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Abstract Sea‐level change threatens the U.S. East Coast. Thus, it is important to understand the underlying causes, including ocean dynamics. Most past studies emphasized links between coastal sea level and local atmospheric variability or large‐scale circulation and climate, but possible relationships with local ocean currents over the shelf and slope remain largely unexplored. Here we use 7 years of in situ velocity and sea‐level data to quantify the relationship between northeastern U.S. coastal sea level and variable Shelfbreak Jet transport south of Nantucket Island. At timescales of 1–15 days, southern New England coastal sea level and transport vary in anti‐phase, with magnitude‐squared coherences of ∼0.5 and admittance amplitudes of ∼0.3 m Sv⁻¹. These results are consistent with a dominant geostrophic balance between along‐shelf transport and coastal sea level, corroborating a hypothesis made decades ago that was not tested due to the lack of transport data. 

Abstract Coastal aquifers supply freshwater to nearly half the global population, yet they are threatened by salinization. Salinities are typically estimated assuming steady‐state, neglecting the effect of cyclical forcings on average salinity distributions. Here, numerical modeling is used to test this assumption. Multi‐scale fluctuations in sea level (SL) are simulated, from tides to glacial cycles. Results show that high‐frequency fluctuations alter average salinities compared with the steady‐state distribution produced by average SL. Low‐frequency forcing generates discrepancies between present‐day salinities estimated with and without considering the cyclical forcing due to overshoot effects. This implies that salinities in coastal aquifers may be erroneously estimated when assuming steady‐state conditions, since present distributions are likely part of a dynamic steady state that includes forcing on multiple timescales. Further, typically neglected aquifer storage characteristics can strongly control average salinity distributions. This has important implications for managing vulnerable coastal groundwater resources and for calibration of hydrogeological models. 

Waves running up and down the beach (‘swash’) at the landward edge of the ocean can cause changes to the beach topology, can erode dunes, and can result in inland flooding. Despite the importance of swash, field observations are difficult to obtain in the thin, bubbly, and potentially sediment laden fluid layers. Here, swash excursions along an Atlantic Ocean beach are estimated with a new framework, V-BeachNet, that uses a fully convolutional network to distinguish between sand and the moving edge of the wave in rapid sequences of images. V-BeachNet is trained with 16 randomly selected and manually segmented images of the swash zone, and is used to estimate swash excursions along 200 m of the shoreline by automatically segmenting four 1-h sequences of images that span a range of incident wave conditions. Data from a scanning lidar system are used to validate the swash estimates along a cross-shore transect within the camera field of view. V-BeachNet estimates of swash spectra, significant wave heights, and wave-driven setup (increases in the mean water level) agree with those estimated from the lidar data. 

Reconnaissance following Hurricane Ida. Wind damage to light structures, flooding, levee failures, coastal erosion. Field photos, Lidar, UAVs. 

Tropical cyclones and other extreme coastal storms cause widespread interruption and damage to meteorological and hydrological measurement stations exactly when researchers need them most. There is a longstanding need to collect collocated and synchronized measurements in areas where storms severely damage civil/coastal infrastructure. To fill this observational gap, researchers led by author Masters developed a state-of-the-art monitoring station called a “Sentinel.” Sentinels are intended for temporary installation on the beach between the mean tidal datum and the sand dunes and are engineered to operate in and measure extreme wind, storm surge, wave, and hazardous water quality conditions. They are envisioned as a shared-use resource—a hardened IoT (Internet of Things) platform set up in the right place at the right time to study wind and wave loads, coastal erosion and morphology changes, water quality, and other processes during extreme coastal storms. 

RAPID Facility staff collected pre-hurricane coastal UAS imagery on September 26 - 27, 2022.