Winter-Spring dynamics of dissolved organic carbon fluxes driven by precipitation in a North Carolina tidal marsh - Marie Cindy Lebrasse; Blake A. Schaeffer; DelWayne R. Bohnenstiehl; Christopher L. Osburn; Megan M. Coffer; Ruoying He; Peter J. Whitman; Wilson B. Salls; David D. Graybill (Estuarine, Coastal and Shelf Science, 2025)

Long-term prediction of the Gulf Stream meander using OceanNet: a principled neural-operator-based digital twin - Michael Gray; Ashesh Chattopadhyay; Tianning Wu; Anna Lowe; Ruoying He (Ocean Science, 2025)
Many meteorological and oceanographic processes throughout the eastern US and western Atlantic Ocean, such as storm tracks and shelf water transport, are influenced by the position and warm sea surface temperature of the Gulf Stream (GS) – the region's western boundary current. Due to highly nonlinear processes associated with the GS, predicting its meanders and frontal position has been a long-standing challenge within the numerical modeling community. Although the weather and climate modeling communities have begun to turn to data-driven machine learning frameworks to overcome analogous challenges, there has been less exploration of such models in oceanography. Using a new dataset from a high-resolution data-assimilative ocean reanalysis (1993–2022) for the northwestern Atlantic Ocean, OceanNet (a neural-operator-based digital twin for regional oceans) was trained to predict the GS's frontal position over subseasonal to seasonal timescales. Here, we present the architecture of OceanNet and the advantages it holds over other machine learning frameworks explored during development. We also demonstrate that predictions of the GS meander are physically reasonable over at least a 60 d period and remain stable for longer. OceanNet can generate a 120 d forecast of the GS meander within seconds, offering significant computational efficiency.

Physical oceanography and its applications: A tribute to Distinguished University Professor Dr. Robert H. Weisberg - Robert W. Helber; Yonggang Liu; Ruoying He; Chunzai Wang (Deep Sea Research Part II: Topical Studies in Oceanography, 2024)

Editorial: Understanding and predicting the Gulf of Mexico ocean dynamics - Steven L. Morey; Ruoying He; Eric P. Chassignet; Julio Sheinbaum (Frontiers in Marine Science, 2024)

Investigation of ocean environmental variables and their variations associated with major Loop Current eddy-shedding events in the Gulf of Mexico - Nazanin Chaichitehrani; Ruoying He (Deep Sea Research Part II: Topical Studies in Oceanography, 2024)

A data-assimilative modeling investigation of Gulf Stream variability - Shun Mao; Ruoying He; John Bane; Glen Gawarkiewicz; Robert E. Todd (Deep Sea Research Part II: Topical Studies in Oceanography, 2023)

Atmospheric forcing of the Hatteras coastal ocean during 2017–2018: The PEACH program - John Bane; Harvey Seim; Sara Haines; Lu Han; Ruoying He; Joseph Zambon (Dynamics of Atmospheres and Oceans, 2023)

Impact of the Gulf Stream on ocean waves - Mohammad Nabi Allahdadi; Ruoying He; Vincent S. Neary (Deep Sea Research Part II: Topical Studies in Oceanography, 2023)

Source–sink recruitment of red snapper: Connectivity between the Gulf of Mexico and Atlantic Ocean - Mandy Karnauskas; Kyle W. Shertzer; Claire B. Paris; Nicholas A. Farmer; Theodore S. Switzer; Susan K. Lowerre‐Barbieri; G. Todd Kellison; Ruoying He; Ana C. Vaz (Fisheries Oceanography, 2022)
Geopolitical fishery management boundaries are often misaligned with the ecological population structure of marine species, which presents challenges for assessment and management of these species. Red snapper, Lutjanus campechanus , is an iconic and heavily exploited species in both the US Gulf of Mexico and off the southeastern US Atlantic coast and is managed separately in the two jurisdictions. It is hypothesized that the Atlantic red snapper stock is sustained partially by larval subsidies from the Gulf of Mexico. Here we use a biophysical modeling approach to simulate recruitment of red snapper across the entire Southeastern US region, and quantify rates of larval exchange across management jurisdictions. The biophysical framework simulates realistic red snapper behaviors and traits with respect to spatial distribution and timing of spawning, larval vertical migration and pelagic larval duration, and settlement habitat. Our results suggest that areas of the West Florida Shelf south of Tampa Bay are important sources of larvae for the Atlantic population, supplying as much as one third of the recruitment during some years. Yet, contributions of Gulf‐spawned red snapper to the Atlantic stock are highly dynamic given large variability in spatial and temporal patterns of red snapper recovery in each region. As such, effective management of the Gulf of Mexico red snapper stock, particularly the spawning population in southwest Florida, may have important consequences for the sustainable harvest of red snapper off the Atlantic coast.

Hurricane-Induced Oceanic Carbon Changes in the Upper Ocean - Laura McGee; Ruoying He (Oceans, 2022)
Changes in marine carbon cycling due to hurricanes with different intensity and translation speeds have not been systematically investigated. This study uses an idealized coupled physical-biogeochemical model and a suite of model sensitivity analyses to better quantify the relationship between hurricane characteristics and marine property changes, including variations in air-sea carbon flux and partial pressure of carbon dioxide in water (pCO2w). We find that strong (category 4–5), mid-speed (5–8 m/s) storms cause the most carbon flux from the atmosphere to the ocean, and that the relationship between air-sea carbon flux and hurricane properties is non-linear. Climate models that do not consider synoptic-scale, storm-induced physical-biogeochemical coupling may underestimate regional carbon sinks.

Overview of the Processes Driving Exchange at Cape Hatteras Program - Harvey Seim; Dana Savidge; Magdalena Andres; John Bane; Catherine Edwards; Glen Gawarkiewicz; Ruoying He; Robert Todd; Michael Muglia; Joseph Zambon; Lu Han; Shun Mao (Oceanography, 2022)
The Processes driving Exchange At Cape Hatteras (PEACH) program seeks to better understand seawater exchanges between the continental shelf and the open ocean near Cape Hatteras, North Carolina. This location is where the Gulf Stream transitions from a boundary-trapped current to a free jet, and where robust along-shelf convergence brings cool, relatively fresh Middle Atlantic Bight and warm, salty South Atlantic Bight shelf waters together, forming an important and dynamic biogeographic boundary. The magnitude of this convergence implies large export of shelf water to the open ocean here. Background on the oceanography of the region provides motivation for the study and gives context for the measurements that were made. Science questions focus on the roles that wind forcing, Gulf Stream forcing, and lateral density gradients play in driving exchange. PEACH observational efforts include a variety of fixed and mobile observing platforms, and PEACH modeling included two different resolutions and data assimilation schemes. Findings to date on mean circulation, the nature of export from the southern Middle Atlantic Bight shelf, Gulf Stream variability, and position variability of the Hatteras Front are summarized, together with a look ahead to forthcoming analyses.

Correction to: Mesoscale and submesoscale mechanisms behind asymmetric cooling and phytoplankton blooms induced by hurricanes: a comparison between an open ocean case and a continental shelf sea case - Laura McGee; Ruoying He (Ocean Dynamics, 2020)

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment - Vincent S. Neary; Seongho Ahn; Bibiana E. Seng; Mohammad Nabi Allahdadi; Taiping Wang; Zhaoqing Yang; Ruoying He (Journal of Marine Science and Engineering, 2020)
Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations - Mohammad Nabi Allahdadi; Ruoying He; Vincent S. Neary (Ocean Science, 2019)
The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

Potential connectivity among spatially distinct management zones for Bonefish (Albula vulpes) via larval dispersal - Xiangming Zeng; Aaron Adams; Mitchell Roffer; Ruoying He (Environmental Biology of Fishes, 2019)

Mesoscale and submesoscale mechanisms behind asymmetric cooling and phytoplankton blooms induced by hurricanes: a comparison between an open ocean case and a continental shelf sea case - Laura McGee; Ruoying He (Ocean Dynamics, 2018)

Risk perception of heat waves and its spatial variation in Nanjing, China - Lei Huang; Qianqi Yang; Jie Li; Jin Chen; Ruoying He; Can Zhang; Kai Chen; Steven Guanpeng Dong; Yang Liu (International Journal of Biometeorology, 2018)

Climate projections of spatial variations in coastal storm surges along the Gulf of Mexico and U.S. east coast - Zhigang Yao; Zuo Xue; Ruoying He; Xianwen Bao; Jun Xie; Qian Ge (Journal of Ocean University of China, 2017)

Statistical downscaling of IPCC sea surface wind and wind energy predictions for U.S. east coastal ocean, Gulf of Mexico and Caribbean Sea - Zhigang Yao; Zuo Xue; Ruoying He; Xianwen Bao; Jun Song (Journal of Ocean University of China, 2016)

Numerical investigation of coastal circulation dynamics near Cape Hatteras, North Carolina, in January 2005 - Yanlin Gong; Ruoying He; Glen G. Gawarkiewicz; Dana K. Savidge (Ocean Dynamics, 2015)

Investigation of hurricane Ivan using the coupled ocean–atmosphere–wave–sediment transport (COAWST) model - Joseph B. Zambon; Ruoying He; John C. Warner (Ocean Dynamics, 2014)

Air–sea interactions during strong winter extratropical storms - Jill Nelson; Ruoying He; John C. Warner; John Bane (Ocean Dynamics, 2014)

Editorial—The 3rd International Workshop on Modeling the Ocean (IWMO 2011) - Lie-Yauw Oey; Tal Ezer; Bo Qiu; Jarle Berntsen; Ruoying He (Ocean Dynamics, 2013)

M2 tidal dynamics in Bohai and Yellow Seas: a hybrid data assimilative modeling study - Zhigang Yao; Ruoying He; Xianwen Bao; Dexing Wu; Jun Song (Ocean Dynamics, 2012)

US GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM) - Eric Chassignet; Harley Hurlburt; E. Joseph Metzger; Ole Smedstad; James Cummings; George Halliwell; Rainer Bleck; Remy Baraille; Alan Wallcraft; Carlos Lozano; Hendrik Tolman; Ashwanth Srinivasan; et al. (Oceanography, 2009)

Coastal Ocean Circulation Influences on Remotely Sensed Optical Properties: A West Florida Shelf Case Study - Robert Weisberg; Ruoying He; Gary Kirkpatrick; Frank Muller-Karger; John Walsh (Oceanography, 2004)