Autonomous underwater glider observations collected during and after 2017 Hurricanes Irma, Jose, and Maria show two types of transient response within the Gulf Stream. First, anomalously fresh water observed near the surface and within the core of the Gulf Stream offshore of the Carolinas likely resulted from Irma's rainfall being entrained into the Loop Current-Gulf Stream system. Second, Gulf Stream volume transport was reduced by as much as 40% for about 2 weeks following Jose and Maria. The transport reduction had both barotropic and depth-dependent characteristics. Correlations between transport through the Florida Straits and reanalysis winds suggest that both local winds in the Florida Straits and winds over the Gulf Stream farther downstream may have contributed to the transport reduction. To clarify the underlying dynamics, additional analyses using numerical models that capture the Gulf Stream's transient response to multiple tropical cyclones passing nearby in a short period are needed.

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We introduce a zero-censored Gaussian process as a systematic, model-based approach to building Gaussian process emulators for range-constrained simulator output. This approach avoids many pitfalls associated with modeling range-constrained data with Gaussian processes. Further, it is flexible enough to be used in conjunction with statistical emulator advancements such as emulators that model high-dimensional vector-valued simulator output. The zero-censored Gaussian process is then applied to two examples of geophysical flow inundation which have the constraint of nonnegativity.

The past 12 years have seen significant steps forward in the science and practice of coastal flood analysis. This paper aims to recount and critically assess these advances, while helping identify next steps for the field. This paper then focuses on a key problem, connecting the probabilistic characterization of flood hazards to their physical mechanisms. Our investigation into the effects of natural structure on the probabilities of storm surges shows that several different types of spatial-, temporal-, and process-related organizations affect key assumptions made in many of the methods used to estimate these probabilities. Following a brief introduction to general historical methods, we analyze the two joint probability methods used in most tropical cyclone hazard and risk studies today: the surface response function and Bayesian quadrature. A major difference between these two methods is that the response function creates continuous surfaces, which can be interpolated or extrapolated on a fine scale if necessary, and the Bayesian quadrature optimizes a set of probability masses, which cannot be directly interpolated or extrapolated. Several examples are given here showing significant impacts related to natural structure that should not be neglected in hazard and risk assessment for tropical cyclones including: (1) differences between omnidirectional sampling and directional-dependent sampling of storms in near coastal areas; (2) the impact of surge probability discontinuities on the treatment of epistemic uncertainty; (3) the ability to reduce aleatory uncertainty when sampling over larger spatial domains; and (4) the need to quantify trade-offs between aleatory and epistemic uncertainties in long-term stochastic sampling.

Storm surge caused by tropical cyclones can cause overland flooding and lead to loss of life while damaging homes, businesses, and critical infrastructure. In 2018, Hurricane Michael made landfall near Mexico Beach, FL, on 10 October with peak wind speeds near 71.9 m s-1 (161 mph) and storm surge over 4.5 m NAVD88. During Hurricane Michael, water levels and waves were predicted near real-time using a deterministic, depth-averaged, high-resolution ADCIRC+SWAN model of the northern Gulf of Mexico. The model was forced with an asymmetrical parametric vortex model (GAHM) based on Michael's National Hurricane Center (NHC) forecast track and strength. The authors report errors between simulated and observed water level time-series, peak water level, and timing of peak for NHC Advisories. Forecasts of water levels were within 0.5 m of observations, and the timing of peak water levels was within 1 hr as early as 48 hr before Michael’s eventual landfall. We also examined the effect of adding far-field meteorology in our TC vortex model for use in real-time forecasts. In general, we found that including far-field meteorology by blending the TC vortex with a basin-scale NWP product improved water level forecasts. However, we note that divergence between the NHC forecast track and the forecast track of the meteorological model supplying the far-field winds represents a potential limitation to operationalizing a blended wind field surge product. The approaches and data reported herein provide a transparent assessment of water level forecasts during Hurricane Michael and highlight potential future improvements for more accurate predictions.