Tropical Cyclonic Energy Variability in North Indian Ocean: Insights from ENSO

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript deals with a very important topic: Natural variability and influence factors on tropical cyclones. The study is well designed and explores the ENSO connection. Also IOD is being explored briefly. The authors restrict their analysis unfortunately to te last 30 years, as little reliable instrumental data are available for the time before. Nevertheless, it would have been good to add a longerterm perspective of the past 100 or 1000 or more years. This can be achieved by historical observations and palaeoclimate reconstuctions. Maybe the authors can add a paragraph on this.

It would have been also good to explain similar connections in the Atlantic basin. Here it becomes clear that the Atlantic hurricanes are linked to the Atlantic Multidecadal Oscillation which oscillates eith 60-70 years.

A few links as food for thought:

https://www.nature.com/articles/s41558-022-01388-4

https://en.wikipedia.org/wiki/Tropical_cyclones_in_India

https://www.sciencedirect.com/science/article/abs/pii/S0921818122002004

 

Summed up, the current paper is worth publishing, after minor additions. I am looking forward to seeing this manuscript in print.

Author Response

The authors greatly appreciate the reviewers' encouragement for the article and suggestions for improvement. We have incorporated references related to global warming and some relevant articles on the Atlantic basin. We have also modified and improved the methodology and conclusion, along with some figures, to make them more consistent with each other. However, one reference discusses paleoclimate, which we did not include as it is beyond the scope of the present work.  We included only those cases with named cyclones and a minimum time resolution of 6 hours.

Reviewer 2 Report

Comments and Suggestions for Authors

Review of Tropical Cyclonic Energy Variability in North Indian Ocean: Insights from ENSO

Authors: D Das, S Chiao, C Roychoudhury, F Khan, S Chaudhuri, and S Mukherjee

The manuscript investigated the relationship between ENSO and TC activity based on accumulated cyclone energy (ACE) over the North Indian Ocean for the 26 years.  Their results indicated that a significant increase in cyclone intensity over the past two decades, with eight of the ten most active years occurring since the 2000s.  Furthermore, they also examined the contributing factors to the relationship between ENSO and ACE.  For example, the higher ACE over the Arabian Sea (ARB) is associated with the combined effect from elevated sea surface height anomaly and low vertical wind shear during El-Nino episodes. 

This research, providing an overview of the general trend of ACE in North Indian Ocean and its relationship with ENSO.  The research is suitable for this journal.  However, major revision is needed before it can be published.  

Major comments

1.      In the abstract the authors mentioned the ACE was computed for a period of 26 years.  In Table 1 the cyclones from 1990-2018 were considered.  It is not clear to me for which 26 years the ACE was analyzed. 

2.      The authors did not mention how the vertical wind shear was calculated.  Need to add this in Section 2.

3.      Lines 149-151: The authors did not explain what so-called “the unique physio-chemical attributes” that is causing the distinctive ACE fluctuation seen in the results.

4.       

 

Minor comments:

The use of English can be polished.  For example, in line 104 “it reaches to” should be “It reaches”.  

The sentence in line 85: “The daily sea surface temperature (SST) is used from NOAA” can be changed to “The daily sea surface temperature (SST) from NOAA is used”. 

The authors’ names are not listed in the conventional way.  For example, is the first name of the first author “D”?  If not, you need to spell it out or list it as “D.”

Comments for author File: Comments.pdf

Comments on the Quality of English Language

Fine

Author Response

 

 

Tropical Cyclonic Energy Variability in North Indian Ocean: Insights from ENSO

Reviewer 2 #The manuscript investigated the relationship between ENSO and TC activity based on accumulated cyclone energy (ACE) over the North Indian Ocean for the 2 years. Their results indicated a significant increase in cyclone intensity over the past two decades, with eight of the ten most active years occurring since the 2000s. Furthermore, they also examined the contributing factors to the relationship between ENSO and ACE. For example, the higher ACE over the Arabian Sea (ARB) is associated with the combined effect of elevated sea surface height anomaly and low vertical wind shear during El-Nino episodes. This research, provides an overview of the general trend of ACE in North Indian Ocean and its relationship with ENSO. The research is suitable for this journal. However, major revision is needed before it can be published.

Major comments

Comment 1: In the abstract the authors mentioned the ACE was computed for a period of 26 years. In Table 1 the cyclones from 1990-2018 were considered. It is not clear to me for which 26 years the ACE was analyzed.

          

Response to Comment 1:

           Thanks for noting that. We've corrected it to 29 years in the manuscript.

 

Comment 2: The authors did not mention how the vertical wind shear was calculated. Need to add this in Section 2.

Response to Comment 2:

We have incorporated details on how the vertical wind shear was calculated in Section 2 of the manuscript. In this study, vertical wind shear (VWS) is computed as the vector wind difference between the upper troposphere at 200 hPa and the lower troposphere at 850 hPa.

 

Comment 3:Lines 149-151: The authors did not explain what so-called “unique physio-chemical attributes” that is causing the distinctive ACE fluctuation seen in the results.

          

Response to Comment 3:

In our study, when we refer to "unique physio-chemical attributes," we are primarily discussing the distinctive physical and chemical characteristics in the Indian Ocean, Arabian Sea, and Bay of Bengal regions. These characteristics include factors such as sea surface temperatures (SST), sea surface height (SSH), and atmospheric conditions, and how they vary is thoroughly discussed in the manuscript. It's important to note that SST is not solely determined by radiation but is often considered a chemical property of the ocean, especially over the Arabian Sea where factors like salinity and nutrients play a vital role in ocean variability.

 

 

Minor comments:

 

Minor Comment 1: The use of English can be polished. For example, in line 104 “it reaches to” should be “It Reaches”.

 

Response to Minor Comment 1: Thank you for your feedback. We have addressed and modified the sentence in the manuscript as suggested.

     

Minor Comment 2: The sentence in line 85: “The daily sea surface temperature (SST) is used from NOAA” can be changed to “The daily sea surface temperature (SST) from NOAA is used”. Modified accordingly in line 85.

 

Response to Minor Comment 2: The authors have revised the sentence in the manuscript as follows: "The daily sea surface temperature (SST) and GODAS Sea Surface Height (SSH) data are obtained from the National Oceanic and Atmospheric Administration (NOAA)”.

 

Minor Comment 3: The authors’ names are not listed in a conventional way. For example, is the first name of the first author “D”? If not, you need to spell it out or list it as “D.”

Response to Minor Comment 3: The full name of the authors is listed.

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript investigates the variability of TC activity in presence of ENSO over the North Indian Ocean during the pre- and post-monsoon season, using accumulated cyclone energy over the last 26 years. The manuscript is well written in general. Some minor comments and suggestions for further improvement are given below:

 

1.     According to L107, the unit of ACE is 10^4 kt^2. However, in Figure 1, 2, & 4, the unit of ACE is 10^-4 kt^2. Please review and revise.

2.     Figure 3, the unit of ACE is 10^5 kt^2. Why not make it consistent with the other figures and use 10^4 kt^2?

3.     Figure 3, what do the boxes and the whiskers represent? It should be indicated in the figure caption.

4.     Figure 4, what do the straight line and the shaded area represent? It should be indicated in the figure caption.

5.     L63-L69, the state-of-the-art review of the TC activity metrics and the reason for the choice of ACE used in the study is a little inadequate. Some discussion on pros/cons, relevance of state of the art, where’s the direction, and what does it mean for practical application, are expected to be provided. Please address.

6.     L82, why is the best track data from India Meteorological Department used, is it better than other best track datasets?

7.     The novelty, contribution and innovation in this paper is unclear. Please describe it concisely in Introduction.

8.     This paper is a case study of the North Indian Ocean. A case study should reach out globally and clearly draw parallels, point to lessons learned elsewhere that are relevant and or identify applications of the key findings of this study to the world. Please address.

9.     What are the potential sources of error in this analysis, and how can the underlying assumptions be improved? Please describe in the discussion.

10.  What are the limitations of this analysis, please describe in the conclusion, discuss how this would affect the results, and point towards further research that could be undertaken to improve.

Author Response

Reviewer 3 #

    1.     According to L107, the unit of ACE is 10^4 kt^2. However, in Figure 1, 2, & 4, the unit of ACE is 10^-4 kt^2. Please review and revise.

2. Figure 3, the unit of ACE is 10^5 kt^2. Why not make it consistent with the other figures and use 10^4 kt^2?
3. Figure 3, what do the boxes and the whiskers represent? It should be indicated in the figure caption.
4. Figure 4, what do the straight line and the shaded area represent? It should be indicated in the figure caption.
5. L63-L69, the state-of-the-art review of the TC activity metrics and the reason for the choice of ACE used in the study is a little inadequate. Some discussion on pros/cons, relevance of state of the art, where’s the direction, and what does it mean for practical application, are expected to be provided. Please address.
6. L82, why is the best track data from India Meteorological Department used, is it better than other best track datasets?
7. The novelty, contribution and innovation in this paper is unclear. Please describe it concisely in Introduction.
8. This paper is a case study of the North Indian Ocean. A case study should reach out globally and clearly draw parallels, point to lessons learned elsewhere that are relevant and or identify applications of the key findings of this study to the world. Please address.
9. What are the potential sources of error in this analysis, and how can the underlying assumptions be improved? Please describe in the discussion.
10. What are the limitations of this analysis, please describe in the conclusion, discuss how this would affect the results, and point towards further research that could be undertaken to improve.

 

 

Comment 1:

According to L107, the unit of ACE is 10^4 kt^2. However, in Figure 1, 2, & 4, the unit of ACE is 10^-4 kt^2. Please review and revise.

Response to Comment 1:

Greatly appreciate this comment. We have reviewed and revised the unit of ACE in Figures 1, 2, & 4 to the correct unit, which is 10^4 kt^2.

Comment 2:

Figure 3, the unit of ACE is 10^5 kt^2. Why not make it consistent with the other figures and use 10^4 kt^2?

Response to Comment 2:

It was a great suggestion. We have incorporated the new plot with 10^4kt^2 to make it consistent with the other figures and the methodology used in the study.

 

Comment 3:

Figure 3, what do the boxes and the whiskers represent? It should be indicated in the figure caption.

Response to Comment 3:

The conventional statistical method of box and whiskers plots used in this study. These plots include the median, interquartile range (box), and outer range (whiskers). The whiskers signify the data's outer range, extending from the box ends. The median's advantage lies in its resistance to outliers when n ≥ 3. The box represents the middle 50% of ranked data, spanning from the lower to upper quartile values (25th to 75th percentile).

 

We've included details of the box whisker plot in the methodology section, clarifying what the box and whisker represent separately. Additionally, we've added references that use box and whisker plots in climate data and previous research that used box whisker plots to study ocean-atmosphere variability over the North Indian Ocean, Arabian Sea, and the Bay of Bengal.

 

Comment 4:

Figure 4, what do the straight line and the shaded area represent? It should be indicated in the figure caption.

Response to Comment 4:

In Figure 4, a time series with mean values is plotted along with a shaded area indicating ±1 the standard deviation. Additionally, a linear trend line is included to illustrate trends over the ARB (Arabian Sea) and BOB (Bay of Bengal) basins for both SST and ACE. We modified the figure caption to include this description in Figure 4.

 

Comment 5:

L63-L69, the state-of-the-art review of the TC activity metrics and the reason for the choice of ACE used in the study is a little inadequate. Some discussion on pros/cons, relevance of state of the art, where’s the direction, and what does it mean for practical application, are expected to be provided. Please address.

Response to Comment 5:

Thank you for highlighting the comment on the state of the art. We have modified the sentences to make them more relevant and aligned with the scope of the study. Additionally, we have discussed the pros and cons in greater detail to provide a short discussion on the chosen metric. ACE combines information about the intensity and duration of tropical cyclones into a single metric. This makes it a comprehensive indicator of a cyclone's overall energy output, reflecting its potential for damage and impact.

 

We appreciate your comment regarding the state-of-the-art review of TC activity metrics and our choice of ACE in this study. It's worth emphasizing that ACE widely acknowledged and globally accepted metric for tropical cyclone activity in research as well as in operational forecasts. It's important to note that the ACE metric has a limitation: it doesn't account for precipitation associated with tropical cyclones and storm surges.

 

 

Comment 6:

L82, why is the best track data from the India Meteorological Department used, is it better than other best track datasets?

Response to Comment 6:

The India Meteorological Department's best track data was chosen for its historical use in past literature, particularly in studies focusing on this region. This selection ensures consistency with existing research, and it's a dataset that has been well-established for this specific area with limited reported bias.

 

 

Comment 7:

The novelty, contribution, and innovation in this paper are unclear. Please describe it concisely in the Introduction.

Response to Comment 7:

To address the novelty of the present research, we will emphasize that In this study, we not only analyze the annual ACE variability for both ocean basins but also conduct an analysis for each cyclone season (both pre and postmonsoon) within ARB and BOB ocean basins, as well as across the entire North Indian Ocean (NIO). This approach provides a more comprehensive understanding of the variability. This study is the first of its kind to not only address basin-wise variability for each cyclone occurrence season but also simultaneously study the associated variability due to the presence of ENSO. This study is important because it helps us understand how El Niño and La Niña affect cyclone seasons in the North Indian Ocean. We look at how these events change the ocean and atmosphere conditions in different seasons and provide insights into the Arabian Sea and Bay of Bengal regions. These cyclones often bring extreme weather and can be highly destructive. By figuring out how El Niño and La Niña influence them, we can better prepare for and respond to these natural disasters, potentially saving lives and reducing damage.

 

We have also addressed the significance of this study in our conclusions.

 

Comment 8:

This paper is a case study of the North Indian Ocean. A case study should reach out globally and clearly draw parallels, point to lessons learned elsewhere that are relevant, and or identify applications of the key findings of this study to the world. Please address.

Response to Comment 8:

 

Given that ENSO is a global phenomenon affecting ocean basins worldwide through modified ocean-atmosphere interactions, the lessons learned from this study can be used as a template for studying the relationship between ocean-atmospheric teleconnections and tropical cyclone activity in other ocean basins like the North Indian Ocean. The North Indian Ocean region itself, home to over 2 billion people and some of the most densely populated coastal areas globally, underscores the critical importance of understanding these interactions. By figuring out how El Niño and La Niña influence these basins and their interaction with cyclones, we can better prepare for and respond to these natural disasters, potentially saving lives and reducing damage. We incorporated these points in the revised manuscript.

 

We've integrated these insights into the revised manuscript, emphasizing their applicability beyond the North Indian Ocean.

 

Comment 9:

What are the potential sources of error in this analysis, and how can the underlying assumptions be improved? Please describe in the discussion.

 

Response to Comment 9:

Thank you for your insightful comment. In conducting this analysis, we have made every effort to minimize assumptions, placing primary reliance on statistical techniques. Potential inaccuracies in the dataset are among the main sources of error that we have considered. Improved observations would undoubtedly enhance our capacity to reduce these errors. Importantly, we would like to emphasize that, in our view, these potential inaccuracies do not substantially affect the core findings or the robustness of the results. Additionally, the assumptions made in statistical techniques could instead introduce some uncertainty.

 

Comment 10:

What are the limitations of this analysis, please describe in the conclusion, discuss how this would affect the results, and point towards further research that could be undertaken to improve.

 

Response to Comment 10:

Please note that we have only categorized the data based on ENSO phases. Therefore, factors influencing variability other than ENSO and seasonal variances have not been addressed, as they fall outside the scope of the present study. Utilizing global coupled models with idealized experiments could provide additional insights into understanding the interactions between ENSO and cyclone activity over these vulnerable regions.

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have revised their manuscript and improved its quality. Well done. 

 

The manuscript could be accepted in its current form. Below are minor suggestions for proofreading:

1. Increase the figure resolusion

2. L309："that In this study" => "that in this study"

3. L313："seasons In the" => "seasons in the"