The authors use observed cloud properties and precipitation events in conjunction with airmass back trajectories to explore the effect that a Finnish boreal forest has on aerosol-cloud interactions, which are a key, potentially cooling, process in the climate system.

This is a nicely conceived study that builds well on Petäjä et al (2022), presenting a wider range climate/weather variables and characteristics and supporting previous work on the importance of northern high latitude forests to the climate system. The analysis uses a long time series (11 years) of meteorological and satellite data, and focuses on air masses from the N and W which pass over only boreal forest between the Scandanavian coast and Hyytiälä. The conclusions are relatively robust and relevant, although I have one or two comments about their choice of how to bin the data. Overall this study re-emphasises the importance of boreal forests for future cloud nucleation and hence climate cooling.

I recommend the manuscript be accepted subject to minor revisions to address my concerns, outlined below.

Abstract:

Would benefit from the inclusion of some quantities to make the scale of the issue more apparent.

Introduction:

The same is true of the first 3 paragraphs of the Introduction which are highly generalised “accepted truths” rather than hard facts and figures.

L40-45: please quantify the proportion of the Earth system’s carbon, water and energy cycles that flow through boreal forests.

L46-47: please give a few examples of positive and negative feedbacks associated with forest-atmosphere exchange processes

L50-52: Estimates of the potential changes in C sink would be useful for context

L54-57: Estimated range of changes in surface T as a result of changes in albedo?

L59: How “significant” a source - please quantify and put in context

L63: What is the estimated emission rate of BVOCs, and monoterpenes in particular, from boreal ecosystems and how does this compare with total global emissions?

L64-65: What does “comparatively potent” mean? Please give some values (atmospheric lifetimes, secondary organic aerosol formation potential, etc) for major monoterpene species.

L68: Can you give a relative increase in emissions for (say) a 2˚ or a 5˚C rise in surface temperature?

L84-89: Can the authors give the current best estimate for increases in boreal biomass and BVOC emissions under future climate scenarios?

L112-114: While I appreciate there is considerable uncertainty, it would still be good for the authors to give the range of possible values of cloud fractional cover between forested and open ground and between the seasons.

L119: Specifically which properties will the authors focus on?

Methods:

L131: It would be useful if the authors could mark this site on the biome map in Fig.1

L135-137: Would it not have been of interest to see how properties of air masses with the same origin, and hence residence time over the forest, differed due solely to presence or lack of biogenic activity?

L144-145: Why were these temporal and spatial resolutions used?

L157: How large might the variation in error between trajectories be?

L159-161: How many trajectories were analysed in total over the 11-year period? Given that this is already being reduced by the selection criteria, i.e. that it must lie 90% or more within the NW quadrant, I would suggest that the authors may need to carry out an uncertainty assessment to ensure the sample size is sufficiently large to reliably draw conclusions.

L170 (Fig. 1): Appears to show large tracts of “grassland” in the NW sector - is this the case? If so, it suggests that ToL is substantially over-estimating the time air masses spend above forest biomes, and that this “error” would be heavily dependent on precise air  mass direction of travel.

L179: Why use median values rather than mean?

L183-186: It is not clear where these instruments were located. Were they also deployed on the tower at the SMEAR II station?

L212:How minor was this fraction? It seems that the authors have now listed such a multitude of reasons for data to be discarded that there must have been periods with very little useable data remaining in the dataset. It would be instructive to know how many observations / trajectories were analysed for each year, origin, etc and what fraction of the possible maximum number of observations this represents.

L217-219: How were the bins selected for each of the variables? Were the bins of equal length, equal number of observations, categorised by some other means (e.g. for temperature whether it was cold, average, warm or heatwave)?

L254-262: On what basis have the authors selected the number concentrations for each of the 4 bins? Why choose 1400, 2200, etc? (I think this might be included in the caption for Fig 3 but should also be in the text)

L272-274: On what have the authors based their assertion that the fractions become relatively stable. It is not apparent from Fig 3 why not e.g. 50, 40, … Have the authors carried out rigorous statistical analysis to test this?

L285-288: Again, it is not immediately apparent from Fig. 4 why the authors should select 20 and 60 hours as the transition times - it appears it would be equally valid to select 25 and 75. How were the two limiting times determined? By eye or statistically?

L302-303: Is this how the value of 60 hours was selected? That 95% of air masses have Nccn > lowest values? Still not clear from either the text or the figure (Fig 5 now).

L318-329: Same as before - how have the authors selected the values of q, T and RH to use as the end points of the bins? How have they ensured self-consistency between binning of these related variables?

L335: Yes, although Figure 2 also showed that August had the greatest variability in ToL.

L366-367: Do the authors mean, the number of trajectories varies on any given day? Or the number of satellite overpasses? If the latter surely the authors could rank satellite products by coverage, reliability, etc and work hierarchically through them, i.e. ensuring there is not a time with >1 retrieval? Without this, surely they place too much emphasis on the meteorological and cloud conditions on those days in comparison to other cloudy days.

L390-392: Can the authors suggest how this might be done? Are they suggesting a similar approach but with a more rigorous or e.g. machine learning-based scrutiny of cloud retrievals? Or are they calling for ground-based observations of cloud fraction and thickness? The latter might, in particular, be a useful approach for discounting frontal clouds.

Fig. 9: It’s not apparent that there is a break in the y-axis of either panel

Fig. 9: What do the authors mean by “predefined”? Based on what criteria? And why was this not similarly done for all binning?

L468-470: Again, in-situ observations would help to clarify why there appears to be a break-down in the relationship at very high specific humidity.

Fig. 11: While (a) does appear to support the hypothesis that higher specific humidity triggers high precipitation in the following hour, it would be useful to know why that only appears to be the case up to a specific humidity of 9g/kg. There seems no obvious reason why mean 1-hour precipitation should fall above this value. It could equally be the case that the 3 points between 8 and 9g/kg are outliers …

Fig. 11: By contrast, panel (b) does not appear to show any robust trend whatsoever. Why have the authors included this in their analysis?

Conclusions:

L507-509: Presumably this is only the case for the very specific case of air masses travelling from the NW sector over Fennoscandia to arrive at Hyytiälä rather than being true for all locations?

L512-515: What are the implications of forest interactions not having had time to take their full effect?

L520-522: It’s really not clear how the authors’ analysis and conclusions could be considered in forestry practices or plans for reforestation. How would they envisage policy-makers and practitioners making use of the information and data presented here?

Review of the paper “Dynamics of aerosol, humidity, and clouds in air masses travelling

over Fennoscandian boreal forests” (ACP 2022-264) by Meri Räty et al.

The paper describes changes of aerosol properties, humidity and cloud properties that appear in originally clean marine air masses when they are transported over boreal forests in Scandinavia. The properties of the air masses under investigation stem from long-term observations with high quality instruments in Hyytiälä, Finland, as well as from MODIS satellite observations. The selection and differentiation of the large set of air masses is done based on back-trajectories calculated with the HYSPLIT model.

The study is of interest to the ACP readership and it is generally well presented. However, there are major questions about the findings related to water vapour and clouds and about the presented calculation of the “Time over Land (ToL)”. Although this concept was used before in another publication (Petäjä, 2022), it needs to be clarified to what extent the given ToL really represents the time in which interactions between emissions from forests and the air mass finally analysed took place. A re-calculation of ToL may require a potentially time consuming new analysis of the data set. I recommend that the paper may be published after major revisions. This will also require that the authors either clarify my major concerns or that they re-evaluate their data set.

Major comments:

Introduction: It remains unclear how the fact that the forest’s properties are potentially changing with climate change is related to your study. This may of course be a motivation, but it is written in way that the reader expects new insights about changes in the air masses under investigation throughout the 11 years period that you look at.

Line 96-98: I am irritated with this description of “recycled water”. This is simply part of the global water cycle and both, evaporation from water surfaces like oceans and lakes, as well as evapotranspiration over land contribute to precipitation over continents.

Line 138 – 165: You describe the “time over land” as the time a backward trajectory that arrivies at Hyytiälä was at a geographical location that is somewhere over the land areas given in Figure 1. In addition, you assume that there will be some type of forest growing on this land surface and that this interacted with the air mass before it was characterised by the observations performed at (or over) Hyytiälä. Despite the fact that the type of forest/trees that various air masses with similar ToL may have been in contact with will be very different, this interaction will only take place when the air mass did not travel in high altitudes. If the air mass travelled well above the planetary boundary layer, it is not likely that significant impacts of the underlying forest will be visible. Therefore, your ToL analysis may be better based on “time over land within the PBL” if you want to draw conclusion out of potential air mass modifications.

Line 168: Figure 1 does not demonstrate convincingly that there is enough forest existing in Fennoscandinavia to support your assumption that there is an influence of tree emissions on an air mass when the trajectory is over land.

Line 195-211: As you explain, cloud fraction can be related to any type of cloud, not necessarily to low level clouds, only, for which a modification of their properties through aerosol particles observed at ground level can be expected. This might have a strong impact on your analysis that is not discussed. You might also try to get additional information on the height of the clouds and restrict your data set to low level clouds.

Line 195-211: Please give more details on the MODIS Level-2 Cloud Product. When is the overpass? Is this the “main time window” mentioned? What is the spatial resolution of individual cloud pixels? Some of the informations is given later but it should be presented here.

Line 254 (and in the following figures 3, 5, 6, 8, 9): On which basis do you define these 4 groups? Why don’t you use median values and percentiles for each ToL bin?

Line 318-329: In my opinion, you cannot conclude that air masses with longer ToL have higher specific humidity (q) because you most likely only see a temperature effect, with warmer air masses having higher saturation pressures. You discuss this, but still I think that you should avoid giving the impression that there is a causal relationship between ToL and q. This is also supported by the fact that you do not see a clear relationship with RH. In the analysis of the temperature dependence on ToL you also mix effects of seasonality with weather patterns and you neglect effects of vertical air mass transport.

Figure 6: It remains unclear why you reduce the bin size to 1 h.

Figure 7: What can I learn from this figure? It just shows the Clausius Clapeyron equation and that relative humidities cover a wide range at a given temperature.

Line 370: “A modest increase seems to occur after ToL exceeds approximately 50 hours.”: You should check whether these differences are statistically significant.

Section 3.3: It looks like your analysis of COT and CF does not reveal any dependence on ToL: This might be connected with the relatively low number of cases that you could analyse, but it may also be related to the fact that you mix all types of clouds.

Section 3.4: Again, you should check whether the differences you see are statistically significant. In addition, one would expect that ToL mainly reflects different weather patterns and is not a variable that can explain the amount of rainfall observed at Hyytiälä.

Line 442 – 450 and Figure 10: In my opinion, you again see mainly the dependence of water vapour saturation pressure (and therefore q, CWT and also precipitation rate) on temperature. It is misleading when you try to explain differences in arriving air masses with ToL.

Line 473/474: This sentence is obscure and needs to be rephrased. Nevertheless, I think it correctly says what you see and the ToL analysis that you put on top of it does not reveal new insights or links with the aerosol size distribution that you want to demonstrate (according to the introduction).

Line 501 – 504: I cannot see where you showed a link between cloud reflectance and CCN in your study.

Minor comments

Line 43: the forest

Line 60/61: “climatically relevant sizes” is a not well defined expression. Please rephrase.

Line 65: which VOCS do you have in mind when you mention “other common BVOCs”? Please add examples.

Line 72-74: “While not exclusive …“. This sentence is unclear. Please explain in a different way what you want to say.

Line 80: correct „potentiantially“

Line 85: correct „photosynthesising“

Line 237: I assume this is from 1 April to 30 September. You should exactly specify this.

Line 269: remove “s”.

Line 286: rephrase “until a seemingly balanced is reached”.

Line 305 appear to be

Line 366: “The number of successful daily observations also varies slightly, which may also lead to some days having better representation than others.”: It remains unclear what you want to say.

Line 368: is shown

Line 470: omit the first “was”

Line 509: established