the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Sep 2025
Drivers and Variability of Marine Heatwaves in the North Indian Ocean and their Impacts on South Asian Monsoon Rainfall
Abstract. Our planet is warming rapidly, and, with it, the frequency and intensity of marine heatwaves (MHWs) are increasing. While MHWs disrupt marine ecosystems, they also significantly influence regional climate systems, including the Asian monsoon. This study investigates the variability, drivers, and monsoon impacts of MHWs in the North Indian Ocean using detrended sea surface temperature anomalies from 1982 to 2024. An Empirical Orthogonal Function (EOF) analysis of MHW intensity reveals two leading modes. The first mode (PC1), explaining 22 % of the variance, shows widespread MHWs with stronger intensity in the Arabian Sea. It is associated with anomalously high pressure over the North Indian Ocean and low pressure in the Southern Hemisphere, which weakens monsoon winds, reduces evaporation and cloud cover, and increases shortwave radiation, thereby warming the upper ocean. The second mode (PC2), explaining 8 % of the variance, displays a dipole pattern, with MHWs in the Bay of Bengal and suppressed activity in the Arabian Sea during its positive phase, and the reverse during its negative phase. Large-scale climate modes modulate MHW development. El Niño combined with the transition phase of MISO (from break to active) triggers basin-wide MHWs (PC1), while La Niña during a similar MISO phase promotes PC2-like warming in the Bay of Bengal. These modes influence rainfall as well. PC1 and PC2+ are linked to wetter conditions in southern India and drier conditions in the north, while PC2- corresponds to widespread dryness. MHW termination can enhance rainfall through the revival of monsoon winds and heat release. These findings suggest potential feedback between MHWs and MISO, with implications for improved monsoon prediction under climate change.
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Interactive discussion
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- RC1: 'Comment on egusphere-2025-3886', Anonymous Referee #1, 20 Oct 2025
-
EC1: 'Comment on egusphere-2025-3886', David Battisti, 28 Oct 2025
Dear Dr. Joseph et al,
I have received one anonymous review of your manuscript (WCD 2025 3886) from a very knowledgeable and fair reviewer. Based on that review and my own read of the manuscript, it is very likely that I will decline the paper for publication in WCD. The primary reason is that nearly all of the findings in the present manuscript concern the identification of a mode of coupled atmosphere-ocean variability in the Northern Indian Ocean on intraseasonal time scales that is already documented in the literature. The existing literature also provides a compelling explanation for the physical processes that give rise to the variability. The anonymous reviewer lists some of the key papers.
In summary, I do not believe it is worth submitting a revised manuscript. However, I do encourage you to submit final comments in response to the criticisms of the manuscript from the anonymous reviewer and me. These comments can be as brief or as detailed as you like.
Regards, David Battisti
Citation: https://doi.org/10.5194/egusphere-2025-3886-EC1 -
AC1: 'Comment on egusphere-2025-3886', Ligin Joseph, 10 Nov 2025
We thank the reviewer for taking the time to evaluate our manuscript and for their constructive comments and suggestions, which have helped us understand how to refine and clarify the focus of our work.
We are pleased that the reviewer found our goal of understanding how marine heatwaves (MHWs) influence the Asian monsoon using detrended sea surface temperature (SST) anomalies interesting. We would like to emphasize that an equally important objective of our study is to identify the drivers and variability of MHWs in the North Indian Ocean. While we acknowledge that a few key studies on SST–MISO interactions were not cited in the initial version, we respectfully disagree with the assertion that our work lacks novelty. The resemblance between our composite patterns and those in previous MISO-related studies (e.g., Zhang et al., 2018) reflects the underlying physical consistency of the coupled ocean–atmosphere system rather than a replication of prior results.
Conceptually and methodologically, our approach differs in several key respects. To our knowledge, this is the first attempt to analyze Indian Ocean MHW variability and monsoon impacts using detrended daily SST anomalies, thereby separating transient heatwave events from the background long-term warming trend. We performed EOF analysis specifically on MHW intensity (SST anomalies during MHW days) rather than on the full SST anomaly field. This distinction is critical: EOFs of MHW intensity capture the dominant spatial modes of extreme ocean warming, not general variability.
A key advantage of this approach is that it allows us to objectively identify spatially extensive and physically coherent MHW events. For example, PC1 events in our analysis (defined as periods when the PC1 time series, based on MHW intensity, exceeds its 90th percentile) cover on average 24% of the Indian Ocean, while PC2+ and PC2– events represent distinct modes over the Bay of Bengal and Arabian Sea, respectively. The 90th percentile threshold was chosen to maintain consistency with the MHW definition itself, ensuring that only the most intense and widespread phases of each mode are classified as extreme events. These objectively derived modes thus avoid arbitrary spatial thresholds (e.g., “10% basin coverage”) commonly used in earlier MHW studies.
We also note that the 31-day binomial smoothing is applied only to the climatological percentile thresholds, not to the daily SST anomalies themselves. This step, following the standard MHW framework (Hobday et al., 2016; Saranya et al., 2022), ensures a seasonally varying yet physically consistent baseline while removing day-to-day noise in the climatology. Because the smoothing affects only the threshold and not the anomaly time series, it does not interfere with or obscure intraseasonal variability. The resulting MHWs thus represent persistent, coherent heat events rather than spurious short-term fluctuations. The close correspondence between our MHW composites and known intraseasonal SST–MISO patterns further supports that MISO dynamics drive many of the observed MHWs.
Importantly, our goal is not to restate MISO dynamics, but to reframe them through the lens of extreme-event oceanography, that is, to show when and how MISO-related SST variability crosses into the MHW regime. This nonlinear, threshold-based view provides new insight into how coupled variability translates into persistent oceanic extremes. While we are not directly examining SST–MISO interactions, our primary focus is on understanding the drivers and variability of MHWs in the North Indian Ocean. Our results show that large-scale climate modes jointly modulate MHW formation: El Niño events, combined with the transition phase of the MISO (from break to active), favor basin-wide MHWs resembling the first EOF mode (PC1), while La Niña during a similar MISO phase induces PC2-like warming in the Bay of Bengal. These combinations of ENSO and MISO phases thus create distinct oceanic environments conducive to MHW development. This further suggests a potentially bidirectional relationship: MISO phases can influence MHW formation, and intense MHWs that develop during particular MISO phases could, in turn, feed back on MISO propagation and intensity by altering surface fluxes. However, exploring this feedback mechanism in detail would require a dedicated analysis beyond the scope of the present paper, and we plan to address it in a separate follow-up study.
Finally, we agree that our earlier Methods section could have been clearer. Here is our workflow step-by-step:
- Calculate the daily SST climatology using an 11-day moving window. This provides sufficient samples for each day and reduces the influence of short-term SST fluctuations
- Smooth the climatological percentile thresholds using a 31-day binomial filter to remove high-frequency noise
- Detect MHWs when detrended SST anomalies exceed the smoothed 90th percentile for at least five consecutive days
- Extract SST anomalies during MHW days to construct the MHW intensity dataset
- Perform EOF analysis on this intensity field to identify the dominant spatial patterns of MHW variability
- Select periods when the principal component (PC) time series exceed their 90th percentile for at least five consecutive days. This final step ensures that the composite analyses represent the most spatially extensive and persistent MHW events corresponding to each dominant mode, rather than transient or localized fluctuations.
In summary, we believe that the similarities between our results and previous MISO studies strengthen, rather than diminish, our conclusions. Our analysis introduces a new conceptual and diagnostic framework for understanding how established modes of coupled variability (MISO, ENSO) manifest as oceanic extremes (MHWs), and how these extremes, in turn, may influence the monsoon system. We therefore consider that the rejection primarily arose from a difference in interpretation and a misunderstanding of our methodology, rather than from a lack of scientific merit. In the future, we plan to further strengthen the study by explicitly comparing MHW-associated SST variability and MISO impacts with non-MHW SST–MISO interactions, which we believe was a missing component in the current analysis.
Saranya, J. S., Roxy, M. K., Dasgupta, P., & Anand, A. (2022). Genesis and trends in marine heatwaves over the tropical Indian Ocean and their interaction with the Indian summer monsoon. Journal of Geophysical Research: Oceans, 127, e2021JC017427. https://doi.org/10.1029/2021JC017427
Hobday, A. J., Alexander, L. V., Perkins, S. E., Smale, D. A., Straub, S. C., Oliver, E. C., Benthuysen, J. A., Burrows, M. T., Donat, M. G., Feng, M., Holbrook, N. J., Moore, P. J., Scannell, H. A., Sen Gupta, A., and Wernberg, T.: A hierarchical approach to defining marine heatwaves, Progress in Oceanography, 141, 227–238, https://doi.org/10.1016/j.pocean.2015.12.014, 2016.
Citation: https://doi.org/10.5194/egusphere-2025-3886-AC1
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-3886', Anonymous Referee #1, 20 Oct 2025
Review of "Drivers and Variability of Marine Heatwaves in the North Indian Ocean and their Impacts on South Asian Monsoon Rainfall" by Joseph, Skliris et al
General comments:
This manuscript analyzes marine heat waves (MHWs) in the Indian Ocean, using SST anomalies to identify two dominant patterns: a basin-wide mode strongest in the Arabian Sea and an east-west dipole pattern. The authors discuss how these MHW patterns are modulated by large-scale climate phenomena like ENSO and the monsoon intraseasonal oscillation (MISO), and how the different MHW modes alter regional precipitation.
The goal of assessing how MHWs alter the Asian monsoon is worthwhile and interesting, and the method of identifying MHWs as anomalies seems a good approach for climate dynamics studies, compared to using an absolute definition that does not account for long-term warming trends. However, this manuscript essentially ignores the well-documented coupled air-sea interaction in the boreal summer intraseasonal oscillation that can explain most of the results presented in Figures 4-8. An existing set of theoretical, observational, and modeling studies published over the last decade or two provides substantial insight into the mechanisms by which air-sea interaction causes the SST, monsoon winds, and precipitating clouds to covary on time scales of weeks to months during boreal summer. For this reason, I have recommended rejection. Should the authors wish to further develop this work, I suggest they first undertake a thorough examination of the below papers and other works cited therein. A revised manuscript should also clearly identify how the methodology used here to explore anomalous MHWs is distinct from the large number of prior studies that have explored anomalous SST variations on intraseasonal time scales in the Indian Ocean.
Specific comments:
1) The spatial patterns of anomalies in SST, precipitation, wind, and surface fluxes shown in Figures 4, 5 and 7 essentially reproduce what is shown in Zhang et al 2018 (Role of North Indian Ocean Air–Sea Interaction in Summer Monsoon Intraseasonal Oscillation, DOI: 10.1175/JCLI-D-17-0691.1) and other prior work on intraseasonal SST variation in the Indian Ocean. For example, the SST/wind/precipitation patterns shown for PC1 in Fig 4 of this manuscript closely resemble the top row of Fig 4 in Zhang et al 2018, with the various surface flux quantities shown in Fig 5 of this manuscript looking very much like the top row of Fig 5 of Zhang et al 2018. The Zhang paper is only one in a fairly large series of papers documenting this sort of behavior on intraseasonal time scales, only a few of which I list below.
This strong overlap with the literature on boreal summer intraseasonal variability results from the choice of defining MHWs using low-passed (by a 31-day binomial filter) SST anomalies, essentially capturing the SST variations that are coupled to the boreal summer intraseasonal oscillation.
The authors acknowledge that their MHW patterns are associated with the MISO (which in turn has strong association with the BSISO, the boreal summer MJO, and general intraseasonal variability in the Indian Ocean), but the discussion in this manuscript is descriptive and often confuses association with causation. A much more thorough assessment of the coupled physics was presented in some of the past work, with Zhang et al 2018, for example, presenting a theoretical air-sea coupling model that demonstrates the period of the oscillation is expected to be proportional to the square root of the ocean mixed layer depth. Even the prior observational analyses have demonstrated that the precipitation and SST anomalies are in quadrature, enabling their coupling in northward propagation. That sort of important detail on the phase relationship was not demonstrated clearly here.
2) A separate issue is that I found the description of the methodology to be insufficient in many places, so that I was confused about what exactly was done. This began in a fairly minor way on line 90 when the authors described the initial processing of SST anomalies, stating that they used an 11-day moving window (presumably a moving average), which was "then smoothed using a 31-day binomial filter". I can probably figure out roughly what was done there, but the selection of MHW events from the PCs in section 4 was very confusing: in Section 2 they state that MHWs are identified when SSTs exceed the 90th percentile, but then do the authors really take an EOF of those MHWs and then select the 90th percentile of the first PC? In other words, they are taking the 90th percentile of the PCs obtained through an EOF analysis of events defined by taking the 90th percentile of SST? Throughout much of the discussion in Sections 4-6 I often lost track of whether the authors were discussing the patterns associated with the PCs or the 90th percentile of those PCs.
3) Much of the discussion of physical mechanisms claimed causation when only association was demonstrated. One brief example is on line 199-200 where the authors state that a weakened meridional pressure gradient causes a weakening of the zonal monsoon winds: this is just geostrophic balance, where neither the winds nor the pressure gradients are causative. The same statement is made on line 267. The authors are correct that some of the anomalies can be causal, such as reduced atmospheric convection and cloudiness leading to enhanced surface shortwave radiation and SST warming. However, phase relationships are important here, as I mentioned above, and the prior papers discussed above and cited below provide a more detailed and quantitative description of the air-sea coupling in these interactions
Technical comments:
I do not list technical corrections due to the major and significant nature of the issues described above.
References:Kemball-Cook and Wang 2001, https://doi.org/10.1175/1520-0442(2001)014<2923:EWAASI>2.0.CO;2
Fu, X., Wang, B., & McCreary, J. P. (2003). Coupling between northward-propagating, intraseasonal oscillations and sea surface temperature in the Indian Ocean.
DeMott, C. A., Stan, C., & Randall, D. A. (2013). Northward propagation mechanisms of the boreal summer intraseasonal oscillation in the ERA-Interim and SP-CCSM. Journal of Climate, 26, 1973–1992
Fu, X., Wang, B., Waliser, D. E., & Tao, L. (2007). Impact of atmosphere–ocean coupling on the predictability of monsoon intraseasonal oscillations. Journal of the Atmospheric Sciences, 64, 157–174
Fu, X., & Wang, B. (2004). The boreal-summer intraseasonal oscillations simulated in a hybrid coupled atmosphere–ocean model. Monthly Weather Review, 132, 2628–2649
Citation: https://doi.org/10.5194/egusphere-2025-3886-RC1 -
EC1: 'Comment on egusphere-2025-3886', David Battisti, 28 Oct 2025
Dear Dr. Joseph et al,
I have received one anonymous review of your manuscript (WCD 2025 3886) from a very knowledgeable and fair reviewer. Based on that review and my own read of the manuscript, it is very likely that I will decline the paper for publication in WCD. The primary reason is that nearly all of the findings in the present manuscript concern the identification of a mode of coupled atmosphere-ocean variability in the Northern Indian Ocean on intraseasonal time scales that is already documented in the literature. The existing literature also provides a compelling explanation for the physical processes that give rise to the variability. The anonymous reviewer lists some of the key papers.
In summary, I do not believe it is worth submitting a revised manuscript. However, I do encourage you to submit final comments in response to the criticisms of the manuscript from the anonymous reviewer and me. These comments can be as brief or as detailed as you like.
Regards, David Battisti
Citation: https://doi.org/10.5194/egusphere-2025-3886-EC1 -
AC1: 'Comment on egusphere-2025-3886', Ligin Joseph, 10 Nov 2025
We thank the reviewer for taking the time to evaluate our manuscript and for their constructive comments and suggestions, which have helped us understand how to refine and clarify the focus of our work.
We are pleased that the reviewer found our goal of understanding how marine heatwaves (MHWs) influence the Asian monsoon using detrended sea surface temperature (SST) anomalies interesting. We would like to emphasize that an equally important objective of our study is to identify the drivers and variability of MHWs in the North Indian Ocean. While we acknowledge that a few key studies on SST–MISO interactions were not cited in the initial version, we respectfully disagree with the assertion that our work lacks novelty. The resemblance between our composite patterns and those in previous MISO-related studies (e.g., Zhang et al., 2018) reflects the underlying physical consistency of the coupled ocean–atmosphere system rather than a replication of prior results.
Conceptually and methodologically, our approach differs in several key respects. To our knowledge, this is the first attempt to analyze Indian Ocean MHW variability and monsoon impacts using detrended daily SST anomalies, thereby separating transient heatwave events from the background long-term warming trend. We performed EOF analysis specifically on MHW intensity (SST anomalies during MHW days) rather than on the full SST anomaly field. This distinction is critical: EOFs of MHW intensity capture the dominant spatial modes of extreme ocean warming, not general variability.
A key advantage of this approach is that it allows us to objectively identify spatially extensive and physically coherent MHW events. For example, PC1 events in our analysis (defined as periods when the PC1 time series, based on MHW intensity, exceeds its 90th percentile) cover on average 24% of the Indian Ocean, while PC2+ and PC2– events represent distinct modes over the Bay of Bengal and Arabian Sea, respectively. The 90th percentile threshold was chosen to maintain consistency with the MHW definition itself, ensuring that only the most intense and widespread phases of each mode are classified as extreme events. These objectively derived modes thus avoid arbitrary spatial thresholds (e.g., “10% basin coverage”) commonly used in earlier MHW studies.
We also note that the 31-day binomial smoothing is applied only to the climatological percentile thresholds, not to the daily SST anomalies themselves. This step, following the standard MHW framework (Hobday et al., 2016; Saranya et al., 2022), ensures a seasonally varying yet physically consistent baseline while removing day-to-day noise in the climatology. Because the smoothing affects only the threshold and not the anomaly time series, it does not interfere with or obscure intraseasonal variability. The resulting MHWs thus represent persistent, coherent heat events rather than spurious short-term fluctuations. The close correspondence between our MHW composites and known intraseasonal SST–MISO patterns further supports that MISO dynamics drive many of the observed MHWs.
Importantly, our goal is not to restate MISO dynamics, but to reframe them through the lens of extreme-event oceanography, that is, to show when and how MISO-related SST variability crosses into the MHW regime. This nonlinear, threshold-based view provides new insight into how coupled variability translates into persistent oceanic extremes. While we are not directly examining SST–MISO interactions, our primary focus is on understanding the drivers and variability of MHWs in the North Indian Ocean. Our results show that large-scale climate modes jointly modulate MHW formation: El Niño events, combined with the transition phase of the MISO (from break to active), favor basin-wide MHWs resembling the first EOF mode (PC1), while La Niña during a similar MISO phase induces PC2-like warming in the Bay of Bengal. These combinations of ENSO and MISO phases thus create distinct oceanic environments conducive to MHW development. This further suggests a potentially bidirectional relationship: MISO phases can influence MHW formation, and intense MHWs that develop during particular MISO phases could, in turn, feed back on MISO propagation and intensity by altering surface fluxes. However, exploring this feedback mechanism in detail would require a dedicated analysis beyond the scope of the present paper, and we plan to address it in a separate follow-up study.
Finally, we agree that our earlier Methods section could have been clearer. Here is our workflow step-by-step:
- Calculate the daily SST climatology using an 11-day moving window. This provides sufficient samples for each day and reduces the influence of short-term SST fluctuations
- Smooth the climatological percentile thresholds using a 31-day binomial filter to remove high-frequency noise
- Detect MHWs when detrended SST anomalies exceed the smoothed 90th percentile for at least five consecutive days
- Extract SST anomalies during MHW days to construct the MHW intensity dataset
- Perform EOF analysis on this intensity field to identify the dominant spatial patterns of MHW variability
- Select periods when the principal component (PC) time series exceed their 90th percentile for at least five consecutive days. This final step ensures that the composite analyses represent the most spatially extensive and persistent MHW events corresponding to each dominant mode, rather than transient or localized fluctuations.
In summary, we believe that the similarities between our results and previous MISO studies strengthen, rather than diminish, our conclusions. Our analysis introduces a new conceptual and diagnostic framework for understanding how established modes of coupled variability (MISO, ENSO) manifest as oceanic extremes (MHWs), and how these extremes, in turn, may influence the monsoon system. We therefore consider that the rejection primarily arose from a difference in interpretation and a misunderstanding of our methodology, rather than from a lack of scientific merit. In the future, we plan to further strengthen the study by explicitly comparing MHW-associated SST variability and MISO impacts with non-MHW SST–MISO interactions, which we believe was a missing component in the current analysis.
Saranya, J. S., Roxy, M. K., Dasgupta, P., & Anand, A. (2022). Genesis and trends in marine heatwaves over the tropical Indian Ocean and their interaction with the Indian summer monsoon. Journal of Geophysical Research: Oceans, 127, e2021JC017427. https://doi.org/10.1029/2021JC017427
Hobday, A. J., Alexander, L. V., Perkins, S. E., Smale, D. A., Straub, S. C., Oliver, E. C., Benthuysen, J. A., Burrows, M. T., Donat, M. G., Feng, M., Holbrook, N. J., Moore, P. J., Scannell, H. A., Sen Gupta, A., and Wernberg, T.: A hierarchical approach to defining marine heatwaves, Progress in Oceanography, 141, 227–238, https://doi.org/10.1016/j.pocean.2015.12.014, 2016.
Citation: https://doi.org/10.5194/egusphere-2025-3886-AC1
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Review of "Drivers and Variability of Marine Heatwaves in the North Indian Ocean and their Impacts on South Asian Monsoon Rainfall" by Joseph, Skliris et al
General comments:
This manuscript analyzes marine heat waves (MHWs) in the Indian Ocean, using SST anomalies to identify two dominant patterns: a basin-wide mode strongest in the Arabian Sea and an east-west dipole pattern. The authors discuss how these MHW patterns are modulated by large-scale climate phenomena like ENSO and the monsoon intraseasonal oscillation (MISO), and how the different MHW modes alter regional precipitation.
The goal of assessing how MHWs alter the Asian monsoon is worthwhile and interesting, and the method of identifying MHWs as anomalies seems a good approach for climate dynamics studies, compared to using an absolute definition that does not account for long-term warming trends. However, this manuscript essentially ignores the well-documented coupled air-sea interaction in the boreal summer intraseasonal oscillation that can explain most of the results presented in Figures 4-8. An existing set of theoretical, observational, and modeling studies published over the last decade or two provides substantial insight into the mechanisms by which air-sea interaction causes the SST, monsoon winds, and precipitating clouds to covary on time scales of weeks to months during boreal summer. For this reason, I have recommended rejection. Should the authors wish to further develop this work, I suggest they first undertake a thorough examination of the below papers and other works cited therein. A revised manuscript should also clearly identify how the methodology used here to explore anomalous MHWs is distinct from the large number of prior studies that have explored anomalous SST variations on intraseasonal time scales in the Indian Ocean.
Specific comments:
1) The spatial patterns of anomalies in SST, precipitation, wind, and surface fluxes shown in Figures 4, 5 and 7 essentially reproduce what is shown in Zhang et al 2018 (Role of North Indian Ocean Air–Sea Interaction in Summer Monsoon Intraseasonal Oscillation, DOI: 10.1175/JCLI-D-17-0691.1) and other prior work on intraseasonal SST variation in the Indian Ocean. For example, the SST/wind/precipitation patterns shown for PC1 in Fig 4 of this manuscript closely resemble the top row of Fig 4 in Zhang et al 2018, with the various surface flux quantities shown in Fig 5 of this manuscript looking very much like the top row of Fig 5 of Zhang et al 2018. The Zhang paper is only one in a fairly large series of papers documenting this sort of behavior on intraseasonal time scales, only a few of which I list below.
This strong overlap with the literature on boreal summer intraseasonal variability results from the choice of defining MHWs using low-passed (by a 31-day binomial filter) SST anomalies, essentially capturing the SST variations that are coupled to the boreal summer intraseasonal oscillation.
The authors acknowledge that their MHW patterns are associated with the MISO (which in turn has strong association with the BSISO, the boreal summer MJO, and general intraseasonal variability in the Indian Ocean), but the discussion in this manuscript is descriptive and often confuses association with causation. A much more thorough assessment of the coupled physics was presented in some of the past work, with Zhang et al 2018, for example, presenting a theoretical air-sea coupling model that demonstrates the period of the oscillation is expected to be proportional to the square root of the ocean mixed layer depth. Even the prior observational analyses have demonstrated that the precipitation and SST anomalies are in quadrature, enabling their coupling in northward propagation. That sort of important detail on the phase relationship was not demonstrated clearly here.
2) A separate issue is that I found the description of the methodology to be insufficient in many places, so that I was confused about what exactly was done. This began in a fairly minor way on line 90 when the authors described the initial processing of SST anomalies, stating that they used an 11-day moving window (presumably a moving average), which was "then smoothed using a 31-day binomial filter". I can probably figure out roughly what was done there, but the selection of MHW events from the PCs in section 4 was very confusing: in Section 2 they state that MHWs are identified when SSTs exceed the 90th percentile, but then do the authors really take an EOF of those MHWs and then select the 90th percentile of the first PC? In other words, they are taking the 90th percentile of the PCs obtained through an EOF analysis of events defined by taking the 90th percentile of SST? Throughout much of the discussion in Sections 4-6 I often lost track of whether the authors were discussing the patterns associated with the PCs or the 90th percentile of those PCs.
3) Much of the discussion of physical mechanisms claimed causation when only association was demonstrated. One brief example is on line 199-200 where the authors state that a weakened meridional pressure gradient causes a weakening of the zonal monsoon winds: this is just geostrophic balance, where neither the winds nor the pressure gradients are causative. The same statement is made on line 267. The authors are correct that some of the anomalies can be causal, such as reduced atmospheric convection and cloudiness leading to enhanced surface shortwave radiation and SST warming. However, phase relationships are important here, as I mentioned above, and the prior papers discussed above and cited below provide a more detailed and quantitative description of the air-sea coupling in these interactions
Technical comments:
I do not list technical corrections due to the major and significant nature of the issues described above.
References:
Kemball-Cook and Wang 2001, https://doi.org/10.1175/1520-0442(2001)014<2923:EWAASI>2.0.CO;2
Fu, X., Wang, B., & McCreary, J. P. (2003). Coupling between northward-propagating, intraseasonal oscillations and sea surface temperature in the Indian Ocean.
DeMott, C. A., Stan, C., & Randall, D. A. (2013). Northward propagation mechanisms of the boreal summer intraseasonal oscillation in the ERA-Interim and SP-CCSM. Journal of Climate, 26, 1973–1992
Fu, X., Wang, B., Waliser, D. E., & Tao, L. (2007). Impact of atmosphere–ocean coupling on the predictability of monsoon intraseasonal oscillations. Journal of the Atmospheric Sciences, 64, 157–174
Fu, X., & Wang, B. (2004). The boreal-summer intraseasonal oscillations simulated in a hybrid coupled atmosphere–ocean model. Monthly Weather Review, 132, 2628–2649