the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Oct 2024
Untangling the Waves: Decomposing Extreme Sea Levels in a non-tidal basin, the Baltic Sea
Abstract. Extreme sea level (ESL) events are typically caused by the combination of various long surface waves, such as storm surges and high tides. In the non-tidal, semi-enclosed Baltic Sea, however, ESL dynamics differ. Key contributors include the Baltic's variable filling state (preconditioning) due to limited water exchange with the North Sea and inertial surface waves, known as seiches, which are triggered by wind, atmospheric pressure, and basin bathymetry. This study decomposes ESL events in the Baltic Sea into three key components: the filling state, seiches, and storm surges. Our results show that storm surges dominate the western Baltic, while the filling state is more influential in the central and northern regions. Using a numerical hydrodynamic model, we further decompose these components based on their driving forces: wind, atmospheric pressure, North Atlantic sea level, baroclinicity, and sea ice. Wind and atmospheric pressure are the primary forces across all components, with the Atlantic sea level contributing up to 10 % to the filling state. These findings offer a deeper understanding of ESL formation in the Baltic Sea, providing critical insights for coastal flood risk assessment in this unique region.
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RC1: 'Comment on nhess-2024-198', Mika Rantanen, 20 Nov 2024
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Review of NHESSD manuscript nhess-2024-198 “Untangling the Waves: Decomposing Extreme Sea Levels in a non-tidal basin, the Baltic Sea” by Lorenz et al.
General comments
This manuscript provides quantitative decomposition of extreme sea level (ESL) events in the Baltic Sea into storm surges, filling and seiches. These components are further decomposed into components from various forcings such as wind and atmospheric pressure. The authors use sea level observations from the entire Baltic Sea coastline and simulations with a numerical model. One of the key results is that storm surges dominate ESL events in the western Baltic Sea, while the filling contribution is more important in the central and northern sea regions.
I found the topic of this manuscript highly relevant and valuable. Here in Finland, it is often stated that surges, filling (preconditioning), and seiches together cause the highest sea levels in the Baltic Sea. However, concrete evidence quantifying their relative contributions has been lacking. The same applies to the specific roles of wind and atmospheric pressure in driving high sea levels. In my opinion, this study fills an important gap by providing detailed quantification of these processes.
I think the overall presentation of the manuscript and its language was very good. The structure was logical, and there was a “red line” in the story which made the reading enjoyable. The background was nicely covered with relevant references, making the impression that the authors do know the topic very well. The results were discussed in a detailed way from various perspectives at the end of the paper. While I am not a marine scientist, I still understood most of the text.
Despite the positive feeling I got from the reading, I still found a few aspects which in my opinion require clarification: these are related to 1) methods and 2) the negative correlation between storm surges and filling. These are explained below. In any case, I can recommend publication after these (minor) comments have been addressed.
Minor comments
- In section 2, you present the observations (2.1), the model simulations (2.2) and the diagnostic decomposition method (2.3). There were some parts which I think were missing:
- In 2.3.1 (L115) you do not explain whether the decomposition is done for observations or model simulations or both. When I first did read these sections I assumed that the decomposition was only done for simulated sea level heights, so it was surprising to see in Fig. 3 that the method is applied to both. There is a brief mention in L92 that the decomposition is also done for observations, but this point should be emphasised later when presenting the decomposition method.
- At Section 2.3.1, you could explain how you derive ηESL. Is that extracted from modelled data or directly from observations?
- At L95, it would be clearer to write that the observational time series for different tide gauges are of different lengths. Or are they? And I assume that the detrending is based on the linear trend of the whole time series and not on a fixed period.
- In Section 2.2, it would make the choice of the model more robust if you could briefly mention whether the model has been used successfully in some previous studies.
- In Section 2.2. It was not clear for me what was the temporal resolution (hourly?) of the simulations, and how long were the simulations? And did you simulate the whole year, including the summer season? Overall the time period which was studied should be written more clearly (I found it from L147 but it could come earlier).
- In Section 2.4 (L158-163), the method of calculating the relative contributions of the forcings for sea level remained a little unclear to me. Could it be demonstrated using a single station example? Like writing down the magnitudes of the relative contributions from a station in Fig. 2d. This came back to me when I tried to interpret the sea ice contribution from Fig 7. You say (probably correctly) that its contribution is negative, but in Fig 7 they all look positive because they are presented as pie charts. Is there a contradiction, or have I misunderstood?
- At Section 3.1.1 (L201-213), I didn’t really understand the reason why filling and surges are negatively correlated, especially because in Fig. 2b they seem to be positively correlated (both are positive at the time of maximum). I read several times the sentence “Since the peak sea level of each event is fixed, a particularly high surge would naturally coincide with a lower filling state relative to the mean of the Gaussian distribution.”, but I still didn’t get the idea.
From a meteorological perspective, strong cyclones are typically associated with (long-lasting) westerly winds, which would intuitively lead to a positive correlation between storm surges and filling. Given that this result appears to be one of the key findings of the study, and also being in an apparent contradiction with other studies, I suggest clarifying the mechanism in greater detail. Providing additional explanation would help resolve this apparent contradiction and strengthen the manuscript’s conclusions.Other, specific comments
L12: This phenomenon: does this refer to the rising mean sea level or ESL events? Isn’t the ESL events the main cause of flooding, with a smaller contribution from rising sea level?
L31. By input data you mean weather prediction models or reanalysis? Can you mention them explicitly as I was wondering what input data is specifically meant here.
L62 These three temporal. Would it be better to put the three components together in brackets, for example, so that the reader does not have to go back to the previous page to see what the three were?
Table 1. TSClim: temperature or salinity?
Table 1. IceClim: inter-annual is written twice. And what does it mean by neglecting the inter-annual variability? Do you run the model with climatological sea ice cover?
L109. Does this mean you performed seven 58-year simulations?
L237. .. up to 30 %. This sentence remains a bit incomplete. Where does it contribute and what? Can you rephrase it?
L252 and L254 I think you write two times the residual term contribution? Is the 2nd (40%) for Danish Straits?
L258. As a meteorologist, I thought first that baroclinicity means atmospheric baroclinicity. Could it be rephrased to add seawater here?
Figure 7-9. Related to minor comment 1f. I don’t understand how the negative contributions from e.g. sea ice forcing is presented in these pie charts. For me it looks like all the forcings are contributing positively.
L271 wind systems. Maybe wind climatology is a better term here?
L279 its mean -> the mean contribution of filling
L281 on this time scale. Which time scale?
L288 Do you speak about the potential increase due to seiches here? It could be added to the sentence.
L296: 10 % on average. Was this result shown in some figure? If not, better to add “not shown”.
L303 ... currently very small. Maybe add reference to Figure?
L339. Aren't meteotsunamis more of a summer phenomenon, so that they generally don't occur at the same time as wind-driven extreme sea level events, which tend to occur in the winter season? If this is the case, it could be mentioned here.
Citation: https://doi.org/10.5194/nhess-2024-198-RC1
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