scholarly journals Atmospheric Rivers Spur High-Tide Floods on U.S. West Coast

Eos ◽  
2021 ◽  
Vol 102 ◽  
Author(s):  
Guanan� G�mez-Van Cortright

Researchers analyzed 36 years of data to understand how atmospheric rivers and other factors drive chronic coastal flooding.

2021 ◽  
Author(s):  
Christopher G Piecuch ◽  
Sloan Coats ◽  
Sönke Dangendorf ◽  
Felix W Landerer ◽  
J T Reager ◽  
...  

2021 ◽  
Author(s):  
Christopher G Piecuch ◽  
Sloan Coats ◽  
Sönke Dangendorf ◽  
Felix W Landerer ◽  
J T Reager ◽  
...  

2020 ◽  
Author(s):  
Peter Robins ◽  
Lisa Harrison ◽  
Mariam Elnahrawi ◽  
Matt Lewis ◽  
Tom Coulthard ◽  
...  

<p>Coastal flooding worldwide causes the vast majority of natural disasters; for the UK costing £2.2 billion/year. Fluvial and surge-tide extremes can occur synchronously resulting in combination flooding hazards in estuaries, intensifying the flood risk beyond fluvial-only or surge-only events. Worse, this flood risk has the potential to increase further in the future as the frequency and/or intensity of these drivers change, combined with projected sea-level rise. Yet, the sensitivity of contrasting estuaries to combination and compound flooding hazards at sub-daily scales – now and in the future – is unclear. Here, we investigate the dependence between fluvial and surge interactions at sub-daily scales for contrasting catchment and estuary types (Humber vs. Dyfi, UK), using 50+ years of data: 15-min fluvial flows and hourly sea levels. Additionally, we simulate intra-estuary (<50 m resolution) sensitivities to combination flooding hazards based on: (1) realistic extreme events (worst-on-record); (2) realistic events with shifted timings of the drivers to maximise flooding; and (3) modified drivers representing projected climate change.</p><p>For well-documented flooding events, we show significant correlation between skew surge and peak fluvial flow, for the Dyfi (small catchment and estuary with a fast fluvial response on the west coast of Britain), with a higher dependence during autumn/winter months. In contrast, we show no dependence for the Humber (large catchment and estuary with a slow fluvial response on the east coast of Britain). Cross-correlation results, however, did show correlation with a time lag (~10 hours). For the Dyfi, flood extent was sensitive to the relative timing of the fluvial and surge-tide drivers. In contrast, the relative timing of these drivers did not affect flooding in the Humber. However, extreme fluvial flows in the Humber actually reduced water levels in the outer estuary, compared with a surge-only event. Projected future changes in these drivers by 2100 are likely to increase combination flooding hazards: sea-level rise scenarios predicted substantial and widespread flooding in both estuaries. However, similar increases in storm surge resulted in a greater seawater influx, altering the character of the flooding. Projected changes in fluvial volumes were the weakest driver of estuarine flooding. On the west coast of Britain containing many small/steep catchments, combination flooding hazards from fluvial and surges extremes occurring together is likely. Moreover, high-resolution data and hydrodynamic modelling are necessary to resolve the impact and inform flood mitigation methodology.</p>


2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jiayi Fang ◽  
Peijun Shi

The sea level rise under global climate change and coastal floods caused by extreme sea levels due to the high tide levels and storm surges have huge impacts on coastal society, economy, and natural environment. It has drawn great attention from global scientific researchers. This study examines the definitions and elements of coastal flooding in the general and narrow senses, and mainly focuses on the components of coastal flooding in the narrow sense. Based on the natural disaster system theory, the review systematically summarizes the progress of coastal flood research in China, and then discusses existing problems in present studies and provide future research directions with regard to this issue. It is proposed that future studies need to strengthen research on adapting to climate change in coastal areas, including studies on the risk of multi- hazards and uncertainties of hazard impacts under climate change, risk assessment of key exposure (critical infrastructure) in coastal hotspots, and cost-benefit analysis of adaptation and mitigation measures in coastal areas. Efforts to improve the resilience of coastal areas under climate change should be given more attention. The research community also should establish the mechanism of data sharing among disciplines to meet the needs of future risk assessments, so that coastal issues can be more comprehensively, systematically, and dynamically studied.


2016 ◽  
Vol 121 (22) ◽  
pp. 13,287-13,300 ◽  
Author(s):  
Ashley E. Payne ◽  
Gudrun Magnusdottir

2014 ◽  
Vol 27 (18) ◽  
pp. 7133-7150 ◽  
Author(s):  
Ashley E. Payne ◽  
Gudrun Magnusdottir

Abstract A large-scale analysis of landfalling atmospheric rivers (ARs) along the west coast of North America and their association with the upper-tropospheric flow is performed for the extended winter (November–March) for the years 1979–2011 using Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis data. The climatology, relationship to the El Niño–Southern Oscillation and the Madden–Julian oscillation, and upper-level characteristics of approximately 750 landfalling ARs are presented based on the 85th percentile of peak daily moisture flux. AR occurrence along the West Coast is dominated by early season events. In composites of upper-level fields during AR occurrences, certain characteristics stand out irrespective of the tropical climate indices. This suggests that extratropical dynamical processes play a key role in AR dynamics. The influence of the large-scale circulation on AR intensity prior to landfall is examined by objectively selecting an extreme subset of 112 landfalling AR dates representing the 95th percentile of strongest cases. Each landfalling AR date that is identified is traced backward in time using a novel semiautomated tracking algorithm based on spatially and temporally connected organized features in integrated moisture transport. Composites of dynamical fields following the eastward progression of ARs show a close relationship of the location of the jet, Rossby wave propagation, and anticyclonic Rossby wave breaking in the upper troposphere of the eastern Pacific and moisture transport in the lower troposphere. Comparison between the strongest and the weakest ARs within the most extreme subset shows differences in both the intensity of moisture transport and the scale and development of anticyclonic Rossby wave breaking in the eastern Pacific.


Author(s):  
Qian Cao ◽  
Shraddhanand Shukla ◽  
Michael J. DeFlorio ◽  
F. Martin Ralph ◽  
Dennis P. Lettenmaier

AbstractAtmospheric rivers (ARs) are responsible for up to 90% of major flood events along the U.S. West Coast. The timescale of subseasonal forecasting (two weeks to one month) is a critical lead time for proactive mitigation of flood disasters. The NOAA/Climate Testbed Subseasonal Experiment (SubX) is a research-to-operations project with almost immediate availability of forecasts. It has produced a reforecast database that facilitates evaluation of flood forecasts at these subseasonal lead times. Here, we examine the SubX driven forecast skill of AR-related flooding out to 4-week lead using the Distributed Hydrology Soil Vegetation Model (DHSVM), with particular attention to the role of antecedent soil moisture (ASM), which modulates the relationship between meteorological and hydrological forecast skill. We study three watersheds along a transect of the U.S. West Coast: the Chehalis River basin in Washington, the Russian River basin in Northern California, and the Santa Margarita River basin in Southern California. We find that the SubX driven flood forecast skill drops quickly after week 1, during which there is relatively high deterministic forecast skill. We find some probabilistic forecast skill relative to climatology as well as ensemble streamflow prediction (ESP) in week 2, but minimal skill in weeks 3-4, especially for annual maximum floods, notwithstanding some probabilistic skill for smaller floods in week 3. Using ESP and reverse-ESP experiments to consider the relative influence of ASM and SubX reforecast skill, we find that ASM dominates probabilistic forecast skill only for small flood events at week 1, while SubX reforecast skill dominates for large flood events at all lead times.


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