Interconnected Hazards Data

Climate change is exacerbating extreme weather events. While most research typically focuses on individual extremes, such as heatwaves or floods or forest fires, our study aims to explore how different extremes interact and compound, impacting vulnerable communities. We examine the cascading and compounding effects of these events occurring simultaneously in terms of space and time. Specifically, we investigate how factors like temperature, rainfall, and other extreme weather conditions coincide in the United States (US) due to climate change. Using data and forecasts from climate models, we analyze both past and future scenarios. We assess the effects of various extreme events, such as heatwaves, floods, and droughts, on different geographical regions.

Our objective is to identify regions at risk of experiencing multiple extreme events simultaneously and to evaluate the vulnerability of the populations residing there. This enables us to pinpoint the areas in the US most threatened by climate change. Understanding the likelihood of multiple extreme events occurring in areas with vulnerable populations is crucial for future planning and disaster risk reduction efforts. By employing machine learning and data assimilation techniques, this study develops a framework to predict likelihood and impacts of associated hazards and assess vulnerability. With a proper understanding of strength and connections, policymakers can make informed decisions to bolster community resilience. Our study serves as a model for comprehending climate risks not only within the US but also globally.