Search for: All records

Successive atmospheric river (AR) events—known as AR families—can result in prolonged and elevated hydrological impacts relative to single ARs due to the lack of recovery time between periods of precipitation. Despite the outsized societal impacts that often stem from AR families, the large-scale environments and mechanisms associated with these compound events remain poorly understood. In this work, a new reanalysis-based 39-yr catalog of 248 AR family events affecting California between 1981 and 2019 is introduced. Nearly all (94%) of the interannual variability in AR frequency is driven by AR family versus single events. Usingk-means clustering on the 500-hPa geopotential height field, six distinct clusters of large-scale patterns associated with AR families are identified. Two clusters are of particular interest due to their strong relationship with phases of El Niño–Southern Oscillation (ENSO). One of these clusters is characterized by a strong ridge in the Bering Sea and Rossby wave propagation, most frequently occurs during La Niña and neutral ENSO years, and is associated with the highest cluster-average precipitation across California. The other cluster, characterized by a zonal elongation of lower geopotential heights across the Pacific basin and an extended North Pacific jet, most frequently occurs during El Niño years and is associated with lower cluster-average precipitation across California but with a longer duration. In contrast, single AR events do not show obvious clustering of spatial patterns. This difference suggests that the potential predictability of AR families may be enhanced relative to single AR events, especially on subseasonal to seasonal time scales.

 

Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high‐resolution hydrodynamic flood model—allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100‐year precipitation event of ~20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a ~30–127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events—suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century.

 

Escalating wildfire activity in the western United States has accelerated adverse societal impacts. Observed increases in wildfire severity and impacts to communities have diverse anthropogenic causes—including the legacy of fire suppression policies, increased development in high-risk zones, and aridification by a warming climate. However, the intentional use of fire as a vegetation management tool, known as “prescribed fire,” can reduce the risk of destructive fires and restore ecosystem resilience. Prescribed fire implementation is subject to multiple constraints, including the number of days characterized by weather and vegetation conditions conducive to achieving desired outcomes. Here, we quantify observed and projected trends in the frequency and seasonality of western United States prescribed fire days. We find that while ~2 C of global warming by 2060 will reduce such days overall (−17%), particularly during spring (−25%) and summer (−31%), winter (+4%) may increasingly emerge as a comparatively favorable window for prescribed fire especially in northern states. 

Climate change is increasing the likelihood of an extreme storm sequence capable of generating severe flooding in California. 

Post-wildfire extreme rainfall events may more than double over the western United States this century. 

Abstract Precipitation extremes will increase in a warming climate, but the response of flood magnitudes to heavier precipitation events is less clear. Historically, there is little evidence for systematic increases in flood magnitude despite observed increases in precipitation extremes. Here we investigate how flood magnitudes change in response to warming, using a large initial-condition ensemble of simulations with a single climate model, coupled to a hydrological model. The model chain was applied to historical (1961–2000) and warmer future (2060–2099) climate conditions for 78 watersheds in hydrological Bavaria, a region comprising the headwater catchments of the Inn, Danube and Main River, thus representing an area of expressed hydrological heterogeneity. For the majority of the catchments, we identify a ‘return interval threshold’ in the relationship between precipitation and flood increases: at return intervals above this threshold, further increases in extreme precipitation frequency and magnitude clearly yield increased flood magnitudes; below the threshold, flood magnitude is modulated by land surface processes. We suggest that this threshold behaviour can reconcile climatological and hydrological perspectives on changing flood risk in a warming climate.