Ground-Based Measurements of Wind and Turbulence at Bucharest–Măgurele: First Results

Round 1

Reviewer 1 Report

The authors analyse the wind and turbulence statistics for a peri-urban site in Romania by means of Doppler wind lidar measurements. The results showed a diurnal cycle and the seasonal variability for the horizontal wind speed. The authors mentioned that it is the first time for Romania to measure wind speed by using Doppler wind lidar measurements. The structure of the article is well-organized. Some comments are listed below:

1.     Figure 2 is not found.

2.     The geographical location of the study area should be addressed and demonstrated by a figure.

3.     To improve the understanding of wind fields in study area for readers, the characteristics of climatological wind fields in different seasons should be described.

4.     More introduction of the PBL classification would be beneficial to readers to realize the classification scheme shown in line 149.

5.     The results show a similar pattern with those based on the ERA5 data. Does it mean that without Doppler wind lidar measurements, the ERA5 can also be used to do the same things? Therefore, I would like to suggest that the authors can demonstrate more about the contribution of the study and further potential application in session 6.

Author Response

Thank you for all the suggestions! All the corrections and additions are highlighted in blue (in both manuscript and below).

            Along with the modifications suggested by the reviewers, we also modified our funding and acknowledgements sections. I hope there will be no problems regarding this modifications.

1. Figure 2 is not found.

We are sorry for this issue, added in the manuscript.

2. The geographical location of the study area should be addressed and demonstrated by a figure.

Figure 1 was updated to include a geographical area of Măgurele, Romania.

2. To improve the understanding of wind fields in study area for readers, the characteristics of climatological wind fields in different seasons should be described.

Figure A2 in the Appendix A (ERA5 climatological wind speed) was introduced and commented at lines 244-248. Full description of the climatology is beyond the scope of this manuscript and will be investigated in future studies.

3. More introduction of the PBL classification would be beneficial to readers to realize the classification scheme shown in line 149.

In the current version of the manuscript there is a full description of the classification scheme as shown in Figure 2. Unfortunately, due to a oversight from our part this figure was not shown in the first version of the manuscript. We believe that this figure would add further clarification of the PBL classification scheme.

4. The results show a similar pattern with those based on the ERA5 data. Does it mean that without Doppler wind lidar measurements, the ERA5 can also be used to do the same things? Therefore, I would like to suggest that the authors can demonstrate more about the contribution of the study and further potential application in session 6.

For this particular site there is a very good agreement between the ERA5 data and Doppler lidar measurements. We agree with the reviewer that in the absence of a wind lidar ERA5 data can be used to retrieve the characteristics of wind fields at this particular site (obviously with lower temporal and vertical resolution). We have addressed the potential applications of this study at the end of section 6 together with further research directions. For example, we would like to investigate how the air flows are influenced by the UHI. Also, Doppler wind lidar will be further used in various pollution case studies or convective studies (added lines 330-331). 

Reviewer 2 Report

Authors presented an interesting study containing the results of lidar measurements and Era-5 dataset reanalysis. We highly appreciate the results obtained. However we have some questions and recommendations.

Major:

-The authors consider different states of the atmospheric boundary layer and say that this layer is not turbulent. Analyzing Figure 3, we see that the frequency of occurrence of Non−turbulent PBL class is very high. Of course, the authors consider the threshold criterion (the rate of dissipation of turbulent kinetic energy), but it is problematic to say that the atmospheric boundary layer is not turbulent, in our opinion. The atmosphere, and in particular the atmospheric boundary layer, is predominantly in a turbulent state, even at Richardson numbers exceeding 0.25 ( this regime may be referred as weak turbulence). With this in mind, we ask the authors to make corrections.

- It is necessary to discuss in the manuscript the lower altitude from which reliable measurements of atmospheric characteristics are possible (lidar cannot measure from 0 m?). May the lower altitude of measurements change?

- Moreover, we would like to note that the lidar is still a remote measuring instrument, and also that it must work in a turbid atmosphere. In this regard, the lidar cannot be sensitive to small-scale turbulence, say, to fluctuations with a size of 1 - 10 cm. In this regard, how do you define the atmospheric boundary layer?

- Also, it is important give more information in the study about cloud cover variations during the period of measurements. Can you add some figure?

Minor:

- Abstract. Lines 5-6. “The analyses showed a diurnal cycle for the horizontal wind speed, with lower values during day time.” You discuss a diurnal cycle for the horizontal wind speed. A diurnal cycle for the horizontal wind speed is not simple. For example, in the upper part of the atmospheric boundary layer (ABL), the wind speed is lowest during the day and highest at night (near surface, the behavior is reverse). Between the upper and lower parts of ABL there is a transitional layer in which the diurnal changes in wind speed are the smallest. Also, diurnal cycle has variations during the year. So, I think that it will be useful to indicate (in abstract), at least, the height, for which you consider a diurnal cycle.

-Abstract. Line 14. Please correct “the Intermittent” to “the intermittent”.

-Figure 2 is missing.

- In order to show that atmospheric parameters including turbulence characteristics may be estimated also by another remote sensing sensors, in Introduction it will be useful to consider the following papers:

i) Smalikho I.N., Banakh V.A., Falits A.V LIDAR INVESTIGATION OF WIND TURBULENCE ON THE COASTAL ZONE OF LAKE BAIKAL AT PRESENCE OF A LOW-LEVEL JET IN THE ATMOSPHERE / Proceedings of SPIE - The International Society for Optical Engineering. 2018. P. 108335A.

ii) Shikhovtsev, A.Y. A Method of Determining Optical Turbulence Characteristics by the Line of Sight of an Astronomical Telescope. Atmos Ocean Opt 35, 303–309 (2022). https://doi.org/10.1134/S1024856022030149

iii) Z. Wang, L. Zhang, and C. Rao, “Characterizing daytime wind profiles with the wide-field Shack-Hartmann wavefront sensor,” Mon. Not. R. Astron. Soc. 483 (4), 4910–4921 (2019).

Author Response

Thank you for all the suggestions! All the corrections and additions are highlighted in blue (in both manuscript and this document).

            Along with the modifications suggested by the reviewers, we also modified our funding and acknowledgements sections. I hope there will be no problems regarding this modifications.

Major:

-The authors consider different states of the atmospheric boundary layer and say that this layer is not turbulent. Analyzing Figure 3, we see that the frequency of occurrence of Non−turbulent PBL class is very high. Of course, the authors consider the threshold criterion (the rate of dissipation of turbulent kinetic energy), but it is problematic to say that the atmospheric boundary layer is not turbulent, in our opinion. The atmosphere, and in particular the atmospheric boundary layer, is predominantly in a turbulent state, even at Richardson numbers exceeding 0.25 ( this regime may be referred as weak turbulence). With this in mind, we ask the authors to make corrections.

Indeed, the rate of occurrence for non-turbulent PBL is high. Based on the current criteria developed in HALO software, this occurrence is typical. Please see similar values in Manninen et al (2018) figs. 8-11. Unfortunately, the further development of these routines is not in the scope of the current manuscript.

- It is necessary to discuss in the manuscript the lower altitude from which reliable measurements of atmospheric characteristics are possible (lidar cannot measure from 0 m?). May the lower altitude of measurements change?

We mentioned in the first paragraph of section 5 (lines 187-189 original manuscript, lines 192-194 new version of manuscript) that the first three bins were dismissed due to technical limitations of the instrument. Thus, the first altitude bin investigated was at approximately 100 m.

- Moreover, we would like to note that the lidar is still a remote measuring instrument, and also that it must work in a turbid atmosphere. In this regard, the lidar cannot be sensitive to small-scale turbulence, say, to fluctuations with a size of 1 - 10 cm. In this regard, how do you define the atmospheric boundary layer?

We agree with the reviewer that the small-scale turbulence is not caught by the lidar, which has a range resolution of 30 m. The PBL is determined based on the values of attenuated backscatter. Thus, PBL has non-zero values based on condition that SNR>=0.01. This threshold was defined previously by Manninen et al (2018) to filter the atmospheric lidar signal from noise. We referred to this aspect at lines 189-192 original manuscript, 194-197 new version of manuscript.

- Also, it is important give more information in the study about cloud cover variations during the period of measurements. Can you add some figure?

The contribution of cloud-driven class of PBL turbulence sources was small compared with the three principal classes shown in Figure 10 therefore the authors choose to not include this figure in the manuscript. Please note that cloud occurrences over the studied area were significant above 1500 m altitude (area not studied here). Moreover, a descriptive study of cloud characteristics over Măgurele was performed between December 2019-May 2021 by our group and already published (https://www.mdpi.com/2073-4433/13/9/1445).

Minor:

 - Abstract. Lines 5-6. “The analyses showed a diurnal cycle for the horizontal wind speed, with lower values during day time.” You discuss a diurnal cycle for the horizontal wind speed. A diurnal cycle for the horizontal wind speed is not simple. For example, in the upper part of the atmospheric boundary layer (ABL), the wind speed is lowest during the day and highest at night (near surface, the behavior is reverse). Between the upper and lower parts of ABL there is a transitional layer in which the diurnal changes in wind speed are the smallest. Also, diurnal cycle has variations during the year. So, I think that it will be useful to indicate (in abstract), at least, the height, for which you consider a diurnal cycle.

We have added the text as suggested except the comments of the transition layer. We think the reviewer referred to the artefact explained at line: 217 (original manuscript), 222-226 (new version of manuscript).

-Abstract. Line 14. Please correct “the Intermittent” to “the intermittent”.

Changed in the manuscript.

-Figure 2 is missing.

We are sorry for this issue, added in the manuscript.

- In order to show that atmospheric parameters including turbulence characteristics may be estimated also by another remote sensing sensors, in Introduction it will be useful to consider the following papers:

2018. i) Smalikho I.N., Banakh V.A., Falits A.V LIDAR INVESTIGATION OF WIND TURBULENCE ON THE COASTAL ZONE OF LAKE BAIKAL AT PRESENCE OF A LOW-LEVEL JET IN THE ATMOSPHERE / Proceedings of SPIE - The International Society for Optical Engineering. 2018. P. 108335A.
2019. ii) Shikhovtsev, A.Y. A Method of Determining Optical Turbulence Characteristics by the Line of Sight of an Astronomical Telescope. Atmos Ocean Opt 35, 303–309 (2022). https://doi.org/10.1134/S1024856022030149

iii) Z. Wang, L. Zhang, and C. Rao, “Characterizing daytime wind profiles with the wide-field Shack-Hartmann wavefront sensor,” Mon. Not. R. Astron. Soc. 483 (4), 4910–4921 (2019).

The following reference (Banakh, V.A.; Smalikho, I.N. Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer. Remote Sensing 2018, 10. https://doi.org/10.3390/rs10081219.) has been added in introduction (lines 56-58 new version of PDF). We would like to mention that we did not address the method of cross-correlation to determine the wind, and thus we have not included the other two references suggested by the reviewer.

Round 2

Reviewer 2 Report

Authors have made corrections, I agree with these corrections. I recommend this manuscript for publication.