the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Sep 2024
SAMURAI-S: Sonic Anemometer on a MUlti-Rotor drone for Atmospheric turbulence Investigation in a Sling load configuration
Abstract. This study introduces the SAMURAI-S, a novel measurement system that incorporates a state-of-the-art sonic anemometer combined with a multi-rotor drone in a sling load configuration, designed to overcome the limitations of traditional mast-based observations in terms of spatial flexibility. This system enables the direct measurement of 3D wind vectors while hovering, providing a significant advantage in manoeuvrability and positional accuracy over fixed mast setups. The capabilities of the system are quantified through a series of 10 min to 28 min flights, conducting close comparisons of turbulence measurements at altitudes of 30 m and 60 m against data from a 60-meter tower equipped with research-grade sonic anemometers. The results demonstrate that SAMURAI-S matches the data quality of conventional setups for horizontal wind measurements while slightly overestimating vertical turbulence components. This overestimation increases as the wind speed increases.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1548', Anonymous Referee #1, 15 Oct 2024
This paper presents very novel work in measuring turbulence from an UAV where the sonic anemometer is placed as a sling load from the UAV. This positioning overcomes difficulties from other solutions such as e.g. using a sideways facing boom. The study also presents methods on how to properly process the measurements data in order to get physically correct output.
The new system opens up for detailed turbulence measurements in environments requiring a spatial resolution such as e.g. wakes from wind turbines.
The authors must have put in a great effort in getting this system to work properly as shown with the comparative study from a recent field campaign. Some remaining issues with the overestimation of vertical wind fluctuations still needs to be investigated further. However, this study convincingly show that these type of measurements are possible and may yield results comparable to a fixed installation, a significant contribution to the field.
The manuscript is well prepared and presents the applied method in a clear manner including relevant figures. I only have some minor comments and suggestions which you find below.
General comments
I think it would be good to get some reflection on the practicalities/maneuverability of the system. How was take-off and landing prepared? Is it necessary with special training using this setup? Is there some danger with high gustiness that the system gets out of control? I could think of e.g. measuring in highly turbulent conditions such as close to forest edges. Also, did you fly it manually or with an autopilot?
The larger values of sigma_w from the UAV measurements seems to be systematic, in all samples. There is a risk that this might be some lingering effect from the downwash of the propellers. I think this needs to be further elaborated on in the discussion.
Specific comments
Line 50, more clearly specify the novelty. Clearly establish the innovation and significance of the study
Line 89, specify that the weight is without payload (?)
Section 2, placement of a sonic anemometer above the drone is not discussed, please add something here.
Section 2, Explaining why Foxtech was chosen over other potential UAVs would provide more context
Section 2, Here some operational considerations could be included: e,g, operational procedures for deploying the UAV and sensor system in the field, details on pre and post flight checks necessary etc. This would be valuable for replicating the study.
Also, potential limitations/challenges associated with the setup can be included here. It would provide a more balanced perspective. For example, addressing the potential impact of strong wind conditions on UAV performance would be useful.
Line 203, why was the 2% limit set (why not e.g. 1% or 3%)?
Line 214, Please define how you determined TKE
Section 4.2, first paragraph: This section could benefit from some more description and motivation of the applied steps.
Line 283, Specify for the reader what you mean by misalignment in this context
Line 300, for completeness why don’t you include also s2, s3 and s4 in the quadrant analysis? Could be interesting to see the results, but you could use different symbols to separate these.
Section 5.1 Please provide some initial text motivating why these particular cases, s1 and s7 were chosen for the case study.
Line 313, you previously introduced skewness and kurtosis, for consistency this could be repeated here. The sentence “Results related to temperature…” would be better placed after the sentence “Figure 8 presents time series of…”.
Figure 8, for completeness the figure caption should explain also the insert text in the figures e.g. “rot2” etc. This comment also goes for Figures 9, 10 and 11.
Table 5, correct capital D in figure caption (on Data). Why not include also the u’w’ and w’t’ terms in the table?
Line 334, can there be a risk that this is something induced by the UAV? Flight 1 was the one closest to the tower and the only one with unstable stratification and winds somewhat in the direction of the tower.
Line 340, which also is seen in the larger sigma_w values in Table 5
Figures 12 and 13: please provide a table with comparative statistics, i.e. bias and RMSE of the UAV based measurements compared to the tower. This would improve the discussion in the paragraph starting on line 360. Additionally, these figures should be placed in section 5.2.
Line 361: Why not use the same notation as in the previous sentence when it comes to the fluxes i.e. w’t’?
Line 362-364: It is hard to determine whether L has low scatter, calculating some comparative statistics would improve this discussion. Additionally, I am not convinced about the explanation about the perceived low scatter for L, u* is to the third power in equation (7). Furthermore, it is not he w’ itself which is important here, rather it’s correlation with the other variable e.g. T’.
Paragraph starting at line 374 and figure 14: It appears only one sample is close to 1.33 for Sw/Su and that the deviation increases with increasing wind speed (as you also mention in the conclusions). Please rephrase the text here to better concur with the figure.
Could the overestimation of this ratio be related to the overestimation of sigma_w? The underestimation of the tower could be due to problems with the setup? To short booms? This is something that can be commented in the text. Of course, it could be investigated since you have a larger dataset from the tower, but it might be out of the scope of this paper.
Conclusions section: This section could benfit from beeing more streamlined, excluding some summary focusing on the main results. Adding the comparative statistics I suggested above would further strengthen this section. Also, some tentative conclusions about the minimum sampling time could be added.
Appendix/supplementary material: It would be interesting to include the spectra from all flights and tower comparisons (e.g. like figure 9 and 11).
Technical corrections
The manuscript is mainly written in the present tense (with some deviations). Personally, I would prefer past tense for everything that you have done but I leave this to the editor. At least, check for inconsistencies which appear at some places.
Line 14, reference from 2010 is not that recent (just a detail)
Figure 1, would benefit of a somewhat more detailed figure caption, e.g. here are batteries and logger mounted, dimensions of payload etc.
Figure 2, also this figure would benefit from a more detailed figure caption
Figure 4 is better located under section 3
Table 4, Figures 12-13 should be placed in section 5
Citation: https://doi.org/10.5194/egusphere-2024-1548-RC1 -
AC1: 'Reply on RC1', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
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AC1: 'Reply on RC1', Mauro Ghirardelli, 14 Feb 2025
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RC2: 'Comment on egusphere-2024-1548', Anonymous Referee #3, 26 Nov 2024
This manuscript outlines a novel atmospheric turbulence measurement via a sonic anemometer mounted to a multi-rotor uncrewed aerial system using a sling load. The authors outline the design of the system, operating parameters and analyze the performance of the method by comparing measurements to tower-based sonic anemometers. The manuscript is well-written, thorough and advances atmospheric measurement techniques. I recommend the paper for publication.
Specific Comments:
Line 89: Define GNSS
Table 1: p5. Define ESC
Line 142: It would be helpful to annotate the image (Figure 1) or diagram (Figure 2) with where the INS is located, the sensor coordinates, the crossbar and the GNSS antennas. This is just for clarity.
Line 147: It would also be helpful to have a diagram of the pitch, yaw, roll and balance of the sling load configuration attachment to the UAS. Connecting the theoretical diagram (Figure 3) to the logistical attachment strategies and pendulum physics (Figure 2) is a key understanding of the novelty of this approach and a visual connection may assist the reader in discerning the language in this paragraph.
Line 186: Do you have any metric on the accuracy of the internal clock of the Raspberry pi? Is there drift or time compression?
Line 188: I do not understand the time adjustment for upside-down mounting orientation. If the measurements are instantaneous to an internal clock, why would time be a factor in transforming the phase space of the measurement. Please clarify.
Line 207: Explain the downsampling process from 50 Hz to 32 Hz. It would appear it would merely be a linear interpolation as the frequencies are too close for any averaging. If it is a smoothing function, please explain what that other smoothing function is.
Line 298 and Lines 402-405: If the flights s2, s3, and s4 have low mean flows and were not included in the quadrant analysis, please qualify the summative statements regarding the quadrant analysis for the assumptions required to apply it.
Citation: https://doi.org/10.5194/egusphere-2024-1548-RC2 -
AC2: 'Reply on RC2', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
-
AC2: 'Reply on RC2', Mauro Ghirardelli, 14 Feb 2025
-
EC1: 'Comment on egusphere-2024-1548, Anonymous Referee #2, 3 Dec 2024', Luca Mortarini, 03 Dec 2024
The Anonymous Referee #2 is experiencing technical problems in uploading is comments.
In agreement with the editorial board and on behalf of the reviewer, I am posting his/her review.
The PIF phenomenon consisting in the presence of strong induced turbulence around a drone-type UAV leads to significant issues in direct measurements of atmospheric parameters. The manuscript proposes an original way to minimize the effect of the PIF phenomenon in direct measurements by hanging a sonic anemometer under the drone as a sling load. The study is interesting, urgent, and relevant to the topic of Atmospheric Measurement Techniques. The results reported by the authors can be of great interest to AMT readers.
In my opinion, the below comments can help the authors to improve significantly the quality of the manuscript.
- Pages 1 and 2, Lines 7-9 and 57. The authors write that “This research aims to assess the accuracy and reliability of the developed measurement approach.” In my opinion, the statement that ‘The results demonstrate that SAMURAI-S matches the data quality of conventional setups for horizontal wind measurements while slightly overestimating vertical turbulence components. This overestimation increases as the wind speed increases” does not fully correspond to the purpose and results of the work. The authors should provide quantitative data on the discrepancy between Drone Data and Mast Data as a function of the increasing wind speed.
- Page 13, Line 253, Eq. (6). This equation should be corrected as Sw -> Suw.
- Pages 17 and 20, Figures 8 and 10. The sonic anemometer allows measuring actual wind speed and actual ambient temperature with high spatial and temporal resolution. The analysis of the measurement series depicted in Figures 8 and 10 should be supplemented with the correlation coefficients, the turbulence scale data, and the distance between the sonic anemometers installed on the drone and the mast. In addition, histograms of the discrepancy between Drone Data and Mast Data, as well as the Cumulative Percent, which characterize the statistics of the discrepancy between the data, should be presented. It will be interesting to readers how the measurement data differ from each other at the actual wind speed and temperature.
- It is desirable to provide the estimated spatial resolution so that a reader could evaluate possible applications of the reported technique.
The manuscript can be published in Atmospheric Measurement Techniques after revision with allowance made for the above comments. I believe that this will qualitatively improve both the clearness of the manuscript itself and the characteristics (accuracy, reliability, etc.) of the approach to monitoring atmospheric turbulence developed by the authors.
Citation: https://doi.org/10.5194/egusphere-2024-1548-EC1 -
AC3: 'Reply on EC1', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1548', Anonymous Referee #1, 15 Oct 2024
This paper presents very novel work in measuring turbulence from an UAV where the sonic anemometer is placed as a sling load from the UAV. This positioning overcomes difficulties from other solutions such as e.g. using a sideways facing boom. The study also presents methods on how to properly process the measurements data in order to get physically correct output.
The new system opens up for detailed turbulence measurements in environments requiring a spatial resolution such as e.g. wakes from wind turbines.
The authors must have put in a great effort in getting this system to work properly as shown with the comparative study from a recent field campaign. Some remaining issues with the overestimation of vertical wind fluctuations still needs to be investigated further. However, this study convincingly show that these type of measurements are possible and may yield results comparable to a fixed installation, a significant contribution to the field.
The manuscript is well prepared and presents the applied method in a clear manner including relevant figures. I only have some minor comments and suggestions which you find below.
General comments
I think it would be good to get some reflection on the practicalities/maneuverability of the system. How was take-off and landing prepared? Is it necessary with special training using this setup? Is there some danger with high gustiness that the system gets out of control? I could think of e.g. measuring in highly turbulent conditions such as close to forest edges. Also, did you fly it manually or with an autopilot?
The larger values of sigma_w from the UAV measurements seems to be systematic, in all samples. There is a risk that this might be some lingering effect from the downwash of the propellers. I think this needs to be further elaborated on in the discussion.
Specific comments
Line 50, more clearly specify the novelty. Clearly establish the innovation and significance of the study
Line 89, specify that the weight is without payload (?)
Section 2, placement of a sonic anemometer above the drone is not discussed, please add something here.
Section 2, Explaining why Foxtech was chosen over other potential UAVs would provide more context
Section 2, Here some operational considerations could be included: e,g, operational procedures for deploying the UAV and sensor system in the field, details on pre and post flight checks necessary etc. This would be valuable for replicating the study.
Also, potential limitations/challenges associated with the setup can be included here. It would provide a more balanced perspective. For example, addressing the potential impact of strong wind conditions on UAV performance would be useful.
Line 203, why was the 2% limit set (why not e.g. 1% or 3%)?
Line 214, Please define how you determined TKE
Section 4.2, first paragraph: This section could benefit from some more description and motivation of the applied steps.
Line 283, Specify for the reader what you mean by misalignment in this context
Line 300, for completeness why don’t you include also s2, s3 and s4 in the quadrant analysis? Could be interesting to see the results, but you could use different symbols to separate these.
Section 5.1 Please provide some initial text motivating why these particular cases, s1 and s7 were chosen for the case study.
Line 313, you previously introduced skewness and kurtosis, for consistency this could be repeated here. The sentence “Results related to temperature…” would be better placed after the sentence “Figure 8 presents time series of…”.
Figure 8, for completeness the figure caption should explain also the insert text in the figures e.g. “rot2” etc. This comment also goes for Figures 9, 10 and 11.
Table 5, correct capital D in figure caption (on Data). Why not include also the u’w’ and w’t’ terms in the table?
Line 334, can there be a risk that this is something induced by the UAV? Flight 1 was the one closest to the tower and the only one with unstable stratification and winds somewhat in the direction of the tower.
Line 340, which also is seen in the larger sigma_w values in Table 5
Figures 12 and 13: please provide a table with comparative statistics, i.e. bias and RMSE of the UAV based measurements compared to the tower. This would improve the discussion in the paragraph starting on line 360. Additionally, these figures should be placed in section 5.2.
Line 361: Why not use the same notation as in the previous sentence when it comes to the fluxes i.e. w’t’?
Line 362-364: It is hard to determine whether L has low scatter, calculating some comparative statistics would improve this discussion. Additionally, I am not convinced about the explanation about the perceived low scatter for L, u* is to the third power in equation (7). Furthermore, it is not he w’ itself which is important here, rather it’s correlation with the other variable e.g. T’.
Paragraph starting at line 374 and figure 14: It appears only one sample is close to 1.33 for Sw/Su and that the deviation increases with increasing wind speed (as you also mention in the conclusions). Please rephrase the text here to better concur with the figure.
Could the overestimation of this ratio be related to the overestimation of sigma_w? The underestimation of the tower could be due to problems with the setup? To short booms? This is something that can be commented in the text. Of course, it could be investigated since you have a larger dataset from the tower, but it might be out of the scope of this paper.
Conclusions section: This section could benfit from beeing more streamlined, excluding some summary focusing on the main results. Adding the comparative statistics I suggested above would further strengthen this section. Also, some tentative conclusions about the minimum sampling time could be added.
Appendix/supplementary material: It would be interesting to include the spectra from all flights and tower comparisons (e.g. like figure 9 and 11).
Technical corrections
The manuscript is mainly written in the present tense (with some deviations). Personally, I would prefer past tense for everything that you have done but I leave this to the editor. At least, check for inconsistencies which appear at some places.
Line 14, reference from 2010 is not that recent (just a detail)
Figure 1, would benefit of a somewhat more detailed figure caption, e.g. here are batteries and logger mounted, dimensions of payload etc.
Figure 2, also this figure would benefit from a more detailed figure caption
Figure 4 is better located under section 3
Table 4, Figures 12-13 should be placed in section 5
Citation: https://doi.org/10.5194/egusphere-2024-1548-RC1 -
AC1: 'Reply on RC1', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
-
AC1: 'Reply on RC1', Mauro Ghirardelli, 14 Feb 2025
-
RC2: 'Comment on egusphere-2024-1548', Anonymous Referee #3, 26 Nov 2024
This manuscript outlines a novel atmospheric turbulence measurement via a sonic anemometer mounted to a multi-rotor uncrewed aerial system using a sling load. The authors outline the design of the system, operating parameters and analyze the performance of the method by comparing measurements to tower-based sonic anemometers. The manuscript is well-written, thorough and advances atmospheric measurement techniques. I recommend the paper for publication.
Specific Comments:
Line 89: Define GNSS
Table 1: p5. Define ESC
Line 142: It would be helpful to annotate the image (Figure 1) or diagram (Figure 2) with where the INS is located, the sensor coordinates, the crossbar and the GNSS antennas. This is just for clarity.
Line 147: It would also be helpful to have a diagram of the pitch, yaw, roll and balance of the sling load configuration attachment to the UAS. Connecting the theoretical diagram (Figure 3) to the logistical attachment strategies and pendulum physics (Figure 2) is a key understanding of the novelty of this approach and a visual connection may assist the reader in discerning the language in this paragraph.
Line 186: Do you have any metric on the accuracy of the internal clock of the Raspberry pi? Is there drift or time compression?
Line 188: I do not understand the time adjustment for upside-down mounting orientation. If the measurements are instantaneous to an internal clock, why would time be a factor in transforming the phase space of the measurement. Please clarify.
Line 207: Explain the downsampling process from 50 Hz to 32 Hz. It would appear it would merely be a linear interpolation as the frequencies are too close for any averaging. If it is a smoothing function, please explain what that other smoothing function is.
Line 298 and Lines 402-405: If the flights s2, s3, and s4 have low mean flows and were not included in the quadrant analysis, please qualify the summative statements regarding the quadrant analysis for the assumptions required to apply it.
Citation: https://doi.org/10.5194/egusphere-2024-1548-RC2 -
AC2: 'Reply on RC2', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
-
AC2: 'Reply on RC2', Mauro Ghirardelli, 14 Feb 2025
-
EC1: 'Comment on egusphere-2024-1548, Anonymous Referee #2, 3 Dec 2024', Luca Mortarini, 03 Dec 2024
The Anonymous Referee #2 is experiencing technical problems in uploading is comments.
In agreement with the editorial board and on behalf of the reviewer, I am posting his/her review.
The PIF phenomenon consisting in the presence of strong induced turbulence around a drone-type UAV leads to significant issues in direct measurements of atmospheric parameters. The manuscript proposes an original way to minimize the effect of the PIF phenomenon in direct measurements by hanging a sonic anemometer under the drone as a sling load. The study is interesting, urgent, and relevant to the topic of Atmospheric Measurement Techniques. The results reported by the authors can be of great interest to AMT readers.
In my opinion, the below comments can help the authors to improve significantly the quality of the manuscript.
- Pages 1 and 2, Lines 7-9 and 57. The authors write that “This research aims to assess the accuracy and reliability of the developed measurement approach.” In my opinion, the statement that ‘The results demonstrate that SAMURAI-S matches the data quality of conventional setups for horizontal wind measurements while slightly overestimating vertical turbulence components. This overestimation increases as the wind speed increases” does not fully correspond to the purpose and results of the work. The authors should provide quantitative data on the discrepancy between Drone Data and Mast Data as a function of the increasing wind speed.
- Page 13, Line 253, Eq. (6). This equation should be corrected as Sw -> Suw.
- Pages 17 and 20, Figures 8 and 10. The sonic anemometer allows measuring actual wind speed and actual ambient temperature with high spatial and temporal resolution. The analysis of the measurement series depicted in Figures 8 and 10 should be supplemented with the correlation coefficients, the turbulence scale data, and the distance between the sonic anemometers installed on the drone and the mast. In addition, histograms of the discrepancy between Drone Data and Mast Data, as well as the Cumulative Percent, which characterize the statistics of the discrepancy between the data, should be presented. It will be interesting to readers how the measurement data differ from each other at the actual wind speed and temperature.
- It is desirable to provide the estimated spatial resolution so that a reader could evaluate possible applications of the reported technique.
The manuscript can be published in Atmospheric Measurement Techniques after revision with allowance made for the above comments. I believe that this will qualitatively improve both the clearness of the manuscript itself and the characteristics (accuracy, reliability, etc.) of the approach to monitoring atmospheric turbulence developed by the authors.
Citation: https://doi.org/10.5194/egusphere-2024-1548-EC1 -
AC3: 'Reply on EC1', Mauro Ghirardelli, 14 Feb 2025
We thank the reviewer for the comments and suggestions on the manuscript. In addition to this message, we have attached a PDF file that includes detailed responses to each comment and the manuscript with all modifications highlighted in red (deleted text) and blue (new text added).
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Mauro Ghirardelli
Stephan T. Kral
Etienne Cheynet
Joachim Reuder
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(19454 KB) - Metadata XML