The paper by Franco-Diaz et al. is an interesting study that combines lidar observations of gravity waves at Kuhlungsborn with NASA's AIRS satellite observations of deep convective clouds in one infrared channel and observations of gravity waves in another infrared channel. The focus of the paper are convective events during summer upstream of Kuhlungsborn that excite gravity waves propagating downstream over Kuhlungsborn. One main finding is that for several strong convective events convective gravity waves are seen at the same time by both the lidar and AIRS although the observational filters of the two instruments are very different. This supports the assumption that convective sources emit a broader spectrum of gravity waves. The authors suggest that sporadic strong events of convective gravity waves should still be important for middle atmosphere dynamics because midlatitude gravity wave activity during summer is quite weak and the events are much stronger than the monthly average gravity wave activity.

Overall, the paper is well written, the figures are adequate, and the topic is of great interest for the readership of ACP. The paper is therefore recommended for publication in ACP after addressing my minor comments.

Main comments are:

(1) There is some confusion about the AIRS observational filter. Please check the paper for consistency and refer to existing literature.

(2) Some readers may be confused by introducing an area for identifying deep convective clouds far upstream of Kuhlungsborn. Therefore some more reasoning should be given earlier in the paper why this selection is made.

Specific Comments:

(1) l.5 Here you just write "using ECMWF". Which product? analyses, forecasts, reanalyses?

(2) l.36: The reference Marlton et al. (2021) is about the effect of assimilating observations in general - not about convective gravity waves. You should at least add one or two papers showing the importance of convective gravity waves, for example Kim et al. (2013) and Bushell et al. (2015).

Kim, Y.-H., A. C. Bushell, D. R. Jackson, and H.-Y. Chun (2013), Impacts of introducing a convective gravity-wave parameterization upon the QBO in the Met Office Unified Model, Geophys. Res. Lett., 40, 1873-1877, doi:10.1002/grl.50353.

Bushell, A. C., Butchart, N., Derbyshire, S. H., Jackson, D. R., Shutts, G. J., Vosper, S. B., and Webster, S.: Parameterized gravity wave momentum fluxes from sources related to convection and large-scale precipitation processes in a global atmosphere model, J. Atmos. Sci., 72, 4349-4371, 2015.

(3) l.64: Here you should add more references to previous work about arc-shaped gravity wave patterns. For example, Gong et al. (2015) performed a global survey of concentric gravity waves seen by AIRS, showing that such patterns occur at midlatitudes. Another example is Ern et al. (2022). In this study an arc-shaped gravity wave pattern is related via backward raytracing to deep convection and latent heat release caused by the 2022 Tonga volcanic eruption.

Gong, J., J. Yue, and D. L. Wu (2015), Global survey of concentric gravity waves in AIRS images and ECMWF analysis, J. Geophys. Res. Atmos., 120, 2210-2228, doi:10.1002/2014JD022527.

Ern, M., Hoffmann, L., Rhode, S., & Preusse, P. (2022). The mesoscale gravity wave response to the 2022 Tonga volcanic eruption: AIRS and MLS satellite observations and source backtracing. Geophysical Research Letters, 49, e2022GL098626. https://doi.org/10.1029/2022GL098626.

(4) l.96: The sensitivity of the AIRS 4mu channels is rather Lz>30km than Lz>15km, see Fig.3d in Hoffmann and Alexander (2009). Further, the number of 15km does not match with the 26km given in your Fig.1. Please check for consistency!

(5) l.100: You should point out the importance of using observed deep convective clouds. As has been shown by Aumann et al. (2023) deep convective clouds in meteorological forecasts, for example the ECMWF IFS, are less reliable.

Aumann, H. H., Wilson, R. C., Geer, A., Huang, X., Chen, X., DeSouza-Machado, S., and Liu, X.: Global Evaluation of the Fidelity of Clouds in the ECMWF Integrated Forecast System, Earth and Space Science, doi:10.1029/2022EA002652, 2023.

(6) l.131/132: "corresponds to ~500km" - not clear what this means! Please be more specific!

By subtracting a 4th-order across-track polynomial, horizontal wavelengths in the approximate range 30km to 1000km should be still in the AIRS data. An approximate sensitivity function is given, for example, in Meyer et al. (2018), Fig. 3a.

This sensitivity function applies to retrieved temperatures. Therefore the magnitude of the sensitivity for brightness temperatures will be quite different, but relative variations in the horizontal wavelength direction should be similar because a 4th order polynomial was applied in both cases. At short horizontal wavelengths the sensitivity is limited by the size of the AIRS footprints.

Meyer, C. I., Ern, M., Hoffmann, L., Trinh, Q. T., and Alexander, M. J.: Intercomparison of AIRS and HIRDLS stratospheric gravity wave observations, Atmos. Meas. Tech., 11, 215-232, https://doi.org/10.5194/amt-11-215-2018, 2018.

(7) Fig.1: Where do the approximate sensitivity ranges for AIRS come from? Are they adapted from Fig.3d in Hoffmann and Alexander (2009)?

(8) l.141: Again, the 15km apply rather to the AIRS 15mu channels than to the 4mu channels (see Fig.3 in Hoffmann and Alexander (2009)). Further, the number of 15km is inconsistent with your Fig.1

(9) l.171: Another reason why selecting a region west of Kuhlungsborn for detecting deep convective clouds makes sense is because gravity waves will propagate radially away from the convective center. However, only the gravity wave structures that propagate opposite to the prevailing stratospheric westward wind (during summer) will become visible for AIRS because their vertical wavelengths are refracted towards larger values by Doppler-shifting.

(10) l.176: Your sentence reads as if two filters are applied simultaneously, which I think is not the case. Suggestion:

using a fifth-order Butterworth filter with a vertical cut-off frequency of 15 km (Baumgarten et al., 2017) and a temporal cut-off

->

using either a fifth-order Butterworth filter with a vertical cut-off frequency of 15 km (Baumgarten et al., 2017), or a temporal cut-off

(11) l.196: As can be seen from Fig.4, major peaks in the lidar data can be separated by up to three days (not by just one day as stated in l.196). Please comment!

(12) l.197: Here you write "vicinity of Kuhlungsborn", which is a bit misleading. Better refer to the area given by the black rectangle in Fig.2!

(13) l.206: Could it also be that convection outside the black rectangle could have caused the gravity waves?

Please note that even for the wave event on 03 July 2015 Kuhlungsborn is just at the edge of the wave pattern seen by AIRS (see Fig.5).

(14) l.207: Again, "around Kuhlungsborn" may be misleading! Please refer to the black rectangle!

(15) l.250/251: longer than ~30km for the 4mu channels

(16) l.255: Please cite also the earlier work by Salby and Garcia (1987) who introduced the depth of the heating concept:

Salby, M. L. and Garcia, R. R.: Transient response to localized episodic heating in the tropics, Part I: Excitation and short-time near-field behavior, J. Atmos. Sci., 44, 458-498, 1987.

(17) l.278: A recent climatology of gravity wave intermittency is given in Ern et al. (2022). In this paper it is shown that the gravity wave distribution in the summer hemisphere is even more intermittent than in the tropics, which supports your findings of sporadically occurring strong convective gravity waves at midlatitudes during summer.

Ern, M., Preusse, P., and Riese, M.: Intermittency of gravity wave potential energies and absolute momentum fluxes derived from infrared limb sounding satellite observations, Atmos. Chem. Phys., 22, 15093-15133, https://doi.org/10.5194/acp-22-15093-2022, 2022.

(18) l.284: Another point worthwhile mentioning is that stratospheric winds are relatively weak when the wave events are detected. Orographic gravity waves should therefore have relatively short vertical wavelengths and should therefore be invisible for AIRS. The same should hold for the jet-generated gravity waves as you mention later. For orographic gravity waves there may even exist critical wind layers at midlatitudes during summer.

Technical Comments:

l.111: systems -> system

Fig.1: sensitivity for AIRS should read Lz ">" ~26km  (not "<" 26km)

l.158: tropopause -> tropopause region ???

l.185: ???

kernel function, which has a broad peak.

->

kernel function has a broad peak.

Fig.4, lower panels: Ocurrence -> Occurrence

l.243: under the threshold -> below the threshold

Fig.A3, y-axis: Ocurrence -> Occurrence

l.349: filtermethods -> filter methods

l.406/407: Title of this paper is not correct, please check!

This manuscript by Franco-Diaz investigates convective gravity wave effects over northern Europe using data from NASA's AIRS satellite instrument, a Rayleigh-Mie radar at Kuhlungsborn, and supporting data from ECMWF operational data.

The manuscript is well-written, clear and quite an easy read, but makes interesting and well-evidenced points, showing some nice case studies. I therefore echo Reviewer 1 in their recommendation that only minor corrections are needed for publication in ACP. In particular, the paper was well-structured, the figures well-chosen, and in general most questions I thought of while reading were answered within a couple of sentences at most.

I include a series of minor comments below. I also strongly echo the comments of Reviewer 1, particularly their comments:

(1) about consistency in the description of AIRS' observational capabilities - for example, lines 95, 131, and 140 disagree on the horizontal-wavelength sensitivity of the products used, while (as reviewer 1 says) line 96 disagrees with other parts about vertical sensitivity.

and (10) about filters, as I also read it the same way

In addition, I would recommend/ask that the authors:

(A) be much more specific about the ECMWF data used, particularly in the abstract where the description given ("using ECMWF") is really quite undescriptive! Reviewer 1 asks for more details of the dataset; I would also like the authors to check that they really mean ECMWF *forecast* data as they say on line 119 - do they mean operational *analysis* data? Using the operational analysis, i.e. ECMWF's best-guess of the atmospheric state, would make perfect sense, while forecast data, which is generated by running the model forward from the analysis, would be a somewhat esoteric option to use for a study like this.

(B) in general, the paper does not reference many other studies which have looked at the same gravity waves in multiple datasets. Discussing  a few of these in the introduction could be useful to contextualise the observational filter differences you see - I would naturally recommend our 2016 paper on orographic waves (https://amt.copernicus.org/articles/9/877/2016/amt-9-877-2016-discussion.html), but studies by many others are of course available on the same topic.

(C) does the 8-hour limit cutoff a chunk of permitted GW periods at this latitude? Presumably, going by the text, the 8h cutoff is chosen to avoid the mesospheric terdiurnal tide impacting the results, but in the 33-43km part of the stratosphere this isn't a major concern as it's so weak in temperature amplitude this far down in the atmosphere

Some additional minor comments follow, but in general I think this is a very good paper and in my view is publishable in something very close to its current form. Good work!

Additional comments:

014 dimensions unclear - should specify these are horizontal wavelengths

018 and also unresolved

077 and afterwards - Aqua is a name, not an acronym, so shouldn't be all-caps

079: would "at least two" work better here?

085: the track-edge value would be useful as it is quite a bit lower (~40km)

089: how is the product "special"? This is quite a vague way of describing the dataset. 

093: I *think* (but a happy to be corrected) that the 4poly method needs referencing to Alexander + Barnet 2003 (JAS)

098: brackets missing from ref

101: what do you mean by "atmosphere" here? Couldn't one say that the clouds you're measuring are part of the atmosphere, just a wetter part?

108: Can MST radar do this?

118: what does "integrated" mean in this context?

Figure 1 implies hard edges, but they're quite fuzzy. Not sure how to fix it this easily, but it might be worth a think. My own papers can be just as bad though on this...

144: The transition from the case study in lines 139-144 to a more statistical study from line 144 onwards is very abrupt, and needs delineating more clearly

145: "as a function of time-averaged over an area" is ungrammatical

Figure 2: a colourbar for the inset would be very useful

183: how long a temporal average? Could affect the results.

206: they are *likely* to be related...

208: that's a very precise height level - is it actually a pressure level? If so might be clearer to specify that, with the height approxn in brackets afterwards, eg something like "10hPa (~16km)". Same comment for line 209.