the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Jun 2024
Multiple time-scale variations of fronts in the Seto Inland Sea, Japan
Abstract. The Seto Inland Sea (SIS) is a critical semi-enclosed coastal sea in Japan, characterized by intricate coastlines and narrow straits that give rise to various fronts. Despite extensive research on tidal fronts, knowledge gaps persist regarding their spatiotemporal dynamics, particularly in certain poorly documented regions. Additionally, the understanding of thermohaline fronts, which emerge during winter, requires further investigation. We aimed to enhance our understanding of tidal and thermohaline fronts in the SIS by analyzing their dynamic processes, including intra-tidal and spring-neap tidal cycles, seasonal variations, and anomalous frontal variability. Using a gradient-based algorithm with an advanced contextual feature-preserving median filter, we processed the high-resolution sea surface temperature dataset to detect and quantify tidal and thermohaline fronts. Our analysis revealed the presence of numerous tidal fronts, predominantly influenced by the M2 tide, across the SIS, with substantial variations in spatial amplitude due to complex coastlines and narrow straits. Intra-tidal movements of tidal fronts corresponded to ebb and flood currents, while spring-neap tidal cycles and seasonal shifts influenced frontal positions and intensities. Additionally, thermohaline fronts were identified in certain regions during winter, characterized by large horizontal temperature and salinity gradients. This study enhances the understanding of tidal and thermohaline fronts in the SIS, emphasizing the importance of intra-tidal and wind-driven influences on frontal dynamics. However, limited observational coverage and resolution emphasize the need for further research to explore long-term temporal changes and better grasp the influence of ambient currents and wind patterns. Such insights are vital for effective coastal management and environmental monitoring in the SIS region.
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RC1: 'Comment on egusphere-2024-1667', Igor Belkin, 27 Jun 2024
Summary and recommendation: This paper is an important contribution and should be published pending a major revision.
Major concerns:
- Satellite data alone are not sufficient to reveal dynamical mechanisms that maintain various fronts except for some obvious cases such as, e.g., river plume fronts. Therefore, it is not clear how the authors can tell a tidal mixing front (TMF) from a “thermohaline” front (using the authors’ terminology). Perhaps, the authors relied on numerous studies by Japanese oceanographers who studied the Seto Inland Sea (SIS) from in situ data. If this is the case, then (A) such in situ studies should be cited with regard to each of 12 fronts identified in this study; (B) vertical sections of T and S across these 12 fronts should be provided in the main text or in the Supplementary Materials.
- The authors write about fronts “around” various straits. This is confusing. The authors should re-write such sentences, avoiding the ambiguous “around” descriptor.
- TMFs are typically aligned with certain isobaths. The depth of such isobaths marks the maximum depth of wintertime convective mixing. The authors apparently ignored this fundamental relation between TMFs’ locations and bathymetry.
- Many references are incomplete. Make sure that volume number, issue number, article number, and pages are always provided when available.
- L140: “Generally, pixels with grad 𝑇>1 ℃⁄km are identified as fronts.” – This threshold (used by many authors) is arbitrary. A discussion of front definitions is warranted.
- L175: “Shapes of tidal fronts in the SIS primarily align orthogonally with the direction connecting the straits and basins, coinciding with the tidal current direction.” – See Comment #3 above.
Comments on Figures:
- Figure 1. The color scale in Figure 1a is not good. Use standard color scales like “jet” or “nipy_spectral” in Matlab. The color scale in Figure 1b is awful. Use jet or nipy_spectral.
- Figures 2, 3, 4, and 6: Color scales are poor. Use jet or nipy_spectral.
Minor comments:
L15: “spatial amplitude” (?)
L30: “crucial in” (?)
L47: “appearance frequency” (?)
L72: “intensigied” – intensified [Use spellchecker!]
L75: “intra- and month-dependent variations” (?)
L145: “…the SST data phase in a tidal cycle…” (?)
L271: “… heavy water … above the light water...” (?) – “Dense water” would be better.
L382: “According to the effects of horizontal motion of water which has a horizontal buoyancy gradient on frontogenesis” – Re-write.
Best regards,
Igor Belkin, 2024-06-27
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AC1: 'Reply on RC1', X.Y. Guo, 14 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1667/egusphere-2024-1667-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-1667', Anonymous Referee #2, 14 Aug 2024
The manuscript is of significant importance, and I recommend its publication, but it requires major revisions.
Figure 1a: The colorbar displays the full range of colors, but these colors are unusual. Using pyGMT or an equivalent tool in MATLAB might offer better and more common maps.Figure 1b: Please use a linear gradient colormap.
You cite many articles, but you don’t summarize their findings. For example, lines 50-53 show a large amount of papers that are not explained.
Line 103: Can you reference Section 3.4 to provide the magnitude of the wind intensity? When you say relaxation, which values (approx) do you mean.
Section 3: How do you demonstrate the dynamics using only SST satellite data? Do you use any other products (satellite, simulations, etc.)?
Line 120: Instead of “were ~0.59 and ~-0.16 K,” I suggest “were approximately 0.59 K and -0.16 K, respectively.”
Equation 4: Could you provide the ratio of the total number of points for the given period of time to the number of cloud-free valid data points (Nb)? It is important to know this ratio for the representativeness of the samples.
Table 1: Can you add the distance to the stations?
Figure 3: Consider dedicating a full page to this map (and some others, they are small, and the lines are hard to observe. A configuration of 4 rows and 3 columns might improve clarity.
Figure 5: Use a consistent format for showing the numbers. Currently, some are rotated to the left, others to the right.
Generally, is much better to use the same colormap for similar representations, many plots have different colormaps.
Line 226: If there is an exception, please specify which ones.
Figure 7: The colormap has changed again. Please ensure consistency.
Figure 12: Can you explain the difference in values at latitude 34ºN?
In conclusions I would define the limitations of using only SST.Citation: https://doi.org/10.5194/egusphere-2024-1667-RC2 -
AC2: 'Reply on RC2', X.Y. Guo, 14 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1667/egusphere-2024-1667-AC2-supplement.pdf
-
AC2: 'Reply on RC2', X.Y. Guo, 14 Sep 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-1667', Igor Belkin, 27 Jun 2024
Summary and recommendation: This paper is an important contribution and should be published pending a major revision.
Major concerns:
- Satellite data alone are not sufficient to reveal dynamical mechanisms that maintain various fronts except for some obvious cases such as, e.g., river plume fronts. Therefore, it is not clear how the authors can tell a tidal mixing front (TMF) from a “thermohaline” front (using the authors’ terminology). Perhaps, the authors relied on numerous studies by Japanese oceanographers who studied the Seto Inland Sea (SIS) from in situ data. If this is the case, then (A) such in situ studies should be cited with regard to each of 12 fronts identified in this study; (B) vertical sections of T and S across these 12 fronts should be provided in the main text or in the Supplementary Materials.
- The authors write about fronts “around” various straits. This is confusing. The authors should re-write such sentences, avoiding the ambiguous “around” descriptor.
- TMFs are typically aligned with certain isobaths. The depth of such isobaths marks the maximum depth of wintertime convective mixing. The authors apparently ignored this fundamental relation between TMFs’ locations and bathymetry.
- Many references are incomplete. Make sure that volume number, issue number, article number, and pages are always provided when available.
- L140: “Generally, pixels with grad 𝑇>1 ℃⁄km are identified as fronts.” – This threshold (used by many authors) is arbitrary. A discussion of front definitions is warranted.
- L175: “Shapes of tidal fronts in the SIS primarily align orthogonally with the direction connecting the straits and basins, coinciding with the tidal current direction.” – See Comment #3 above.
Comments on Figures:
- Figure 1. The color scale in Figure 1a is not good. Use standard color scales like “jet” or “nipy_spectral” in Matlab. The color scale in Figure 1b is awful. Use jet or nipy_spectral.
- Figures 2, 3, 4, and 6: Color scales are poor. Use jet or nipy_spectral.
Minor comments:
L15: “spatial amplitude” (?)
L30: “crucial in” (?)
L47: “appearance frequency” (?)
L72: “intensigied” – intensified [Use spellchecker!]
L75: “intra- and month-dependent variations” (?)
L145: “…the SST data phase in a tidal cycle…” (?)
L271: “… heavy water … above the light water...” (?) – “Dense water” would be better.
L382: “According to the effects of horizontal motion of water which has a horizontal buoyancy gradient on frontogenesis” – Re-write.
Best regards,
Igor Belkin, 2024-06-27
-
AC1: 'Reply on RC1', X.Y. Guo, 14 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1667/egusphere-2024-1667-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-1667', Anonymous Referee #2, 14 Aug 2024
The manuscript is of significant importance, and I recommend its publication, but it requires major revisions.
Figure 1a: The colorbar displays the full range of colors, but these colors are unusual. Using pyGMT or an equivalent tool in MATLAB might offer better and more common maps.Figure 1b: Please use a linear gradient colormap.
You cite many articles, but you don’t summarize their findings. For example, lines 50-53 show a large amount of papers that are not explained.
Line 103: Can you reference Section 3.4 to provide the magnitude of the wind intensity? When you say relaxation, which values (approx) do you mean.
Section 3: How do you demonstrate the dynamics using only SST satellite data? Do you use any other products (satellite, simulations, etc.)?
Line 120: Instead of “were ~0.59 and ~-0.16 K,” I suggest “were approximately 0.59 K and -0.16 K, respectively.”
Equation 4: Could you provide the ratio of the total number of points for the given period of time to the number of cloud-free valid data points (Nb)? It is important to know this ratio for the representativeness of the samples.
Table 1: Can you add the distance to the stations?
Figure 3: Consider dedicating a full page to this map (and some others, they are small, and the lines are hard to observe. A configuration of 4 rows and 3 columns might improve clarity.
Figure 5: Use a consistent format for showing the numbers. Currently, some are rotated to the left, others to the right.
Generally, is much better to use the same colormap for similar representations, many plots have different colormaps.
Line 226: If there is an exception, please specify which ones.
Figure 7: The colormap has changed again. Please ensure consistency.
Figure 12: Can you explain the difference in values at latitude 34ºN?
In conclusions I would define the limitations of using only SST.Citation: https://doi.org/10.5194/egusphere-2024-1667-RC2 -
AC2: 'Reply on RC2', X.Y. Guo, 14 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1667/egusphere-2024-1667-AC2-supplement.pdf
-
AC2: 'Reply on RC2', X.Y. Guo, 14 Sep 2024
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