Shian Michael

Shian Michael is an independent software publisher whose catalog is hosted on GitHub and focuses on scientific and meteorological tooling for the Python ecosystem. The publisher's current offering consists of a single package, SHARPpy-Reimagined, a modernized reimplementation of sounding analysis and visualization inspired by the SHARPpy (Sounding/Hodograph Analysis and Research Program in Python) project widely used in severe weather forecasting and atmospheric research. The software is built for Python 3.11 and newer and renders its interface through Qt6 via the PySide6 bindings, reflecting a design emphasis on contemporary, actively maintained dependencies rather than legacy frameworks. Its core functionality centers on the analysis and graphical presentation of atmospheric soundings, the vertical profiles of temperature, humidity, and wind that meteorologists use to assess instability, storm potential, and other convective parameters. Data ingest workflows cover three principal sources common in operational and research settings: University of Wyoming (UWyo) upper-air observations, the ECMWF ERA5 global reanalysis dataset, and output from the Weather Research and Forecasting (WRF) numerical model. This combination makes the package suitable for a range of use cases, from real-time operational forecasting and case-study diagnostics to retrospective climatological investigations and model evaluation. Typical users include operational meteorologists, atmospheric science researchers, graduate students, and weather enthusiasts who need interactive, SHARPpy-style skew-T and hodograph rendering without relying on the aging dependencies of the original project. By concentrating on a single, well-defined product within the atmospheric sciences category, the publisher occupies a focused niche in the open-source scientific software landscape, delivering domain-specific analysis and visualization capabilities through a modern, maintainable technology stack.