Extreme weather situations increasingly lead to hazardous situations with high demands on de-cision-making and communication. Weather and impact forecasts serve to prepare for such an emergency situation, and extreme data must be processed during operations. Therefore, extreme data is categorised with reference to global weather data and data from local situation reconnais-sance using sensors carried by mobile robots. A concept is presented in which information quality is explicitly considered in visualization for situational awareness. This extends existing principles of information visualisation with regard to the uncertainty resulting from extreme data. The re-sults are intended to help decision-makers at different management levels to make informed decisions.