The paper “Sensitivity of land-atmosphere coupling strength to perturbations of early-morning temperature and moisture profiles in the European summer” explores the uncertainty of classifying land-atmosphere interactions using the CTP-HI framework by systematically perturbing the temperature and moisture profiles from a regional climate model and then analyzing how the coupling classification changes. The paper is well written and has a logical organization that makes it easy to follow. The experiment design is interesting and the results provide new insights into the coupling between the land and the atmosphere for this particular model. Based on this, the paper is well suited for Earth System Dynamics and merits publication. Despite these positive aspects, the paper is not particularly clear in defining the larger research question and discussing the results in a way that is consistent with the work being done. Based on this, three suggestions for improvement are given below.

First, it is difficult to know how much to trust the results of this paper since the analysis is based on a regional climate model that may have its own set of biases that will skew the results from the coupling classification. As applied here, the CTP-HI classification is fixed and therefore, a model with a consistent bias in the atmospheric profiles will give skewed results. This climatological inconsistency in the CTP-HI framework for some data sets was shown in Ferguson and Wood (2011) and was the reason for developing a data set specific method of classifying the CTP-HI space (Roundy et al. 2013). One possible way of addressing this limitation is to compare the surface temperature and humidity from the model to observations. This would at least provide a means of assessing where the model is biased and may provide insights into the results such as why are there very few dry soil advantage days in the model (Figures 6 and 7). Regardless of what is done to address this, there needs to be a clearer discussion that the results in this paper are model specific and may or may not represent the real world.

Second, on first reading the title and abstract, I thought this was more of a modeling study where the model was perturbed and then run like the original Findell paper. However, this work does not actually do any new model runs, nor does it actually look at coupled model processes within the model and could just as easily be applied to a reanalysis data set which would have the added benefit of having assimilated observations. This does not dimension the results but begs the question as to why a regional model run is used in the analysis as opposed to reanalysis? Why not do both and compare them? At a minimum, revising the title and abstract so that it better reflects the work done would be beneficial. In my opinion, this work is interesting because it is answering the question of what happens to the coupling if there is a change in temperature or moisture? It would be great to see the title and abstract reflect this.

Third, on a whole the results are fairly predictable in that if you change the temperature and humidity profiles then you will change the calculated CTP-HI, which will then change coupling classification for that particular day. This means that areas that will be most affected will be those that lie on the boundaries between the strict classification thresholds. So what is really being analyzed in this work is what regions are most often on the boarder of the classification regimes and what kind of perturbations will bump them into the other regime. This is not to say that work is not meaningful, but I think it would greatly improve the paper by discussing this simple idea extensively in the introduction to help better setup the results.

In addition, below are several minor suggestions for improving the paper.

Lines 74-75: The CTP-HI framework has been applied using satellite data and has given reasonable results (Roundy and Santanello 2017).

Line 123: Consider revising to “but may limit the investigation of pre-conditioning”

Lines 310 and 332: There are a couple instances of using the word chapter in the paper. For this kind of paper, “section” would be better.

Line 352: The figure caption needs more detail here. Is this the average for the entire domain or just part of it?

Line 386: Precipitation is not really validated in this work. This may be true if one assumes that the Findell et al. framework holds for the model used in this study, but no analysis is given to show this. It is probably best to avoid making the jump to precipitation and just stick with the classification.

References

Ferguson, C. R., and E. F. Wood, 2011: Observed Land-Atmosphere Coupling from Satellite Remote Sensing and Reanalysis. J. Hydrometeorol., 12, 1221–1254, https://doi.org/10.1175/2011jhm1380.1.

Roundy, J. K., and J. A. Santanello, 2017: Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics. J. Hydrometeorol., 18, 863–877, https://doi.org/10.1175/JHM-D-16-0171.1.

Roundy, J.K., C. R. Ferguson, and E. F. Wood, 2013: Temporal Variability of Land–Atmosphere Coupling and Its Implications for Drought over the Southeast United States. J. Hydrometeorol., 14, 622–635, https://doi.org/10.1175/JHM-D-12-090.1.

Summary/overall impression:

This article uses regional climate simulations to test the sensitivity of land-atmosphere coupling in Europe to changes in atmospheric moisture and temperature profiles, by applying a well-known land-atmosphere coupling metric. I genuinely enjoyed reading this article and feel that the results have important implications for considering the influence of L-A coupling in a changing climate. The article is well-organized and uses novel methods that are based upon previous studies to address the authors’ hypotheses. I feel that this study will make a valuable contribution to the scientific literature. Moreover, the authors do an excellent job with the use of visuals to tell their story. As the authors’ results are so clearly valuable, I have a few suggestions that I hope will help ensure the authors’ main points are communicated clearly.

Specific comments:

L24-25: I may suggest rearranging the first two sentences, leading off with what L-A coupling is. i.e. “Land-atmosphere coupling describes the covariability between land and atmospheric states, and plays a key role for understanding….” An additional suggestion here may be to specify which states in the climate system.

L26: Schumacher et al. 2019 would be another relevant source for the influence of coupling on heat waves:

Schumacher, D. L., Keune, J., Van Heerwaarden, C. C., de Arellano, J. V. G., Teuling, A. J., & Miralles, D. G. (2019). Amplification of mega-heatwaves through heat torrents fuelled by upwind drought. Nature Geoscience, 12(9), 712-717.

L81: When you say. “The approach is based on they hypothesis…” it implies (to me) that this hypothesis was presented by numerous members of the broader scientific community and thus, supporting references should be provided. Though I am guessing you mean the hypothesis you are presenting specifically in this paper, in which case I might reword this to read “The approach is based on our hypothesis…”

L84: It’s not entirely clear what you mean by “the differences in the mean and vertical distribution.” An extra sentence or two could improve clarity so that the reader knows what to expect in the rest of the analysis, especially if they are the type of reader that skips around sections and doesn’t necessarily read the methods in depth. Are you meaning to say that you are considering how the mean changes, or how moisture and temperature deviate from the mean? Additionally, it may be helpful to clarify whether the change in vertical distribution going to be considered separately from your analysis of changes in the mean state (or deviation from the mean state) here.

Section 2.1.1: This is well-organized, concise and easy to understand. Nice job.

Figure 1: I also really like how this figure is presented and summarizes your past work with respect to the metric you are using.

Figure 5: Once again… great use of visuals.

L343-346: Forgive me if this is beyond the scope of the current study, or if I missed something here. I find it interesting that the hot and dry divergence factors increase CTP, but also increase the surface inversion. While we generally associate higher CTP with dry soil advantage, could a greater inversion strength over wet soils also lead to more moisture buildup in the PBL, and thus a lowering of the LCL to the PBLH, that may also trigger convection? In this case, would we expect the CTP-HI metric to be sufficient for diagnosing coupling potential? Papers by Ek et al. (1994 and 2004) may be relevant to a discussion of impact on surface inversion here. You may ignore this comment if I’m missing the point.

2721. Ek and L. Mahrt, 1994: Daytime Evolution of Relative Humidity at the Boundary Layer Top. Mon. Wea. Rev., 122, 2709–2721. doi: 10.1175/1520-0493

99. B. Ek and A. A. M. Holtslag, 2004: Influence of Soil Moisture on Boundary Layer Cloud Development. J. Hydrometeor, 5, 86–99. doi: 10.1175/1525-7541

L355-357: Since you are discussing the influence of temperature in the “hot case,” it can be a bit confusing when you then say “fraction of nAC-days within the hotspot” as my mind first thought hotspot in a literal, temperature sense. I would suggest changing this to read: “within the L-A coupling hotspot.”

L360-362: Is this where CTP is increased, but so is the temperature inversion? So perhaps the likelihood of convective triggering over wet soils could be tied to the comments associated with L343-346 above?

Broader comment regarding discussion: How might overall warming of the climate impact the length of the season in which we consider L-A coupling to be most influential? Your results imply that warming enhances coupling strength, so would that also mean that L-A coupling might be and important driver of hydroclimatic variability over a longer warm season? For example, instead of JJA, perhaps the “coupling season” would now be MJJAS?

L466-468: I wholeheartedly agree that we need more vertical resolution, everywhere, however, I do believe you can argue that while Wakefield et al. (2021) shows that vertical resolution is a limiting factor, you can still get representative estimates of the L-A coupling pre-conditioning even when vertical resolution is unfortunately limited. Therefore, I think you can use this reference to argue both points… your limitation in vertical resolution introduces uncertainty, but that uncertainty is not so large that it substantially impacts the validity of your results.

L479: I’m not sure about the use of the word “reliable.” My mind immediately jumps to an operational use of the word and thinking about model reliability. I do like that you say the feedback class is insensitive to changes though. Maybe “wherefore a consistent regime can be expected,” if that’s the message you are trying to convey.

Technical:

L123: Change “but maybe limit investigations” to “may limit investigations.”

L142: Change “deep convection is inhibited by an inversion, only shallow clouds…” to “deep convection is inhibited by an inversion and only shallow clouds…” or separate into two sentences.

L382: Typo “Please not that…” should say. “Please note that…”

L483-484: I might suggest rewording “cases reduced the coupling so that…” to “cases reduced the coupling sufficiently to cause disappearance of the strong positively. Coupled region over the Eastern European plain.”