Predicting Major Storm Surge Levels

Round 1

Reviewer 1 Report

 

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Atmosphere

"Predicting Major Storm Surge Levels"

by Robert Mendelsohn

Reviewer’s report

The paper presents an analysis of the surge levels along the East Coasts of United States. More in details, the author shows that the actual procedure adopted by the National Atmospheric and Oceanic Administration (NOAA) tends to underestimate large surges, caused by major hurricanes.

The argument is of some interest for the scientific community and can be published after a major revision.

In my opinion the surges due to major hurricanes cannot be analysed together with surges due to “regular” wind because these two classes of events don’t belong to the same “family”.

However, the author should address the following issue:

• Which method do you adopt to evaluate the parameter of the GEV distributions (Method of moments, Maximum likelihood, etc)?
• Please check if by adopting other method to evaluate the parameter of the GEV distributions the underestimate of large surges decreases.
• The method suggested by the author to evaluate the return period of the surges due to major hurricane appears too simplistic, due to the very low amount of data.

Finally, there are some typos within the text:

1. 51 “lcoation"
2. 104 “duifferent"
3. 106 “whethe”
4. 182 “thse”

 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

I thank the author for addressing my points and including the computer experiment in Section 3. 

Major Points:

1. GEV regression: As mentioned in my previous comments, the GEV model is fit to the mean-adjusted surge heights (accounting for the overall sea level rise). Here, the author is estimating the location, scale, and shape parameters of the appropriate GEV distribution. In the model-fitting procedure, no covariates or predictor variables are explicitly included in the fitted GEV model. So, we cannot call this a regression model because we are not explicitly determining the relationship between the response variable (heights) and other covariates. I suggest the author remove "regression analysis" from the manuscript (page 1 line 42 and  page 4 line 156)
2. Empirical study: I thank the author for including the empirical study in Section 3. The results demonstrate the limitations of the GEV model and advantages of the proposed approach. In the final paragraph (lines 290-297), would it be possible to include the number of: (1) actual hurricanes;  (2) extreme events predicted  by the proposed approach; and (3) extreme events predicted  by the GEV model? It would be nice to include these numbers for 1 or 2 sites, rather than reporting the predicted frequencies.
3.  Since the tide gauge data is adjusted for sea level rise, the manuscript analyzes pre-processed data. Adding additional details about this adjustment would be helpful for other researchers, especially those who many want to reproduce these results. this can be included in the manuscript or the appendix. 

 

Minor Edits:

1. Page 2 Line 54: "hurricnaes"
2. Page 2 Line 58: "errros"
3. Page 2 Line 58: Should be "GEV models" as the GEV is a formal probability distribution. 
4. Page 2 Line 63: "uisng"
5. Page 7 Line 231: "huricane"
6. Page 7 Line 256: double space between "the" and "hurricane"
7. Page 8 Line 259: "hurricances"
8. Page 8 Line 264: "si"

Author Response

We once again thank Reviewer 1 for his constructive comments. They have greatly improved the paper.

1. GEV regression: As mentioned in my previous comments, the GEV model is fit to the mean-adjusted surge heights (accounting for the overall sea level rise). Here, the author is estimating the location, scale, and shape parameters of the appropriate GEV distribution. In the model-fitting procedure, no covariates or predictor variables are explicitly included in the fitted GEV model. So, we cannot call this a regression model because we are not explicitly determining the relationship between the response variable (heights) and other covariates. I suggest the author remove "regression analysis" from the manuscript (page 1 line 42 and  page 4 line 156)

The language describing the estimation of the GEV model no longer mentions a regression on page 1 and 4 .

 

1. Empirical study: I thank the author for including the empirical study in Section 3. The results demonstrate the limitations of the GEV model and advantages of the proposed approach. In the final paragraph (lines 290-297), would it be possible to include the number of: (1) actual hurricanes;  (2) extreme events predicted  by the proposed approach; and (3) extreme events predicted  by the GEV model? It would be nice to include these numbers for 1 or 2 sites, rather than reporting the predicted frequencies.

This section was added to address this comment. "Over the last 90 years, across the 23 sites, the GEV model predicts one would have seen 10 surges from major hurricanes, the actual number of major hurricane surges was 39, and the predicted number of major hurricane surges was 38."

 

1.  Since the tide gauge data is adjusted for sea level rise, the manuscript analyzes pre-processed data. Adding additional details about this adjustment would be helpful for other researchers, especially those who many want to reproduce these results. this can be included in the manuscript or the appendix. 

The following sentences now describe how SLR was calculated in more detail.

The data must first be adjusted for sea level rise (SLR). Mean sea level is regressed on time at each station [11]. SLR captures the effect of rising ocean temperatures. Tidal station specific SLR also captures the effect of land subsidence. The regression measures the average relative SLR at each station. These measures are ideal for making decisions about flood and coastal protection because these all depend on relative sea level heights. However, it should be noted that the relative SLR is not the same as the absolute change in ocean height. Adding the relative SLR back on top of past maximum tides updates past records to current mean sea levels. These adjustments are intended to make the underlying surge probability distribution equivalent over time.       

 

Minor Edits:

All corrected.

1. Page 2 Line 54: "hurricnaes"
2. Page 2 Line 58: "errros"
3. Page 2 Line 58: Should be "GEV models" as the GEV is a formal probability distribution. 
4. Page 2 Line 63: "uisng"
5. Page 7 Line 231: "huricane"
6. Page 7 Line 256: double space between "the" and "hurricane"
7. Page 8 Line 259: "hurricances"
8. Page 8 Line 264: "si"

 

 

Reviewer 2 Report

The authors responded adequately to my previous issues. Therefore, the document can be accepted for publication.

Author Response

We have followed the reviewer's suggestion that typos be fixed.