the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Nov 2024
Understanding Boreal Summer UTLS Water Vapor Variations in Monsoon Regions: A Lagrangian Perspective
Abstract. Water vapor in the Upper Troposphere and Lower Stratosphere (UTLS) plays a crucial role in climate feedback by influencing radiation, chemistry, and atmospheric dynamics. The amount of water vapor entering the stratosphere is sensitive to cold point temperatures (CPT), making Northern Hemisphere summer monsoons more favorable for transporting water vapor into the stratosphere. This study uses a Lagrangian method to reconstruct water vapor over the Asian (ASM) and North American (NAM) monsoons, investigating their contributions to stratospheric water vapor. The Lagrangian method tracks air parcels and identifies the coldest temperature along each trajectory, contrasting with local methods that rely on vertical temperature profiles. The reconstructed water vapor fields are validated against satellite observations from SAGE III/ISS and NASA’s Aura MLS. SAGE III/ISS shows stronger moisture enhancements than MLS, but both datasets reveal similar water vapor anomalies within the ASM and NAM anticyclones. Although the Lagrangian method is dry-biased compared to observations, it effectively reconstructs UTLS water vapor (correlation coefficient 0.75), capturing moist anomalies in the ASM but performing less well in the NAM. Our analysis shows that, large-scale cold point tropopause temperatures in the vicinity of the monsoons primarily drive the moisture anomalies, with NAM water vapor significantly influenced by long-range transport from South Asia. Some convection-related processes, such as east-west shifts within the ASM, are not fully captured due to unresolved temperature variability in ERA5 and missing ice microphysics. Despite biases and computational challenges, the Lagrangian method provides valuable insights into UTLS water vapor transport.
- Preprint
(5620 KB) - Metadata XML
-
Supplement
(1670 KB) - BibTeX
- EndNote
Status: open (until 13 Jan 2025)
-
RC1: 'Comment on egusphere-2024-3260', Stephen Bourguet, 16 Dec 2024
reply
Review of Wang et al., Understanding Boreal Summer UTLS Water Vapor Variations in Monsoon Regions: A Lagrangian Perspective
To the editor
This paper aims to improve our understanding of lower stratospheric water vapor anomalies that occur over the Asian and North American summer monsoons, a problem that has implications for surface climate and stratospheric chemistry. This paper uses a Lagrangian trajectory method to identify the role of cold point temperatures in the vicinity of the monsoon in setting the water vapor content of air reaching the lower stratosphere. I believe that this is a valuable contribution that can be suitable for publication in ACP following revisions.To the authors
General feedback
This work uncovers a correlation between Lagrangian cold point temperatures and water vapor anomalies over the Asian summer monsoon. However, the mechanism presented here can only explain a fraction of the overall water vapor anomaly. While the dry bias of the Lagrangian trajectory method has been noted before, the dry biases in Fig. 2 make it difficult to claim that elevated Lagrangian cold point temperatures contribute significantly to the water vapor anomalies. For example, at 15.5 km the ASM reconstructed anomaly is about 1 ppm, while the SAGE anomaly is about 5 ppm. Therefore, the current method only accounts for about 1/5 of the observed moistening in the ASM. In the NAM, the Lagrangian method does not show a moistening. In both regions, I feel that the current presentation of these results overstates the moistening that can be explained by this method. This framing needs to be improved prior to publication.Moreover, I would argue that the central conclusion of this paper is that a small portion of moistening over the ASM is caused by an altered transport pathway through the UTLS, not that the moistening can be explained by the Lagrangian method. A secondary conclusion would be that the altered pathway is not significant for the NAM. In other words, the ASM allows some portion of air to avoid the “cold trap” and the dehydration that would occur within. This results in a water vapor anomaly that occurs regardless of direct injection of water vapor/ice into the lower stratosphere (although the majority of the anomaly is driven by these other processes). The correlation between the Lagrangian reconstructions and ASM observations suggest that this cold-trap-avoidance mechanism is robust, but it does not prove that the mechanism is the dominant source of water vapor anomalies.
The proposed mechanism would also gain meaning with additional discussion of other water vapor sources. For example, Smith et al. (2017) studied a summertime water vapor enhancement over North America and found that frequent deep convection can deliver water vapor to the lower stratosphere. O’Neill et al. (2021) also provide a mechanism by which water vapor injection occurs over intense convection. Studies like these would explain why the hydration captured by the Lagrangian trajectory method is smaller than the observed hydration, especially over the NAM.
Additionally, the choice of the 6-hr resolution needs to be justified for two reasons. First, the monsoon can act on timescales shorter than 6 hours, so it is possible that the Lagrangian trajectories do not fully capture the effect of the monsoons. Li et al. (2020) found that the improved temporal resolution of ERA5 led to more rapid transport than ERA-i, so it is possible that the 6-hr data used here does not fully capture convective transport. Second, it has been shown that trajectories calculated with 6-hr data have transport errors and warm CPT biases relative to those calculated with 1-hr data (Pisso et al., 2010; Bourguet and Linz, 2022). It is possible that the warm CPT biases cancel out when calculating anomalies, but it is also possible that the anomalies calculated with 6-hr data are larger than those that would be calculated with 1-hr data. This would mean that the mechanism presented here is actually smaller than these results would suggest.
I would also advise moving the LAG_single comparison to the Supplemental. It is well known that single trajectories are not meaningful and that ensembles should be used instead. As currently presented, the comparisons with LAG_single distract from the main results. I also feel that the MLS results could also be moved to the Supplemental to improve the focus on the comparison between reconstructed and observed water vapor. (The same conclusions are drawn when comparing reconstructions with MLS and SAGE.)
Specific points
- Lines 2–4: “The amount of water vapor entering the stratosphere is sensitive to cold point temperatures, making NH summer monsoons more favorable for transporting water vapor into the stratosphere.” Water vapor enhancements over Northern Hemisphere summer monsoons do not follow from elevated cold point temperatures. Deep convection can lower the CPT, so this statement needs to be clarified.
- Line 5: “investigating their contributions to stratospheric water vapor.” To my understanding, the water vapor reconstructions in this work are confined to the tropical lower stratosphere, and there is no evaluation of how monsoon water vapor anomalies contribute to the stratospheric water vapor budget. Therefore, I would avoid saying that the contributions to stratospheric water vapor are evaluated here.
- Lines 9–11: “it effectively reconstructs UTLS water vapor (correlation coefficient 0.75), capturing moist anomalies in the ASM, but performing less well in the NAM.” Following from general feedback above, the high correlation here does not mean that the Lagrangian method can explain the magnitude of the water vapor anomalies. I think it would be more appropriate to say that the Lagrangian water vapor reconstructions correlate well with observed ASM water vapor, suggesting a role for altered transport pathways in driving water vapor anomalies.
- Line 17: “The water vapor” -> remove “The”.
- Line 25: “Large-scale vertical transport enhances lower stratospheric water vapor…” Is this meant to say that large-scale vertical transport spreads convectively-injected water vapor? Large-scale transport on its own does not enhance lower stratospheric water vapor.
- Line 33: “Several studies have successfully reconstructed UTLS water vapor using Lagrangian methods….” I would argue that studies are able to capture UTLS water vapor anomalies, not total water vapor concentrations (e.g., Smith et al., 2021; Bourguet and Linz, 2022). This is an important distinction given the uncertainty surrounding the dry bias in Lagrangian reconstructions.
- Lines 78–79: “within both Asian monsoon and North American monsoon regions” -> tropical water vapor is also considered. Could be easier to say “across the tropics.”
- Lines 96–98: Clarify that 1-2-1 vertical smoothing is done on 1 km grid. (It’s not currently clear if smoothing is done on 0.5 km grid or 1.0 km grid.)
- Line 125: SAGE vertical resolution is reported as 0.5 km here. When is 0.5 km used, and when is 2.0 km vertical resolution used?
- Section 2.3: How many trajectories are calculated in total, and how many are with the ASM and NAM, respectively?
- Lines 171ff: “The large-scale patterns in the reconstructions are consistent with the observations….” I would argue that this is misleading, even with the acknowledgement of the dry bias that follows. The NAM anomaly is not present in reconstructions, so broad statements about large-scale patterns should be avoided. Similarly, in the following paragraph, the assertion that the “reconstruction captures the enhancements in water vapor concentrations and their locations” is misleading. The quality of the water vapor reconstructions in the ASM and the NAM should be discussed separately to avoid conflating the two.
- Line 188: Specify that the cyan squares are in Fig. S1.
- Lines 249–252: Please be more specific with what you mean by “exhibit no significant differences in overall structure” and explain how this suggests that the tropics and monsoon regions have the same primary controlling mechanisms. To me, the tropical scatter plots (Fig. 4d, g) appear qualitatively different than the NAM scatter plots (Fig. 4f, i). Also, although the ASM scatter plots appear more similar to the tropical scatter plots, these plots only consider the relationship between the CPT and observed water vapor, so it is possible that other mechanisms could contribute to the two separately.
- Lines 261–275: I would advise either removing this paragraph or moving it to the Discussion or Conclusion section.
- Section 3.2: I suggest including a panel to Fig. 5 with the location of the LCP for all tropical trajectories. This would allow for a comparison of CPT locations between the monsoon regions and the tropics, which would support the idea that the monsoons alter the transport pathways through the UTLS.
- Lines 291–293: “This suggests that the increased water vapor in the ASM is primarily attributed to dehydration processes occurring in the vicinity of the monsoon over Asia.” This needs to be clarified. The location of the highest reconstructed water vapor concentrations suggests that the increased water vapor captured by the Lagrangian reconstruction (about 1/5 of the observed increase) is primarily driven by changes to transport near the ASM. The remaining 4/5 of the observed anomaly is attributable to other processes.
- Lines 316–318: The contribution of distant CPTs to the reconstructed NAM water vapor anomaly does not imply significance of distant CPTs to the observed anomalies. Instead, the relative inability of the NAM reconstruction to capture observed water vapor anomalies implies that local processes (e.g., direct injection of water vapor) are crucial for explaining the final moisture composition with the anticyclone. However, the Lagrangian method cannot reproduce observations, so you cannot draw objective conclusions about the behavior of the atmosphere with this method.
- Line 351: “the ASM anomalies are nearly fully captured.” The ASM observation and reconstruction patterns in Fig. 1 are qualitatively similar, but Fig. 2 shows that the ASM water vapor reconstruction does not capture a majority of the observed anomalies. Thus, I would caution against the quoted statement.
- Lines 370–372: Similar to the previous point, Fig. 2 shows that the Lagrangian water vapor reconstruction does not successfully capture the magnitude of the moist anomalies over the ASM. A portion of the moist anomalies can be explained by the Lagrangian reconstruction, but the large dry bias in the anomalies implies that a mechanism other than freeze-drying is needed to explain observations.
I hope you find this feedback helpful, and I look forward to reading a revised manuscript.
–Stephen Bourguet
References
Smith et al. (2017), A case study of convectively sourced water vapor observed in the overworld stratosphere over the United States, J. Geophys. Res. Atmos., 122, 9529–9554, doi:10.1002/2017JD026831.
O’Neill et al. (2021), Hydraulic jump dynamics above supercell thunderstorms. Science 373, 1248-1251. doi:10.1126/science.abh3857.
Li et al. (2020), Dehydration and low ozone in the tropopause layer over the Asian monsoon caused by tropical cyclones: Lagrangian transport calculations using ERA-Interim and ERA5 reanalysis data, Atmos. Chem. Phys., 20, 4133–4152, doi:10.5194/acp-20-4133-2020.
Pisso et al. (2010), Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution, Atmos. Chem. Phys., 10, 3155–3162, doi: 10.5194/acp-10-3155-2010.
Bourguet and Linz, (2022), The impact of improved spatial and temporal resolution of reanalysis data on Lagrangian studies of the tropical tropopause layer, Atmos. Chem. Phys., 22, 13325–13339, doi:10.5194/acp-22-13325-2022.
Smith et al. (2021) Sensitivity of stratospheric water vapour to variability in tropical tropopause temperatures and large-scale transport, Atmos. Chem. Phys., 21, 2469–2489, doi: 10.5194/acp-21-2469-2021.
Citation: https://doi.org/10.5194/egusphere-2024-3260-RC1
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 105 | 34 | 8 | 147 | 26 | 4 | 3 |
- HTML: 105
- PDF: 34
- XML: 8
- Total: 147
- Supplement: 26
- BibTeX: 4
- EndNote: 3
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1