Investigating the Joint Probability of High Coastal Sea Level and High Precipitation

• Published in: Journal of marine science and engineering Vol. 12; no. 3; p. 519
• Main Authors: Pais, Namitha Viona, O’Donnell, James, Ravishanker, Nalini
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2024
• Subjects: Bivariate analysis; Coastal management; Coastal waters; Coastal zone management; Connecticut; dependence structure; Environmental risk; extreme value analysis; Extreme values; Floods; Germany; harmonics; Hypotheses; Investigations; joint probability precipitation; Precipitation; Precipitation (Meteorology); Probability theory; Rain; Regression analysis; Risk management; Risk reduction; Sea level; Storm surges; Storms; Tidal waves; Time series; Value analysis; Variables; Germany; Connecticut; United States > US
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse12030519

The design strategies for flood risk reduction in coastal towns must be informed by the likelihood of flooding resulting from both precipitation and coastal storm surge. This paper discusses various bivariate extreme value methods to investigate the joint probability of the exceedance of thresholds in both precipitation and sea level and estimate their dependence structure. We present the results of the dependence structure obtained using the observational record at Bridgeport, CT, a station with long data records representative of coastal Connecticut. Furthermore, we evaluate the dependence structure after removing the effects of harmonics in the sea level data. Through this comprehensive analysis, our study seeks to contribute to the understanding of the joint occurrence of sea level and precipitation extremes, providing insights that are crucial for effective coastal management.