Please see attached review.

In this paper, time-series of stratospheric and mesospheric ozone and water vapor profiles observed from the high-latitude station Ny Alesund with the two ground-based Microwave (MW) radiometers MIAWARA-C and GROMOS-C are discussed. Time-series and climatologies are compared against MLS/AURA satellite observations and MERRA-2 reanalysis data, and the annual and interannual variability is discussed for Ny Alesund based on all three data-sets, and for a “conjugate station” at high SH latitudes based on MLS and MERRA-2 data. Ascending and descending rates in summer respectively winter are derived for the NH from the ground-based MW observations and MLS, for the SH for MLS only. MLS and the ground-based instruments agree very well, both regarding the absolute values up to the mid-mesosphere and the day-to-day variability, while MERRA-2 shows systematic differences to both the ground-based MW observations and MLS in the mesosphere, and to MLS in the SH lower stratospheric ozone hole area. However, considering the low vertical resolution of the ground-based MW observations, it might be more appropriate to degrade MLS and MERRA-2 data to the vertical resolution of MIAWARA-C respectively GROMOS-C before computing the relative differences. However, the good agreement with MLS data demonstrates a high quality of the MIAWARA-C and GROMOS-C instruments, and ground-based observations like these will be of increasing importance in the near future when the last remaining satellite limb observing instruments have reached the end of their lifetime, to continue long-term time-series at least locally, to constraint models like MERRA-2, and hopefully to provide a connection to future limb satellite missions, though the only limb sounder mission that I know of with a coverage comparable to MLS is the Earth Explorer 11 candidate mission CAIRT, with EE11 expected to launch in the early 2030s. In this sense, the presentation of the MIAWARA-C and GROMOS-C data, their evaluation against MLS, and discussion of properties derivable from these data, are very valid and important results adequate for publication in ACP (or AMT).

However, in its current stage, it was not clear to me what the main focus of the paper is – evaluation of the data, derivation of stratospheric annual and interannual variability, interhemispheric differences? – as all these aspects are somewhat mixed together. In my opinion, the paper could become much more clear and concise by restructuring it in such a way that the different aspects are clearly separated. As the evaluation of the MIAWARA-C and GROMOS-C data is an important prerequisite for using them to derive annual/interannual and interhemispheric variabilities, this should be discussed first. Results concerning the interhemispheric differences in the dynamical variability of the stratosphere mainly confirm previous results; what is new here is the instruments used, as well as the concise derivation of descent and ascent rates in both hemispheres from the climatological annual variation of H2O. This is an interesting comparison, though I don’t really follow the argument that this is evidence for interhemispheric coupling; this point needs a more detailed explanation.

A few minor issues are listed below.    

Abstract: state altitude / pressure range of investigation, as well as time-period (2015-2021?) and the vertical range and times of year over which the descent/ascent ranges have been determined.

Line 37: The meridional transport of trace gases into the polar cap is controlled by the strength of the polar vortex …. Add: during polar winter.

Sentences in lines 69-70 and 70-71 have partly redundant information, and could be shortened accordingly.

Line 74-76: please clarify in this sentence that MLS data are used to provide the observations for the conjugate station.

Sections 2.1, 2.2, 2.3: Instrument descriptions: please add from when to when data are available, as well as the instruments precision/noise error, to the descriptions of GROMOS-C, MIAWARA-C, and MLS

Section 2.4, MERRA-2 description: please add description how ozone and water vapor information is derived within MERRA-2. Data assimilation (which altitudes), photochemical model (how detailed)? This information is important to understand the deficiencies of MERRA-2 compared to the observations shown in later sections, and should already be provided here.

Line 154: Fig. 2 shows that the ozone VMR starts to increase …

Lines 163-164: this sentence appears to end in the middle

Lines 164-165, 169-170: I think these details about ozone in the MERRA-2 dataset should be presented in the description of MERRA-2 in Section 2.3 already. That would make the argument here more simple – it seems to be a known and well understood bias in MERRA (at least it is consistent with what I would expect from a model that uses a simplified stratospheric chemistry scheme in the mesosphere).

172-173: below 1 hPa. If you look closely, you will note that the annual variation in MERRA-2 ozone is significantly different from the observed variation throughout the mesosphere above 1 hPa.

Line 189-190: erase either the captured, or the agrees

Line 202-213, discussion of ozone and water vapor at conjugate latitudes: the differences in the stratospheric dynamics between NH and SH and its impact on stratospheric ozone is fairly well known, and well understood. I see two take-away messages from figures 4 and 5: (1) while MERRA-2 generally does a good job in reproducing the variability of stratospheric ozone and water vapor, it fails in the mesosphere as discussed in previous sections, and also underestimates the vertical extent of the ozone hole, which appears to end at lower altitudes (larger pressures) in MERRA-2 than in MLS. This is reflected also in water vapor, where MERRA-2 fails to reproduce the vertical layering (e.g. July 2015 or July 2017), and appears to underestimate the area of dehydration. (2) The detailed information about the SH winter as shown here for the “conjugate station” will be lost after the end of the last three limb sounders still observing (MLS/AURA, SABER, SMR/ODIN), while for the NH, information will hopefully continue to be available from ground-based MW observations.

Lines 217-218: It is important … I do agree with this sentence. However, this evaluation of GROMOS-C and MIAWARA-C should be discussed much earlier in the paper, before the annual/interannual variability and descent rates are discussed.

Sections 4.1, 4.2, and 4.3: In general, it would be beneficial to clearly separate the evaluation of the MW data from the data analysis, and to discuss the evaluation first. That is, first discuss the climatologies and their relative differences in the NH, where MW observations are available. Discuss the difference between NH and SH in the next section, then the time-series, and finally the descent rates.

Section 4.3, discussion of Figure 10: is it possible that some of the differences are due to the low vertical resolution of the groundbased MW instruments? That is, could the agreement between MLS and GROMOS/MIAWARA be even better if the MLS data were convolved to the vertical resolution of the GROMOS/MIAWARA observations, e.g., by applying a convolution with the averaging kernels?

Lines 372-375: I don’t really understand the reasoning here. My understanding of the interhemispheric coupling (based mainly on Körnich and Becker, 2010) is that disturbances are transmitted from the winter stratosphere to the summer mesosphere in the other hemisphere; so a high variability in NH winter downwelling would imply a high variability of SH summer upwelling, which is indeed observed; but also a low variability in the SH winter downwelling would imply a low variability of the NH summer upwelling, however, the converse is observed. I’d say the issue of interhemispheric coupling and how your results relate to that, needs a bit more explanation / discussion.

Line 378: that results in both what?