Research
I have used combinations of numerical models, remote sensing, tide gauges and CTDs to investigate natural hazards and renewable energies for climate change mitigation and adaptation as follows:
06
Ocean Thermal Energy Conversion
To evaluate the feasibility of Ocean Thermal Energy Conversion (OTEC) in regions such as Hawai‘i and Guam, I have developed a high-resolution numerical model that accurately resolves vertical ocean temperature structures. This model surpasses the spatial and temporal resolution of existing observational datasets and operational models, enabling more precise assessments of OTEC resource potential and deployment viability. In addition to resource characterization, the model supports environmental impact analyses of OTEC operations, offering critical insights for sustainable implementation. Details are available in this paper.
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05
Ocean Current Energy
The Gulf Stream presents significant potential for marine energy due to its persistent strength and proximity to the U.S. coast. This study advances understanding of the ocean current energy by employing a high-resolution, long-term ocean model to capture the spatiotemporal variability of the Gulf Stream and its influence on energy availability. By focusing on two key regions (off the coasts of North Carolina and Florida), it reveals how regional differences in Gulf Stream structure and dynamics result in distinct energy characteristics, offering valuable insights for optimal site selection and system design. Details are available in this paper. This work is being further advanced to incorporate turbine feedback and assess the effects of energy extraction on flow dynamics.​
04
Coastal Ocean Model Evaluation
Developed SCHISM model in New York City
I am contributing to the NOAA project titled “Unified Forecast System Coastal Applications Team Water Quantity Model Evaluation.” In this effort, I evaluate the coastal ocean model SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) with a focus on key variables such as water levels, surface currents, temperature, and salinity as parameters critical for supporting marine navigation and operational forecasting. As part of the evaluation, I configured and deployed SCHISM for the New York City region and conducted comprehensive skill assessments using observational datasets. The evaluation also included sensitivity analyses of hydrodynamic outputs to various input data sources, including FES2014, TPXO, CMEMS, HYCOM, GRTOFS, ERA5, HRRR, and GFS. These comparisons help identify the most reliable boundary and forcing datasets for improving coastal model performance in complex urban environments.
Details are available in this manuscript.
03
Delayed Coastal Flooding
Oceanic adjustments associated with hurricanes have received considerably less attention than direct atmospheric impacts such as wind, pressure, and precipitation, despite their significant influence on coastal sea levels. Using a high-resolution, three-dimensional coastal ocean model, I investigate the spatiotemporal dynamics of these oceanic responses during and after hurricane events. The study reveals that such adjustments can lead to delayed coastal flooding, resulting in persistent, state-scale inundation lasting for several weeks following a hurricane. These findings provide critical insights into the mechanisms driving extreme water levels from oceanic processes and help close existing gaps in flood forecasting, hazard assessment, and climate resilience planning. This work establishes a scientific basis for informing best practices among researchers, engineers, and policymakers. Please find details in this paper.
Increased water levels by oceanic adjustment after Hurricane Matthew (2016). This 2-D map shows the maximum water levels during the post-hurricane period.
02
Extreme Water Level
Different peak timing of local (LF) and remote forcing (RF). The time histories show temporal variation in the storm surges depending on different forcing during Matthew (MT) and Dorian (DR).
I use a city-scale coastal ocean model to investigate the primary drivers of extreme water levels during Hurricanes Matthew (2016) and Dorian (2019). This research highlights the critical role of the relative timing between remote oceanic forcing (Gulf Stream variations, Ekman transport, and coastally trapped waves) and local atmospheric forcing (wind stress and air pressure) along the U.S. Southeast coast. The analysis reveals that synchronization of these forcings can significantly amplify storm surge, increasing peak water levels by up to 30% during Hurricane Matthew and 50% during Hurricane Dorian. These findings enhance our ability to estimate worst-case flood scenarios and improve the accuracy of coastal hazard assessments. Detailed model configurations, numerical experiments and analysis are summarized in this paper.
01
Operational Forecast System
In collaboration with the Euro-Mediterranean Center on Climate Change (CMCC), I developed a 3-day operational coastal flood forecasting system for Chatham County, Georgia. The system is validated using a dense network of water level sensors (SeaLevelSensors.org), ensuring reliable and practical guidance for local emergency planning and coastal resilience. Building on this work, I contribute to the CEAR Hub project (CEARHub.org) to expand the forecast system across the entire Georgia coast. This next-generation system integrates multiple flood drivers such as tides, storm surge, precipitation, and river discharge to support precise inundation simulations and enhance flood preparedness for coastal communities.
3-day operational forecast system
