Peter Rogowski

Extratropical cyclones (ECs) produce comparable wave heights and hazardous sea states to those under hurricanes. With strong wind speeds and considerably larger diameters, the impact of ECs on the global wave climate is substantial. Because ECs occur more frequently, move more quickly, and exist in a large variety of sizes and shapes, these storms are not as well documented. Here, we present findings from a global EC tracking algorithm aimed at creating an EC database of wave producing storms. We focus on the major ocean basins of extratropical cyclone activity: The North Atlantic, North Pacific, and Southern Oceans. Our tracking algorithm uses mean sea level pressure fields from the European Centre for Medium‐Range Weather Forecasts (ECMWF) high resolution, advanced data assimilating, ERA5 reanalysis over the years 1979–2020. The 42 year‐long data set of thousands of cyclone tracks allows seasonal patterns and longer‐term trends of EC activity to be analyzed in these ocean regions. In addition, we employ 36 years of satellite radar altimeter‐derived significant wave height (H_s) data from 14 inter‐calibrated satellite missions to study the wave climate induced by the identified ECs in each basin. The resulting wave climatology compares well with previous results in the mid to high latitudes. We then analyze average wave heights under different EC characteristics, including cyclone translational speed and maximum winds, which have strong effects on wave height variability. Finally, a brief analysis of EC and wave climate under positive and negative phases of the North Atlantic Oscillation is presented.

Soon after the publication of the original manuscript

As part of a U.S. – Vietnam collaborative effort, a numerical model is used to describe the dynamics associated with the Gulf of Tonkin seasonal variability. Unique to this study is the synthesis of historical and recent observations throughout the gulf that are leveraged to validate the model's seasonal component. The dynamics is primarily forced by seasonally reversing monsoons, remote transports through the Qiongzhou Strait and by the western boundary current, and river discharge. Monsoonal winds set up pressure gradients across the gulf that tend to be balanced by geostrophic flows (cyclonic during the winter and anticyclonic during the summer). However, a number of processes modify the wind‐driven dynamics with all of them promoting cyclonic circulation. In the eastern region, the tides influence the seasonal variability via (a) a tidal‐residual flow producing an influx of mass through the Qiongzhou Strait and (b) through modification of the summer baroclinic density field. In the western region, the seasonal variability can be strongly dependent on river buoyancy flows and intrusions of the western boundary current. Southwest summer winds produce a low salinity bulge near the Red River mouth that releases and advects as a southward coastal current during the fall as winds relax and reverse direction. Additionally, the vorticity budget shows that topographic steering constrains the seasonal variability promoting intrusions of the western boundary current during winter monsoon conditions, when the current carries water of shallow origin from the Chinese shelf.

Landfalling tropical cyclones (TC) generate extreme waves, introducing significant property, personal, and financial risks and damage. Accurate simulations of the sea state during these storms are used to support risk and damage assessments and the design of coastal structures. However, the TCs generate a complex surface gravity wave field as a result of the inherently strong temporal and spatial gradients of the wind forcing. This complexity is a significant challenge to model. To advance our understanding of the performance of these models on the eastern seaboard of the United States, we conduct an assessment of four hindcast products, three based on WAVEWATCH-III and the other using the Wave Modeling project, for six major landfall TCs between 2011–2019. Unique to our assessment was a comprehensive analysis of these hindcast products against an array of fixed wave buoys that generate high quality data. The analysis reveals a general tendency for the wave models to underestimate significant wave height (Hs) around the peak of the TC. However, when viewed on an individual TC basis, distinct Hs error patterns are evident. Case studies of hurricanes Sandy and Florence illustrate complex Hs bias patterns, likely resulting from various mechanisms including insufficient resolution, improper wind input and source term parameterization (e.g., drag coefficient), and omission of wave–current interactions. Despite the added challenges of simulating complex wave fields in shallow coastal waters, the higher resolution Wave Information Study and National Centers for Environmental Prediction (ST4 parameterization only) hindcasts perform relatively well. Results from this study illustrate the challenge of simulating the spatial and temporal variability of TC generated wave fields and demonstrate the value of in-situ validation data such as the north Atlantic buoy array.

Tropical cyclones (TC) are some of the most intense weather systems on Earth and are responsible for generating hazardous waves on the sea surface that dominate the extreme wave climate in several regions, including the Gulf of Mexico and the U.S. East Coast. Modeling these waves is crucial for engineering applications, yet it is notoriously difficult, due to TC’s compact structure and rapid evolution in space and time relative to other weather systems. To better understand the wave structure under TCs, we use satellite altimeter data paired with TC tracks. We parse the data by TC intensity and forward translation velocity, finding evidence of extended fetch. We use the altimeter data to evaluate operational hindcasts, including the US Army Corps of Engineer’s Wave Information Study, National Oceanic and Atmospheric Administration’s National Centers for Environmental Prediction Production Hindcast, and the Institut français de recherche pour l’exploitation de la mer (Ifremer) hindcast. The Ifremer hindcast (1990–2016) is examined in detail. Near the eye in the TC-centered reference frame, we find a pattern of model underestimation in the left sector and overestimation in the right sector except near the eye where wave height remains underestimated. This pattern holds, albeit modulated, across various intensities, forward translation velocities, and radii of maximum winds; the exceptions being the fastest translating storms where the error pattern shows a trend towards overestimation in all sectors. The error patterns for intense and compact TCs exhibited more severe underestimation, which dominated the region near the TC eye.

Accurate surface meteorological (MET) observations reported reliably and in near–real time remain a critical component of on-scene environmental observation systems. Presented is a system developed by Scripps Institution of Oceanography that allows for rapid, global deployment of ground-based weather observations to support both timely decision-making and collection of high-quality weather time series for science or military applications in austere environments. Named the Expeditionary Meteorological (XMET), these weather stations have been deployed in extreme conditions devoid of infrastructure ranging from tropical, polar, maritime, and desert environments where near continuous observations were reported. To date, over 1 million weather observations have been collected during 225 deployments around the world with a data report success rate of 99.5%. XMET had its genesis during Operation Iraqi Freedom (OIF), when the U.S. Marine Corps 3rd Marine Aircraft Wing identified an immediate capability gap in environmental monitoring of their operation area due to high spatiotemporal variability of dust storms in the region. To address the sensing gap, XMET was developed to be a portable, expendable, ruggedized, self-contained, bidirectional, weather observation station that can be quickly deployed anywhere in the world to autonomously sample and report aviation weather observations. This paper provides an overview of the XMETs design, reliability in different environments, and examples of unique meteorological events that highlight both the unit’s reliability and ability to provide quality time series. The overview shows expeditionary MET sensing systems, such as the XMET, are able to provide long-term continuous observational records in remote and austere locations essential for regional spatiotemporal MET characterization.

The spatial and temporal evolution of an introduced dye tracer in a small reservoir was observed using a robotic autonomous underwater vehicle (AUV), providing quantifiable data of the convective processes which drive transport and mixing. The tracer served as a surrogate for advanced treated water that has been proposed to be introduced into a reservoir as part of an overall system for efficient water reclamation, a critical management tool for addressing water issues facing the southwest. While emergent autonomous technology has been widely applied in the field of oceanography, applications in the field of limnology remain limited. Here, we introduce survey methods used to map the evolution of the introduced dye, which was influenced by differential cooling of the reservoir. A cooling event during the study modified the diurnal cycle of the reservoir, generating horizontal temperature gradients that caused the dye to migrate quickly out of the shallow side‐arm where it was introduced. The dispersion of the dye throughout the reservoir was well captured by the sampling resolution of the AUV providing three‐dimensional data sets of complex convective processes that were used to validate a numerical lake/reservoir model. The operational efficiency, adaptive sampling capabilities, and resolution of observations make the AUV an appealing alternative compared to traditional boat‐based survey methods for rapidly assessing reservoirs. Survey method limitations, advantages, and future recommendations are discussed. The study demonstrates the utility of an AUV in a small reservoir, providing the framework for increased use of high‐resolution mobile instrument platforms in future limnology studies.

Remote sensing of the complex interactions between bathymetry, tidal flow, and waves in coastal inlets provides high‐resolution data sets that can be exploited to characterize the morphological variability of shallow ebb tidal deltas (ETD). Here we used observations from a mobile X‐band radar platform to determine optimal conditions during which radar‐derived shoal signatures best represent positions of underlying shoals. Significant increases in the spatial errors of radar shoal signatures were observed when offshore wave energy intensified. Consequently, the lowest spatial errors occurred when the radar shoal signatures were primarily a function of the tidal flow (i.e., low sea state). We used these findings to quantify shoal migration patterns at the New River Inlet, North Carolina. We found that the southwestern portion of the ETD had the largest morphological variability with typical shoreward migration rates of 2–3 m/day driven by incident wave energy. The migration rates and patterns estimated from X‐band observations were consistent with numerical modeling results and a previous video‐based New River remote sensing study. Our results confirm that X‐band radar can be used to quickly map shallow ETDs (e.g., 5 min of observations), allowing for rapid morphological assessments from shore or boat‐based platforms. The methods would prove particularly useful for initial assessment as well as continual monitoring of dynamic tidal inlets where large morphological responses can be rapidly assessed and used for geomorphological studies, and as decision aids for maritime or engineering operations.