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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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Jeremiah O. Piersante, Russ. S. Schumacher, and Kristen L. Rasmussen

Abstract

Ensemble forecasts using the WRF Model at 20-km grid spacing with varying parameterizations are used to investigate and compare precipitation and atmospheric profile forecast biases in North and South America. By verifying a 19-member ensemble against NCEP Stage IV precipitation analyses, it is shown that the cumulus parameterization (CP), in addition to precipitation amount and season, had the largest influence on precipitation forecast skill in North America during 2016-2017. Verification of an ensemble subset against operational radiosondes in North and South America finds that forecasts in both continents feature a substantial mid-level dry bias, particularly at 700 hPa, during the warm season. Case-by-case analysis suggests that large mid-level error is associated with mesoscale convective systems (MCSs) east of the high terrain and westerly subsident flow from the Rocky and Andes Mountains in North and South America. However, error in South America is consistently greater than North America. This is likely attributed to the complex terrain and higher average altitude of the Andes relative to the Rockies, which allow for a deeper low-level jet and long-lasting MCSs, both of which 20-km simulations struggle to resolve. In the wake of data availability from the RELAMPAGO field campaign, the authors hope that this work motivates further comparison of large precipitating systems in North and South America, given their high impact in both continents.

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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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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 , https://doi.org/10.1175/WAF-D-11-00116.1 . 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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Jake P. Mulholland, Stephen W. Nesbitt, Robert J. Trapp, and John M. Peters

observations of the early evolution of bow echoes . Wea. Forecasting , 19 , 727 – 734 , https://doi.org/10.1175/1520-0434(2004)019<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 complexes . Quart. J. Roy. Meteor. Soc. , 123 , 389 – 405 , https://doi.org/10.1002/qj.49712353807 . 10.1002/qj.49712353807 Letkewicz , C. E. , and M. D. Parker , 2011 : Impact of environmental

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Stephen W. Nesbitt, Paola V. Salio, Eldo Ávila, Phillip Bitzer, Lawrence Carey, V. Chandrasekar, Wiebke Deierling, Francina Dominguez, Maria Eugenia Dillon, C. Marcelo Garcia, David Gochis, Steven Goodman, Deanna A. Hence, Karen A. Kosiba, Matthew R. Kumjian, Timothy Lang, Lorena Medina Luna, James Marquis, Robert Marshall, Lynn A. McMurdie, Ernani Lima Nascimento, Kristen L. Rasmussen, Rita Roberts, Angela K. Rowe, Juan José Ruiz, Eliah F.M.T. São Sabbas, A. Celeste Saulo, Russ S. Schumacher, Yanina Garcia Skabar, Luiz Augusto Toledo Machado, Robert J. Trapp, Adam Varble, James Wilson, Joshua Wurman, Edward J. Zipser, Ivan Arias, Hernán Bechis, and Maxwell A. Grover

Abstract

This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in Córdoba and Mendoza provinces in Argentina, and western Rio Grande do Sul State in Brazil in 2018-2019 that involved more than 200 scientists and students from the US, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates and other unusual lightning phenomena, but few tornadoes. The 5 distinct scientific foci of RELAMPAGO: convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multi-national education, public outreach, and social media data-gathering associated with the campaign, is summarized.

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Sujan Pal, Francina Dominguez, María Eugenia Dillon, Javier Alvarez, Carlos Marcelo Garcia, Stephen W. Nesbitt, and David Gochis

1. Introduction Some of the world’s deepest and largest convective storms develop at the foothills of the Sierras de Córdoba (SDC), a 2000-m north–south mountain range, east of the Andes, located in central Argentina ( Zipser et al. 2006 ). These intense and frequent convective storms organize into mesoscale convective systems (MCSs) and then travel toward the eastern part of Argentina ( Salio et al. 2002 , 2007 ; Rasmussen and Houze 2011 ; Rasmussen et al. 2014 ; Vidal 2014 ; Mulholland

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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 , https://doi.org/10.1175/1520-0434(1992)007<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, https://doi.org/10.1175/0065-9401-28.50.71 . 10

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

convection-allowing NWP . Wea. Forecasting , 23 , 931 – 952 , https://doi.org/10.1175/WAF2007106.1 . 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 , https://doi.org/10.1175/1520-0434(2004)019<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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