General Remarks

Dear Cristina, Thank you for addressing an important issue in wind energy science. I would like to expand on and clarify certain points that I believe could further strengthen the scope and implications of this work.

My comments below may go beyond the topic of wind turbine wakes. Here, I aim to provide a slightly different perspective with the hope of creating greater alignment across wind energy, wind engineering, and meteorology. Bridging the differences in practices and definitions between these domains could lead to a more coherent and standardized approach, ultimately benefiting both research and practical applications in wind energy.

I would go beyond the statement that the variance of the wind speed is often miscalculated. I would argue that using the variance of the wind speed itself—rather than treating the variance of the along-wind and cross-wind velocity components separately—is fundamentally problematic. In wind engineering and micrometeorology, these components are considered separately due to their distinct characteristics. The design of wind turbines, particularly for structural and turbulent loading considerations, is based on the variances of the along-wind and cross-wind components, not the wind speed. The continued use of wind speed variance might be a legacy of outdated practices.

Specific Comments:

Line 15-20: The distinction between aligning the x-axis with the wind direction or with the East-West coordinate system is not unique to wind energy; it largely depends on the spatial and temporal scales of interest. In boundary-layer meteorology, particularly micrometeorology, the x-axis is typically aligned with the mean wind direction due to the focus on turbulence, as detailed in Kaimal and Finnigan (1994). In mesoscale meteorology, where the emphasis is on mean wind speed, the x-axis is, indeed, often aligned with the East-West direction. To avoid conflating discipline-specific conventions, I recommend acknowledging this broader context.

Conflict of Definitions in Different Fields: There may be conflicting definitions of "turbulence" between mesoscale and microscale meteorology that require clarification. In micrometeorology, turbulence is typically considered a three-dimensional process occurring within temporal scales of up to one hour and spatial scales smaller than a few kilometres. In micrometeorology, the variance of the along-wind and across-wind components differs significantly. Motions exceeding these scales are often classified as “non-turbulent motion,” consistent with the concept of the spectral gap. However, mesoscale meteorology may occasionally describe such motions as “2D turbulence.” These differences reflect divergent focuses and terminologies across disciplines and should be recognized explicitly.

Line 28-29: The statement “turbulence intensity is a function of the standard deviation of wind speed” could be misleading. From micrometeorology and wind engineering perspectives, turbulence intensity is typically defined based on the individual velocity components (along-wind, cross-wind, and vertical), not wind speed. Defining turbulence intensity based on wind speed lacks physical relevance. In my humble opinion, its continued use in wind energy science is puzzling.

Line 31: While it is true that mesoscale meteorology often simplifies wind velocity as a 2D vector, this approach does not hold in micrometeorology or wind energy, where the vertical velocity component significantly contributes to turbulence kinetic energy (TKE). I understand that the inclusion of TKE in this discussion depends on the desired level of detail. If brevity is prioritized, this aspect could be omitted.

Table 1: The two examples in Table 1 effectively demonstrate the value of the proposed equation. However, it is unclear whether the statistics are based on six hours of data or shorter sub-samples. If turbulence is the focus, time averaging over six hours is not appropriate, especially since the second panel shows clear non-stationary fluctuations. If the table uses shorter intervals (e.g., 10 minutes to 30 min), I recommend expanding the analysis to include all samples from Figure 1. Comparing the wind speed variance estimated by the older equation with that from your proposed equation would strengthen the analysis. A scatter plot of these comparisons across the full dataset would complement Table 1. This visualization would make it easier to assess the overall performance and accuracy of the new equation relative to the older one.