Improving Coastal Storm Surge Monitoring Through Joint Modeling Based on Permanent and Temporary Tide Gauges

• Published in: Geophysical research letters Vol. 51; no. 11
• Main Authors: Yang, Lianjun, Jin, Taoyong, Jiang, Weiping
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 16-06-2024; Wiley
• Subjects: Artificial intelligence; Climate change; Coastal plains; Coastal storms; Coastal zone; Coasts; Environmental monitoring; Gauges; Global warming; Hurricanes; Intercomparison; Modelling; Monitoring; Monitoring systems; Optimization; Sea level; Spatial discrimination; Spatial resolution; Storm surges; Storms; Tidal waves; Tide gauges; Tides; Typhoons
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2024GL108886

With climate change, there will be higher requirements for monitoring storm surges (SSs) in nearshore areas. However, this capability is limited by the sparseness of tide gauge (TG) stations. Establishing and maintaining a permanent, high‐spatial coverage, in situ TG network is complex and expensive. Here, we propose a joint modeling method developed from the all‐site modeling data‐driven framework by importing temporary TGs into coastal regions with insufficient permanent TG stations. The assessments show that this method can significantly optimize the capability of extreme SS monitoring during typhoons and hurricanes. Moreover, the evaluation based on Coupled Model Intercomparison Project Phase 6 data indicates that it will monitor extreme SSs more effectively during 2025–2050 compared with only using existing permanent in situ TGs (reducing root mean square error and absolute mean bias by ∼50%). The joint modeling method provides an applicable and sustainable solution for optimizing the SS monitoring capability in coastal areas.
Plain Language Summary
Each year, storm surges (SSs) generated by typhoons and hurricanes cause loss of life and property in coastal areas. With global warming, the destruction from extreme events will increase in the future, thus posing challenges to nearshore SS monitoring. High spatiotemporal resolution and high‐precision monitoring data are crucial for early warning and forecasting, which can better prepare coastal communities for incoming storms. However, as the only means to observe continuous and high‐frequency sea levels, tide gauges often provide limited information due to insufficient spatial resolution. In addition, establishing and maintaining a permanent tide gauge (TG) monitoring network with high spatial coverage is expensive and unrealistic. A joint modeling method based on artificial intelligence technology through importing temporary tide gauges established during extreme events to the existing TG networks can significantly optimize the future SS monitoring capability, providing a valuable and applicable reference for regions affected by powerful typhoons and hurricanes and thereby improving the nearshore SS monitoring system.
Key Points
A storm surge (SS) joint modeling method developed from the all‐site modeling data‐driven framework
Temporary tide gauge (TG) stations can reduce the cost of establishing and maintaining permanent TGs
Improve extreme SS monitoring precision by ∼50% from 2025 to 2050 compared with only using permanent TGs