedent rainfall and ENSO phases, which both show no discernible relationship with the average number of annual tornado days. Analysis of tornado touchdowns and topography does not indicate any strong relationship between tornado touchdowns and elevation. Results suggest a possible signature of land surface heterogeneity—particularly that around urban and forested land cover—in tornado climatology.



PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0166895 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger ◽  
Tyler Fricker


Author(s):  
Makenzie J. Krocak ◽  
Jinan N. Allan ◽  
Joseph T. Ripberger ◽  
Carol L. Silva ◽  
Hank C. Jenkins-Smith

AbstractNocturnal tornadoes are challenging to forecast and even more challenging to communicate. Numerous studies have evaluated the forecasting challenges, but fewer have investigated when and where these events pose the greatest communication challenges. This study seeks to evaluate variation in confidence among US residents in receiving and responding to tornado warnings by hour-of-day. Survey experiment data comes from the Severe Weather and Society Survey, an annual survey of US adults. Results indicate that respondents are less confident about receiving warnings overnight, specifically in the early morning hours (12 AM to 4 AM local time). We then use the survey results to inform an analysis of hourly tornado climatology data. We evaluate where nocturnal tornadoes are most likely to occur during the time frame when residents are least confident in their ability to receive tornado warnings. Results show that the Southeast experiences the highest number of nocturnal tornadoes during the time period of lowest confidence, as well as the largest proportion of tornadoes in that time frame. Finally, we estimate and assess two multiple linear regression models to identify individual characteristics that may influence a respondent’s confidence in receiving a tornado between 12 AM and 4 AM. These results indicate that age, race, weather awareness, weather sources, and the proportion of nocturnal tornadoes in the local area relate to warning reception confidence. The results of this study should help inform policymakers and practitioners about the populations at greatest risk for challenges associated with nocturnal tornadoes. Discussion focuses on developing more effective communication strategies, particularly for diverse and vulnerable populations.



2014 ◽  
Vol 35 (10) ◽  
pp. 2993-3006 ◽  
Author(s):  
Tory J. Farney ◽  
P. Grady Dixon


2003 ◽  
Vol 67-68 ◽  
pp. 671-684 ◽  
Author(s):  
John Tyrrell
Keyword(s):  


2003 ◽  
Vol 18 (5) ◽  
pp. 795-807 ◽  
Author(s):  
Patrick W. S. King ◽  
Michael J. Leduc ◽  
David M. L. Sills ◽  
Norman R. Donaldson ◽  
David R. Hudak ◽  
...  


2015 ◽  
Vol 143 (3) ◽  
pp. 702-717 ◽  
Author(s):  
Mateusz Taszarek ◽  
Harold E. Brooks

Abstract Very few studies on the occurrence of tornadoes in Poland have been performed and, therefore, their temporal and spatial variability have not been well understood. This article describes an updated climatology of tornadoes in Poland and the major problems related to the database. In this study, the results of an investigation of tornado occurrence in a 100-yr historical record (1899–1998) and a more recent 15-yr observational dataset (1999–2013) are presented. A total of 269 tornado cases derived from the European Severe Weather Database are used in the analysis. The cases are divided according to their strength on the F scale with weak tornadoes (unrated/F0/F1; 169 cases), significant tornadoes (F2/F3/F4; 66 cases), and waterspouts (34 cases). The tornado season extends from May to September (84% of all cases) with the seasonal peak for tornadoes occurring over land in July (23% of all land cases) and waterspouts in August (50% of all waterspouts). On average 8–14 tornadoes (including 2–3 waterspouts) with 2 strong tornadoes occur each year and 1 violent one occurs every 12–19 years. The maximum daily probability for weak and significant tornadoes occurs between 1500 and 1800 UTC while it occurs between 0900 and 1200 UTC for waterspouts. Tornadoes over land are most likely to occur in the south-central part of the country known as the “Polish Tornado Alley.” Cases of strong, and even violent, tornadoes that caused deaths indicate that the possibility of a large-fatality tornado in Poland cannot be ignored.



2019 ◽  
Vol 110 (4) ◽  
pp. 1075-1094 ◽  
Author(s):  
Kelsey N. Ellis ◽  
Daniel Burow ◽  
Kelly N. Gassert ◽  
Lisa Reyes Mason ◽  
Megan S. Porter


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