Enhancing Early Warnings Systems: Training and Insights from Severe Weather Case Studies in Argentina

Argentina plays a strategic role in implementing the Early Warnings for All (EW4All) initiative due to its exposure to diverse and extreme weather events, including severe convective storms in mid-latitudes and heavy rainfall. These hazards pose significant risks to communities, underscoring the need for advanced forecasting techniques and effective early warning systems.

The Department of Atmosphere and Ocean Science (DCAO) from the University of Buenos Aires (UBA) is one of the Argentine components of Regional Satellite Meteorology Training Centers of Excellence (CoE) under the Virtual Laboratory for Education and Training in Satellite Meteorology (VLab) initiative. DCAO-UBA is committed to delivering high-quality education and training for Argentinian students and participants from across Regions RA-III and RA-IV. In particular, its contribution to the EW4ALL initiative focuses on the development of specialized training resources designed to address the distinct challenges of detecting and monitoring extreme weather events using remote sensing. In these resources, two case studies with significant impact are analyzed: a supercell hailstorm on November 11, 2018, and a strong mesoscale convective system associated with heavy precipitation on December 13 and 14, 2018.

The November 11, 2018, hail event was associated with the development of a supercell storm that produced significant severe hail in central Argentina. This event occurred during the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaigns. These campaigns provided an outstanding dataset for studying mid-latitudes severe weather events in Argentina. The storm was captured by multiple observational platforms, including ground-based radars, radiosondes, and surface stations, as well as the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM) onboard GOES-16. In addition, the availability of Mesoscale Domain Sector (MDS) measurements during RELAMPAGO-CACTI represents a unique opportunity for studying severe convective storms development in the region at high temporal resolution. This case study highlights the importance of satellite-based nowcasting tools and their application in real-time severe weather monitoring, contributing to improved early warning capabilities in Argentina.

The heavy precipitation event of December 13-14, 2018, was associated with the development of a strong mesoscale convective system (MCS) in central Argentina. A cold front moving across the region created favorable conditions for deep convection, with large convective available potential energy and strong deep-layer shear supporting the formation of long-lived supercells. During the night, these storms evolved into an intense linear MCS along the eastern slopes of the Córdoba hills. The system produced widespread severe weather, including urban flooding in Córdoba City, which underscores the need for improved forecasting and warning dissemination strategies. This event was documented as part of an Intensive Operation Period (IOP) within the RELAMPAGO field campaign and was later incorporated into the Forecast and Warning of Flash Flood Events (PREVENIR) project. The PREVENIR project seeks to enhance early warning capabilities for flash floods in Argentina by integrating high-resolution numerical weather prediction models with satellite and radar observations. This case exemplifies the challenges of forecasting and issuing timely warnings for high-impact convective events in complex terrain.

Both case studies demonstrate the critical role of satellite data, particularly from geostationary platforms such as GOES-16, in real-time monitoring and early warning applications. The use of ABI and GLM information, combined with ground-based observations, allows improved detection of convective initiation, monitoring of storm development, and assessment of severe weather impacts. These examples serve as training resources to enhance the capabilities of forecasters in the region, reinforcing the objectives of the EW4All initiative.

The DCAO-UBA aims to use these case studies to develop targeted training modules, focusing on best practices for integrating satellite and in-situ data in operational nowcasting. By sharing these experiences, we contribute to the broader goal of strengthening early warning systems across WMO Regions III and IV. This presentation will showcase our methodology for developing training materials, including case study selection, data integration techniques, and instructional design strategies. Additionally, we will discuss lessons learned from this pilot initiative and explore collaboration opportunities with other Centres of Excellence within the EW4All framework.