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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 the Córdoba and Mendoza provinces in Argentina and western Rio Grande do Sul State in Brazil in 2018–19 that involved more than 200 scientists and students from the United States, 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 five 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 multinational education, public outreach, and social media data gathering associated with the campaign, is summarized. [ABSTRACT FROM AUTHOR]

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain. [ABSTRACT FROM AUTHOR]

• This work presents the longest radar-based climatology of supercells storms using weather radar data in central Argentina. • Predominance of cyclonic supercells (a ratio of 90 • The characteristics of the pre-convective environments associated with supercells in Paraná have yielded similarities to Córdoba region (Argentina). • The Storm Relative Helicity deficit in the 0–1 and 0–3 km layers generates the greatest differences between the pre-convective environments associated with supercells between central and Eastern Argentina and U.S. Great Plains. • The previous point suggests the need to adapt the thresholds of those environmental parameters that particularly depend on the helicity relative to the storm in central-eastern Argentina if they are to be used for forecasting purposes in this region. Some of the strongest storms on Earth occur over central-eastern Argentina. These storms are associated with severe weather phenomena such as big hail, heavy rain, intense wind gusts, and, occasionally, tornadoes. The relatively recent expansion of the radar network in this area brings the chance to better characterize severe weather storms. This study presents a nine-year climatology of supercells (SCs) and their associated mesocyclones (MCs) based on radar data over central Argentina, together with a preliminary analysis of the thermodynamic environment in which they develop. We propose an MC detection algorithm based on the Non-Maximum Suppression (NMS) technique and a subjective classification. The MCs have shown a mean lifetime of 73 min, with their maximum intensity located at 4.7 km above ground level (AGL) on average. The monthly frequency of SCs in central-eastern Argentina is similar to that reported in previous studies near the Sierras de Córdoba, with two relative maxima, one in November and the other one in February, and with an absolute minimum in June. The diurnal cycle shows an absolute maximum at around 0100 UTC (2200 local time) and a minimum between 0900 and 1500 UTC (0600 and 1200 local time). Based on the results obtained here, the pre-convective environments associated with SCs in the Paraná region are very similar to its analogs in the Sierras de Córdoba. They are characterized by high values of convective instability and vertical wind shear. Storm relative helicity (in the low and middle layers) and wind shear in the first kilometer above the surface are lower than those found in the U.S. Great Plains. Although the analysis shows that there are environmental parameters that can discriminate well between SC and non-SC events, their values are shown to be far from the thresholds considered in the U.S. Results hence suggest the need to adapt the thresholds of some of the parameters studied here, particularly those based on storm-relative helicity, to central-eastern Argentina. [ABSTRACT FROM AUTHOR]

Storms in central Argentina are known for producing large and severe hail. Environmental conditions and strong interaction with topography in this region provide unique conditions for the initiation and intensification of severe storms. The RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations) and CACTI (Clouds, Aerosols, and Complex Terrain Interactions) field campaigns deployed between October 2018 and April 2019 over west-central Argentina have collected unprecedented periods of intensive observation in the region. During the Intense Observation Period (IOP) number 10 (November 26, 2018), 4 cm diameter hail was reported over wide areas of the province of Mendoza. This was the first time a severe hailstorm was measured with multi-platform observations in Mendoza as the IOP deployment included multiple atmospheric soundings, observations from the Center for Severe Weather Research (CSWR) Doppler on Wheel radars (DOWs) and high temporal resolution satellite data from the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM) onboard GOES-16. High-temporal frequency soundings and surface observations collected prior to the convection initiation are analyzed, allowing a detailed description of the pre-convective environment. The establishment of the upslope flow and the role of boundary layer processes that resulted in the development of the severe hailstorm are also analyzed. In addition, several GOES-16 ABI and GLM derived products are investigated, in order to test their ability to forecast convective initiation and provide hail proxies in the region. • A hailstorm in Mendoza is observed with the instruments available during RELAMPAGO. • Upslope flow, diurnal mixing and a shortwave trough promotes convection initiation. • Supercell development over the lower terrain favoured severe hail formation. • GOES-16 GLM- and ABI-based algorithms show skill to forecast storm severity. [ABSTRACT FROM AUTHOR]