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In the last 20 years, extreme weather-related events like floods, landslides, droughts, and wildfires have caused the death of 1.23 million people and a loss of 2.97 trillion dollars. Studies show that low and lower-middle income countries are the most impacted ones given the lack of investment in disaster risk management. To reduce the impact of these events, weather researchers have been developing numerical weather models that inform public agencies about the impending extreme events in advance. Despite being powerful tools, these models can suffer from several sources of uncertainty, ranging from the approximation of micro-scale physical processes to the location-dependent calibration of parameters, which is especially critical in developing countries. To minimize uncertainty effects, researchers generate several different weather scenarios to compose an ensemble of simulations that typically are inspected using manual, laborious, and error-prone approaches. In this paper, we propose an interactive visual analytics system, called X-Weather , developed in close collaboration with weather researchers from Brazil. Our system contributes a set of statistics and probability-based visualizations that allows the assessment of extreme weather events by effortlessly navigating through and comparing ensemble members. We demonstrate the effectiveness of the system through two case studies analyzing tragic events that happened in the mountain region of Rio de Janeiro in Brazil. [Display omitted] • Our visualizations help identify extreme weather scenarios in large simulation ensembles. • Our web-based system enables the investigation of individual weather ensemble members. • Two case studies highlight our system's utility by analyzing extreme weather events. [ABSTRACT FROM AUTHOR]

Urban and sustainable planning considering risk analyzes is urgent given the intensification of extreme natural phenomena. In recent years, more than 25,000 people have been affected by natural hazards in the city of Duque de Caxias (State of Rio de Janeiro - Brazil). This research sought to prepare and provide governmental authorities in the city of Duque de Caxias with an auxiliary tool in order to direct actions aimed at preventing flood risks, urban planning and sustainable development, through the elaboration of the map of areas prone to flooding. The work used the empirical method of combining Analytic Hierarchy Process (AHP) and the GIS platform, giving weights to the following chosen criteria: slope, altitude and land use and occupation. In comparison with the flood data reported between 1996 and 2015 in Duque de Caxias, the results showed that, despite the low quality of data for comparison, the map managed to indicate the areas most susceptible to flooding, proving to be a useful tool for risk management and urban planning in the city. The research showed that the use of AHP for making flood risk maps can be a reliable methodology and applicable to other cities in Brazil. [ABSTRACT FROM AUTHOR]