the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Wind-Wave Characteristics and extremes along the Emilia-Romagna coast
- 1Department of Physics and Astronomy, University of Bologna, Bologna, 40127, Italy
- 2Euro-Mediterranean Center on Climate Change, Lecce, 73100, Italy
- 3Hydro-Meteo-Climate Service of the Agency for Prevention, Environment and Energy of Emilia-Romagna, Arpae-SIMC, Bologna, 40122, Italy
- 1Department of Physics and Astronomy, University of Bologna, Bologna, 40127, Italy
- 2Euro-Mediterranean Center on Climate Change, Lecce, 73100, Italy
- 3Hydro-Meteo-Climate Service of the Agency for Prevention, Environment and Energy of Emilia-Romagna, Arpae-SIMC, Bologna, 40122, Italy
Abstract. This study examines the wind-wave characteristics along the Emilia-Romagna coasts (northern Adriatic Sea, Italy) with a 10-year wave simulation for the period 2010–2019 performed with the high-resolution unstructured-grid WW3 coastal wave model. The wave parameters (significant wave height, mean and peak wave period, and direction) were validated with the in-situ measurements at a coastal station Cesenatico. In the coastal belt, the annual mean wave heights varied from 0.2–0.4 m, and the seasonal mean was highest for the winter period (> 0.4m). The Emilia-Romagna coastal belt was characterized by wave and spectra seasonal signals with two dominant frequencies of the order of 10 s/ 5–6 s for autumn and winter, and 7–9 s/4 s for spring and summer. The wavelet power spectra of significant wave height for 10-years show considerable variability, having monthly and seasonal periods. This validated and calibrated data set enabled us to study the probability distributions of the significant wave height along the coasts and define a hazard index based on a fitted Weibull probability distribution function.
Umesh Pranavam Ayyappan Pillai et al.
Status: final response (author comments only)
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RC1: 'Comment on nhess-2022-103', Anonymous Referee #1, 28 Apr 2022
General comments
The manuscript (MS) examine an in-depth analysis of wind-wave characteristics along Emilia-Romagna (ER) coasts (northern Adriatic Sea, Italy) for 10 years starting from 2010 after fine tuning the numerical model-Wave Watch III at a buoy location. I appreciate the author’s efforts to include multidimensional analysis for better understanding of the seasonal and extreme wave impacts along the selected coast. The flow of the MS and specially discussion of research gap gives a clear idea for a reader about this work. There is no doubt about the quality of work. But these are some suggestions for authors which can even elevate the clarity of this research.
- There is a great discussion on wind speed in the MS. The wind speed values (section 4.1.1) seems like a low range for me. I strongly recommend the authors to check those values with in-situ measurements if you have any.
- Authors could discuss a bit more literatures on research conducted in similar way along global study regions than Adriatic Sea
- Could 10 years include the climatological impacts of wind-wave characteristics? The MS analyse more of seasonal aspects than climatological/long-term variation.Â
Some specific comments are mentioned below
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Specific comments
Kindly go through the below mentioned comments and alter the MS wherever is necessary:
- It will be greatly appreciated to mark the names mentioned in text to be on the figures. For eg. Line 74 mentions about Po delta, it will be easier for the readers to understand the work more if it’s marked in the figure too for visualization.
- Line 26: Than IPCC,2007, now IPCC report citations could be included.
- What is restricted/controlled fetch? It will be good to get more clarity on MS too.
- Line 85: Indicating the dominance of swell or sea in the selected study domain can enhance the knowledge beforehand.
- Figure 1: This can be more legible and well distributed. The mesh and bathymetry info can be in one figure. The figure is not indicating anything like region, the Sea etc. Including that can be a good idea. Figure 1. (a) can be an inset image and other information are important could be enlarged. A legible north arrow with map scales, coordinates lat & long N, E Â degree etc are also recommended (this comment is applicable for all maps).
- Give the legend names (eg. Figure 7, wave height (m) than mentioning meter in legend ranges), x- and y-axis variables in each plots, etc
- Line 199: Mention which ECMWF wind: ERA5, ERA interim etc.
- Appreciate explaining why the zones or control points are assigned? Or on what basis?
- Line 156: Why there is no ST6+ JONSWAP (EXP4)?
- Line 157: Apt to mention why the representative months are February and September?
- Section 3.3: Why the validation was done for each year separately? What is the significance of that?
- Figure 3 (f-j): It might be suitable to use 45-degree line than best fit line to best understand the underestimation and bias in validation. Check for wave characteristic notations in graph axis too.
- Sub-section 4.1.1 is the only subsection under 4.1, which can be merged with section 4.1 itself.
- Section 4.1.1: The wind speed values seems to be lower than a desired value. And SD is more than the annual mean wind speed which is not right. Check those values for wind speed everywhere. The mean value can come around 5 m/s to 20 m/s to produce the wave characteristics indicated in the MS. Make changes in text and figures accordingly. I recommend comparing these values with in-situ measurement if you have any for authors clarity.
- Figure 4 &6, mark degree N, E on Latitude and Longitude coordinate axis
- Revise Figure 5 according to new wind speed data and try to correlate Figure 5 and Figure 7 for any influence of predominant wind direction on wave characteristics.
- Line 285: Sticking to one notation of position can help the reader understand better. Either ‘control points’ or ‘stations. Indicating ‘point’ can sometimes make confusions.
- What is the significance of analysis of 25th day of month and monthly mean seasonal spectra for each year? What are the concluding remarks of these analysis could be mentioned?
- Line 315: ‘As seen from the Fig.???’ to be filled
- Line 425: ‘the comparison of Tm and Tp…… 10 years’ needs clarity. Please reframe by adding adequate information.
- A discussion on limitations/uncertainties of this study could be added. Such as limitations of Weibull distribution
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Technical /minor corrections
Some of the minor technical/typos noticed are mentioned here:
- Line 13: ‘direction’ to ‘wave direction’
- Significant wave height could be H subscript s. This applies with every wave characteristic. Using the global notations can be beneficial for a wider audience in understanding this research more.
- Expand acronym at first appearance will be appreciated. Few eg: are line 26 IPCC, WW3 is not expanded anywhere in MS, Line 101: ‘JONSWAP parameterization (Joint North Sea Wave Project)’, this can be ‘Joint North Sea Wave Project (JONSWAP) parameterization’, Explain ST4, ST6, CFL etc. Could use the acronyms after defining. PDF is expanded twice and is using the same.
- Line 121: check ‘~4.5 km hourly’
- After defining Significant wave height (HS) use the same in everywhere.
- I recommend the authors to make the decimal places consistent in entire MS. Eg. Line 126 location coordinates has 4 decimal places. Most research work would go for 2 decimal numbers.
- Line 180: ‘measurement’s’ to ‘measurements’
- Line 188: ‘Fig. 3’ to ‘Figure 3’
- Line 190: ‘relatively a good’ to ‘relatively good’
- Line 250: ‘and northern’ to ‘and the northern’
- Line 327: ‘upon blowing of the wind’ to ‘wind characteristics’
- Line 348: ‘costal’ to ‘coastal’
- Line 423: ‘A Hs’ to ‘An’
- Line 435: ‘waves’ to ‘wave’
[The same comments are attached in a pdf file too]
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RC2: 'Comment on nhess-2022-103', Anonymous Referee #2, 28 Apr 2022
General comments
The manuscript represent an important work and a substantial contribution to the understanding of natural hazards on ER area by the use of new methods like the hazard index. The used data and tools are up to international state of the art.
The scientific approaches and the applied methods are valid and discussed in an appropriate and balanced way. There are many references considering previous works on the area. The scientific methods and assumptions are clearly presented and can be reproduced thanks to the codes in annexe. The discussion could be broadened by a point on wind quality which is detailed below in this review.
The scientific data and results are precisely and clearly illustrated and presented with appropriate figures and tables. Rare remarks below are aimed to document still wider the results.
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Specific comments
The forcing by a 6-hourly wind at 0,125° on a area with such an important space and time variability than the Adriatic Sea seems to be the first limit of the wave climatology. Several results show it : first of all, the degraded scores on summer. Indeed, you show the worse correlation and bias of SWH in this season. The wave model understimate the wave height of 11 cm. It is known that global atmospheric model at such a scale don’t represent explicitly the convection and are not appropriate to simulate surface wind due to heating flux that occurs at this season. It is consistent with the lack of energy in the wave model compared to the observation.
This limit also appear through the small standard deviation in summer. Is the standard deviation of the observation so weak than in the model during this season ? A part of this decrease is due to the summer low wave height, but it could also come partially from a poor representation of convective wind.
I would recommand to better document this limit by some elements, for instance :
- a comparison with an observed wind climatology, even by a station on land. It could also be the climatology from a mesoscale model with hourly time step. Does it present the same standard deviation of wind speed in summer than the experiment, the same wind rose ? Are the relative quality of wind different between the seasons ?
- more explorative : what is the error in SWH or period depending on the wind direction observation (or from a mesoscale model) ? Indeed the global ECMWF model may have specific limitation for some local wind.
Moreover, a mention of this limit should appear in the discussion. Even in winter a 6-hourly wind has consequences on the model wave quality. Mediterranean sea is known for its very dynamic storms.
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l.151 Sensitivity experiments for wave model parametrizations : no test of different parameters value of each physics has been conducted, at least there is no mention of it in the paper. The validation of the method by 3 model configurations seems all the same sufficient. But the conclusion could be less affirmative regarding the better capacity of ST6 to represent sea state on ER area. We could think that another parametrisation of ST4 than the one in Ardhuin et al. 2010 could have produced better results than EXP3.
So I advice to moderate the sentence l.421-422 (Summary and conclusions) in a way like : « The sensitivity tests has shown the good accuracy of ST6+SHOWEX physics for wave hindcasts in the study area. »
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l.160 and 191Â : It would be very interesting to add the mean value of the observation for the sensitivity periods and the whole 10 years. Thus the reader would be aware of the relative error at this point.
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l.267Â : Is it possible to add a comparison against the observed wave rose of the station 6Â ?
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l.304 : The bimodality in winter and summer doesn’t seem so obvious on the graphics. In winter, I consider visually 3 cases of double peaked spectra. In summer, it is more complicated to distinguish and I don’t see a lot more than 1 case. Thus majority of cases appear to be single peaked.
I would recommand either to write clearly the number or proportion of cases that are bimodal by season in order to attest it solidly, or to pursue the exploration of data by adding more cases. Indeed all the days of February (August) of the 10 years could be examined. The proportion of bimodal cases could then be adressed on a significant number of occurrences.
If the results show effectively a proportion of around 30 % of bimodal spectra on these 2 seasons, I would nuance the conclusion. For instance, it would be appropriate to write « during winter and summer the spectra have often/sometimes bimodal characteristics », than « during winter and summer the spectra have bimodal characteristics » (l304-305).
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Technical corrections
l.24 : « is crucial » instead of « is a crucial »
l.30 : « Other state-of-the-art models include » instead of « Other state-of-the-art models includes »
l.89 : the formulation isn’t very clear. Proposition : « Armaroli et al. (2012) reported that waves originating from east correspond to a proportion of 91%HS < 1,25 m, owing to the controlled fetch. »
l.93 : « action-density » without space.
l.109 : « The model spectrum is sampled in 24 directions and 30 frequencies (0,0500-0,7932 Hz), with an increment factor of 1.1.
l.113 : ST4 isn’t mentioned there, wich is a bit confusing. Indeed ST4 and ST6 are both introduced earlier, and are actually used in the validation. It would be clearer to add a mention here of JONSWAP and ST4, precising that they were used only for the validation.
l.176Â : Please indicate in the legend of the table 3 the number of used buoys to be sure that it takes into account only the station 6 or the whole control points.
l.388Â : The chosen value of Xc could appear in the legend of Table 4. Its value appears only in page 20.
l.418Â : I would suppress the upper-case C of Conclusions, except if asked by the editor.
Umesh Pranavam Ayyappan Pillai et al.
Data sets
Data/ codes supporting manuscript titled "Wind-Wave Characteristics and extremes along the Emilia-Romagna coast" submitted to NHESS Umesh Pranavam Ayyappan Pillai; Nadia Pinardi; Ivan Federico; Salvatore Causio; Francesco Trotta; Silvia Unguendoli; Andrea Valentini https://doi.org/10.5281/zenodo.6360348
Umesh Pranavam Ayyappan Pillai et al.
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