As climate changes, coastal communities face increasing threats not only from individual hazards, but from their combined impacts. This study investigates compound coastal flooding (CCF) potential arising from concurrent precipitation and storm surge along the Pacific Coast of North America, focusing on how these interactions may intensify under future scenarios. Using high-resolution multi-model RCP8.5 projections from the Canadian Coastal Climate Risk Information System, we analyzed CCF pattern changes across three future periods through 2100 to capture the evolving nature of joint hazard occurrence. We applied two approaches to identify compound events: (1) conditional block maxima (BM), with separate conditioning on annual maxima of surge and precipitation, and (2) peaks-over-threshold (POT), which isolates co-occurring events where both drivers exceed their 95th percentile thresholds within a short matching window. The choice of method significantly affects the resulting dependence structure. The conditional BM approaches reveal a distinct latitudinal gradient, peaking with positive dependence in the mid-latitudes, while the POT approach captures uniformly lower, but structurally important, correlations domain-wide. Projected joint return periods (JRPs) for extreme compound events exceeding the 98th percentile return level reveal severe, methodology-dependent hazard intensification. BM approaches, particularly when conditioned on annual maximum surge, project substantial northern JRP reductions by 2100; however, weak ensemble signals render these shifts largely indistinguishable from internal climate variability. Backed by strong multi-model consensus for the far future, POT projects a drastic escalation in northern hazard frequency, with compound events in Alaska and British Columbia becoming up to 5 to 10 times more frequent. These findings emphasize that resilient coastal planning requires diverse analytical frameworks.
This study investigates the role of atmospheric rivers (ARs) in modulating precipitation and wildfire activity across South America using the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) together with Moderate Resolution Imaging Spectroradiometer (MODIS) burned area, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) observations. The results reveal widespread declines in AR frequency and AR-associated precipitation across much of the continent, particularly during March–May (MAM) and June–August (JJA) over the Brazilian savanna (Cerrado) and Chaco, regions characterized by extensive burned area and recurrent wildfire activity. Spatial and temporal analyses reveal a dual role of ARs in regional fire dynamics. On short timescales (0–3 months), enhanced AR-associated precipitation suppresses fire activity by increasing fuel moisture and reducing incoming surface solar radiation through greater cloud cover. At longer lags (3–6 months), enhanced moisture availability promotes vegetation growth and fuel accumulation, producing dry biomass that can subsequently increase wildfire susceptibility during the following dry season. In central Brazil, burned area peaks and negative precipitation–fire correlations occur at lags of approximately 3–4 months, highlighting the delayed response of ecosystem productivity and fire occurrence to AR variability. Variations in AR activity are accompanied by large-scale circulation anomalies, including upper-level trough–ridge patterns and changes in Integrated Vapor Transport (IVT), which modulate regional moisture transport, precipitation, and the subsequent vegetation–fire response. These findings demonstrate that future changes in AR frequency and intensity may substantially influence the hydroclimate, vegetation productivity, and wildfire regimes of South America, with important implications for fire early-warning systems, ecosystem management, and climate adaptation strategies.
