Influence of Hurricane Wind Field Variability on Real‐Time Forecast Simulations of the Coastal Environment
Abstract
Dynamic conditions occur in the coastal ocean during severe storms. Forecasting these conditions is challenging, and large‐scale numerical models require significant computing power. In this paper, we describe a real‐time modeling system (DUNEX‐RT), developed in support of the During Nearshore Event experiment (DUNEX) off the coast of North Carolina, United States of America. The model is run with wave, current, and water level boundary conditions from larger‐scale models, and provides 36‐h forecasts of significant wave height, depth‐averaged velocity, and water levels every 6‐h using Delft3D‐SWAN. Observations and forecasts run at different times are compared and communicated via an interactive website to verify model performance in real‐time and to visualize uncertainty from changing inputs. Here, we evaluate model sensitivity to inputs from seven different atmospheric hindcasts and two atmospheric forecasts for Hurricane Dorian in September 2019. The results emphasize the importance of accurate wind forcing, with significant differences observed between the output model results for different input atmospheric forcing models and forecasts produced at different times. The best results were achieved using atmospheric forcing from the high resolution rapid refresh model, and overall, DUNEX‐RT had low errors at 33 wave, water level, and current sites across the system. The model results for water levels and significant wave heights were also accurate over a longer period of 49 days. Overall, the good forecast skill achieved for the wide range of conditions over this time results suggest that this high‐resolution regional approach could be applied to forecast conditions in other coastal areas.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2021
- Source ID
- 10.1029/2020jc016489
Entities
People
- Alexander Rey
- Ryan P. Mulligan
Organizations
- Natural Sciences and Engineering Research Council
- Office of Naval Research Global
- Queen's University