<p>This study focuses on building a regional index to identify the occurrence of severe storms in Argentina based on large-scale environmental conditions, referred to as the Subtropical South American Severe Index (SSASE) The goal of the study is to assess the capability of the regional index in capturing the spatio-temporal distribution of severe storm occurrence in the region. For building the regional index, a comprehensive database of severe storms covering the period from 1991 to 2020 was gathered, based on multiple sources such as press reports and station reports. The regional index is based on favorable environmental conditions capturing atmospheric instability, the 0 - 500 hPa wind shear and the moisture flux convergence. The addition of the latter, allows including one of the key ingredients for organized convection in the region. Environmental conditions are taken from the ERA5 dataset. Results demonstrate that this approach provides a robust framework for generating a plausible climatology of the occurrence of severe events. The regional index allowed characterizing the annual and diurnal cycles of the occurrence of severe events and improved the representation of local features in comparison with well known indices used worldwide, offering a more accurate depiction of severe storm activity in the region.</p> Graphical Abstract <p>This graphical abstract visually represents the development of a severe storm index based on environmental conditions for Subtropical South America. The methodology integrates hail and tornado reports with pseudo-soundings derived from ERA5 reanalysis. As depicted by the arrows in the workflow, a linear discriminant analysis was applied to classify severe storm environments using CAPE, shear (0–500 hPa), and the vertically integrated moisture flux divergence (VIMFD), calculated from the pseudo-soundings near the reports. This analysis allowed building a regional index based on the behaviour of these environmental features. The index was then used to construct a climatology of severe events. As an example, the final section of the workflow illustrates the yearly frequency of severe events based on the regional index. In addition, the index is also used to explore the diurnal and annual cycles of severe storm occurrence and also its interannual variability. Compared to widely used global indices, this new index better represents local severe storm characteristics, providing a more accurate depiction of storm activity in the region.</p>