Case Study: Fluminense Federal Institute improves flood prediction research with Meteomatics Weather API

Fluminense Federal Institute uses Meteomatics to study flooding after Brazil’s 200+ fatal Petrópolis mudslides

The Fluminense Federal Institute is a public education institution in Brazil where PhD candidates Alex Tavares Silva and Larissa Carneiro Rangel were conducting research on mitigating the impacts of flooding. Their challenge was obtaining high-resolution historical and forecast precipitation data, which was essential for their computational modeling and flood prediction algorithms, as other governmental data sources often had gaps in their records or insufficient temporal resolution.

The vendor Meteomatics provided the researchers with special academic access to its Weather API, which supplied the high-resolution meteorological data they needed. Meteomatics' data was used to fill gaps in their records and improve their algorithms, which aim to predict heavy rainfall and enable more effective urban infrastructure planning to mitigate floods. The researchers reported a very good experience with the API, specifically highlighting its Python module as a potential tool that works well with computational intelligence algorithms.

Fluminense Federal Institute