An Integrated Goodness-of-Fit and Vine Copula Framework for Windspeed Distribution Selection and Turbine Power-Curve Assessment in New South Wales and Southern East Queensland

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review Report for the Manuscript

 

 An Integrated Goodness-of-Fit and Vine Copula Framework for Wind speed Distribution Selection and Turbine Power-Curve Assessment in New South Wales and Southern East Queensland

[atmosphere-3807373-peer-review-v1]

 

Overall Evaluation:

The manuscript addresses an important topic in wind energy resource assessment by applying a comprehensive statistical framework, combining univariate goodness-of-fit (GoF) evaluation and a regular vine (R-vine) copula to model spatial dependence, followed by stochastic power curve simulations. While the methodological integration is conceptually sound and the writing is generally clear, the manuscript has significant weaknesses, particularly in the clarity of presentation, technical choices, and practical relevance to the wind energy sector.

Recommendation: Major Revisions

 

Specific Comments

1. Typos and Formatting

• Line 3: Typographical error—please correct.
• Line 16: Expand the abbreviations AIC and BIC on first use for clarity.
• Lines 28–29: Please alphabetize the keywords.

2. Repetition

• Lines 91–93: The discussion here is repetitive and needs condensation for clarity.

3. Instrumentation and Measurement Details

• The Study Area and Data section lacks critical information on the measurement setup. Please include:

• A complete list of the instruments used at each site (e.g., anemometers, LiDARs).
• Sampling frequency and averaging intervals of wind speed measurements.
• Installation height of each device and any correction method (e.g., log law).

• Present these details in a dedicated table for better clarity and reproducibility.

4. Wind Speed at 10 m vs Hub Height

• Line 290 and Section 5.3: The analysis focuses on 10 m wind speed, which does not align with standard practices in wind energy where hub-height wind speeds are more relevant.

• Use of 10 m wind speed to estimate power production may misrepresent actual energy yield, especially during meteorological events like low-level jets (LLJ) or sea-breeze fronts.
• The authors should consider either:

• Using actual hub-height measurements (e.g., from LiDAR), or
• Estimating rotor-equivalent wind speeds using standard methods.

5. Equation Sections (4.1 & 4.2)

• These sections are too detailed without adding significant novelty.

• The equations for marginal distributions and GoF tests are standard. If there’s no modification or novel implementation, the equations can be summarized with references to key literature.
• Focus more on how the methods were applied uniquely in this context rather than reiterating well-known formulations.

6. Turbine Power Curve Modelling

• Line 429 and Section 5.3: Power should be computed using rotor-equivalent wind speed, not point measurements at 10 m.

• The use of a cubic ramp model is simplistic and does not account for vertical wind shear or atmospheric stability effects.
• Furthermore, the log-law extrapolation used is unreliable during events like LLJ or in coastal zones where Monin–Obukhov similarity theory (MOST) may not hold.
• These limitations should be acknowledged explicitly, and alternatives (e.g., stability-aware models or direct use of LiDAR) should be considered.

 

General Critique

The authors attempt a sophisticated integration of univariate and multivariate statistical tools for wind distribution analysis, which is appreciated. However, the methodology appears somewhat disconnected from practical wind energy engineering needs, particularly in the following ways:

• Hub-height relevance is largely ignored.
• Instrumentation and measurement uncertainties are not addressed.
• Meteorological complexities, particularly in coastal regions, are oversimplified by extrapolating 10 m data.

 

Suggestions for Revision

To improve the manuscript, the authors should:

1. Revise the abstract and introduction to clarify the contribution and practical implications of the work, especially in relation to wind energy assessment at hub height.
2. Provide instrumentation details, including a table listing instruments, measurement heights, and frequencies.
3. Justify or revise the use of 10 m wind data—preferably reduce the dataset to LiDAR-based hub-height measurements and perform the full analysis again.
4. Simplify the mathematical sections (Sections 4.1 and 4.2), and remove equations that are not central to the novelty of the work.
5. Recompute power simulations using rotor-equivalent wind speed, or at least discuss limitations of the current approach in detail.
6. Clarify the impact of meteorological phenomena on the statistical assumptions used (e.g., validity of log-law and MOST).

Conclusion

The manuscript addresses an interesting and relevant problem using advanced statistical methods. However, significant revisions are needed to improve its technical robustness, relevance to wind energy applications, and clarity of presentation. Until the issues mentioned are addressed—particularly regarding the treatment of wind speed at hub height—major revisions are required before the manuscript can be considered for publication.

 

 

Comments for author File: Comments.pdf

Author Response

Please see attachment. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

General comments:

This study estimated the statistical distribution parameters for Weibull, Gamma, Lognormal, and Generalized Extreme Value distributions for 11 sites in New South Wales and southern Queensland. Annual electricity productions for two wind turbine models are calculated.

 

Overall, the manuscript is properly structured and well written. The study is generally complete. Before possible publication, the following comments and suggestions should be addressed.

 

Specific comments:

1. Daily mean wind speed data is used in this study. However, wind speed shows significant diurnal variation. The daily resolution may not be adequate for wind resource assessment. Usually at least hourly mean (or higher resolution) wind speed is required. If high resolution data is not available, at least some discussions on the limitation of using daily mean wind data for wind resource assessment should be included.
2. Before turbine power calculation and annual yield estimation, the wind speed needs to be extrapolated to the turbine hub height, e.g., 100 m. Usually the empirical power law is used for this extrapolation. The authors should perform this conversion in this study, or the turbine power calculation is not accurate.
3. The quality control step on temporal consistency may be inappropriate. It is possible to observe very high or very low wind speed in a 15-day window. For example, if a tropical cyclone passes, it is possible that the daily wind speed reaches 30 m/s on the day it passes, while the 15-day mean and standard deviation remain low.
4. What is the form of the logarithmic law used? The equation should be shown. The value of roughness length used for each station should be given.
5. Atmospheric stability should be considered when applying the logarithmic law extrapolation. How was the stability parameter estimated in this study?
6. Figure 2 is not necessary. Please consider removing it.

Author Response

Please see attachment. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Review Report for the Manuscript

 

 An Integrated Goodness-of-Fit and Vine Copula Framework for Wind speed Distribution Selection and Turbine Power-Curve Assessment in New South Wales and Southern East Queensland

[atmosphere-3807373-peer-review-v2]

 

The authors have attempted to revise the manuscript based on the first review; however, I find that the revision does not adequately address the core concerns previously raised. I recommend that the manuscript undergo another major revision.  My detailed observations are as follows:

1. Understanding of Meteorological Phenomena

The revised manuscript still suggests that the authors may lack a proper understanding of certain meteorological processes, particularly those influencing wind profiles in coastal environments. While the use of the log law for wind speed extrapolation is explained, the method is only valid under neutral atmospheric stability conditions over flat terrain. The manuscript does not sufficiently discuss the limitations of applying this approach in complex coastal settings, where factors such as coastal blockage and internal boundary layer growth can significantly alter wind profiles.

2. Instrumentation Details

The authors have provided a generalised description of Bureau of Meteorology (BOM) standards but have not specified that LiDAR systems—commonly deployed at airports and highly relevant for hub-height wind speed measurement—are used in several of the study locations. This omission weakens the credibility of the dataset description and its applicability to wind energy resource assessment.

3. Presentation of Results

The presentation remains broad and not sufficiently linked to specific measurement setups. It would be more meaningful for the results to be clustered according to the type of measurement device (e.g., cup anemometers, LiDAR), as this would allow for a clearer comparison of performance and limitations between datasets.

4. Use of Log Law Extrapolation

The manuscript does not address the fact that the log law is unsuitable under non-neutral stability conditions, especially in coastal regions where mesoscale phenomena (sea-breeze fronts, low-level jets, etc.) are frequent. The surface roughness parameter is particularly critical and highly uncertain in coastal areas, and the current text does not reflect the complexity involved in estimating it under such conditions.

5. Overall Assessment

Despite the revisions, I remain unconvinced by the methodology’s physical validity and the robustness of the results. The current framework oversimplifies critical meteorological complexities, and the lack of site- and instrument-specific result clustering reduces the practical applicability of the findings for wind energy engineering.

Recommendation:
The authors should:

1. Provide explicit details on the use (or absence) of LiDARs and other instrumentation at each site.
2. Restructure the results to be presented in clusters corresponding to the measurement devices used.
3. Reassess the applicability of the log law in coastal regions, with explicit discussion of stability effects, internal boundary layer development, and uncertainties in surface roughness​.
4. Strengthen the meteorological interpretation of the results to ensure the conclusions are physically sound.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The reviewer is satisfied with the author‘s response and revisions. It is recommended that the manuscript be accepted in its current form.

Author Response

Thank you.