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Katherine L. Horgan, David M. Schultz, John E. Hales Jr., Stephen F. Corfidi, and Robert H. Johns

by Rochette and Moore (1996) , Rochette et al. (1999) , and Moore et al. (1998 , 2003 ) focused on elevated convective storms that produce heavy rainfall, finding they were associated with elevated instability. Sometimes elevated convection produces severe weather in the form of large hail, strong winds, and/or tornadoes (e.g., Branick et al. 1988 ; Colman 1990b ; Schmidt and Cotton 1989 ; Bernardet and Cotton 1998 ; Banacos and Schultz 2005 ). Grant (1995) examined 11 cases of

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Harold E. Brooks, Charles A. Doswell III, Xiaoling Zhang, A. M. Alexander Chernokulsky, Eigo Tochimoto, Barry Hanstrum, Ernani de Lima Nascimento, David M. L. Sills, Bogdan Antonescu, and Brad Barrett

1. Introduction There are many variations in the definition of what constitutes a severe convective storm. From a physical perspective, a convective storm is one driven by buoyancy. Buoyancy is determined by differences in air density leading to a vertical pressure gradient that is unbalanced by gravity, leading in turn to the development of vertical acceleration ( Doswell and Markowski 2004 ). Note that buoyancy can be either negative or positive, so the vertical acceleration due to buoyancy

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Lawrence D. Carey and Kurt M. Buffalo

1. Introduction Although the overwhelming majority (i.e., about 90%) of ground flashes lower net negative charge across the contiguous United States (CONUS; Orville and Huffines 2001 ), a few severe storms can generate positive cloud-to-ground (+CG) flash rates, densities, and percentages comparable to those typically observed for negative cloud-to-ground (−CG) flashes in active thunderstorms (e.g., MacGorman and Burgess 1994 ; Stolzenburg 1994 ; Carey and Rutledge 1998 ; Lang and Rutledge

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Ruoyun Ma, Jianhua Sun, and Xinlin Yang

1. Introduction Severe convective weather (SCW), such as short-duration heavy rainfall (SDHR), thunderstorm high winds (THWs), and hail, occurs frequently over North China ( J. Chen et al. 2013a ; Yang et al. 2017 ; Li et al. 2018 ) and poses a great threat to life and property in this region. Accurate forecasting of severe convective storms (SCSs) over North China is particularly challenging, as storm initiation and evolution over this region are influenced greatly by the complex underlying

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Robert A. Warren, Harald Richter, and Richard L. Thompson

1. Introduction It has long been recognized that the characteristics of convective storms are strongly governed by the vertical structure of the atmosphere in their immediate environment. Much of our understanding of the relationship between the near-storm environment (NSE) and the occurrence of severe convective weather (tornadoes, large hail, and damaging straight-line winds) stems from the study of proximity soundings, which dates back to the mid-twentieth century ( Showalter and Fulks 1943

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Thea N. Sandmæl, Cameron R. Homeyer, Kristopher M. Bedka, Jason M. Apke, John R. Mecikalski, and Konstantin Khlopenkov

1. Introduction Severe and tornadic storms have been extensively studied using ground-based weather radar and satellite observations during the past four decades. A common goal of past research efforts has been enabling improvements in tornado prediction, which can save lives. Substantial efforts are almost always underway to improve tornado warnings, including ongoing projects like Warn-on-Forecast and the Probability of Severe (ProbSevere) model ( Stensrud et al. 2009 ; Cintineo et al. 2018

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Steven V. Vasiloff and Kenneth W. Howard

1. Introduction During the past 10 yr, the frequency of damaging winds from downbursts occurring in the Phoenix, Arizona, metropolitan area and surrounding suburbs has markedly increased, presumably due to population growth and better reporting ( SPC 2007 ). Within the southwestern U.S. Sonoran Desert, downbursts from severe storms frequently produce strong outflows that entrain dust and reduce visibility to dangerous levels, particularly hazardous to traffic along the Interstate Highway System

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Richard Dworak, Kristopher Bedka, Jason Brunner, and Wayne Feltz

) improve forecaster understanding of OT detection output relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) demonstrate the utility of an OT detection product for diagnosing hazardous convective storms over the continental United States. The volume of data used in this study far exceeds that from previous work, which had primarily relied on a limited sample size of case studies, or in the case of Bedka (2011) , a relatively small severe weather event

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Daniel R. Chavas and Daniel T. Dawson II

1. Introduction While substantial advances have been made in the understanding and prediction of severe convective storms (SCS), operational predictability remains limited and thus substantial risks to life and property persist. Our ability to predict these weather risks in the current or future climate depends crucially on a physical understanding of the dependence of SCS events on their larger-scale environment. Forecasting and research applications have largely focused on bulk (i

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Montgomery L. Flora, Corey K. Potvin, Patrick S. Skinner, Shawn Handler, and Amy McGovern

1. Introduction The National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast program [WoF; Stensrud et al. 2009 , 2013 ] is tasked with providing forecasters with reliable, probabilistic severe weather hazard guidance at very short lead times 1 (e.g., 0–3 h). Though operational convection-allowing models (CAMs) cannot fully resolve convective processes ( Bryan et al. 2003 ), CAMs with ≤3-km horizontal grid spacing can partially resolve important storm-scale features ( Potvin

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