Testing a spaceborne passive‐microwave severe hail retrieval over Argentina using ground‐based dual‐polarization radar data
Year: 2024
Type: article
Abstract: Passive‐microwave hail detection methods rely on the scattering signal produced by large ice hydrometeors. Recently, passive‐microwave hail retrieval methods have been trained by pairing Tropical Rainfall Measuring Mission ( TRMM ) Microwave Imager (TMI) and Global Precipitation Measurement ( GPM ) Microwave Imager (GMI) data with United States surface hail reports to present a global hail climatology. In particular, Southeastern South America (SESA) stands out as a hotspot for hail occurrence, more specifically northeastern Argentina. However, the analysis performed with the available ground hail reports in Argentina shows some differences from the available ground hail reports in Argentina, as it locates the most frequent hail storms in the southwestern (Mendoza and Córdoba) and northeastern (Misiones) regions of SESA. To assess the retrieval from a regional perspective, we take a case study approach and focus on polarization‐corrected temperature features (PCTFs) with a detected . We mainly rely on polarimetric weather radars and a hydrometeor identification algorithm (HID) as a proxy for ground truth. Results indicate that the hail retrieval responds mainly to low 37‐GHz polarized corrected (brightness) temperatures (PCTs) and large PCTF area, while HID outputs show that high probabilities of hail also correspond to abundantly suspended graupel. The observed passive‐microwave hail detection hotspot could be influenced by mesoscale convective systems with deep columns of graupel‐sized frozen hydrometeors, common in northeastern Argentina.
DOI: 10.1002/qj.4861
Institutions: Centre National de la Recherche Scientifique, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos, Institut de Recherche pour le Développement, Marshall Space Flight Center, National Meteorological Service
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403175620