General Comments:

In this work, Differential optical absorption spectroscopy (DOAS) technique is applied to TROPOMI data to obtain OClO Slant column densities (SCDs), for Arctic and Antarctic latitudes, from November 2017 until October 2020. These SCDs have been also compared with meteorological data from the ECMWF model (temperature and potential vorticity) and CALIOP PSCs observations. Through this study, the temporal and spatial evolution of the OClO SCDs can be examined, as well as the correlation with the studied parameters, allowing also identifying possible causes of chlorine activation. A comparison between both hemispheres has also been presented, and some interesting unusual episodes concerning formation, development or deactivation of polar vortex have been studied.

The research performed in this work has been clearly presented and explained and represents useful information for the Atmospheric science community. Thus, I think that this paper should be published in ACP. However, I think that some questions should be clarified.

Specific Comments

• Has some cloud-screening been applied to the DOAS data? Could tropospheric clouds have a significate impact in the presented DOAS measurements?

• Page 5, lines 133-135: Most of the information provided by the DOAS measurements come from air mases located at certain altitude and distance from the observation point, depending on the geometry of observation, Solar zenith angle, etc.. Has been this taken into account in the comparison between the TROPOMI and the ECMWF or CALIPSO data? Is this what you mean when talking about the multilinear interpolation? Do you use a spherical radiative transfer model to do so?

• Second panel from top of figure 2 and similar figures: Just as suggestion, the colour scale of these colour maps are contrary to the rest of the panels of these figures (red means low values of PV and blue means high values). Perhaps, using similar colours scale for all the panels would be more visually intuitive.

• Figures using “Longitude” as Y axis: even if positive and negative values of longitude are usually assigned to East and West longitudes, respectively, this should be clarified somewhere in the figure captions or in the text.

• Page 12, line 211 and page 13, line 212: The provided longitude values correspond to East longitudes instead West longitudes, Is it right?

• Page 16, line 242: The provided OClO SDCs values include also those below the detection limit?

• Page 28, lines 407-409: The commented exceptional OClO increase could be related to aerosols, as commented previously by the authors (page 3, line 59)?

Technical Corrections:

• Some sentences are too long. I think some “,” should be introduced. As example: Page 2, lines 29-31; Page 6, line 166: “For the comparison, ..”; Page 6, line 169: “In addition, ..”; Page 6, line 166: “For this winter, ..”; etc.
• Page 4, line 113: Introduce the meaning of the ECMWF acronym.
• Page 5, line 135: “..19.5 km of altitude”.
• Page 5, line 137: “..The obtained correlative dataset..”.

In this paper, the new TROPOMI OClO slant column density (SCD) product developed by the MPIC group is compared to meteorological data for both Antarctic and Arctic regions for the first three winters of the S-5p satellite mission (November 2017–October 2020). A good qualitative correlation is generally obtained in both hemispheres between the OClO SCD and the selected meteorological parameters, namely the minimum polar hemispheric temperature, the polar vortex area, and the area where air temperature is below the temperature of nitric acid trihydrate (NAT) PSC particles formation. In addition, the TROPOMI OClO SCDs are also found to coincide well with PSC observations from the CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) PSC observations. The various high OClO level periods observed in both Northern and Southern polar winters are discussed in terms of polar vortex activation and deactivation processes and stability.

This study fits well with the scope of ACP. Moreover, the manuscript is clearly structured and the method and results are generally presented and discussed in an appropriate and balanced way. Therefore I recommend the paper for publication in ACP after addressing the following comments:

General comment: This is a suggestion for a future study rather than a comment to address here but it would be interesting to include also the TROPOMI BrO and O₃ column data sets in the loop. Comparing those data sets with the presented OClO and PSC observations and meteorological parameters could provide a unique opportunity to investigate the relationship between halogens activation, stratospheric ozone depletion and meteorological conditions during the last three winters, especially in the Northern polar region where the polar vortex can be highly variable.

Specific comments:

Page 2, line 46: Maybe you should give the typical solar zenith angle threshold value above which the OClO abundance can be detected from passive DOAS measurements. A number for the detection limit (in molec/cm2) should be also given here.

Page 4, lines 93-97: Did you apply any filtering on cloudy pixels in the construction of your OClO SCD gridded product? Since the OClO formation is enhanced in the presence of PSCs, how the latter can influence the quality of your OClO retrieval? Please elaborate.

Page 4, line 120: The SZA range (89-90°) used for the selection of OClO SCD should be better justified. Did you test other SZA ranges since both the altitude of the air mass probed by the TROPOMI sensor and the altitude of the maximum OClO concentration peak depend on the SZA?

Page 5, lines 135-137: In order to select meteorological quantities, it is assumed that the retrieved OClO SCDs are mostly sensitive to the 475K potential temperature level, which corresponds roughly to an altitude of 19-20km. How far this assumption is valid? It needs also to be better justified.

Technical corrections:

Page 4, line 91: ‘coveradge’ -> ‘coverage’

Some sentences are very long and difficult to follow (e.g. first sentence of Section 3, page 5).

The color bar scale values of the subplot stratospheric T – T_NAT (3^rd subplot from the top) in figures 4, 7, 10, and 13 are difficult to read.