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Chengcheng Xu, Chen Wang, and Pan Liu

quartiles of this distance are 2.7 and 6.9 km. Weather conditions were defined based on visibility or precipitation intensity according to the definitions used in meteorology. The low-visibility weather was classified as haze, mist, and fog based on the magnitude of visibility, and the intensity of rainfall was classified as light, moderate, and heavy based on the precipitation intensity ( Vautard et al. 2009 ; Glickman 2000 ). Considering the sample size in each category, the moderate and heavy rain

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Mario Cools, Elke Moons, and Geert Wets

1. Introduction a. Background A clear insight into how weather conditions influence traffic is essential for policymakers. This is underlined by policy issues that are often related to adverse weather events such as increased fuel consumption, economic losses due to traffic delays, and higher traffic counts. Day-to-day weather conditions such as fog and precipitation can reduce travel, for instance when drivers postpone or cancel discretionary activities, but can also have an increased effect

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Jose A. Algarin Ballesteros and Nathan M. Hitchens

the fact that Weber et al. conducted their study for all four seasons instead of just winter. Only three weather categories were used: thunderstorms, heavy fog, and reduced visibility. Their results presented reduced visibility (52%) as the primary year-round cause for flight delays, while thunderstorms and heavy fog were observed with similar frequencies, 25% and 23%, respectively. Given that New York City, with an estimated population of 8.5 million in 2015 ( U.S. Census 2017 ), is the country

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Dana M. Tobin, Matthew R. Kumjian, and Alan W. Black

any precipitation with above-freezing temperatures were reported at nearby weather stations for all warm-season (May–September) sleet and snow entries. To date, it is the only study to filter FARS precipitation types for possible inaccuracies. C18 were the first to correlate FARS atmospheric conditions to weather conditions reported at nearby weather stations, specifically rain, snow, and fog. Therein, FARS fatal crash counts from 2007 to 2014 were matched with Quality Controlled Local

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J. D. Tamerius, X. Zhou, R. Mantilla, and T. Greenfield-Huitt

1. Introduction Approximately 23% of crashes in the United States occur in adverse weather conditions ( U.S. DOT 2011 ). Adverse weather conditions, such as rain, snow, ice, fog, wind, and temperature, are known to increase the frequency of motor vehicle crashes ( Qin et al. 2007 ; Andrey et al. 2003 ; Abdel-Aty et al. 2011 ; Basagaña et al. 2015 ). Precipitation modulates the risk of crashes through reduced visibility and road friction ( Andrey and Yagar 1993 ). A meta-analysis of previous

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Christopher A. Fiebrich, Jadwiga R. Ziolkowska, Phillip B. Chilson, and Elizabeth A. Pillar-Little

operated in a profiling mode at two Oklahoma Mesonet sites, while fixed-wing WxUAS flew transects between the sites. Such data enabled the monitoring of capping inversions, low-level moisture flow, directional wind shear, and atmospheric buoyancy. Other applications that call for improved low-altitude data collection are the prediction of winter precipitation type ( Tripp et al. 2021 ) and fog forecasts. Even though the data resolution of WxUAS profile measurements will likely be lower compared to

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António Lobo, Sara Ferreira, Isabel Iglesias, and António Couto

, cloudy, fog, dust, wind, rain, storm, or snow. Lee and Abdel-Aty (2005) used an ordered probit model to estimate the likelihood of five pedestrian injury severity levels (no injury, possible injury, nonincapacitating evident injury, incapacitating evident injury, and fatal injury). The authors considered, among other effects, the impact of clear versus adverse weather in Florida, having found that adverse weather increases injury severity due to the higher crash impacts caused by the decrease in

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Joshua D. Eachus and Barry D. Keim

mobile telephones. While nearly one-half of respondents want to know about river flooding, winter storms, extreme temperatures, and dense fog, less than 30% want those alerts pushed to their mobile telephones. Fig . 1. Respondent selections of watches and warnings about which they want to know. Fig . 2. Respondent selections of watches and warnings for which they want push notification to their mobile telephone. d. Warning format At the end of the survey, each respondent was randomly shown one of

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Alan W. Black, Gabriele Villarini, and Thomas L. Mote

, ( Bergel-Hayat et al. 2013 ), temperature ( Bergel-Hayat et al. 2013 ; Brijs et al. 2008 ), wind speed and direction ( Brijs et al. 2008 ; Levine et al. 1995 ), and visibility-reducing hazards such as fog, smoke, and dust ( Ashley et al. 2015 ; Abdel-Aty et al. 2011 ) have been examined, most research has focused on crashes during rain and snow. Both frozen precipitation, such as snow, sleet, and freezing rain ( Black and Mote 2015a , b ; Andrey et al. 2013 ; Mills et al. 2011 ; Andrey 2010

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Neda Kazemi, Maryam Sharifzadeh, and Mostafa Ahmadvand

frost-protection practice was applied and was 0 otherwise. The dummy codes are then multiplied with the efficiency weights to produce values corresponding to each behavior and summed. Weighted behavior scores ranged from 4.22 to 12.20. The practices considered are dropped irrigation, surface irrigation, furrow irrigation, wind machines, sprinkling irrigation, fogging, open air heating, burning fuel and tires, foaming insulation, and covering trees with insulating materials (e.g., polyethylene cages

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