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T. Connor Nelson, James Marquis, Adam Varble, and Katja Friedrich

context of the surrounding mesoscale heterogeneity, and section 4 analyzes profiles deemed best representative of the near-cloud environment of successful and unsuccessful CI events. Summary and conclusions are presented in section 5 . 2. Data overview An ensemble of Weather Research and Forecasting (WRF) convection-allowing numerical models (CAMs), employing 3–4-km horizontal grid spacing, were run by various institutions participating in the project, including the Colorado State University (CSU

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Zhixiao Zhang, Adam Varble, Zhe Feng, Joseph Hardin, and Edward Zipser

, S. S. , and W. M. Frank , 1993 : A numerical study of the genesis of extratropical convective mesovortices. Part I: Evolution and dynamics . J. Atmos. Sci. , 50 , 2401 – 2426 ,<2401:ANSOTG>2.0.CO;2 . 10.1175/1520-0469(1993)050<2401:ANSOTG>2.0.CO;2 Clarke , S. J. , S. L. Gray , and N. M. Roberts , 2019 : Downstream influence of mesoscale convective systems. Part 1: Influence on forecast evolution . Quart. J. Roy. Meteor. Soc. , 145

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Jeremiah O. Piersante, Kristen L. Rasmussen, Russ S. Schumacher, Angela K. Rowe, and Lynn A. McMurdie

subtropical South America (SSA) are deeper and more frequent than those east of the Rocky Mountains in North America ( Zipser et al. 2006 ; Houze et al. 2015 ). Specifically, the cloud shields associated with SSA mesoscale convective systems (MCSs) are approximately 60% larger than those occurring in the continental United States (CONUS; Velasco and Fritsch 1987 ) and their precipitation areas are larger and longer lived ( Durkee et al. 2009 ; Durkee and Mote 2010 ), contributing up to ~95% of warm

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Russ S. Schumacher, Deanna A. Hence, Stephen W. Nesbitt, Robert J. Trapp, Karen A. Kosiba, Joshua Wurman, Paola Salio, Martin Rugna, Adam C. Varble, and Nathan R. Kelly

significant severe thunderstorms in the contiguous United States. Part II: Supercell and QLCS tornado environments . Wea. Forecasting , 27 , 1136 – 1154 , . 10.1175/WAF-D-11-00116.1 Trapp , R. J. , D. J. Stensrud , M. C. Coniglio , R. S. Schumacher , M. E. Baldwin , S. Waugh , and D. T. Conlee , 2016 : Mobile radiosonde deployments during the Mesoscale Predictability Experiment (MPEX): Rapid and adaptive sampling of upscale convective

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James N. Marquis, Adam C. Varble, Paul Robinson, T. Connor Nelson, and Katja Friedrich

. This work was aided by an undergraduate research assistant at the University of Colorado, Thomas Jarman. Data availability statement Data utilized are available on NCAR’s Earth Observing Laboratory and ARM’s Data Discovery catalogs. REFERENCES Alexander , L. S. , D. M. Sills , and P. A. Taylor , 2018 : Initiation of convective storms at low-level mesoscale boundaries in southwestern Ontario . Wea. Forecasting , 33 , 583 – 598 , . 10.1175/WAF-D-17

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Robert J. Trapp, Karen A. Kosiba, James N. Marquis, Matthew R. Kumjian, Stephen W. Nesbitt, Joshua Wurman, Paola Salio, Maxwell A. Grover, Paul Robinson, and Deanna A. Hence

representative of an average of the lowest 100-hPa of the atmosphere from each sounding are shown with dotted lines. One of the forecast uncertainties during IOP4 was the geographical location and timing of the initiation of deep convection, especially given the strength of the capping inversion and associated convective inhibition (CIN) present in the 1200 UTC soundings ( Fig. 3 ). Parcel lifting was expected in association with horizontal moisture convergence along an east–west-oriented mesoscale boundary

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Jake P. Mulholland, Stephen W. Nesbitt, Robert J. Trapp, Kristen L. Rasmussen, and Paola V. Salio

.1002/2015RG000488 . 10.1002/2015RG000488 Johns , R. H. , and C. A. Doswell , 1992 : Severe local storms forecasting . Wea. Forecasting , 7 , 588 – 612 ,<0588:SLSF>2.0.CO;2 . 10.1175/1520-0434(1992)007<0588:SLSF>2.0.CO;2 Johnson , R. H. , and B. E. Mapes , 2001 : Mesoscale processes and severe convective weather. Severe Convective Storms , Meteor. Monogr. , No. 50, Amer. Meteor. Soc., 71–122, . 10

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Jake P. Mulholland, Stephen W. Nesbitt, and Robert J. Trapp

convection-allowing NWP . Wea. Forecasting , 23 , 931 – 952 , . 10.1175/WAF2007106.1 Klimowski , B. A. , M. R. Hjelmfelt , and M. J. Bunkers , 2004 : Radar observations of the early evolution of bow echoes . Wea. Forecasting , 19 , 727 – 734 ,<0727:ROOTEE>2.0.CO;2 . 10.1175/1520-0434(2004)019<0727:ROOTEE>2.0.CO;2 Laing , A. G. , and J. M. Fritsch , 1997 : The global population of mesoscale convective

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Zachary S. Bruick, Kristen L. Rasmussen, and Daniel J. Cecil

the understanding of how, why, and when hailstorms form and what characteristics may differentiate them from convection that does not produce hail. Through this analysis, a more comprehensive understanding of the climatology of hail and hail-producing environments will be presented. The results from this study will provide context for the results of the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign (1

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Zachary S. Bruick, Kristen L. Rasmussen, Angela K. Rowe, and Lynn A. McMurdie

circulations modulate global circulations by disrupting the propagation of Rossby waves generated by tropical convection ( Grimm and Ambrizzi 2009 ). Therefore, ENSO impacts convection globally. In the United States, increased rainfall from mesoscale convective systems (MCSs) ( Anderson and Arritt 2001 ) and increased precipitation over the southern states and Gulf of Mexico ( Dai 2001 ; Lee et al. 2014 ) are correlated with El Niño, while more severe weather events in the southeast United States occur

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