According to the United Nations Office for Disaster Risk Reduction (UNDRR), the indirect economic losses caused by climate-related disasters increased by over 150 % during 1998–2017 compared to the period 1978– 1997 . Among the most prominent high-impact weather events are flooding, storms, and heatwaves. Scientists need to improve the accuracy and communication of weather forecasting to reduce or even avoid the damage caused by these kinds of weather hazards.
Citizens continuously generate an enormous amount of digital content of diverse kinds, such as blog posts, tweets, and photos and videos. People tend to proactively participate in digital media and communicate this kind of severe weather events in internet channels such as social media, news feeds, and citizen science projects, which represents a huge opportunity to improve current weather forecasting. To engage users in weather forecasting, meteorologists need effective visual communication tools to process the information and make it to citizens.
In this talk, I will present some initial efforts in the visual analysis of citizen-generated data to extract useful information associated with severe weather events and identify expert users among the social networks and a perceptually-based visual design of a mobile application for citizen science on high-impact weather events.
 P.Wallemacq and R. House. UNISDR and CRED report. economic losses, poverty, and disasters 1998–2017. Brussels: Centre for research on the epidemiology of disasters (CRED), 31, 2018.