Improving Coastal Storm Surge and Inundation Forecasts by Assimilating SWOT Products

Hurricanes, cyclones, and typhoons are major global natural hazards causing frequent and recurrent devastation worldwide. Although advances in early warning systems and storm surge forecasts are being developed worldwide, the existing uncertainty in providing accurate and reliable water levels and flood inundation extent at the operational level remains a scientific challenge. The NASA Surface Water and Ocean Topography (SWOT) mission, planned to launch in April 2022, provides a unique opportunity to fundamentally transform and advance our ability to forecast storm surges and map storm inundation. Advances in numerical models, the proliferation of in-situ data collection technology, and previous satellite altimetry missions provide ever-improving tools to support societal resilience to tropical storms. Data assimilation integrating high-resolution NASA SWOT observations of oceanography, coastal, and riverine spatial dynamics with storm surge and inundation modeling can revolutionize our understanding of spatial-temporal storm surge process dynamics. Therefore, the primary objective of this work is to quantify the utility of integrating SWOT products within a storm surge model to provide a better characterization of spatial-temporal storm surge processes for operational forecasting. We developed a SWOT-focused storm surge forecasting framework to evaluate the potential of utilizing satellite altimetry. Specifically, we performed a synthetic experiment to evaluate the effectiveness of assimilating synthetic SWOT observations in a storm surge model. The general experiment scheme is based on a hindcast run that represents the truth of the system states. The experiment is run along the U.S. Atlantic coast with a focus on the Chesapeake Bay and analyzes the storm surge inundation caused by hurricane Sandy (2012). A mesh has been produced for the ADCIRC model to simulate the storm surge inundation n the study region. As SWOT has a temporal resolution gap of 21 days, the DA system is expected to improve the quality of the open-loop (i.e., no data assimilation) ADCIRC simulation by interpolating through time and by assimilating the synthetic SWOT sea surface height observations.