Preprints
https://doi.org/10.5194/egusphere-2023-2134
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2023-2134
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
17 Oct 2023
| 17 Oct 2023
Estuarine hurricane wind can intensify surge-dominated extreme water level in shallow and converging coastal systems
Abstract. Based on the projected increase in hurricane landfall frequency on the middle to lower U.S. East Coast, we examined the crucial role of the estuarine wind field in exacerbating coastal flooding. A regionally refined atmospheric and two high-resolution hydrology and ocean models are integrated to provide plausible and physically-consistent ensembles of hurricane events and the associated flooding inside the Delaware Bay and River, a U.S. mid-Atlantic estuary. Model results show that the hurricane propagation direction, estuarine geometry, remote surge from the open ocean, and direct nearshore upwind stress could magnify the flood magnitude. More specifically, inland-bound tracks that make landfall before reaching the mid-Atlantic coast produce a more significant surge within Delaware Bay than the shore-parallel tracks, where the estuarine wind direction plays the primary role in surge amplification. Ultimately, this study emphasized the need for integrated models to capture the nonlinear dynamics and interactions in flood hazard modeling.
How to cite. Deb, M., Benedict, J., Sun, N., Yang, Z., Hetland, R., Judi, D., and Wang, T.: Estuarine hurricane wind can intensify surge-dominated extreme water level in shallow and converging coastal systems, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2134, 2023.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Download & links
Download & links
- Preprint
(17117 KB) - Metadata XML
- BibTeX
- EndNote
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2023-2134', Anonymous Referee #1, 17 Jan 2024
The authors did a good job in presenting interesting analyses and results to the scientific community. The research topic aligns with the scope of the journal Natural Hazards and Earth System Sciences. However, as there are several things requiring improvement in the manuscript at this point, I think the article should go through minor revisions and English editing before accepting and publishing. Specific review comments are provided to the authors as follows. The reviewer is willing to review the revised version of this manuscript if needed.
- Lines 038–053: While some earlier research has been provided in the INTRODUCTION section, the authors are encouraged to review and include two additional relevant publications that particularly addressed related research themes and Atlantic Ocean tropical cyclones. First, Parker et al. (2023; https://doi.org/10.1007/s11069-023-05939-6) used the GTSM-ERA5 model to investigate the proportional impacts of storm surge, wave setup, and astronomic tides on extreme water levels along the U.S. Southeast Coast. Their study revealed distinctive regional trends in the average contributions of storm surge and waves to extreme water levels during a 38-year period. Extreme water levels in the region result from combined surge, tide, and wave effects. The significance of each component varies across different locations. Next, Hsu et al. (2023; https://doi.org/10.5194/nhess-23-3895-2023) used the COAWST model to analyze how the storm characteristics of three historical hurricanes affected the storm surges and wave runup along the South Atlantic Bight. It was revealed that a slower storm translation speed prolongs total water level exceedance, potentially causing greater economic losses. Wave setup and swash predominantly impacted peak total water level, with pre-storm wave runup sometimes surpassing peak storm total water level under specific conditions.
- Lines 102–104: It would be great if the authors could explain how the total number of parameter sets (i.e., 50) was determined. Is it, for instance, based on any earlier research? Or did the authors carry out a sensitivity study?
- Figure 2(d): The authors are encouraged to indicate the direction reference. In other words, does a vector pointing toward the top in the lower part of the figure indicate southward wind? Also, is the length of the vectors proportional to the wind speed?
- Lines 104–107: Does this mean that the initial locations of the track/storm eye of ensemble E1 is the re-analyzed storm eye location on August 26th, 2011 00:00, and the initial locations of the track/storm eye of ensemble E2 is the re-analyzed storm eye location on August 25th, 2011 12:00? If yes, the authors might want to indicate it and provide more information here.
- Lines 157–159: The authors are encouraged the make the format of date/time consistent throughout the manuscript. In lines 105, the authors used 26 August 2011 00Z and 25 August 2011 12:00Z, which were already different from each other. These date/time formats in lines 105 are also different from the format in lines 157–159. The authors are also encouraged to make the date/time formats on figure axes consistent throughout the manuscript (e.g., Figures A1, A2, and B1).
- Lines 164–166: The authors are encouraged to provide more details about why Cases A and B were selected specifically from ensembles E1 and E2. For instance, do they have the highest peak surges or largest wind speed at specific locations compared to other cases in the two ensembles? In addition, the authors are encouraged to quantitatively demonstrate how similar are the surges produced by Cases A and B. For example, does this statement imply that the difference in peak surge elevations is less than a particular amount during a specific period? Or does this imply that the root-mean-square difference (or any other indicators) between the two time series is smaller than any given number?
- Lines 170–172: Does this mean that, regardless of the storm eye's instantaneous location, all computational grids within the polygon must have zero wind speeds? Furthermore, it is recommended that the authors explain the process by which this polygon was created and established. For instance, will the results change significantly if the shape of this polygon changes?
- Lines 197–199: While it is understood that the gradients of the curves look ‘similar’ by eye, the authors are encouraged to quantitatively describe how similar are the along-channel peak WSE gradients. For example, root-mean-square difference or model skill might be good indicators.
- Lines 223–260: The authors are encouraged to include some more relevant studies in the discussion section. In addition to the works of Parker et al. (2023) and Hsu et al. (2023) mentioned above, Suh and Lee (2018; https://doi.org/10.1016/j.csr.2018.09.007) analyzed the effects of storm translation speed and storm path on surge propagation processes and surge level along the coast. The authors might also want to consider including Suh and Lee (2018) in the INTRODUCTION. Incorporating discussions on these relevant works in the DISCUSSION AND CONCLUSIONS section is thought to be advantageous for readers, offering a more comprehensive background.
Citation: https://doi.org/10.5194/egusphere-2023-2134-RC1 -
AC1: 'Reply on RC1', Mithun Deb, 27 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2134/egusphere-2023-2134-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-2134', Anonymous Referee #2, 07 Mar 2024
GENERAL COMMENTS
This paper presents an interesting study about the role of estuarine wind fields in the amplification of coastal flooding caused by hurricanes.
The approach is robust and based on an integral approach that combines a regional atmospheric model with high-resolution hydrology and hydrodynamics models applied in Delaware Bay and River. The models used are validated and the results and discussion supports the final conclusions.
The results are relevant and present a contribution to the understanding of hurricanes in estuarine environments.
The document is concise and well-structured. Therefore, I recommend the publication of the paper with Minor Revision.
Specific comments:
- The selection of Hurricane Irene (2011) is very appropriate due to the severity and the influence on the study site. However, did the authors consider the option of using other hurricane tracks instead of perturbing Hurricane Irene or to complement the results obtained with Hurricane Irene?
- Regarding the generation of the ensembles, please justify the selection of 50-member ensembles and the two times selected for the initialization (separated by 12 hours). Please, discuss the sensitivity of the results/conclusions to these parameters.
- The validation of the FVCOM model (Appendix C) shows good results. However, the validation was carried out by forcing the model with ERA5 instead of E3SM outputs. Why was the FVCOM model not validated with E3SM outputs? It is suggested to include the validation of the hydrodynamic model with the forcing data used in the analysis or discuss in more detail this issue in the paper. This comparison would be also useful for understanding the uncertainty that justifies the generation of the 50-member ensembles.
- In Fig.3 and several parts of the document, the authors mention ‘simulations without the effect of estuarine wind fields, remote wind fill and full wind fill’. It is not clear how these types of wind fields (estuarine, remote and will) are considered in the numerical model. For example, does a simulation without estuarine wind fields refer to a simulation with astronomical tides only or with astronomical tides and pressure (but without wind)? For a simulation with remote wind fields, how are the estuarine wind fields switched off?. Please, explain in more detail.
- The results are mainly based on the comparison of cases A and B. How are the remaining Ensemble 1 and 2 simulations used in the analysis?
- The study focuses on convergent estuaries, can similar results and conclusions be expected for other types of estuaries? I would suggest the authors explain this in more detail in the discussion section.
Citation: https://doi.org/10.5194/egusphere-2023-2134-RC2 -
AC2: 'Reply on RC2', Mithun Deb, 27 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2134/egusphere-2023-2134-AC2-supplement.pdf
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2023-2134', Anonymous Referee #1, 17 Jan 2024
The authors did a good job in presenting interesting analyses and results to the scientific community. The research topic aligns with the scope of the journal Natural Hazards and Earth System Sciences. However, as there are several things requiring improvement in the manuscript at this point, I think the article should go through minor revisions and English editing before accepting and publishing. Specific review comments are provided to the authors as follows. The reviewer is willing to review the revised version of this manuscript if needed.
- Lines 038–053: While some earlier research has been provided in the INTRODUCTION section, the authors are encouraged to review and include two additional relevant publications that particularly addressed related research themes and Atlantic Ocean tropical cyclones. First, Parker et al. (2023; https://doi.org/10.1007/s11069-023-05939-6) used the GTSM-ERA5 model to investigate the proportional impacts of storm surge, wave setup, and astronomic tides on extreme water levels along the U.S. Southeast Coast. Their study revealed distinctive regional trends in the average contributions of storm surge and waves to extreme water levels during a 38-year period. Extreme water levels in the region result from combined surge, tide, and wave effects. The significance of each component varies across different locations. Next, Hsu et al. (2023; https://doi.org/10.5194/nhess-23-3895-2023) used the COAWST model to analyze how the storm characteristics of three historical hurricanes affected the storm surges and wave runup along the South Atlantic Bight. It was revealed that a slower storm translation speed prolongs total water level exceedance, potentially causing greater economic losses. Wave setup and swash predominantly impacted peak total water level, with pre-storm wave runup sometimes surpassing peak storm total water level under specific conditions.
- Lines 102–104: It would be great if the authors could explain how the total number of parameter sets (i.e., 50) was determined. Is it, for instance, based on any earlier research? Or did the authors carry out a sensitivity study?
- Figure 2(d): The authors are encouraged to indicate the direction reference. In other words, does a vector pointing toward the top in the lower part of the figure indicate southward wind? Also, is the length of the vectors proportional to the wind speed?
- Lines 104–107: Does this mean that the initial locations of the track/storm eye of ensemble E1 is the re-analyzed storm eye location on August 26th, 2011 00:00, and the initial locations of the track/storm eye of ensemble E2 is the re-analyzed storm eye location on August 25th, 2011 12:00? If yes, the authors might want to indicate it and provide more information here.
- Lines 157–159: The authors are encouraged the make the format of date/time consistent throughout the manuscript. In lines 105, the authors used 26 August 2011 00Z and 25 August 2011 12:00Z, which were already different from each other. These date/time formats in lines 105 are also different from the format in lines 157–159. The authors are also encouraged to make the date/time formats on figure axes consistent throughout the manuscript (e.g., Figures A1, A2, and B1).
- Lines 164–166: The authors are encouraged to provide more details about why Cases A and B were selected specifically from ensembles E1 and E2. For instance, do they have the highest peak surges or largest wind speed at specific locations compared to other cases in the two ensembles? In addition, the authors are encouraged to quantitatively demonstrate how similar are the surges produced by Cases A and B. For example, does this statement imply that the difference in peak surge elevations is less than a particular amount during a specific period? Or does this imply that the root-mean-square difference (or any other indicators) between the two time series is smaller than any given number?
- Lines 170–172: Does this mean that, regardless of the storm eye's instantaneous location, all computational grids within the polygon must have zero wind speeds? Furthermore, it is recommended that the authors explain the process by which this polygon was created and established. For instance, will the results change significantly if the shape of this polygon changes?
- Lines 197–199: While it is understood that the gradients of the curves look ‘similar’ by eye, the authors are encouraged to quantitatively describe how similar are the along-channel peak WSE gradients. For example, root-mean-square difference or model skill might be good indicators.
- Lines 223–260: The authors are encouraged to include some more relevant studies in the discussion section. In addition to the works of Parker et al. (2023) and Hsu et al. (2023) mentioned above, Suh and Lee (2018; https://doi.org/10.1016/j.csr.2018.09.007) analyzed the effects of storm translation speed and storm path on surge propagation processes and surge level along the coast. The authors might also want to consider including Suh and Lee (2018) in the INTRODUCTION. Incorporating discussions on these relevant works in the DISCUSSION AND CONCLUSIONS section is thought to be advantageous for readers, offering a more comprehensive background.
Citation: https://doi.org/10.5194/egusphere-2023-2134-RC1 -
AC1: 'Reply on RC1', Mithun Deb, 27 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2134/egusphere-2023-2134-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-2134', Anonymous Referee #2, 07 Mar 2024
GENERAL COMMENTS
This paper presents an interesting study about the role of estuarine wind fields in the amplification of coastal flooding caused by hurricanes.
The approach is robust and based on an integral approach that combines a regional atmospheric model with high-resolution hydrology and hydrodynamics models applied in Delaware Bay and River. The models used are validated and the results and discussion supports the final conclusions.
The results are relevant and present a contribution to the understanding of hurricanes in estuarine environments.
The document is concise and well-structured. Therefore, I recommend the publication of the paper with Minor Revision.
Specific comments:
- The selection of Hurricane Irene (2011) is very appropriate due to the severity and the influence on the study site. However, did the authors consider the option of using other hurricane tracks instead of perturbing Hurricane Irene or to complement the results obtained with Hurricane Irene?
- Regarding the generation of the ensembles, please justify the selection of 50-member ensembles and the two times selected for the initialization (separated by 12 hours). Please, discuss the sensitivity of the results/conclusions to these parameters.
- The validation of the FVCOM model (Appendix C) shows good results. However, the validation was carried out by forcing the model with ERA5 instead of E3SM outputs. Why was the FVCOM model not validated with E3SM outputs? It is suggested to include the validation of the hydrodynamic model with the forcing data used in the analysis or discuss in more detail this issue in the paper. This comparison would be also useful for understanding the uncertainty that justifies the generation of the 50-member ensembles.
- In Fig.3 and several parts of the document, the authors mention ‘simulations without the effect of estuarine wind fields, remote wind fill and full wind fill’. It is not clear how these types of wind fields (estuarine, remote and will) are considered in the numerical model. For example, does a simulation without estuarine wind fields refer to a simulation with astronomical tides only or with astronomical tides and pressure (but without wind)? For a simulation with remote wind fields, how are the estuarine wind fields switched off?. Please, explain in more detail.
- The results are mainly based on the comparison of cases A and B. How are the remaining Ensemble 1 and 2 simulations used in the analysis?
- The study focuses on convergent estuaries, can similar results and conclusions be expected for other types of estuaries? I would suggest the authors explain this in more detail in the discussion section.
Citation: https://doi.org/10.5194/egusphere-2023-2134-RC2 -
AC2: 'Reply on RC2', Mithun Deb, 27 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2134/egusphere-2023-2134-AC2-supplement.pdf
Viewed
Total article views: 438 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Oct 2023)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 282 | 124 | 32 | 438 | 22 | 22 |
- HTML: 282
- PDF: 124
- XML: 32
- Total: 438
- BibTeX: 22
- EndNote: 22
Viewed (geographical distribution)
Total article views: 428 (including HTML, PDF, and XML)
Thereof 428 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Latest update: 16 Jul 2024
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
James Benedict
Los Alamos National Laboratory, Los Alamos, NM 87544, USA
Ning Sun
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Zhaoqing Yang
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
Robert Hetland
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
David Judi
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Taiping Wang
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
Short summary
We coupled earth system, hydrology, and hydrodynamic models to generate plausible and physically consistent ensembles of hurricane events and their associated water levels from the open coast to tidal rivers of Delaware Bay and River. Our results show that the hurricane landfall locations and the estuarine wind can significantly amplify the extreme surge in a shallow and converging system, especially when the wind direction aligns with the surge propagation direction.
We coupled earth system, hydrology, and hydrodynamic models to generate plausible and physically...