Sea breeze winds are observed at various locations worldwide, but the spatially continuous mapping of sea breeze winds is rare. We have developed a scheme to map the areas of the southeastern United States (SEUS) coast influenced by sea breeze winds using a range of surface re‐analysis data to identify their occurrence. Changes in wind direction and dew point temperature are both used to detect a potential sea breeze signature, which is then confirmed by cumuliform clouds seen in satellite images or coastal fronts shown as cohesive lines in radar reflectivity images. Filters are employed to remove onshore winds not induced by the temperature difference between land and sea. From March to September 2019, this scheme identified 134 days with sea breeze occurrence somewhere in the SEUS, a frequency of 63 percent. The number of sea breezes increased from March to July and then decreased to September. Deep inland propagation of sea breezes during this period left footprints in a band parallel to the coastline up to about 220 km inland, after which the sea breeze winds quickly diminished. Comparisons show that the findings using the scheme are consistent with site observations, theoretical estimates, and idealized and semi‐idealized numerical model simulations.

Extreme atmospheric wind and precipitation events have created extensive multiscale coastal, inland, and upland flooding in United States (U.S.) coastal states over recent decades, some of which takes days to hours to develop, while others can take only several tens of minutes and inundate a large area within a short period of time, thus being laterally explosive. However, their existence has not yet been fully recognized, and the fluid dynamics and the wide spectrum of spatial and temporal scales of these types of events are not yet well understood nor have they been mathematically modeled. If present-day outlooks of more frequent and intense precipitation events in the future are accurate, these coastal, inland and upland flood events, such as those due to Hurricanes Joaquin (2015), Matthew (2016), Harvey (2017) and Irma (2017), will continue to increase in the future. However, the question arises as to whether there has been a well-documented example of this kind of coastal, inland and upland flooding in the past? In addition, if so, are any lessons learned for the future? The short answer is “no”. Fortunately, there are data from a pair of events, several decades ago—Hurricanes Dennis and Floyd in 1999—that we can turn to for guidance in how the nonlinear, multiscale fluid physics of these types of compound hazard events manifested in the past and what they portend for the future. It is of note that fifty-six lives were lost in coastal North Carolina alone from this pair of storms. In this study, the 1999 rapid coastal and inland flooding event attributed to those two consecutive hurricanes is documented and the series of physical processes and their mechanisms are analyzed. A diagnostic assessment using data and numerical models reveals the physical mechanisms of downstream blocking that occurred.

Sea breezes have been observed to move inland over 100 km. These airmasses can be markedly different from regional airmasses, creating a shallow layer with differences in humidity, wind, temperature and aerosol characteristics. To understand their influence on boundary layer and cloud development on subsequent days, we identify their frequency and characteristics. We visually identified sea breeze fronts on radar passing over the Savannah River Site (SRS) between March and October during 2015–2019. The SRS is ~150 km from the nearest coastal location; therefore, our detection suggests further inland penetration. We also identified periods when sea breeze fronts may have passed but were not visually observed on radar due to the shallow sea breeze airmass remaining below the radar beam elevation that ranges between approximately 1–8 km depending on the beam angle and radar source (Columbia, SC or Charleston, SC). Near-surface atmospheric measurements indicate that the dew point temperature increases, the air temperature decreases, the variation in wind direction decreases and the aerosol size increases after sea breeze frontal passage. A synoptic classification procedure also identified that inland moving sea breezes are more commonly observed when the synoptic conditions include weak to moderate offshore winds with an average of 35 inland sea breezes occurring each year, focused primarily in the months of April, May and June.

The Lagrangian tracking approach is often used in numerical modeling (NM) to simulate and predict the movement of marine particles such as plastic, oil spills, and floating wreckage. The uncertainties in NM reduce prediction accuracy as a result of the coarse temporal and spatial resolution, along with waves, winds, and currents. From 29 August to 22 December 2020, the United States Defense Advanced Research Projects Agency's Ocean of Things program deployed 422 floating drifters in the Gulf of Mexico, providing an opportunity of using the observed trajectories as ground truth to train Artificial Intelligence (AI) models to correct NM float trajectory predictions. A Regional Ocean Model System (ROMS) and AI Hybrid model was developed to implement AI to correct the ROMS‐predicted 1‐day float trajectories. The AI model is built on a convolutional neural network and Gated Recurrent Unit. The results of the ROMS‐AI Hybrid model show that 82.0% of the trajectory predictions were improved at the 24 hr, with the corresponding overall mean separation error decreasing by 11.82 km, from 20.56 to 8.74 km, which is a 57% improvement, and the error growth rate decreasing from 5.06 km per 6 hr to 1.95 km per 6 hr. The evident improvement indicates that the ROMS‐AI Hybrid model can correct the ROMS simulation to improve the 1‐day prediction of the float trajectories and shows great potential to predict the cluster of the floats.

This study addresses the limitations of and the common challenges faced by one-dimensional river-routing methods in hydrological models, including the National Water Model (NWM), in accurately representing coastal regions. We developed a two-way coupling between the NWM and the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The approach demonstrated improvements in modeling coastal river dynamics, particularly during extreme events like Hurricane Matthew. The coupled model successfully captured tidal influences, storm surge effects, and complex river–river interactions that the standalone NWM missed. The approach revealed more accurate representations of peak discharge timing and magnitude as well as water storage and release in coastal floodplains. However, we also identified challenges in reconciling variable representations between hydrological and hydraulic models. This work not only enhances the understanding of coastal–riverine interactions but also provides valuable insights for the development of next-generation hydrological models. The improved modeling capabilities have implications for flood forecasting, coastal management, and climate change adaptation in vulnerable coastal areas.

The HAFS model is an effort under the NGGPS and UFS initiatives to create the next generation of hurricane prediction and analysis system based on FV3-GFS. It has been validated extensively using traditional verification indicators such as tracker error and biases, intensity error and biases, and the radii of gale, damaging and hurricane strength winds. While satellite images have been used to verify hurricane model forecasts, they have not been used on HAFS. The community radiative transfer model CRTM is used to generate model synthetic satellite images from HAFS model forecast state variables. The 24 forecast snapshots in the mature stage of hurricane Dorian in 2019 are used to generate a composite model synthetic GOES-R infrared brightness image. The composite synthetic image is compared to the corresponding composite image generated from the observed GOES-R data, to evaluate the model forecast TC vortex intensity, size, and asymmetric structure. Results show that the HAFS forecast TC Dorian agrees reasonably well with the observation, but the forecast intensity is weaker, its overall vortex size smaller, and the radii of its eye and maximum winds larger than the observed. The evaluation results can be used to further improve the model. While these results are consistent with those obtained by traditional verification methods, evaluations based on composite satellite images provide an additional benefit with richer information because they have near-real-times spatially and temporally continuous high-resolution data with global coverage. Composite satellite infrared images could be used routinely to supplement traditional verification methods in the HAFS and other hurricane model evaluations. Note since this study only evaluated one hurricane, the above conclusions are only applicable to the model behavior of the mature stage of hurricane Dorian in 2019, and caution is needed to extend these conclusions to expect model biases in predicting other TCs. Nevertheless, the consistency between the evaluation using composite satellite images and the traditional metrics, of hurricane Dorian, shows that this method has the potential to be applied to other storms in future studies.