This paper reports a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level and inclusion of the impact of local interventions in the flooding system. For the first time we consider pluvial, fluvial and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centred on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high quality local models and the entire catalogue of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near future time horizon we project clear patterns of changing flood hazard (-3.8 to +16% changes in 100yr inundated area at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defence protection may become compromised by this time.

Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (1) preconditioned, (2) multivariate, (3) temporally compounding, and (4) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, based on a bottom-up approach, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (1) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (2) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non-stationary multivariate process. For instance, future mean sea-level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (3) In Portugal, deep-landslides are often caused by temporal clusters of moderate precipitation events. Finally, (4) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.