Climatic, Decadal, and Interannual Variability in the Upper Layer of the Mediterranean Sea Using Remotely Sensed and In-Situ Data

Round 1

Reviewer 1 Report

The study analysed the sea-level, SST, SSS and freshwater flux based on the traditional EOF method. It provides some important information about how the decadal signal associated with Northern Ionian Gyre circulation reversals is clearly identifiable in three (i.e., ADT, SST and SSS) of the four parameters studied. The paper is well-written and well-structured; however, I have some major comments that presently prevent me to suggest publication of this work in its present form.

• What basis did the authors use (i.e., references, or anything else?) to make this geographical choice of the three main sub-basins (WMED, CMED, EMED).

In my opinion, it is very ambiguous to put Adriatic Sea with Ionian as CMED; they are very different in terms of water properties (Temp, Salinity, and water masses). I propose either combining these basins (Ionian, Aegean, Levantine, and Adriatic) as EMED or separating them and omit CMED definition.

 

• Other important climate factors (e.g., Climate Indices, net heat flux, wind stress) and their relationship to interannual and decadal variability were not mentioned or discussed in the study. Some examples of similar discussions can be found in (Tsimplis 2001; Pinardi et al., 2015; Nagy et al. 2019; Mohamed and Skiliris, 2021).

 

Tsimplis, M.N., 2001. Forcing of the Mediterranean Sea by atmospheric oscillations over the North Atlantic. Geophysical Research Letter, vol. 28, no. 5, pp 803-806.

Pinardi, N., Zavatarelli, M. Adani, G. Coppini, C. Fratianni, P. Oddo, S. Simoncelli, M. Tonani, V. Lyubartsev, and Dobricic, S., 2015. The Mediterranean Sea large scale low frequency ocean variability from 1987 to 2007: a retrospective analysis, Progress in Oceanography, doi: 10.1016/j.pocean.2013.11.003.

Nagy, H., Di-Lorenzo, E., and El-Gindy, A. 2019. The Impact of Climate Change on Circulation Patterns in the Eastern Mediterranean Sea Upper Layer Using Med-ROMS Model. Journal of Progress in Oceanography (175) 226:244; https://doi.org/10.1016/j.pocean.2019.04.012

Mohamed, B.; Skliris, N. Steric and atmospheric contributions to interannual sea level variability in the eastern Mediterranean Sea over 1993–2019. Oceanologia 2021, 63, 1–13. 

 

• The authors mentioned in the introduction ’The BiOS is a feedback mechanism, driven by the difference in salinity between the salty and warmer waters originating in the eastern Mediterranean and the less saline AW entering from the Sicily Channel [30, 36, 37, 32], that is the most accredited to lead to the quasi-decadal reversal of the Northern Ionian Gyre (NIG) from anticyclonic to cyclonic and vice-versa’’.

Other studies, in addition to the ones mentioned by the authors, investigated the BiOS from various perspectives, such as (eg., Korres et al., 2000; Demirov and Pinardi, 2002; Mihanović, et al. 2015; Pinardi et al. 2015; Nagy et al. 2019).  These studies found the Ionian reversal mechanism has emerged, due to the high space–time consistency of the reanalysis fields and it was evident in the streamfunction, providing further evidence of the wind-driven nature of the mechanisms causing the northern Ionian reversal. I believe the authors should discuss their findings from different points of view.

 

Korres, G., Pinardi, N. and Lascaratos, A., 2000. The ocean response to low frequency inter-annual atmospheric variability in the Mediterranean Sea. Part I. Sensitivity experiments and energy analysis. J. Clim. 13 (4), 705–731.

Demirov, E., and Pinardi, N., 2002. Simulation of the Mediterranean circulation from 1979 to 1993 model simulations: Part II. Energetics of Variability J.Mar.Sys. (33/34): 23-50.

Mihanović, H., Vilibić, I., Dunić, N., Šepić, J., 2015. Mapping of decadal middle Adriatic oceanographic variability and its relation to the BiOS regime. J. Geophys. Res. Oceans, 120. http://dx.doi.org/10.1002/2015JC010725.

 

• Regarding the interannual variability and trend, it is unclear in the manuscript which method the author used to eliminate the seasonal cycle and extract the interannual and decadal variability. Although I see the word (trend) in several places throughout the manuscript, I didn't find any values for these trends across the entire manuscript. Why did the authors show the trend line from the principal components (PCs) rather than the variable itself (SST, SSS, and ADT)?

 

 

Minor Comments

• Unfortunately, I couldn't find any line-numbering in the paper, which would have made it easier to review and give comments.
• In the abstract ‘’The aim of this research is to identify possible interconnection between these and other parameters that contribute to the regulatory effect of the sea on the climate. For this purpose, variability of four oceanographic and air/sea interaction parameters (sea-level, SST, SSS and freshwater flux) are estimated over the last 27 years using in-situ data, satellite and model products’’

I recommend that the authors improve the abstract by including the most important research findings (i.e., EOF trend results for SST, SSS, and fresh water), and the above text be moved to the introduction section (aim of this research).

Introduction

• Thermohaline properties of the Mediterranean and, steric and mass sea-level variations, occur on interannual and decadal scales [13, 14, 15]. Recently, Mohamed and Skiliris, (2021) have studied the steric and atmospheric contributions to interannual sea level variability in the eastern Mediterranean Sea over 1993–2019. The study covers the same time period as yours, so you can add it and compare your findings to it.
• Figure 1. a) Schematic representation of the thermohaline circulation in the Mediterranean Sea where the intermediate and deep-water formation sites are highlighted. This figure is unclear (i.e., Bathymetry, Circulation, background map). I believe you made the background map white, as well as the colormap from 0-500. This must be changed using arrows and gyres. Furthermore, you are missing some circulation features such as the Mid Mediterranean Jet (MMJ), Shikmona Gyre, and Ieraperta Gyre; please see the schematic created by (Pinardi et al 2003; Pinardi et al. 2005; Pujoul et al. 2005).

 

 

Pinardi N., Allen I., Demirov E., De Mey P., Korres G., Lascratos A., Le Traon PY., Maillard C., Manzella G. and Tziavos C., 2003. Mediterranean Forecasting System: First Phase of Implementation (1998-2001). J. Annales Geophysicae.(21):1-21.

Pinardi, N., Arneri, E., Crise, A., Ravaioli, M. and Zavatarelli, M.,2005. The Physical, sedimentary, and ecological structure and variability of shelf areas in the Mediterranean Sea. In: The Sea. Harvard University, Vol14.chapter 32.

Pujol, M-I., and Larnicol G., 2005. Mediterranean Sea eddy kinetic energy variability from 11 years of altimetric data. Journal of Marine Systems, Volume 58, Issue 3-4, p. 121-142. Doi:10.1016/j.jmarsys.2005.07.005.

 

 

 

 

Comments for author File: Comments.docx

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The paper systematically analyzed several sets of remote-sensing data about the Mediterranean Sea. The focus of the study is to identify the climate, decadal and interannual signals of the regional ocean. The methodology is mainly EOF approach, which gives both spatial and temporal patterns of the data. It would be better to unify/synthesize these several variables. They all seem to correlated. The conclusions are generic, which I did not see surprise or conflict with previous studies, but a further confirmation is certainly worthy of publishing.

The paper is well written. One minor suggestion: remove the sentence in Fig. 1 caption "cyan circles show ... in Fig. 10c and 10d", which seems unnecessary to jump from Fig. 1 to Fig. 10. The cyan color is unclear in the figure.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Review report on “Climatic, decadal and interannual variability in the upper layer of the Mediterranean Sea using remotely sensed and in-situ data” by Milena Menna et al.

 

1. Line 13: The Mediterranean Sea (MED).
2. Keywords: Delete the number.
3. Lines 157-182: Please consider shortening the content and expressing it briefly.
4. Figure 2A: It is better to change the interval of colorbar to [- 1.5 1.5].
5. Figure 3A: Add “0.5” on the colorbar.
6. Figure 4A to 4D: For the four subgraphs, the configuration of the color bar looks very inappropriate. In addition to changing the color, the interval of the color bar is preferably [- 0.8, 0.8], but considering that there are few data less than 0, it may be suggested that the author can consider using another color configuration for values lower than 0.
7. Figure 5: As in the previous suggestion, the author should consider highlighting the data of [- 1 0] interval.
8. Figure 6: Please ensure that the colorbar range of the four subgraphs is the same representation. Figure E covers the lower edge of figure C.
9. Figure 9A: Add “-4” on the colorbar. Figure 9C: Change the colorbar interval to [-4 4].
10. Table 1 and Table 2: Please follow the format in the journal template.
11. Figure S1A: Change the colorbar interval to [-20 20]. Figure S1C: What is the upper boundary value of the colorbar?

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

Major comments:

1. I don't see enough for this journal using of remote sensing. You use only complete products and don't do anything with the satellites yourself. However, it will be up to the editors to decide
2. There is no discussion section. there should be proposals to explain the causes of climate fluctuations. increase in the global ocean level,  global warming, connection with atmospheric indices (NAO,AO).
3. it is necessary to add a wind analysis that affects all hydrometeorological processes in the region. Please read the article JMSE | Free Full-Text | Sea Surface Temperature Variability and Marine Heat Waves over the Aegean, Ionian, and Cretan Seas from 2008–2021 (mdpi.com) about heat waves. They found the strong correlation between wind and SST for spring seasons. it is quite possible that you will find wind connections and your parameters for different parts of the Mediterranean sea.
4. Needed the analysis of correlations with total heat flux, and atmospheric indices (NAO,AO).

Minor comments:

1. Abstract - please do not use abbreviations and their transcripts in abstract
2. Abstract and keywords - please add about the EOF analysis
3. keywords - please add SST, ADT and others parameters
4. Salinity data derived from the Word Ocean Database - please add the information about the amount of data, how often there are profiles per month for a specific point.
5. The Argo float vertical salinity profiles - - please add the information about the amount of data.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

 The authors were successfully addressed all of my comments, therefore I accept this work for publication in the Journal of Remote Sensing in its current form.

Author Response

The authors thank Reviewer1# for her/his time and effort in reviewing the manuscript and for her/his fruitful comments, which were helpful in improving the paper. 

Reviewer 3 Report

Dear authors,

Thanks to the authors for revising the manuscript based on my comments, I am so satisfied that I can now recommend this manuscript for acceptance for publication.

Author Response

The authors thank Reviewer3# for her/his time and effort in reviewing the manuscript and for her/his fruitful comments, which were helpful in improving the paper. 

Reviewer 4 Report

Figure 5 and 9 - please change the colorbar, because you have  a black color for a base map  and black in colorbar. it is unacceptable.

 

I am very sorry that the authors did not want to improve their study based on my comments.

"The aim of this work is to study the spatial and temporal (climatic, decadal and interannual) variability of four oceanographic/air-sea interaction parameters" - it is your aim.

In the conclusions you say:

"The influence of wind-stress curl on the decadal variability of MED was not directly addressed in this work".

It is very strange to talk about the air-sea interaction parameters and not consider the main factor of this interaction. 

such studies are a statement of variability without explaining it.

"It is not possible to do a similar analysis in this work, as the seasonal component is removed before calculating the EOFs, and therefore this signal is not present in our results." you just don't  understand the of analyzing correlations just for spring or summer.  this is not a seasonal analysis. this is an analysis of long-term multiyear variability but only in certain seasons.  air-sea interaction goes through several stages: heating, mixing, convection. These stages appear in different seasons. For example: windy spring or calm spring has an impact on heat fluxes in interannual analysis. but in other seasons, other processes occur, and if we consider all year average data at once, then there is no correlation. I hope you understand what I'm talking about and in future work it will be taken into account  

Author Response

The authors thank Reviewer4# for her/his time and effort in reviewing the manuscript and for her/his fruitful comments, which were helpful in improving the paper. 

We modified the colourbars of Figures 5 and 9 as suggested by the Reviewer4.