Automated Application for Visualizing Rainfall and Hail Estimations Derived from an Algorithm Based on Meteosat Multispectral Image Data

Abstract

The scope of this study is an attempt to develop an automated visualization module to monitor rainfall and hail estimations in real-time, highlighting areas with potential risk from extreme weather phenomena. The rainfall/hail products are provided by a known satellite-based algorithm that uses exclusively Meteosat multispectral images. 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 predefined 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 h before the latest available satellite images.

Keywords

• visualization
• meteosat
• rainfall estimations
• automated application
• real-time monitoring