I think you have addressed all questions raised by the two reviewers. Once you integrate the corrections in text (as per your rebuttal) the paper can go through a final review (for minor revisions) and be ready for publication.

Thank you for submitting the final version and completing the review process

Although the editor is now satisfied with the paper, I have some comments that may be a bit larger than "technical corrections" that I would like to see conseidered. I don't want to reject the paper which I find a valuable contribution to a much discussed subject in the field, but I feel that the paper should be improved a bit more. In general there are still issues with roman/italics. More specifically I have the following comments:

p 2 l 24: "In contrast"? I do not see the contrast. Berg reports vanishing effect of non-Gaussian turbulence on fatigue and extreme loads, Milan reports intermittent power output from wind turbines and farms.

P 7: "Model wind turbine": Please provide a bit more detail on the resemblance of this turbine with a conventional pitch-regulated turbine.

Caption to fig 6: "exemplary" -> "example"

P 9 l 9: It is right that variables should be italic, but units like "mm" should be roman.

P 9 l 16 "x" should be italic.

Figure 4: Please provide the spectrum of the Gaussian time series on the same plot. Please use italics for variables on the axes as it is done in Figure 1. This also applies to many other figures.

Figure 5b shows particularities of the filter in the controller (running block averaging, as far as I understand). I think it confuses more than it explains anything. The only use of this analysis seems to be related to the choice of time scales (sec 5), but this could be done without these coherences. I think is would clarify the paper if this coherence analysis is left out. It does help to prove the essential point of the paper.

p 12 l 5. I would prefer to write + sigma_u, not to have the time argument. This applies to other places like Table 3.

The non-Gaussian time series in Figures 6, 7, and 8 appear artificial in the sense that they do not necessarily resemble atmospheric time series. Some statistical properties agree better with averages from nature, but others like the spectrum in Figure 4 may not.

The Discussion should relate the present work to the literature and also show some self-criticism. As referee #2 states (and I agree) many of the time series that are supposed to be more realistic look very artificial. Earlier results from Mücke et al showed showed limited consequences of non-Gaussianity and so did Berg et al. How are these new findings related to the existing literature?

I would like you to consider and incorporate these comments \emph{without increasing the length of the paper}. After that is done, I will reconsider positively the paper. You are welcome to contact me if you would like to discuss my comment.

Best regards,
Jakob Mann, Editor-in-Chief