the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Influence of Storm Type on Compound Flood Hazard of a Mid-Latitude Coastal-Urban Environment
Abstract. A common feature within coastal cities is small, urbanized watersheds where the time of concentration is short, leading to vulnerability to flash flooding during coastal storms that can also cause storm surge. While many recent studies have provided evidence of dependency in these two flood drivers for many coastal areas worldwide, few studies have investigated their co-occurrence locally in detail, nor the storm types that are involved. Here we present a bivariate statistical analysis framework with historical rainfall and storm surge and tropical cyclone (TC) and extratropical cyclone (ETC) track data, using New York City (NYC) as a midlatitude demonstration site where these storm types play different roles. In contrast to prior studies that focused on daily or longer durations of rain, we apply hourly data and study simultaneous drivers and lags between them. We quantify characteristics of compound flood drivers including their dependency, magnitude, lag time and joint return periods, separately for TCs, ETCs, non-cyclone associated events, and merged data from all events. We find TCs have markedly different driver characteristics from other storm types and dominate the joint probabilities of the most extreme rain-surge compound events, even though they occur much less frequently. ETCs are the predominant source of more frequent, moderate compound events. The hourly data also reveal subtle but important spatial differences in lag times between the joint flood drivers. For Manhattan and southern shores of NYC during top-ranked TC rain events, rain intensity has a strong negative correlation with lag time to peak surge, promoting pluvial-coastal compound flooding. However, for the Bronx River in northern NYC, fluvial-coastal compounding is favoured due to a 2–6 hour lag from the time of peak rain to peak surge.
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RC1: 'Comment on hess-2024-135', Anonymous Referee #1, 11 Nov 2024
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The article “Influence of Storm Type on Compound Flood Hazard of a Mid-Latitude Coastal-Urban Environment” explores the differences between tropical cyclone (TC), extra-tropical cyclone (ETC) and non-cyclone (NC) as drivers of compound flooding to New York city, USA. The authors examine historic time-series of hourly rain and tide gauge data, using dependence and joint probability analysis methods, to explore the potential influence of storm type on near-simultaneous pluvial and storm surge flooding events. The study found that TCs dominate the most extreme pluvial/storm surge compound flood events, but ETCs are responsible for the majority of moderate and high frequency occurrences. There are important magnitude and lag differences depending on coastal location.
Strengths:
- Aim and objectives: the aims and objectives of the study are clearly stated. The use of long time-series of gauged data is to be welcomed.
- Discussion and conclusions: the focus on compound floods due to TC- and ETC-linked drivers is timely, given the rising frequency of extreme weather even within temperate zones, due to climate change.
- Statement of limitations: it benefits this study that simplifications and assumptions are clearly stated. This text provides context and is a source of ideas for future research.
Minor issues:
- Sea level rise trend: it was not completely clear how the trend of sea level rise has been removed from the 75-year time-series data measured at the tide gauges. Could the authors please expand on this?
- Distinction between TCs, ETCs and NCs/convective storms: It was not clear to me how the authors categorized the different storm types in section 2. Was this pre-assigned to each storm by the National Hurricane Centre, or was a threshold (e.g. as defined by the Saffir-Simpson scale) applied afterwards? This is key information for anyone wishing to reproduce the study.
- POT approach: could the authors please expand on the selection of the top-5 ranked rain/surge events each year? For context, it would be interesting to know how many of these events (out of all 75 x 5 events picked, per gauge), were categorized TCs, ETCs or NC/convective storms. A simple table would be enough. Only being able to capture a few TC events in the record, even with a long time-series, has to be recognized as an unavoidable limitation.
- Return period assumptions: the data are not longer than 75-years, how do the authors defend the calculation of return periods in excess of this (e.g. in figure 8)?
- Assumption of stationary storm surge over time: While it is stated that this first baseline assessment does simplify conditions, it could also be worth mentioning that recent research has identified that elsewhere, storm surge extremes are not in fact stationary, over similar time-scales (e.g. Calafat et al 2022, DOI: https://doi.org/10.1038/s41586-022-04426-5 )
- Figures: the majority of figures would be difficult to read for those who print in B&W, or are color-blind. Would recommend a different color palette (colorbrewer2.org, for example, suggests great color combinations that overcome this problem). In addition, would suggest that Figure 1 would benefit from (a) a simpler (line drawing) background rather than satellite imagery; (b) an inset, or wider view, to illustrate the NYC location with more of the Long Island Sound and Atlantic visible (to better understand storm surge, and significance of storm orientation at each gauge location); and (c) to perhaps reconsider the color scheme of gauge location points for the reasons stated to above. Additionally, figure 8 would benefit from larger font in the x-, and y- axis labels.
- Statement of relevance: the manuscript might benefit from a clearer description of the significance of the results of this study, which focuses on a relatively small urban watershed referencing a small number of gauges, to the current scientific knowledge of pluvial/coastal compound flooding. How do these findings contribute to the scientific conversation?
Overall:
Because of the use of hourly time-series data, this study provides useful insights into how lag time, magnitude, and orientation of storm-linked drivers all contribute to the state of flooding within an urban watershed of high economic value. The use of this more discrete data, creates a useful distinction between impacts in compound flooding due to TCs, ETCs, and convective storms. The study would benefit from clarifying some details of the methodology and results, as detailed above.
Technical corrections:
- L486 “in toto”?
- L114 - how long is the data collected at Battery gauge?
- L 143 – what is a “sewershed”?
- L165-L167. At a single gauge is this statement correct? This feature of storm surge is known due to onshore and offshore winds in different quadrants of the TC position; however usually one tide gauge records rising levels due to onshore winds, and a neighbor some km away would (hopefully be well-placed to) capture the negative surge due to offshore winds. Of course this effect changes with cyclone path/coastline orientation, and cyclone size.
Citation: https://doi.org/10.5194/hess-2024-135-RC1
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