Temporal compounding increases economic impacts of atmospheric rivers in California.

Temporally compounding atmospheric river (AR) events cause severe flooding and damage in California. However, the contribution of temporal compounding to AR-induced loss has yet to be systematically quantified. We show that the strongest ARs are more likely to be part of sequences, which are periods of elevated hydrologic hazard associated with temporally clustered ARs. Sequences increase the likelihood of flood-related impacts by 8.3% on AR days and 5.4% on non-AR days, and across two independent loss datasets, we find that ARs within sequences have over three times higher expected losses compared to ARs outside of sequences. Expected losses also increase when the preceding AR is higher intensity, when time since the preceding AR is shorter, and when an AR is the second or later event within a sequence. We conclude that temporal compounding is a critical source of information for predicting an AR's potential consequences.

Integrating urban traffic models with coastal flood maps to quantify the resilience of traffic systems to episodic coastal flooding.

Sea level rise and coastal floods are disrupting coastal communities across the world. The impacts of coastal floods are magnified by the disruption of critical urban systems such as transportation. The flood-related closure of low-lying coastal roads and highways can increase travel time delays and accident risk. However, quantifying the flood-related disruption of the urban traffic system presents challenges. Traffic systems are complex and highly dynamic, where congestion resulting from road closures may propagate rapidly from one area to another. Prior studies identify flood-related road closures by spatially overlaying coastal flood maps onto road network models, but simplifications within the representation of the road network with respect to the coastline or creeks may lead to an incorrect identification of flooded roads. We identify three corrections to reduce potential biases in the identification of flooded roads: 1. We correct for the geometry of highways; 2. We correct for the elevation of bridges and highway overpasses; and 3. We identify and account for road-creek crossings. Accounting for these three corrections, we develop a methodology for accurately identifying flooded roads, improving our ability to quantify flood impacts on urban traffic systems and accident rates.

When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond.

As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.

Extreme oceanographic forcing and coastal response due to the 2015-2016 El Niño.

The El Niño-Southern Oscillation is the dominant mode of interannual climate variability across the Pacific Ocean basin, with influence on the global climate. The two end members of the cycle, El Niño and La Niña, force anomalous oceanographic conditions and coastal response along the Pacific margin, exposing many heavily populated regions to increased coastal flooding and erosion hazards. However, a quantitative record of coastal impacts is spatially limited and temporally restricted to only the most recent events. Here we report on the oceanographic forcing and coastal response of the 2015-2016 El Niño, one of the strongest of the last 145 years. We show that winter wave energy equalled or exceeded measured historical maxima across the US West Coast, corresponding to anomalously large beach erosion across the region. Shorelines in many areas retreated beyond previously measured landward extremes, particularly along the sediment-starved California coast.