the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Satellite-detected sea surface chlorophyll-a blooms in the Japan/East Sea: magnitude and timing
Abstract. The Japan/East Sea (JES) is known as a mid-latitude “Miniature Ocean” that features multiscale oceanic dynamics processes. We investigate the variability of the sea surface chlorophyll-a concentration (SSC) and bloom timing in the JES based on satellite remote sensing products spanning 1998–2019. The JES SSC exhibits strong seasonal variability and blooms twice annually, which are mainly governed by the physical environmental conditions. However, the influences of local oceanic dynamic processes (e.g., upwelling, oceanic fronts, mesoscale eddies, and near-inertial oscillations) on the bloom magnitude and timing of the entire JES are not critical, compared with the PAT and stratification. In addition, significant interannual variabilities of spring bloom magnitude occur along the JES's northwestern coast, and that of fall bloom magnitude occur in the deep Japan Basin. For spring bloom, the interannual variability of the bloom timing (initiation timing, termination timing and duration), which significantly affect the interannual bloom magnitude anomalies, are correlated with climate modes such as AO and ENSO. For fall bloom, on the interannual time scale, the bloom duration is mainly affected by the initiation timing. Both of them have a significant influence on the bloom magnitude. The initiation/termination timing of spring blooms has shifted earlier by 0.37/0.45 days annually along the JES's northwestern coast; the counterpart of fall blooms has shifted 0.49/1.28 days earlier annually in the deep Japan Basin.
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RC1: 'Comment on egusphere-2022-547', Yuntao Wang, 02 Jul 2022
The study of Satellite-detected sea surface chlorophyll-a blooms in the Japan/East Sea: magnitude and timing by Wang et al. applied satellite observations over 20 years for identifying the chlorophyll bloom in the Japan/East Sea. By comparing with all the major physical parameters, e.g., wind, eddies and fronts, they find the impact of solar radiation and stratification are actually more important to determine the bloom of phytoplankton. The presented information is interesting, but the scientific soundness should be further confirmed. In particular, the satellite observations are limited in the surface, but the nutrient supply at subsurface is also predominant. A major revision is necessary for presenting the credibility of their conclusion and improving the description.
Major comments:
- The dynamical dependence between interannual index and regional chlorophyll should be further investigated. It is not surprising to find some statistically significant correlation, but the underlying mechanisms should be further explored. The authors tried to present a dependence between ENSO and chlorophyll bloom via the intensity of Tsushima Warm Current. If this is the case, the intensity of the current should be added for presenting a comprehensive relationship. In particular, the lag among ENSO, warm current, front, chlorophyll is of great interesting.
- Highly similar method has been formerly applied in other oceans, e.g., the South China Sea. But they presented more robust features with intercorrelation at seasonal/semiseasonal and interannual variability that the authors should consider to implement in this study. In particular, the seasonal/semiseasonal cycles are usually prominent for all the parameters (Legaard and Thomas, 2006) and a significant correlation can be achieved all the time by adding a lag. It is more meaningful to explore the dependence at interannual variability after removing the seasonal/semiseasonal cycle.
- The authors should explore some better manner to present the seasonal signal in Figure 6. The information is very straightforward and multiple images are not necessarily needed to show the features. Similar method has been applied in the Kuroshio Extension region that can be applied here as well where similar patterns can be combined.
- Most of the correlations are very small between blooms and interannual index (Figure 10) that are not statistically significant. The figure can be moved into supplementary material.
Minor comments:
- In Figure 1, though it is a schematic image, the Subpolar front is not corrected presented and please refer to Xi et al. (2022) for a more realistic pattern. Kuroshio is wrongly spelled. Change the ‘Pacific’ to horizontal direction.
- Figure 2: Reduce the size of dots. List the equation of linear regression in the figure.
- Figure 3: Reduce the color range from 0.2~5 to 0.3~3 or some others that can emphasize the difference. Add the contour of 0.55 as a reference like Figure 4.
- Figure 4: Reduce the color range from 0.1~10 to 0.1~6 or some others that can emphasize the difference.
- The same colorbars should be applied respectively for spring bloom / fall bloom in Figure 11.
- Define PAR in the abstract at their first appearance. And it was wrongly spelled as PAT.
Reference:
Legaard, K. R., and Thomas, A. C. (2006), Spatial patterns in seasonal and interannual variability of chlorophyll and sea surface temperature in the California Current, J. Geophys. Res., 111, C06032.
Xi, J. et al. (2022) Variability and Intensity of the Sea Surface Temperature Front Associated with the Kuroshio Extension. Front. Mar. Sci. 9:836469.
Citation: https://doi.org/10.5194/egusphere-2022-547-RC1 - AC1: 'Reply on RC1', Tengfei Xu, 16 Jul 2022
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RC2: 'Comment on egusphere-2022-547', Anonymous Referee #2, 02 Aug 2022
Wang et al. analyzed long term variation of satellite chlorophyll in JES. Although the authors put together many kind of different data, the descriptions were fairly simplify for this complex ecosystem with large spatial variation. The discussion (many are in the results) is very poor and speculative, ignoring previous studies. Unfortunately, I cannot recommend the publication.
- The analysis of the interannual variation was only limited to the northwest coastal area for spring and deep Japan Basin for fall. Although it is based on the high variation of 1st mode of EOF, those areas are only limited areas of the JES, and I do not think it is suitable to conclude it is applicable to the whole JES.
- As the results correlations are OK, but the just correlation cannot explain the cause and effect. I think authors deeply concern about the cause and effect seriously.
- Discussion is very weak, and almost nothing was discussed about the reviews in the introduction.
- It may be a good idea to show correlations with Table(s).
Abstract
19 Delete “However”.
19-21 I do not think the authors really showed PAR and stratification is more important than other processes.
21 PAT should be PAR, and it need to be defined.
21 ‘In addition” may not be a good connection here.
23-24 Timing affect magnitude?
24-25 In the text, it was said ENSO is not important?
25 Duration is mainly affected by initial timing?
26 Duration and initial timing have significant influence on the bloom magnitude?
1. Introduction
78 SSC “is” related
79 “based on composite analyses without test of confidence level” It is not very clear what is the problem.
89 I am not sure previous analysis really did not focus on the whole area and this study did.
90 favorable/restricting factors? You only showed the correlations, and the cause/effect can be discussed.
2. Data and Methods
100 Is WOD18 station data? Is the comparison to satellite data based on daily match-up?
103 Did you check if there is no interannual vias?
105 Are PAR and k data daily, and later make monthly composite?
119 Add “climatology” for WOA18 temporal coverage.
124-126 “To identify blooms, the threshold is about 0.55” I do not understand this sentence. Is the value spatial average?
155 What is “an adaptive data analysis technique”?
163 Was logarithmic transform not used before calculating monthly mean of SSC?
3. Results
3.1
166 “Seasonal variability of bloom magnitude” Bloom is only spring and fall, and this title seems to be strange.
185 Is the analysis with average of whole JES?
187 Is this shortwave radiation same as PAR?
188-220 I think this include too much speculations and sloppy words, and they should move to discussion and discuss carefully.
I think the dynamics depends on the regions of the JES.
202, 205 The sea ice melting effect should be important for very limited area.
204 “favors” should be “corresponds”
208 “ocean dynamics” is too broad words.
208-209 “dominate the upper layer nutrients” It is too general.
210 “in accordance with the enhanced upwelling and frontal probability” It is too general.
211-212 EKE distribution was not shown.
212-220 None of those points are shown as the results.
221-240 Is the PCA analysis was conducted with monthly seasonal climatology of the whole spatial average?
I think if it spatial average it is very difficult to understand because of the regional difference of the JES.
3.2
245 What is the criteria of “significance”.
251 “JES SSC” Are these from the black boxed areas?
254 You should not know about “Photosynthetic activity”.
3.3
265 Is this about northwestern coast?
275 Just correlation cannot say “controlled”.
277 favorable?
277-278 I think this sentence mixed spring and fall blooms.
280-281 There is no data of increase of PAR.
282 Is this about deep Japan Basin?
288 There is no data of change wind.
290-291 It is already written.
292 Delete “The correlation show that”.
4. Discussion
This is very poorly written.
5. Summary
350 “SSC bloom” should be “phytoplankton bloom“.
(1) I am not sure which part gives this conclusion. At least, comparison of correlations of different processes is not shown.
354 PAR
(3)(4) It is very difficult to understand the idea from Fig. 14 (just a time series plot).
(5) “Relative to the AO” As English, it is difficult to understand the contrast to ENSO.
I do not understand how ENSO counterbalance in SSC.
Fig. 8 The areas averaged for (c) and (d) are?
Fig. 9 Is the value from the box in Fig. 8?
Fig. 10 Is the value from the box in Fig. 8?
Citation: https://doi.org/10.5194/egusphere-2022-547-RC2 - AC2: 'Reply on RC2', Tengfei Xu, 18 Aug 2022
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EC1: 'Comment on egusphere-2022-547', Xinping Hu, 26 Aug 2022
Dear Dingqi Wang:
Thank you for submitting your manuscript to Ocean Science. Two referees pointed out deficiencies in discussing mechanisms that controll the various types of correlations and a lack of quantitative analysis of these mechanisms. Some restructuring between the Results and Discussion sections may also be needed. You have addressed some of these issues in your rebuttal and I would like to invite you to submit a significantly revised version resolving the deficiencies. This revised manuscript will be evaluated again before a final decision can be made.
Best regards, ,Xinping Hu, Associate EditorCitation: https://doi.org/10.5194/egusphere-2022-547-EC1
Status: closed
-
RC1: 'Comment on egusphere-2022-547', Yuntao Wang, 02 Jul 2022
The study of Satellite-detected sea surface chlorophyll-a blooms in the Japan/East Sea: magnitude and timing by Wang et al. applied satellite observations over 20 years for identifying the chlorophyll bloom in the Japan/East Sea. By comparing with all the major physical parameters, e.g., wind, eddies and fronts, they find the impact of solar radiation and stratification are actually more important to determine the bloom of phytoplankton. The presented information is interesting, but the scientific soundness should be further confirmed. In particular, the satellite observations are limited in the surface, but the nutrient supply at subsurface is also predominant. A major revision is necessary for presenting the credibility of their conclusion and improving the description.
Major comments:
- The dynamical dependence between interannual index and regional chlorophyll should be further investigated. It is not surprising to find some statistically significant correlation, but the underlying mechanisms should be further explored. The authors tried to present a dependence between ENSO and chlorophyll bloom via the intensity of Tsushima Warm Current. If this is the case, the intensity of the current should be added for presenting a comprehensive relationship. In particular, the lag among ENSO, warm current, front, chlorophyll is of great interesting.
- Highly similar method has been formerly applied in other oceans, e.g., the South China Sea. But they presented more robust features with intercorrelation at seasonal/semiseasonal and interannual variability that the authors should consider to implement in this study. In particular, the seasonal/semiseasonal cycles are usually prominent for all the parameters (Legaard and Thomas, 2006) and a significant correlation can be achieved all the time by adding a lag. It is more meaningful to explore the dependence at interannual variability after removing the seasonal/semiseasonal cycle.
- The authors should explore some better manner to present the seasonal signal in Figure 6. The information is very straightforward and multiple images are not necessarily needed to show the features. Similar method has been applied in the Kuroshio Extension region that can be applied here as well where similar patterns can be combined.
- Most of the correlations are very small between blooms and interannual index (Figure 10) that are not statistically significant. The figure can be moved into supplementary material.
Minor comments:
- In Figure 1, though it is a schematic image, the Subpolar front is not corrected presented and please refer to Xi et al. (2022) for a more realistic pattern. Kuroshio is wrongly spelled. Change the ‘Pacific’ to horizontal direction.
- Figure 2: Reduce the size of dots. List the equation of linear regression in the figure.
- Figure 3: Reduce the color range from 0.2~5 to 0.3~3 or some others that can emphasize the difference. Add the contour of 0.55 as a reference like Figure 4.
- Figure 4: Reduce the color range from 0.1~10 to 0.1~6 or some others that can emphasize the difference.
- The same colorbars should be applied respectively for spring bloom / fall bloom in Figure 11.
- Define PAR in the abstract at their first appearance. And it was wrongly spelled as PAT.
Reference:
Legaard, K. R., and Thomas, A. C. (2006), Spatial patterns in seasonal and interannual variability of chlorophyll and sea surface temperature in the California Current, J. Geophys. Res., 111, C06032.
Xi, J. et al. (2022) Variability and Intensity of the Sea Surface Temperature Front Associated with the Kuroshio Extension. Front. Mar. Sci. 9:836469.
Citation: https://doi.org/10.5194/egusphere-2022-547-RC1 - AC1: 'Reply on RC1', Tengfei Xu, 16 Jul 2022
-
RC2: 'Comment on egusphere-2022-547', Anonymous Referee #2, 02 Aug 2022
Wang et al. analyzed long term variation of satellite chlorophyll in JES. Although the authors put together many kind of different data, the descriptions were fairly simplify for this complex ecosystem with large spatial variation. The discussion (many are in the results) is very poor and speculative, ignoring previous studies. Unfortunately, I cannot recommend the publication.
- The analysis of the interannual variation was only limited to the northwest coastal area for spring and deep Japan Basin for fall. Although it is based on the high variation of 1st mode of EOF, those areas are only limited areas of the JES, and I do not think it is suitable to conclude it is applicable to the whole JES.
- As the results correlations are OK, but the just correlation cannot explain the cause and effect. I think authors deeply concern about the cause and effect seriously.
- Discussion is very weak, and almost nothing was discussed about the reviews in the introduction.
- It may be a good idea to show correlations with Table(s).
Abstract
19 Delete “However”.
19-21 I do not think the authors really showed PAR and stratification is more important than other processes.
21 PAT should be PAR, and it need to be defined.
21 ‘In addition” may not be a good connection here.
23-24 Timing affect magnitude?
24-25 In the text, it was said ENSO is not important?
25 Duration is mainly affected by initial timing?
26 Duration and initial timing have significant influence on the bloom magnitude?
1. Introduction
78 SSC “is” related
79 “based on composite analyses without test of confidence level” It is not very clear what is the problem.
89 I am not sure previous analysis really did not focus on the whole area and this study did.
90 favorable/restricting factors? You only showed the correlations, and the cause/effect can be discussed.
2. Data and Methods
100 Is WOD18 station data? Is the comparison to satellite data based on daily match-up?
103 Did you check if there is no interannual vias?
105 Are PAR and k data daily, and later make monthly composite?
119 Add “climatology” for WOA18 temporal coverage.
124-126 “To identify blooms, the threshold is about 0.55” I do not understand this sentence. Is the value spatial average?
155 What is “an adaptive data analysis technique”?
163 Was logarithmic transform not used before calculating monthly mean of SSC?
3. Results
3.1
166 “Seasonal variability of bloom magnitude” Bloom is only spring and fall, and this title seems to be strange.
185 Is the analysis with average of whole JES?
187 Is this shortwave radiation same as PAR?
188-220 I think this include too much speculations and sloppy words, and they should move to discussion and discuss carefully.
I think the dynamics depends on the regions of the JES.
202, 205 The sea ice melting effect should be important for very limited area.
204 “favors” should be “corresponds”
208 “ocean dynamics” is too broad words.
208-209 “dominate the upper layer nutrients” It is too general.
210 “in accordance with the enhanced upwelling and frontal probability” It is too general.
211-212 EKE distribution was not shown.
212-220 None of those points are shown as the results.
221-240 Is the PCA analysis was conducted with monthly seasonal climatology of the whole spatial average?
I think if it spatial average it is very difficult to understand because of the regional difference of the JES.
3.2
245 What is the criteria of “significance”.
251 “JES SSC” Are these from the black boxed areas?
254 You should not know about “Photosynthetic activity”.
3.3
265 Is this about northwestern coast?
275 Just correlation cannot say “controlled”.
277 favorable?
277-278 I think this sentence mixed spring and fall blooms.
280-281 There is no data of increase of PAR.
282 Is this about deep Japan Basin?
288 There is no data of change wind.
290-291 It is already written.
292 Delete “The correlation show that”.
4. Discussion
This is very poorly written.
5. Summary
350 “SSC bloom” should be “phytoplankton bloom“.
(1) I am not sure which part gives this conclusion. At least, comparison of correlations of different processes is not shown.
354 PAR
(3)(4) It is very difficult to understand the idea from Fig. 14 (just a time series plot).
(5) “Relative to the AO” As English, it is difficult to understand the contrast to ENSO.
I do not understand how ENSO counterbalance in SSC.
Fig. 8 The areas averaged for (c) and (d) are?
Fig. 9 Is the value from the box in Fig. 8?
Fig. 10 Is the value from the box in Fig. 8?
Citation: https://doi.org/10.5194/egusphere-2022-547-RC2 - AC2: 'Reply on RC2', Tengfei Xu, 18 Aug 2022
-
EC1: 'Comment on egusphere-2022-547', Xinping Hu, 26 Aug 2022
Dear Dingqi Wang:
Thank you for submitting your manuscript to Ocean Science. Two referees pointed out deficiencies in discussing mechanisms that controll the various types of correlations and a lack of quantitative analysis of these mechanisms. Some restructuring between the Results and Discussion sections may also be needed. You have addressed some of these issues in your rebuttal and I would like to invite you to submit a significantly revised version resolving the deficiencies. This revised manuscript will be evaluated again before a final decision can be made.
Best regards, ,Xinping Hu, Associate EditorCitation: https://doi.org/10.5194/egusphere-2022-547-EC1
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