the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Combined Wind Lidar and Cloud Radar for Wind Profiling
- 1Delft University of Technology
- 2Royal Netherlands Meteorological Institute
- 1Delft University of Technology
- 2Royal Netherlands Meteorological Institute
Abstract. This paper introduces an experimental setup for retrieving horizontal wind speed and direction profiles by combining wind lidar and cloud radars and the 2 level datasets produced. The experiment took place in Cabauw, the Netherlands, between September 13th and October 3rd 2021. The intermediate processing steps for generating the Level 1 and Level 2 data, such as second trip echos filtering, offset correction, wind retrieval, re-gridding and flagging, are described. In Level 1 (https://doi.org/10.5281/zenodo.6926483, Dias Neto (2022a)), the data from lidar and radars are kept in the original spatial and temporal resolution, while in Level 2 (https://doi.org/10.5281/zenodo.6926605, Dias Neto (2022b)), they are re-grided to a common spatial and temporal resolution. Statistical analyses of the lidar’s and radar’s wind speed and direction profiles indicate a correlation higher than 0.95 for both variables, and the bias of wind direction and speed are 0.24° and -0.16 ms−1, respectively. Applications of this dataset include numerical model validation, momentum transport studies and spectral analysis for different cloud regimes.
José Dias Neto et al.
Status: closed
-
RC1: 'Comment on essd-2022-268', Anonymous Referee #1, 19 Oct 2022
Review of the article titled “Combined wind lidar and cloud radar for wind profiling” by Neto and coauthors for publication in ACP.
The authors have used data collected by two scanning radars, and one scanning lidar to derive profiles of horizontal wind speed and direction. The derived winds are compared to those from the radiosondes, and from the lidar only for validation. The authors have further applied the technique to a case of frontal passage and evaluated the model’s performance in simulating the winds. The article is detailed and well-written, and the developed technique can be used for deriving winds at other locations as well. Below I am mentioning few things that can further improve the manuscript.
Major Concerns:
It is unclear to me why the authors have not used radar wind profilers (RWP). The RWP have been used for multiple decades now to derive winds and their backscatter is not that affected by hydrometeors unless it is heavy rain. The modern wind profilers also can sample much lower in the boundary layer (~50 m). Same is also true for SODAR. It will be much easier for your group to use RWP and SODAR rather than derive winds this manner. So I’d like to know the reasoning behind this, and at least some discussion in the article. Just to be clear, this has no bearing on the proposed technique and the rationale behind the article.
The winds derived from the PPI sequence (radar or lidar) have some inherent limitation on the uncertainty of the retrieved winds. As the derived winds assume that they do not change over the domain where the observations are collected. So in your FFWVA algorithm, the energy will go into other harmonics rather than the first. Can you please elaborate on this. There are too many references that have probed horizontal winds from the weather radars, so cannot mention one. But please look at publications from Chandra, Rizkov, kumjian etc. The horizontal domain over which the winds are derived, the vertical resolution, and temporal resolution are all very critical. It will be great if you can tell us the impact of very low winds, and very high winds on your retrieval technique. Lastly, Figure 14 shows rain echoes in excess of 20 dBz, so maybe you are looking at drops more than 1-2 mm in diameter. When viewed by a tilted radar axis these drops contribute some to the horizontal winds as they are carried by them due to shear. This also needs to be mentioned/explored. Uncertainties in these retrievals will finally determine how far off your model is and can potentially lead to inaccurate conclusions. Thanks.
Can you comment on how you discern Doppler lidar echoes that are from the insects, aerosols, and from the rain? This is a very important issue as it affects the wind determination. You are already mentioning the Wainwright paper for insects, I know of the Ghate et al. 2021 JAMC paper for the hydrometeors. This will affect results shown in Figure 17.
I still find it very hard to believe that insects are moving with horizontal wind as insects have been shown to stay near the water/vegetation. Do these insects just get blown away by the winds over the day, and hence things clear out? This way you’d need a lot of insects to be generated each day! It can be imagined that insects have very small impact on vertical wind, but not horizontal winds. See Chandra et al. 2010 JAS for radar retrievals from insect echoes.
Minor Concerns:
Figure 4: there is no red curve.
Line 240, define DFT.
Figure 11: Mention units.
Line 312: What is NHI?
- RC2: 'Comment on essd-2022-268', Anonymous Referee #2, 21 Oct 2022
-
AC1: 'Authors Comment on essd-2022-268', José Dias Neto, 05 Dec 2022
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2022-268/essd-2022-268-AC1-supplement.pdf
Status: closed
-
RC1: 'Comment on essd-2022-268', Anonymous Referee #1, 19 Oct 2022
Review of the article titled “Combined wind lidar and cloud radar for wind profiling” by Neto and coauthors for publication in ACP.
The authors have used data collected by two scanning radars, and one scanning lidar to derive profiles of horizontal wind speed and direction. The derived winds are compared to those from the radiosondes, and from the lidar only for validation. The authors have further applied the technique to a case of frontal passage and evaluated the model’s performance in simulating the winds. The article is detailed and well-written, and the developed technique can be used for deriving winds at other locations as well. Below I am mentioning few things that can further improve the manuscript.
Major Concerns:
It is unclear to me why the authors have not used radar wind profilers (RWP). The RWP have been used for multiple decades now to derive winds and their backscatter is not that affected by hydrometeors unless it is heavy rain. The modern wind profilers also can sample much lower in the boundary layer (~50 m). Same is also true for SODAR. It will be much easier for your group to use RWP and SODAR rather than derive winds this manner. So I’d like to know the reasoning behind this, and at least some discussion in the article. Just to be clear, this has no bearing on the proposed technique and the rationale behind the article.
The winds derived from the PPI sequence (radar or lidar) have some inherent limitation on the uncertainty of the retrieved winds. As the derived winds assume that they do not change over the domain where the observations are collected. So in your FFWVA algorithm, the energy will go into other harmonics rather than the first. Can you please elaborate on this. There are too many references that have probed horizontal winds from the weather radars, so cannot mention one. But please look at publications from Chandra, Rizkov, kumjian etc. The horizontal domain over which the winds are derived, the vertical resolution, and temporal resolution are all very critical. It will be great if you can tell us the impact of very low winds, and very high winds on your retrieval technique. Lastly, Figure 14 shows rain echoes in excess of 20 dBz, so maybe you are looking at drops more than 1-2 mm in diameter. When viewed by a tilted radar axis these drops contribute some to the horizontal winds as they are carried by them due to shear. This also needs to be mentioned/explored. Uncertainties in these retrievals will finally determine how far off your model is and can potentially lead to inaccurate conclusions. Thanks.
Can you comment on how you discern Doppler lidar echoes that are from the insects, aerosols, and from the rain? This is a very important issue as it affects the wind determination. You are already mentioning the Wainwright paper for insects, I know of the Ghate et al. 2021 JAMC paper for the hydrometeors. This will affect results shown in Figure 17.
I still find it very hard to believe that insects are moving with horizontal wind as insects have been shown to stay near the water/vegetation. Do these insects just get blown away by the winds over the day, and hence things clear out? This way you’d need a lot of insects to be generated each day! It can be imagined that insects have very small impact on vertical wind, but not horizontal winds. See Chandra et al. 2010 JAS for radar retrievals from insect echoes.
Minor Concerns:
Figure 4: there is no red curve.
Line 240, define DFT.
Figure 11: Mention units.
Line 312: What is NHI?
- RC2: 'Comment on essd-2022-268', Anonymous Referee #2, 21 Oct 2022
-
AC1: 'Authors Comment on essd-2022-268', José Dias Neto, 05 Dec 2022
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2022-268/essd-2022-268-AC1-supplement.pdf
José Dias Neto et al.
Data sets
The Tracing Convective Momentum Transport in Complex Cloudy Atmospheres Experiment - Level 2 José Dias Neto https://doi.org/10.5281/zenodo.6926605
The Tracing Convective Momentum Transport in Complex Cloudy Atmospheres Experiment - Level 1 José Dias Neto https://doi.org/10.5281/zenodo.6926483
José Dias Neto et al.
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