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 assess the potential of ocean thermal energy conversion (OTEC) in regions like Hawaii and Guam, I am developing a high-resolution numerical model capable of accurately capturing vertical ocean temperature profiles. This model offers significantly greater detail than existing observational datasets and models, enabling more precise evaluations of the feasibility and practical deployment of OTEC systems. Details are available in this manuscript.
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05
Ocean Current Energy
Western boundary currents, such as the Gulf Stream, offer significant potential for marine energy extraction due to their persistent strength and directional stability. However, progress has been limited by the scarcity of reliable data from coarse-resolution models and sparse observations. To overcome these challenges, I am developing multi-scale, high-resolution numerical models that accurately simulate the ocean current and available energy, incorporate turbine feedback, and account for the effects of energy extraction. Details are available in this manuscript.
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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
