the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A long pathway of high water vapor from the Asian summer monsoon into the stratosphere
Paul Konopka
Christian Rolf
Marc von Hobe
Sergey M. Khaykin
Benjamin Clouser
Elizabeth Moyer
Fabrizio Ravegnani
Francesco D'Amato
Silvia Viciani
Nicole Spelten
Armin Afchine
Martina Krämer
Fred Stroh
Felix Ploeger
Abstract. During the StratoClim Geophysica campaign, air with total water mixing ratios up to 200 ppmv and ozone up to 250 ppbv was observed within the Asian summer monsoon anticyclone up to 1.7 km above the local cold point tropopause (CPT). To investigate the temporal evolution of enhanced water vapor being transported into the stratosphere, we conduct forward trajectory simulations using both a microphysical and an idealized freeze-drying model. The models are initialized at the measurement locations and the evolution of water vapor and ice is compared with satellite observations of MLS and CALIPSO. Our results show that these extremely high water vapor values observed above the CPT are very likely to undergo significant further freeze-drying due to experiencing extremely cold temperatures while circulating in the anticyclonic dehydration carousel. We also use the Lagrangian dry point (LDP) of the merged backward and forward trajectories to reconstruct the water vapor fields. The results show that the extremely high water vapor mixed in with the stratospheric air has a negligible impact on the overall water vapor budget. The LDPs are a better proxy for the large-scale water vapor distributions in the stratosphere during this period.
Paul Konopka et al.
Status: open (until 31 May 2023)
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RC1: 'Comment on egusphere-2023-498', Anonymous Referee #1, 21 May 2023
reply
Review of “A long pathway of high water vapor from the Asian summer
monsoon into the stratosphere” by Konopka et al.
This is an important paper, and it provides good evidence that ‘convective moistening of the stratosphere’ over monsoons is far more complicated than some of the earlier proponents have envisioned. Previous discussions of the convective moistening process have assumed that
Convection reaching above the tropopause simply resets the relative humidity to saturation. In this study, it is evident that the air parcels may continue to dehydrate due to the elevated cold points as they move around in the Asian monsoon anticyclone. In my own mind, the higher the convection, the colder the air due to adiabatic expansion and the more complete the dehydration. This paper shows that parcels launched at the top of other convective events, can transit through colder air undergoing later dehydration.
I found the abstract quite descriptive and useful. I recommend that a longer version of the abstract be repeated in the summary section which could be expanded.
In general, the figures are hard to read, and the captions are too long. The author might consider breaking up the figures into smaller groups and edit the captions.
I would delete Fig. 5, not very helpful.
Specific comments:
I would reference Brewer (1949) as the originator of the CP regulation of water vapor theory.
The introduction is too brief to cover this complex and important scientific field. For example, you might also expand on some of the previous publications mentioned. The Randel & Park (2019) paper is a particularly important prelude to these conclusions. Additionally, there are additional trajectory model simulations by Ueyama & Schoeberl and collaborators are relevant – these papers also used convection and ice formation models. The Avery paper focusses on El Nino, not the monsoon. Lumping the regular monsoon convection system with El Nino seems like a stretch to me.
Table 1 is confusing. 10.08 flights? Is this the date? Why is this relevant? I would put a comment in the Table on the difference between Type A and Type B. Perhaps a comment line ‘recent convective influence’ and ‘aged convective influence’ for A and B - something that the reader can immediately grasp.
I would put the references to the instruments in Figure 1 caption into the text. All the references make the caption difficult to read. “time distance?” you mean time since encountering an LDP.
The exact LDP is a little uncertain since gravity waves could create an LDP even after the temperature along the path has warmed up a little. I assume you observed temperature fluctuation measurements as part of the aircraft flights. You could translate this into an uncertainty in the LDP time using Delta-T and the temperature along the path. These fluctuations could be important. It wasn’t clear from the text that Podglajen et al. (2016) gravity wave parameterization is included, or if it is included, does it match observations over mountainous Himalayas?
You might add some additional references on CO photolysis beyond von Hobe (2021). CO is measured by MLS. Minschwaner et al., (2010) is the classic paper on CO lifetime, also see Liang et al. (2023) and references therein.
Clearly type B is ‘aged air’ with higher ozone, lower CO whereas type A is ‘younger air’. So it was a little surprising to see the LDP age for type A all over the map (Fig.1 C). This confusing point was straightened out in Fig. 1d so maybe 1c could be eliminated or make the symbols smaller.
FIG. 2 – it might be useful to locate where the Part b Lagrangian dry point is located on the map shown in Part a. I would have shown the type A trajectory in 2c – makes your point better – and put the Type A label inside 2d. Remove the not-needed information from caption of Fig. 2
Line 80. CALIPSO does not detect ice mixing ratios. It detects particles and then using a model the ice mixing ratios are inferred… maybe ‘..which can be used to infer ice mixing ratios (Avery et al., 2012).
Fig. 4 caption, although way too long, was actually readable.
How does the aircraft temperatures compare with ERA5. The type B trajectories will encounter ERA5 temperatures, if these temperatures are too warm and you are downstream from the coldest temperature, then you might see a bias. Can you validate these temperatures against GNSS-RO?
How do you account for the vertical averaging kernel in the MLS measurements?
Line 100 Schoeberl and Dessler used forward trajectories.
I think some explanation on what is done with full trajectories is needed. Does the full start at the measurement point and go backward X days, or – like Ueyama et al. (2023) does it terminate at convection?
Line 111 ‘highest ice concentration found mainly at southern edge.’ Where the temperatures are coldest according to Fig. 4.. might want to point that out.
Line 117 … vertical sampling resolution than CALIPSO
Line 124 ‘ are not able to freeze out the excess water’ … assuming the temperatures from ERA5 are correct and there are no gravity waves. How much colder would the temperatures have to be to get the right water vapor? I suspect only a couple degrees…
Line 126.. I am confused about the backward trajectories. Presumably you start with the aircraft measurement of water and you go backward in time to get a temperature field.
Then starting with a saturated parcel at the furthest back time where it has encountered convection, you dehydrate and arrive at the predicted measurement. Do the two values of water agree? I am wondering if the instrument measured air might be wet biased. Do they agree with MLS? I think that this weird Type B bias needs more discussion as to possible sources of error.
I would delete Fig. 5. I found it confusing and not helpful.
Citation: https://doi.org/10.5194/egusphere-2023-498-RC1
Paul Konopka et al.
Paul Konopka et al.
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