Meteotsunamis are atmospherically forced ocean waves with characteristics similar to seismic tsunamis. Several recent hazardous meteotsunamis resulted in damage and injuries along U.S. coastlines, such that the National Oceanic and Atmospheric Administration (NOAA) is investigating ways to detect and forecast meteotsunamis to provide advance warning. Better understanding meteotsunami occurrence along U.S. coastlines is a necessary step to pursue these objectives. Here a meteotsunami climatology of the U.S. East Coast is presented. The climatology relies on a wavelet analysis of 6-min water-level observations from 125 NOAA tide gauges from 1996 to 2017. A total of 548 meteotsunamis, or about per year, were identified and assessed using this approach along the U.S. East Coast. There were a total of 30 instances when gauges observed waves of more than 0.6 m, which is assumed to be a potentially impactful event, and several cases with wave heights more than 1 m. Tide gauges along the open coast observed the most frequent events, including more than five events per year at Atlantic City, New Jersey; Duck, North Carolina; and Myrtle Beach, South Carolina. The largest waves were observed by gauges in estuaries that amplified the meteotsunami signal, such as those in Providence, Rhode Island, and Port Canaveral, Florida. Seasonal trends indicate that meteotsunamis occur most frequently in the winter and summer months, especially July. This work supports future meteotsunami detection and warning capabilities at NOAA, including the development of an impact catalog to aid National Weather Service forecasters.
Abstract. Rip currents pose a major global beach hazard; estimates of annual rip-current-related deaths in the United States alone range from 35 to 100 per year. Despite increased social research into beach-goer experience, little is known about levels of rip current knowledge within the general population. This study describes the results of an online survey to determine the extent of rip current knowledge across the United States, with the aim of improving and enhancing existing beach safety education material. Results suggest that the US-based "Break the Grip of the Rip!" ® campaign has been successful in educating the public about rip current safety directly or indirectly, with the majority of respondents able to provide an accurate description of how to escape a rip current. However, the success of the campaign is limited by discrepancies between personal observations at the beach and rip forecasts that are broadcasted for a large area and time. It was the infrequent beach user that identified the largest discrepancies between the forecast and their observations. Since infrequent beach users also do not seek out lifeguards or take the same precautions as frequent beach users, it is argued that they are also at greatest risk of being caught in a dangerous situation. Results of this study suggest a need for the national campaign to provide greater focus on locally specific and verified rip forecasts and signage in coordination with lifeguards, but not at the expense of the successful national awareness program.
Sea level rise is increasing the frequency of high tide flooding in coastal communities across the United States. Although the occurrence and severity of high-tide flooding will continue to increase, skillful prediction of high tide flooding on monthly-to-annual time horizons is lacking in most regions. Here, we present an approach to predict the daily likelihood of high tide flooding at coastal locations throughout the U.S. using a novel probabilistic modeling approach that relies on relative sea-level rise, tide predictions, and climatological non-tidal residuals as measured by NOAA tide gauges. The structure of the model will also enable future incorporation of mean sea level anomaly predictions from numerical, statistical, and machine learning forecast systems. A retrospective skill assessment using the climatological sea level information indicates that this approach is skillful at 61 out of 92 NOAA tide gauges where at least 10 high tide flood days occurred from 1997–2019. In this case, a flood day occurs when the observed water level exceeds the gauge-specific high tide flood threshold. For these 61 gauges, on average 35% of all floods are accurately predicted using this model, with over half of the floods accurately predicted at 18 gauges. The corresponding False-Alarm-Rate is less than 10% for all 61 gauges. Including mean sea level anomaly persistence at leads of 1 and 3 months further improves model skill in many locations, especially the U.S. Pacific Islands and West Coast. Model skill is shown to increase substantially with increasing sea level at nearly all locations as high tides more frequently exceed the high tide flooding threshold. Assuming an intermediate amount of relative sea level rise, the model will likely be skillful at 93 out of the 94 gauges projected to have regular flooding by 2040. These results demonstrate that this approach is viable to be incorporated into NOAA decision-support products to provide guidance on likely high tide flooding days. Further, the structure of the model will enable future incorporation of mean sea level anomaly predictions from numerical, statistical, and machine learning forecast systems.
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