A New Formulation and Code to Compute Aerodynamic Roughness Length for Gridded Geometry—Tested on Lidar-Derived Snow Surfaces

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript presents a useful combination of geometric methods and remote sensing techniques to quantitatively evaluate snow surface roughness using high-resolution LiDAR data. While it provides a valuable computational tool and detailed implementation, the study does not appear to offer new theoretical insights beyond the existing geometric approach.

Considering its brief length and practical orientation, I suggest the authors consider submitting this work as a technical note.

Additionally, validation using actual field observations (e.g., wind profile or eddy-covariance measurements) would significantly strengthen the manuscript.  The absence of validation makes it challenging for readers to assess the applicability compared to traditional wind-profile-based methods. If direct validation data are unavailable, please discuss clearly the potential ways such validation might be carried out and provide convincing reasoning about the reliability of your current results.

Overall, with these considerations addressed, this work will offer a beneficial resource to the community.

Author Response

This manuscript presents a useful combination of geometric methods and remote sensing techniques to quantitatively evaluate snow surface roughness using high-resolution LiDAR data. While it provides a valuable computational tool and detailed implementation, the study does not appear to offer new theoretical insights beyond the existing geometric approach.

 

• This paper presents a detailed approach and code to quantify aerodynamic roughness (z0). The z0 formulation is not new, but the approach is novel. This is added to the Introduction of the paper.

 

Considering its brief length and practical orientation, I suggest the authors consider submitting this work as a technical note.

 

• We will leave this distinction up to the editors.

 

Additionally, validation using actual field observations (e.g., wind profile or eddy-covariance measurements) would significantly strengthen the manuscript.  The absence of validation makes it challenging for readers to assess the applicability compared to traditional wind-profile-based methods. If direct validation data are unavailable, please discuss clearly the potential ways such validation might be carried out and provide convincing reasoning about the reliability of your current results.

 

• This paper is meant to compute the geometric-based aerodynamic roughness (z0), and not be a comparison between the anemometric and geometric approaches to compute z0. The latter comparison is the topic for other papers. Text has been added to the Discussion about this.

 

Overall, with these considerations addressed, this work will offer a beneficial resource to the community.

 

• Thank you.

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript entitled “A Geometric-based Aerodynamic Roughness Length Formulation and Code Applied to Lidar-derived Snow Surfaces” proposes a new algorithm and code based on Lettau’s (1969) geometric approach to compute the aerodynamic roughness length (z0) of snow-covered surfaces. The method was applied to three snow surface datasets representing different phases of the snow season at varying resolutions.

 

While this study is generally interesting and useful for related studies, there are some issues needs to be well addressed to ensure the reliability of the results and the understandability to the authors.

 

• A major concern is that: what distinguishes the calculation of aerodynamic roughness length (z₀) on snow surfaces from that on general surfaces? While the proposed method appears theoretically applicable to any surface type in principle, why does the study emphasize snow surfaces specifically? I suggest this should be made clear in the introduction section.

 

• Can you introduce the conventional accuracy requirements for calculating z0 on a snow-covered surface? As the results of the paper indicate, using different resolutions will have a significant impact on the calculation of z0. So, how to evaluate the accuracy of z0 values? What is the precision requirement? How much impact will the uncertainty in deriving z0 have on subsequent applications? These need to be clearly stated in the introduction to facilitate readers' understanding of the entire research background and theoretical foundation.

 

• In methodology section, the description is almost texts. It is not very easy for readers to follow. Is it possible to be presented in a more reader-friendly version, such as combining figures, flow charts and so on to show more clear how the method works?

 

• While the author used three different snow surface datasets at different resolutions, it is obviously the method is scale-dependent. Thus, the question is which resolution is preferred? The finer, the better? Or is there some optimal resolutions? I suggest the author explicitly discuss the scale issues and provide recommendations for the potential users of their computer codes

 

• I believe that the computer codes can really work well on the three datasets. But, can you provide any comparisons with other existing algorithms? So we can be clear that the method is reliable and the result is reasonable?

 

• I suggest discuss in more details on the applicability of the computer codes? Are they applicable to bare surfaces? To snow surface acquired at coarser resolutions, such as airborne or even spaceborne lidar data?

 

• Are the codes open source and freely available to potential users? I suggest the authors explicitly introduce how to access the codes.

Author Response

(x) The English could be improved to more clearly express the research.

• We have addressed the comments below. No specific details have been given to rewrite the paper.

This manuscript entitled “A Geometric-based Aerodynamic Roughness Length Formulation and Code Applied to Lidar-derived Snow Surfaces” proposes a new algorithm and code based on Lettau’s (1969) geometric approach to compute the aerodynamic roughness length (z0) of snow-covered surfaces. The method was applied to three snow surface datasets representing different phases of the snow season at varying resolutions.

 

• No response needed.

 

While this study is generally interesting and useful for related studies, there are some issues needs to be well addressed to ensure the reliability of the results and the understandability to the authors.

 

•  

 

A major concern is that: what distinguishes the calculation of aerodynamic roughness length (z₀) on snow surfaces from that on general surfaces? While the proposed method appears theoretically applicable to any surface type in principle, why does the study emphasize snow surfaces specifically? I suggest this should be made clear in the introduction section.

 

• Good point. This code can be applied to any surface. We have changed the title to “A New Formulation and Code to Compute Aerodynamic Roughness Length for Gridded Geometry - Tested on Lidar-derived Snow Surfaces.” Text has been added early in the paper to present this code. For evaluation, we apply the code to three different snow surfaces at different resolutions to illustrate the differences in z0.

 

Can you introduce the conventional accuracy requirements for calculating z0 on a snow-covered surface? As the results of the paper indicate, using different resolutions will have a significant impact on the calculation of z0. So, how to evaluate the accuracy of z0 values? What is the precision requirement? How much impact will the uncertainty in deriving z0 have on subsequent applications? These need to be clearly stated in the introduction to facilitate readers' understanding of the entire research background and theoretical foundation.

 

• This is presented in the paper with the range of z0 values that are found in the literature. We moved the references to snow from the Introduction to a separate section after the Methodology. Here we briefly discussion the variability of z0 in the literature and also the implications for sublimation modeling.

 

In methodology section, the description is almost texts. It is not very easy for readers to follow. Is it possible to be presented in a more reader-friendly version, such as combining figures, flow charts and so on to show more clear how the method works?

 

• Good idea. This table has been added.

 

While the author used three different snow surface datasets at different resolutions, it is obviously the method is scale-dependent. Thus, the question is which resolution is preferred? The finer, the better? Or is there some optimal resolutions? I suggest the author explicitly discuss the scale issues and provide recommendations for the potential users of their computer code.

 

• We now discuss this in the context of the various methods that are available to measure any surface: lidar (terrestrial, airborne, satellite) and photogrammetry (same approaches). There is a balance between resolution and extent, and working across scales may be important – you don’t need to scan the whole earth at a millimeter resolution.

 

I believe that the computer codes can really work well on the three datasets. But, can you provide any comparisons with other existing algorithms? So we can be clear that the method is reliable and the result is reasonable?

 

• The two methods beside Lettau (MacDonald and Counihan) have been shown to not work well for snow (Sanow et al., 2018). We have found no other explicit formulation for Lettau in the literature. Others (e.g., Munro, 1989) just stated that they use the Lettau approach. Here, we detail how we apply Lettau’s equation.

 

I suggest discuss in more details on the applicability of the computer codes? Are they applicable to bare surfaces? To snow surface acquired at coarser resolutions, such as airborne or even spaceborne lidar data?

 

• Yes, the code can be applied to any gridded dataset. We de-emphasize the application to snow surfaces, and just use those as an example, across scales.
• One (coarsest) of the datasets is from airborne lidar. Spaceborne lidar, as well as photogrammetry are now options to collect surface data. Text has been added to the Discussion.

 

Are the codes open source and freely available to potential users? I suggest the authors explicitly introduce how to access the codes.

 

• We now cite the code earlier in the text (several times), and not just at the end.

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors should clearly state what new contribution their approach offers over previous methods and explain its added value to the field, rather than simply providing a code implementation of existing techniques. 

Author Response

Comment 1: The authors should clearly state what new contribution their approach offers over previous methods and explain its added value to the field, rather than simply providing a code implementation of existing techniques. 

 

Reply: What is novel in our paper is 1) that we articulate how we define individual roughness elements to compute z0 and then use Lettau's equation, as this is no explicitly stated in any of the papers that use the Lettau approach, and 2) we use the watershed approach. We have added a sentence to the Abstract to summarize this, and a paragraph in the Introduction to explain how what we did is novel.