| 29 Aug 2025
Characterizing atmospheric stability in complex terrain
Abstract. Characterizing atmospheric stability becomes challenging in heterogeneous complex terrain. We use data from 47 meteorological towers associated with the Perdigão field campaign to recommend data processing approaches and to assess the limitations of shorter or fewer towers. We quantify atmospheric stability according to the Obukhov length, the turbulence kinetic energy, and the turbulence dissipation rate using a range of decomposition periods including consistent 10 minute periods to match convention in the wind energy community and consistent 30 minute periods to match convention in the atmospheric science community. Atmospheric stability characterization is impacted by the Reynolds decomposition period, so care should be taken to use appropriate intervals. Additionally, 10 m measurements do not provide reliable 100 m hub-height stability predictions. Finally, we demonstrate a methodology that can indicate the necessary number and location of towers to characterize atmospheric stability. Holistically, this work addresses challenges in relying on sparse surface measurements.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.
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Review of "Characterizing atmospheric stability in complex terrain" by Agarwal & Lundquist
This paper addresses an important and timely topic: characterizing atmospheric stability in complex terrain using Perdigao tower data. The authors evaluate stability metrics with different Reynolds decomposition intervals, and quantify the predictive skill of low level vs hub height stability. They apply clustering methods to recommend a necessary number of met masts which is good but rather academic because usually the problem is the opposite: how many more met masts than 1 are needed to properly sample the site conditions (and where numerical estimates of wind field covariance are helpful - see the other general comment).
The analysis is carefully executed, the dataset is of very high quality, and the topic is relevant to both atmospheric science and wind energy.
However, the paper in its current form is incomplete. Perdigao has also been extensively studied with mesoscale and large-eddy simulation (LES) modeling, yet the study relies exclusively on observational/statistical analyses, while ignoring the context and assistance that numerical models can provide. Without at least a discussion — and preferably some demonstration — of how models complement observations, the results risk being overly narrow and less generalizable, especially when the conclusions are drawn from data from a single site.
I therefore recommend major revision to address the points above, and a few specific comments below.
Specific comments
L32: Discussing various papers about the effects of stability before at least defining it broadly. Some of these papers even analyze data from complex terrain.
L152: The Obukhov length is not proportional to the height above the surface. It is the height above the surface.
L162: Please define Tv. Is it even meaningful to use theta-v and Tv in the context when theta is then anyway assumed to be constant?
L250: Please clarify if the linear regression is calculated at specific time-stamps? If yes, please discuss how the vertical information propagation may adversely affect this metrics.
L274, Figure 2: The case (e) tse09 (valley) stable exhibits the opposite behavior from every other case. This would merit some discussion.
L277: Not entirely clear how it is discernible from Fig. 2h that the stable ogive shifts to mesoscale fluctuations at 60 min. Do you mean that the curves which appear to have flattened, suddenly receive a kink?
L307: "more diffuse" is not the best choice of words. It would be better said that the winds are less bidirectional, or aligned with the terrain.
L310, Figure 3: Please discuss why the ogives (are they really ogives, strictly speaking?) for u* are so different from those for the heat flux?
L477: It is too optimistic to claim that this work improves the characterization of atmospheric stability. It only demonstrates the challenges, based on data from one site.
L486: "... towers that extend to hub height ...". Should they not be extended to the rotor top? Arguably, similar if not larger discrepancies will occur when the top of the boundary layer, which often is at about HH, intersects the rotor area.