Assessing Potential Links between Climate Variability and Sea Levels along the Coasts of North America

In order to better understand the extent to which global climate variability is linked to long-term mean and extreme sea level patterns, correlations between average sea levels at coastal sites throughout North America and low-frequency oscillations of several climate indices (CIs) were analyzed for the entire period of 1948-2018 as well as three equal-length sub-periods using correlation analysis. Correlation strength was assessed using Pearson's correlation coefficient, while significance was estimated using Leave-One-Out Cross-Validation and a bootstrapping technique (p-value). The sliding window size, lag time, and beginning month were varied for optimal correlation; 60-month sliding windows, along with 0 lag time, resulted in the strongest correlations. Strong (r >= 0.60) and significant (p-value <= 0.05) correlations were identified. The Western Hemisphere Warm Pool Eastern Asia/Western Russia index and ENSO exhibited the strongest and most widespread correlation with coastal sea levels. Further analysis was performed to identify and quantify the magnitude of any sea level trends using the Theil-Sen estimator, while the Mann-Kendall (MK) test was used to estimate the significance of said trends. The results revealed that a complex set of ocean-atmosphere interactions govern long-term coastal sea level variability in large coastal regions of North America. The final results of this study allow a greater understanding of potential links between climate variability and long-term sea levels along the coasts of North America, as well as insights into sudden shifts in these relationships, which will contribute toward more accurate long-term forecasts.