the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Sep 2025
The Role of El Niño Southern Oscillation in driving Coastal Hazards in the U.S. Pacific Northwest
Abstract. Since the 1982–83 major El Niño event, the El Niño Southern Oscillation (ENSO) has been suspected to be a major driver of coastal hazards in the U.S. Pacific Northwest (PNW). However, limited availability of observations, combined with the diversity of ENSO characteristics, has led to significant challenges constraining the teleconnections between ENSO effects and hazardous impacts on the coast. Defining these teleconnections provides key insight into internal climate dynamics and will inform hazard management. Here, we used a stochastic climate emulator to probabilistically assess the role of ENSO phase, ENSO strength, and synoptic weather in driving flooding and erosion hazard proxies on the U.S. PNW coast. When compared to the last 45 years of observations, our simulations suggest that ENSO is not necessarily a strong predictor of coastal hazards in the PNW, and instead, indicate that the relationship between ENSO and coastal hazard teleconnections is more complex than previously believed.
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Status: open (until 24 Oct 2025)
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RC1: 'Comment on egusphere-2025-4039', Anonymous Referee #1, 17 Sep 2025
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AC1: 'Reply on RC1', Meredith Leung, 23 Sep 2025
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Thank you for your supportive comments and clear direction on how to improve the manuscript. Your feedback on separating the discussion and conclusion is much appreciated, particularly your suggestions for subsections to improve clarity. We will re-organize our text into the described sections in our revision and include a concrete and expanded discussion of avenues for future work.
Citation: https://doi.org/10.5194/egusphere-2025-4039-AC1
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AC1: 'Reply on RC1', Meredith Leung, 23 Sep 2025
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RC2: 'Comment on egusphere-2025-4039', Anonymous Referee #2, 05 Oct 2025
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This study investigates the relationship between ENSO and coastal hazard risk in the U.S. Pacific Northwest using a stochastic climate emulator. The results show that the ENSO may not be a necessarily have a strong relationship with the coastal hazards in this region. Overall, this study is comprehensive and well designed. However, I still have several questions and suggestions for improving the current work.
1) In the abstract, only the term “coastal hazards” was mentioned. However, this study only investigated the cross-shore hazard without including the shoreline hazard. It is suggested to make it more specific to avoid misleading conclusions.
2) The Introduction Section is too long. It would be better to make it more concise, only highlight the existing limitation and research gaps, and remove some unnecessary details in previous studies. Also, in the Discussion & Conclusion, several previous studies were mentioned. It is suggested to incorporate some into the Introduction Section, and only highlight the new findings and new questions raised from this study.
3) In Fig. 1, what does the number in the top left of the sub-figures of AWT and DWT mean?
4) In the k-means clustering, how to determine the value of k?
5) Could you justify the usage of Gaussian copulas in the stochastic climate emulator?
6) Line 310, one of the empirical wave runup formulas was used to calculate the TWL, but it is expected that different empirical formulas may lead to different estimates. Why this particular one was employed? How would you quantify the uncertainty propagation through the simulation process?
7) Line 316: How did you define an “unsafe beach”?
8) Line 348, what methods were used to construct the probability density functions of the hydrodynamic variables? Some inherent parameters of these methods may have a significant effect on the shape of the probability density curves.
9) Lines 373-374: How did you define the “anomalies” of those variables?
10) Line 401: Why could the EP El Nino exhibit negative winter wave energy anomalies? Are there any evidence observed from any historical events?
11) Lines 420-421: Fig. 5(d) actually shows that the probability density curves for the historical and simulated variables are different to some extent. Also, The legend of Fig. 5(d) is not consistent with the color in the figure.
12) Line 524: Could you elaborate what the model limitations are?Minor Issues
13) The label of vertical axis of Fig. 2(b) was covered by Fig. 2(c).
14) In Figs. 5 and 6, the numbers in the violin plots are not clear and some overlapped with each other.Citation: https://doi.org/10.5194/egusphere-2025-4039-RC2
Data sets
TESLA-Cascadia Total Water Levels and Chronic Hazard Proxies Meredith Leung, Laura Cagigal, Randall Pittman, Fernando Mendez, and Peter Ruggerio https://doi.org/10.17603/ds2-mr46-5g54
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This manuscript investigates the relationship between the El Niño Southern Oscillation (ENSO) and coastal hazards in the U.S. Pacific Northwest (PNW) using a stochastic climate emulator. By generating probabilistic simulations, the authors assess the role of ENSO phase, intensity, and synoptic weather in driving flooding and erosion proxies. A central finding is that ENSO, while linked to hydrodynamic anomalies, is not as reliable a predictor of coastal hazard impacts in the PNW as often inferred from the observational record. This represents a valuable contribution to the literature and has implications for climate-informed coastal hazard management.
Currently, Section 4 merges discussion and conclusion, which makes the text somewhat lengthy and diffuse. I recommend splitting into two sections:
Discussion: further organized into subsections (e.g., ENSO mechanisms, interaction with other climate modes, methodological limitations, comparison with prior studies).
Conclusion: concise summary of the main findings and their implications.
Future research directions. Although the manuscript briefly mentions PDO and other climate modes, the outlook for future work could be strengthened. A dedicated subsection at the end of the discussion would improve clarity. Possible directions include:
Incorporating PDO and other large-scale climate modes into stochastic simulations to assess multi-mode interactions.
Coupling the emulator with shoreline change models to capture longshore sediment transport and ENSO-related shoreline rotation.
Exploring the implications of enhanced ENSO variability under anthropogenic climate change, as recent literature suggests.
Some paragraphs in the discussion are dense and could benefit from restructuring or condensation. For example, the comparison between simulated and historical anomalies could be streamlined with summary tables or schematic figures to highlight the key differences.
Recommendation: Moderate revision. The study is timely and well executed, but the manuscript would benefit from clearer structuring of the discussion, a more concise conclusion, and a stronger forward-looking perspective.