Automated application for visualizing rainfall and hail estimations derived from an algorithm based on Meteosat multispectral image data.

The real-time monitoring of crucial meteorological parameters derived from geostationary satellites is considered of high importance given the fact that they provide high local-scale accuracy about their spatiotemporal evolution, and consequently, the potential damages from extreme weather to infrastructure and private properties can be eliminated. The scope of this study is an attempt to automatically visualize in real-time rainfall and hail estimations coming from a known satellite-based algorithm that uses Meteosat multispectral imagery exclusively. The application is fully automated, written in the Python programming environment using open-source libraries, and provides colored graphs about the spatial variation of the examined parameters with the same temporal resolution as the Meteosat imagery. Additional functions of this application include warnings for extreme situations each time pre-defined threshold values are exceeded, as well as geographical areas that are vulnerable to heavy rainfall and/or hail occurrences. This application is a pilot operating over the Greek periphery. Also, there is a capability to create small video animations for the spatiotemporal evolution of the rainfall and hail estimations up to 6 hours before the latest available satellite images.