Survey of U.S. Adults Reveals Simpler Graph Types Improve Interpretation of Extreme Precipitation

Extreme precipitation events are becoming more frequent and intense, elevating the risk of floods that threaten lives, property, and infrastructure. Climate scientists often create and use visuals to help communicate these hazards. However, many visuals lack careful consideration of how effectively they are understood and used, especially in supporting decision-making, despite established guidelines for effective graph design. Using an online survey of U.S. adults, we tested how graph type influenced the interpretation, usability, and decision-making related to information about extreme precipitation in flood risk scenarios, following diagnostic design guidelines and the System Usability Scale. Our results show that interpreting extreme precipitation data is challenging for most participants, with simpler graph types—such as bar graphs—leading to better understanding and higher usability scores. However, there was no significant impact of graph type on flood risk decisions, perceived likelihood of flooding, or confidence in decision choices. More complex graph types with detailed features or statistics hindered interpretation, despite offering potentially more comprehensive information. These findings suggest that while simpler visualizations improve usability and interpretation, they may sacrifice important details needed for effective flood risk management. The study emphasizes the importance of balancing simplicity with depth in data visualization and highlights the importance of following design guidelines to support better decision-making in the face of climate risks.