the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Apr 2025
Seasonality of the Quasi-biennial Oscillation signal in water vapor in the tropical stratosphere
Abstract. Stratospheric water vapor is an important greenhouse gas, which affects the radiation balance and temperature structure of the stratosphere and troposphere. Although previous studies have investigated the water vapor variability associated with the quasi-biennial oscillation (QBO), the seasonal difference in the water vapor QBO are still not well understood. Using the ERA5 reanalysis and SWOOSH observations, this study compares the stratospheric water vapor distribution in northern winter and summer under different QBO phases. The water vapor and zonal winds are positively correlated in the mid-to-lower stratosphere; however this relationship weakens in the northern summer. The mean vertical transport term via the QBO related residual circulation is the leading factor controlling the water vapor distribution in most of the stratosphere. This dynamic transport of water vapor in the lower stratosphere by the residual circulation is larger in boreal winter than in summer. Further, the dehydration effect by cold temperature in the lower stratosphere is also more effective in boreal winter than in summer. Tropical deep convection exhibits opposite variations for a given QBO phase in boreal winter versus summer especially over the Indo-Pacific Oceans. This further enhances the temperature difference between the QBO easterly and westerly phases in winter and reduces the temperature contrast in summer. It is still a challenge for models to reproduce the water vapor QBO: CMIP6 models tend to underestimate the water vapor QBO amplitude, and the seasonal contrast in the water vapor QBO between boreal winter and summer is underrepresented in most models.
- Preprint
(4465 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
CC1: 'Comment on egusphere-2025-1123', Farahnaz Khosrawi, 14 May 2025
The authors analyse the seasonal cycle of the QBO using several CMIP6 model simulations, the SWOOSH merged satellite data set and ERA5 reanalysis data.
This is an interesting study, but the authors need to motivate a bit more why it is interesting/important to investigate the seasonal cycle of the QBO. Just stating that this has not done before is, in my opinion, not enough.
Following the description of results was for me quite difficult since there were on one hand too many figures and on the other hand these were not well explained. Starting with Figure 2 it is not stated which data set has been used for the analysis and thus which data set is shown on the figures. I could also find no statement on this in the main text. Are you using here a multi-model mean? Or the SWOOSH data? Or is the analysis based on the reanalysis data?
It should be made more clear which data set has been used for what in your analysis. Also a clear statement/discussion on the uncertainty of these data sets is missing.
Specific comments:
Introduction: Here it should also be discussed that many models have/had problems in simulating QBO and that for that considering waves is important (e.g. Giorgetta et al. 2006). How has this overcome in the CMIP6 model simulations? Which effort has been made so that the models are able to simulate a QBO.
P3, L65: Here you should provide a motivation why investigating the seasonal cycle of the QBO is important/of interest.
P3, L83-87: Add a few more sentence on the SWOOSH data set itself and the quality of this data set. Have all e.g. biases been removed? How have the satellite data sets been merged and what is the advantage of using this merged data set instead of using one or several satellite data sets separately?
P5, L137: What do these differences mean for your study? Which data set is more realistic? The SWOOSH QBO or the reanalysis QBO? What are the known uncertainties of these data sets?
P5, L124: In Figure 2 the QBO from ERA5 and SWOOSH is shown but then the QBO is analysed in detail but without stating which data set has been used.
Figure 2-10: Which data set has been analysed?
P7, Figure 3: In the figure it is written “q”. If the specific humidity is shown here this should be clearly stated or if you have calculated from q the water vapour mixing ratio then you should write in the figure legend and on the axis “H2O”.
P11, L263: Leads to cold “temperatures”? Please be more clear.
Figures: 14 figures are too much. I would suggest to put some of the figures in an appendix and focus in the main text of the manuscript on the most important figures.
Technical corrections:
P7, L162: shows weak -> shows a weak
P7, Figure 3 caption: “Figure. 3” should be “Figure 3.” Note, this needs to be corrected also for all other figures, too.
P8, L179: un der -> under
P9, L206: 100hPa -> 100 hPa
P10, L223: warm -> warms
P13, L299: in tropics -> in the tropics
References:
Giorgetta, M. A., Manzini, E., Roeckner, E., Esch, M., and Bengtsson, L.: Climatology and forcing of the quasi-biennial oscillation in the MAECHAM5 model, J. Clim., 19, 3882–3901, 2006.
Citation: https://doi.org/10.5194/egusphere-2025-1123-CC1 -
RC1: 'Comment on egusphere-2025-1123', Anonymous Referee #1, 23 May 2025
The authors present an analysis of the seasonality of QBO effects on stratospheric water vapor in ERA5 reanalysis data, the observation-based SWOOSH data set, and CMIP models. In general, I find that this analysis provides sufficient new knowledge about the QBO impact on stratospheric water vapor to merit publication. I also think that mostly the analysis is well presented. I have some specific concerns about details of the analysis, its interpretation, and references to earlier work that I will list in the following, and which I think should be addressed before I can recommend a publication.
Introduction: I think the motivation for this study should be sharpened. From the introduction I have the impression that the main research gap is given in the following sentences: “However, it still remains unclear whether the effects of the QBO on stratospheric water vapor differ between northern winter and summer. The seasonality of the water vapor QBO signal has been seldom studied.” “Seldom” would not mean never, so what is known about the seasonality and what not? And why is the difference between northern winter and summer of specific interest? I’d further appreciate that the authors formulate a hypothesis on expected impacts of the seasonality which could be based on existing knowledge on the seasonality of stratospheric water vapor and circulation and on the mean imprint of the QBO on these two quantities. Additionally I think it would be good to be more specific about why a seasonality of the QBO imprint on stratospheric water vapor would matter.
2a Datasets: What is the motivation for using ERA5 and SWOOSH? To which degree can these datasets be considered independent. Have observations used to build SWOOSH also been assimilated in ERA5? What may be the advantages of one or the other dataset?
L117: The authors write that divM “represents the eddy transport of water vapor” To my understanding it doesn’t represent the full eddy transport, which is partly already included in the residual advection terms. It only appears in the case of tracers which are not inert. I have to admit my knowledge of this formalism is only partial, but other readers may also benefit from a more comprehensive discussion of these terms.
L134: “Since HALOE started from 1992, the water vapor QBO amplitude in the upper stratosphere between 1–5 hPa has increased, which is also shown in ERA5 reanalysis.” To me this statement is unclear. Is the assumption that the assimilation of HALOE data is causing this increase in the datasets, or could the timing be accidental? This is related to the above comments on the independence of ERA5 and SWOOSH data. I also don’t understand why the following sentence starts with “Alternately, …” Do you mean “alternatively”? But even then, it seems that the two sentences discuss different phenomena, changes in time in the first, and changes with altitude in the second sentence.
L164: The authors write that the “relationship between the QBO and water vapor [shown in Fig. 3] is to be expected” because the cold point temperature determines tropical water vapor. I’d agree that “a” relationship is to be expected, but why “this” relationship? Why would it be expected that both at 10 and 70 hPa there would be an in-phase relationship? Given the in-phase relationship at these two levels and the different vertical propagation directions of QBO winds and water vapor, would the relationship be out of-phase at levels inbetween (e.g. 20 or 30 hPa). If this is so, it would be good to mention it in order not to raise the false impression of an in-phase relationship everywhere. Please consider this issue also for point I of the summary section.
Fig. 10: I think the results of this figure are not sufficiently discussed. It is said that “the residual circulation explains partially the water vapor variation in the tropical stratosphere” which I find to vague. What means partially? What else is important? And is it horizontal or vertical advection that matters? If possible I’d like to see a conclusion from this analysis arguing if tropical water vapor anomalies are mainly related to the upward propagation of different amounts of water vapor entering the stratosphere in different QBO phases or some other phenomenon. Similar for extratropical anomalies. This would also be the place for an attempt to explain the analysed differences between hemispheres and seasons.
4b: Factors affecting the water vapor distribution: The discussion of temperature anomalies is motivated by the relevance of the cold point temperature. However, the following paragraph discusses temperature anomalies also elsewhere. What is the motivation for this? Furthermore: The QBO influence on cold point temperature has been discussed by other studies. It would be good to provide references and discuss to what extent this study provides similar or different results.
L218: “as expected from thermal wind balance” It may be useful to add a reference here as not every reader may be familiar with the concept of thermal wind balance in the tropical atmosphere.
Figs. 4, 6, 7, 10: Please use consistent vertical extensions in these plots to facilitate comparison of the figures.
Fig. 8: The seasonal dependence of QBO-related temperature anomalies in the tropopause regions has been analysed earlier, e.g. by Tegtmeier et al. (GRL, 2020) or by Serva et al. (QJRMS, 2022). I’m almost certain there are even more papers on this, but I haven’t performed a proper literature survey. Please discuss to what extent your results agree or disagree with earlier studies.
L298: “This combination suggests that the QBO might be able to influence convection in this region.” There have been many earlier studies on the dependence of convection on QBO phases. Please discuss to what extent your results agree or disagree with earlier studies. As the main goal of this study is to analyse the QBO-dependence of stratospheric water vapor, I’d like to see a discussion if the dependence of convection might impact the water vapour distribution. If not I’d suggest to remove this part.
Section 5: Figures 1 and 11 use different color scales. This may be useful to show the simulated signals more clearly, but it should be mentioned explicitly. Related to that I’d find it useful to state clearly very early that for all models the signal is too weak. Potential reasons for that should be discussed. I understand the analysis presented in Fig. 14 as an attempt to identify an explanation, but I don’t see a clear conclusion presented by the authors. If the tropopause temperature anomaly is crucial for the water vapour entry, wouldn’t it be more straightforward to analyse how the strength of this anomaly in CMIP models relates to the simulation of the water vapour signal?
L327: “Since stratospheric water vapor has important climatic effects, evaluation of the simulated water vapor QBO by CMIP6 models is helpful in diagnosing how to improve the performance of the models (Keeble et al., 2021; Ziskin Ziv et al., 2022).” This may provide some of the motivation I was missing in the introduction. However, I find the statement very vague. What do you have in mind? Model performance with respect to what? How would it help in diagnosing how to improve it?
L367: Is this statement really true for CESM-WACCM-FV2? The table indicates a winter correlation of only 0.29, not higher than 0.5.
L423: As mentioned above, a seasonality of QBO signals in tropopause temperature has been identified in previous papers. Please indicate to what extent your findings are new.
L443: “This study … finds that BD circulation change related to QBO might be a mediator bridging the QBO and water vapor.” I have difficulties to understand this statement. Please be more precise. What means mediator? Why might? Hasn’t it been shown clearly in this and earlier studies that QBO and stratospheric water vapour are related? So what is actually new in this finding?
L444: “It provides a new perspective to better understand the stratospheric water vapor QBO signals.” Also this sentence is unnecessarily vague. What is this new perspective?
Citation: https://doi.org/10.5194/egusphere-2025-1123-RC1 -
RC2: 'Comment on egusphere-2025-1123', Anonymous Referee #2, 17 Jun 2025
General Comments
I recommend rejection of this manuscript as it suffers from two fundamental flaws:
- ERA5 Stratospheric Water Vapor (SWV) is the central dataset in this manuscript. It is studied in sections 3 and 4 and it is used as reference for CMIP6 evaluation (section 5). The manuscript fails to consider the nature of the ERA5 reanalysis of water vapour, i.e. an optimal representation between model state, in-situ humidity observations in the troposphere and satellite radiance observations which are sensitive to humidity only in the troposphere. This appears clearly in Hersbach et al. (2020) where section 5 provides an exhaustive description of the assimilated observations.
While satellite retrievals from limb-scanning instruments are assimilated after 2002 in the case of ozone (i.e. MIPAS and Aura-MLS), no similar dataset is assimilated for water vapor. SWV has a negligible impact on satellite observations of microwave and infrared radiances because they are observed in a nadir-looking geometry. Hence ERA5 SWV is not influenced by these observations, is fundamentally nothing more than the output of a GCCM with Specified Dynamics, and is thus far from a “true” dataset. This is also indicated by Hersbach et al. in their Fig. 12, where analysis increments of humidity are not shown above 300 hPa while analysis increments of temperature, zonal wind and ozone are also shown at 50 hPa and 3 hPa; and in the discussion of their Fig. 19 (SWV above the South Pole) where it is specifically written that “no humidity observations are assimilated at this level” (850 K isentropic surface i.e. mid-stratosphere).
The accuracy of ERA5 in the stratosphere (and its 2000-2006 correction ERA 5.1) are summarized in section 7 of Hersbach et al. (2020 – see especially their Fig. 15) and extensively discussed by Simmons et al. (2020, not cited in the manuscript). Yet such uncertainties are not considered in this manuscript, which also fails to mention the well-known moist bias in ERA5 at the tropical tropopause (Krüger et al., 2022). An earlier study of stratospheric water vapor in ERA5 did conclude that SWV is better represented in ERA5 than in ERA-Interim (Wang et al., 2020) but this earlier study of the QBO in ERA5 SWV is not cited either.
The confusion between ERA5 SWV and observed SWV could have been partially overcome by using the SWOOSH dataset, which is entirely based on observations. Yet SWOOSH is only used for Fig. 1. After a very superficial comparison between ERA5 and SWOOSH SWV (line 134), the authors seem to believe that ERA5 assimilated HALOE SWV data (lines 135-136) while this is not true. - This manuscript attempts to study the seasonality of the QBO signal in water vapor by comparing composite of anomalies in “boreal summer” and “boreal winter” (which I understand as JJA and DJF, respectively). While the methodology section severely lacks details, one can still read (line 99) that “The anomaly refers to the deviation of the monthly data from the monthly climatology…” . Since these anomalies are the signal after removal of the seasonal cycle, it makes no sense to study the differences between their composites for DJF and JJA. Yet this method is at the core of the manuscript, as shown by Figs 4 to 10 and 12 to 14. Furthermore, section 2 states that a “Butterworth first-order bandpass filter was used to extract the water vapor variations at the period of 15-60 months”. How can the seasonality of the dataset be preserved after the application of such a filter? The methodology used here would have been greatly clarified (and probably invalidated) by showing time series of SWV prior to calculation of anomalies, and also prior to the application of the bandpass filter.
Compare with the methodology used and explain in much better detail by Wang et al. (2020), where seasonal cycle in ERA5 SWV is clearly shown by anomalies from the climatological annual mean (fig. 2) while the QBO cycle in ERA5 SWV is shown by anomalies relative to the monthly climatology (fig. 3).
The large differences found here between DJF and JJA anomalies are thus quite difficult to interpret. They could be due to inconsistent periods for the removal of the monthly climatologies. In other words: the period used for the climatological seasonal cycle is 1960-2020 (line 98) but are the “composite” SWV anomalies shown from Fig. 4 onwards also computed for that period?
Other comments
In case the manuscript undergoes major revisions, the following issues should be addressed as well:
- The abstract should better introduce the key concepts, i.e. the QBO and “the seasonal difference in the water vapor QBO”.
- The introduction itself is not written in a rigorous manner:
- The very strong statement of the first sentence (“Water vapor is the dominant greenhouse gas in the atmosphere”) is not clearly supported by the two provided references (Dessler et al., 2013; Solomon et al., 2010) which are about the feedback between SWV and tropospheric climate.
- The modulation of chemical processes by SWV (line 31) is actually a weak feedback, as explained by Wohltmann et al. (2024). Tian et al. (2023) does not address specifically this statement; I was not able to check Tian et al. (2009) as this reference is incomplete.
- Admittedly, “the seasonality of the water vapor QBO signal has been seldom studied” (line 65). But why is it interesting to study this seasonality? The introduction fails in its primary aim.
- Many more details are necessary about the datasets (section 2a). What is their time resolution at download time (i.e. prior to derivation of the anomalies): hourly, daily, monthly? Has ERA-5 been downloaded on model levels or (much less accurate) on pressure levels? What are the uncertainties of SWV in SWOOSH (see comment 1 for ERA5)? Two generic papers are cited for CMIP6, but what are the specific references about the CMIP6 historical simulations? Could a reference be found about the overall quality of SWV in these simulations?
- The base climatology is calculated for the period 1960-2020. Does it make sense two very different periods of ERA5 (compare fig. 1a with fig. 1b) to compute its base climatology ? See also comment 2. The period 1960-2020 presumably applies only to ERA5, as the CMIP6 simulations end in 2014. Does it make sense to compare anomalies for different periods?
- Line 104-105 define criteria of +/- 5 m/s for QBO “events”. Are these the criteria used to build the W QBO and E QBO composites ? Please clarify.
- All water vapor anomalies are shown in ppm units. Does this refer to water vapor volume mixing ratio (a.k.a. mole fraction) or mass mixing ratio ?
- Figure 2 shows only two contour lines for the zonal wind, with no labels. Yet lines 142-147 discuss the numerical values, which are impossible to read from the figure.
- Similarly for fig.4: lines 179-180 and 187-188 discuss a difference in tropopause pressure between the W QBO and the E QBO, but this can not be seen on the figure. BTW, how is defined the tropopause here? Are you using a thermal, dynamical or SWV-based definition ?
- What is the meaning of the dotted regions on Fig. 4?
- Figures 12 is not explained at all, and discussed very succinctly with figure 13 and Table 1 (lines 344-359). This should be expanded.
Additional references
Krüger, K., Schäfler, A., Wirth, M., Weissmann, M., & Craig, G. C. (2022). Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes. Atmospheric Chemistry and Physics, 22(23), 15559-15577.
Simmons, A., Soci, C., Nicolas, J., Bell, B., Berrisford, P., Dragani, R., ... & Schepers, D. (2020). Global stratospheric temperature bias and other stratospheric aspects of ERA5 and ERA5. 1.
Wang T, Zhang Q, Hannachi A, Hirooka T, Hegglin MI. Tropical water vapour in the lower stratosphere and its relationship to tropical/extratropical dynamical processes in ERA5. Q J R Meteorol Soc. 2020; 146: 2432–2449. https://doi.org/10.1002/qj.3801
Citation: https://doi.org/10.5194/egusphere-2025-1123-RC2 - ERA5 Stratospheric Water Vapor (SWV) is the central dataset in this manuscript. It is studied in sections 3 and 4 and it is used as reference for CMIP6 evaluation (section 5). The manuscript fails to consider the nature of the ERA5 reanalysis of water vapour, i.e. an optimal representation between model state, in-situ humidity observations in the troposphere and satellite radiance observations which are sensitive to humidity only in the troposphere. This appears clearly in Hersbach et al. (2020) where section 5 provides an exhaustive description of the assimilated observations.
-
RC3: 'Comment on egusphere-2025-1123', Anonymous Referee #3, 23 Jun 2025
This paper presents an analysis of the effect of the QBO on stratospheric water vapor, in particular comparing boreal winter and summer. The first part of the analysis is based on ERA5 reanalysis and SWOOSH observations, the second part on CMIP6 climate model simulations. In my opinion, the main new results are: (i) differences in stratospheric water vapor between QBO westerly and easterly phases are significantly smaller in boreal summer than winter, (ii) this seasonal difference in the QBO effect is partly related to stratospheric circulation and partly to convection, (ii) current climate models have issues in simulating these seasonal differences.
Overall, I think this paper addresses an interesting question, presents valid analysis and new results, and should be suitable for publication in ACP. However, I have 2 major comments and a list of specific comments which I'd ask the authors to address before I can recommend publication.
Major comments:
1.) Vertical propagation of QBO effect:
This comment concerns the comparison of the QBO effect on water vapor at different levels. For instance, the paragraph starting at L156 is not clear and even somewhat misleading to me. Why is it meaningful to compare correlations between zonal wind and water vapor calculated at different levels? I see basically two pathways how the QBO can affect stratospheric water vapor: by modulating tropical tropopause temperatures and by modulating stratospheric transport (e.g. via induced secondary circulation). I'd suggest to decribe these two pathways clearly, e.g. already in the introduction.
The signal from modulating tropical tropopause temperatures propagates upwards and therefore comparison of regressions at different levels needs including lag times. Said that, couldn't it just be that the significant positive correlation at 70 an 10hPa just coincidentally results from the upward propagating tape recorder signal (Fig. 1) and downward propagating wind anomalies (Fig. 2), but has no deeper physical meaning? I see similar difficulties when interpreting Fig. 4, which also compares the QBO effect at different levels. Hence, I'd suggest to include such lag times for a proper comparison of the QBO effect at different levels (e.g. correlating water vapor at different levels with one QBO-index at 30hPa, including lag, see Diallo et al., 2022, https://doi.org/10.5194/acp-22-14303-2022). If this goes beyond the scope of the paper, one could also remove Figs. 3 and 4 and the related discussion from the paper, but then clearly state early in the paper that the QBO here is always defined at 30hPa.
Related to that, the respective sentences in the abstract (L15) and summary (L402) need to be clarified or removed.
2.) New results versus state-of-the-art:
At some parts the paper is not very clear in what the new results and what just state-of-the-art is. For instance in the summary there are large text parts describing well-known facts regarding the QBO (e.g. L410-418), and also in the rest of the paper (see a few of my specific comments below). Sure, it is absolutely necessary to relate to previous work. But I'd recommend to say more clearly what the new findings of this paper are (my view on these is summarized in my general comment above). Perhaps a clearer structuring of the summary around these could be helpful (first stating the respective new finding, then discussing). Also, formulating related research questions in the introduction could help the reader here.
Specific comments:
L18: I don't understand what is meant by "...dynamic transport...", probably "vertical transport"? And also the connection to the next sentence is not clear to me. Sure, in boreal winter dehydration is stronger. Please reformulate both sentences to clarify what is meant.
L35: The "tropical path" is the "primary channel" for water vapor into the stratospheric overworld - for the lowermost stratosphere this is not clear. Please clarify.
L134: Overall, I find the agreement between ERA5 and SWOOSH here not too strong and would recommend to discuss the differences in more detail (e.g. the too fast upward propagation of the signal in ERA5, or the too strong dampening of the amplitude).
L137: I'm wondering about the years after 2015. Why is there no clear QBO signal in water vapor during these years in ERA5? SWOOSH observations show a water vapor QBO also in these years. Pleae comment.
Figure 2, caption: State the dataset used (ERA5) in the caption. Also describe the contour values and the meaning of dashed/solid.
L156ff: Refer to Fig. 3 at the beginning of the text where it is discussed.
L162: The weakening of the QBO signal above 5hPa is well known, and one could refer to e.g. Baldwin et al. (2001). (This comment is related to major comment 2).
L164: What relationship is to be expected? Please clarify.
Figure 4, caption: Explain the meaning of the shading in the caption.
L258: I don't understand the intention behind this sentence "rising branch in the tropics stronger than the sinking branch in the extratropics". Tropical upwelling should always be balanced by extratropical downwelling. Please clarify.
Figure 7: It would be good to have the same y-axis range and labels as in other figures (e.g. Fig. 4, 6) to ease comparison.
Figure 7, caption: Residual circulation upwelling (!) ... And then give the units directly after "upwelling", not just at the end of the caption.
L295: There is a recent paper by Pena-Ortiz et al. (2024, https://doi.org/10.5194/acp-24-5457-2024
) which demonstrates a relation between the QBO and convection in the Asian summer monsoon, of relevance for water vapor variability in the monsoon UTLS. I think it could be enlightening to relate the QBO-convection relation found here to their results.Figure 9, caption: Should be "OLR" not "temperature" anomalies in L310.
L312ff: The take home message from the tracer continuity analysis is not becoming very clear to me from the text here. I think the main result is that it is mainly mean advection by the residual circulation that causes the observed differences between easterly and westerly QBO phases. Please clarify the text that this is getting clearer. (This comment is related to major comment 2).
L329ff: ERA5 shows a change in the QBO-related anomaly pattern around 10hPa: below there is a tape-recorder of upward propagating anomalies, whereas above there seems to be a more direct effect of transport modulated by the QBO-induced secondary circulation. This change in anomaly pattern is only visible in a few models (e.g. CESM2-WACCM). I find this an important difference between ERA5 and CMIP6 models and would recommend to discuss it.
L351: But even for this model the agreement with ERA5 is not very high.
L367: Table 1 says that CESM2-WACCM-FV2 for boreal winter has a correlation coefficient of 0.29. So I'm wondering why it is mentioned here as one of the two models where correlation is higher than 0.5.
L375ff: For the analysis here, a QBO index at 50hPa is used. Before (L102ff) it was argued that in this paper a 30hPa-index is used as only at such high level all models have a sufficiently significant QBO variability. This seems somewhat contradictory to me. Please clarify.
L402: The enhanced correlation for lower and upper stratosphere seems method-related to me (see my major comment above). I'd remove this statement here or clarify.
L410ff: In my opinion, most of this paragraph is well-known facts regarding the QBO and induced secondary circulation. Only the last sentence (starting L418) describes the new results of the present paper. I'd recommend to restructure and shorten, so that the focus is on new results. (This comment is related to major comment 2).
L420: ... controlling factor ... in the tropical lower stratosphere...
Technical corrections:
L13: seasonal differenceS
L58: The reference is sometimes written "Ziskin Ziv et al. (2022)", sometimes "Ziskin et al. (2022)" (e.g. L60). Please use the same citation label.
L192: ... anomalies ... are ...
L212: regulateS
L206: ... at 100hPa during winter ... (would be good to add the season here).
L247: anomalously strong upwelling ... anomalously strong downwelling ...
L256: in the Northern hemisphere suptropics
L427: I'm not entirely sure what is meant here. Do you mean: "The influence of OLR on the tropopause cold point temperature in summer is opposite to the tropical stratospheric temperature anomalies related to the QBO secondary circulation, which ..."Citation: https://doi.org/10.5194/egusphere-2025-1123-RC3
Model code and software
Seasonality of the Quasi-biennial Oscillation signal in water vapor in the tropical stratosphere Qian Lu https://doi.org/10.5281/zenodo.14999285
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 400 | 49 | 20 | 469 | 15 | 35 |
- HTML: 400
- PDF: 49
- XML: 20
- Total: 469
- BibTeX: 15
- EndNote: 35
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1