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William V. Sweet
and
Chris Zervas

Abstract

Climatologies of sea level anomalies (>0.05 m) and daily-mean storm surges (>0.3 m) are presented for the 1960–2010 cool seasons (October–April) along the East Coast of the United States at Boston, Massachusetts; Atlantic City, New Jersey; Sewells Point (Norfolk), Virginia; and Charleston, South Carolina. The high sea level anomaly and the number of storm surges, among the highest in the last half century during the 2009/10 cool season, are comparable during strong El Niño cool seasons. High numbers of daily storm surges occur in response to numerous East Coast extratropical cool-season storms and have a positive correlation with the El Niño phase of the El Niño–Southern Oscillation (ENSO). Patterns of anomalously high sea levels are attributed to El Niño–related changes to atmospheric pressure over the Gulf of Mexico and eastern Canada and to the wind field over the Northeast U.S. continental shelf.

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Joseph Park
,
Robert Heitsenrether
, and
William Sweet

Abstract

The National Oceanic and Atmospheric Administration (NOAA) is transitioning the primary water level sensor at the majority of tide stations in the National Water Level Observation Network (NWLON) from an acoustic ranging system to a microwave radar system. Field comparison of the acoustic and microwave systems finds statistically equivalent performance when temperature gradients between the acoustic sensor and water surface are small and when significant wave height is less than roughly 0.5 m. When significant wave height is greater than approximately 0.5–1 m, the acoustic system consistently reports lower water levels. An analysis of 2 months of acoustic and microwave water level data at Duck, North Carolina, finds that the majority of differences between the two sensors can be attributed to systemic errors in the acoustic system and that the microwave system captures water level variability with higher fidelity than the acoustic system. NWLON real-time data products include the water level standard deviation, a statistic that can serve as a proxy for significant wave height. This study identifies 29 coastal water level stations that are candidates for monitoring wave height based on water level standard deviation, potentially adding a significant source of data for the sparsely sampled coastal wave fields around the United States, and finds that the microwave sensor is better suited than the acoustic system for wave height estimates.

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Katie Kirk
,
Gregory Dusek
,
Philippe Tissot
, and
William Sweet

Abstract

The demand for nearshore wave observations is increasing due to spatial gaps and the importance of observations for accurate models and better understanding of inundation processes. Here, we show how water level (WL) standard deviation (sigma, σ) measurements at three acoustic NOAA tide gauges that utilize an Aquatrak sensor [Duck, North Carolina, Bob Hall Pier (BHP) in Corpus Christi, Texas, and Lake Worth, Florida] can be used as a proxy for significant wave height (H m0). Sigma-derived H m0 is calibrated to best fit nearby wave observations and error is quantified through RMSE, normalized RMSE (NRMSE), bias, and a scatter index. At Duck and Lake Worth, a quadratic fit of sigma to nearby wave observations results in a R 2 of 0.97 and 0.83, RMSE of 0.11 and 0.11 m, and NRMSE of 0.09 and 0.22, respectively. A linear fit between BHP sigma and H m0 is best, resulting in R 2 0.62, RMSE of 0.22, and NRMSE of 0.26. Regression fits deviate across NOAA stations and from the classic relationship of H m0 = 4σ, indicating H m0 cannot be accurately estimated with this approach at these Aquatrak sites. The dynamic water level (DWL = still WL ± 2σ) is calculated over the historic time series showing climatological and seasonal trends in the stations’ daily maximums. The historical DWL and sigma wave proxy could be calculated for many NOAA tide gauges dating back to 1996. These historical wave observations can be used to fill observational spatial gaps, validate models, and improve understanding of wave climates.

Significance Statement

There is a large spatial gap in nearshore real-time observational wave data that can provide critical information to researchers and resource managers regarding inundation and erosion, help validate coastal hydrodynamic models, and provide the maritime community with products that help ensure navigational safety. This study utilizes existing infrastructure to help fill the demand for nearshore wave observations by deriving a proxy for wave height at three sites. This work shows spatial variability in the regression fits across the sites, which should be explored at more stations in future work. Multidecadal length time series were also used at the sites to investigate climatological and seasonal trends that provide insight into wave climates and wave driven processes important for coastal flooding.

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Fredric Lipschultz
,
David D. Herring
,
Andrea J. Ray
,
Jay Alder
,
LuAnn Dahlman
,
Arthur DeGaetano
,
James F. Fox
,
Edward Gardiner
,
Jamie Herring
,
Jeff Hicks
,
Forrest Melton
,
Philip E. Morefield
, and
William V. Sweet
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