An extreme sea level indicator for the contiguous United States coastline

Rashid, M. M.; Wahl, Thomas; Chambers, D. P.; Calafat, Francesc; Sweet, William

doi:10.1038/s41597-019-0333-x

Cited by 33 publications

(29 citation statements)

References 34 publications

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“…Storm tide distributions (Supplementary Figure 3) are more evenly distributed but still show a skewed upper end tail (Box plots of these distributions are shown in Supplementary Figure 4). Many studies have shown extreme high coastal flood levels from tide gauges follow similar extreme value distributions (Tebaldi et al, 2012;Sweet et al, 2014; US Army Corps of Engineers, 2014; Marcos et al, 2015;Moftakhari et al, 2015;Booth et al, 2016;Rashid et al, 2019). The larger population of tidal peak maximum TWL and skew surge , N = 28,231) from which the Delmarva TC-based storm tides and skew surges were extracted, did indeed closely follow the Normal distribution over the long-term once detrended.…”

Section: Delmarva Tropical Cyclone Storm Tide and Skew Surge Summarymentioning

confidence: 79%

“…Wilkerson and Brubaker (2013) investigated the spatial variability of storm surge in the lower Chesapeake Bay over all extreme coastal flooding events but included only a few tropical cyclones. Rashid et al (2019) looked at interannual and multi-decadal variability of extreme storm surge during the peak extratropical (November -April) and tropical (May -October) seasons. Although they included surges from all types of storm events, they concluded that the Mid-Atlantic region varied differently than the Northeast and Southeast portions of the U.S. Atlantic Coast at long time scales.…”

Section: Introductionmentioning

confidence: 99%

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Skew Surge and Storm Tides of Tropical Cyclones in the Delaware and Chesapeake Bays for 1980–2019

2021

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Coastal flooding poses the greatest threat to human life and is often the most common source of damage from coastal storms. From 1980 to 2020, the top 6, and 17 of the top 25, costliest natural disasters in the U.S. were caused by coastal storms, most of these tropical systems. The Delaware and Chesapeake Bays, two of the largest and most densely populated estuaries in the U.S. located in the Mid-Atlantic coastal region, have been significantly impacted by strong tropical cyclones in recent decades, notably Hurricanes Isabel (2003), Irene (2011), and Sandy (2012). Current scenarios of future climate project an increase in major hurricanes and the continued rise of sea levels, amplifying coastal flooding threat. We look at all North Atlantic tropical cyclones (TC) in the International Best Track Archive for Climate Stewardship (IBTrACS) database that came within 750 km of the Delmarva Peninsula from 1980 to 2019. For each TC, skew surge and storm tide are computed at 12 NOAA tide gauges throughout the two bays. Spatial variability of the detrended and normalized skew surge is investigated through cross-correlations, regional storm rankings, and comparison to storm tracks. We find Hurricanes Sandy (2012) and Isabel (2003) had the largest surge impact on the Delaware and Chesapeake Bay, respectively. Surge response to TCs in upper and lower bay regions are more similar across bays than to the opposing region in their own bay. TCs that impacted lower bay more than upper bay regions tended to stay offshore east of Delmarva, whereas TCs that impacted upper bay regions tended to stay to the west of Delmarva. Although tropical cyclones are multi-hazard weather events, there continues to be a need to improve storm surge forecasting and implement strategies to minimize the damage of coastal flooding. Results from this analysis can provide insight on the potential regional impacts of coastal flooding from tropical cyclones in the Mid-Atlantic.

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Section: Delmarva Tropical Cyclone Storm Tide and Skew Surge Summarymentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Skew Surge and Storm Tides of Tropical Cyclones in the Delaware and Chesapeake Bays for 1980–2019

2021

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“…For example, integrating historical records into the tide gauge record of Venice increases the 50‐year ESL by factor 1.3 (Marcos et al., 2009 ). Decadal variability of 50‐year ESL has been found to lie at around 10 cm (Marcos et al., 2015 ; Menendez & Woodworth, 2010 ; Rashid et al., 2019 ).…”

Section: Resultsmentioning

confidence: 99%

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

et al. 2021

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Key Points• We present the first comparison of uncertainties in global to world-regional scale assessments of current and future coastal flood risk. • The largest uncertainty relates to future coastal adaptation, which can influence future coastal flood risk by factors of 20-27. • Uncertainties in socioeconomic development, elevation data, defense levels, emissions and ice sheets can affect risks by factors of 2-6.

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“…We use hourly sea level data from the National Oceanic and Atmospheric Administration (NOAA; http://tidesandcurrents.noaa.gov/) database. Following Rashid et al (2019), we identify 35 sites (Fig. 1) with long records extending back to 1950 or earlier and where time series at individual sites are 80% or more complete.…”

Section: Storm Surgementioning

confidence: 99%

Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline

Nasr¹,

Wahl²,

Rashid³

et al. 2021

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Abstract. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers: oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse for the first time the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis datasets. We assess the overall dependence from observations by using Kendall’s rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find highest dependence between different drivers at locations in the Gulf of Mexico, southeast, and southwest coasts. Regarding different driver combinations, the highest dependence exists between surge-waves, followed by surge-precipitation, surge-discharge, waves-precipitation, and waves-discharge. We also perform a seasonal dependence analysis (tropical vs extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East coast and stronger dependence during the extra-tropical season on the West coast. Finally, we compare the dependence structure of different combinations of flooding drivers using observations and reanalysis data and use the Kullback–Leibler (KL) Divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tail dependence between surge-discharge on the East and West coasts and overestimate tail dependence between surge-precipitation on the East coast, while they underestimate it on the West coast. The comprehensive analysis presented here provides new insights on where compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, during which time of the year (tropical versus extra-tropical season) compound flooding is more likely to occur, and how well reanalysis data captures the dependence structure between the different flooding drivers.

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An extreme sea level indicator for the contiguous United States coastline

Cited by 33 publications

References 34 publications

Skew Surge and Storm Tides of Tropical Cyclones in the Delaware and Chesapeake Bays for 1980–2019

Skew Surge and Storm Tides of Tropical Cyclones in the Delaware and Chesapeake Bays for 1980–2019

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline

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