the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospheric visibility inferred from continuous-wave Doppler wind lidar
- 1ZX Lidars, The Old Barns, Fairoaks Farm, Hollybush, Ledbury, HR8 1EU, U.K.
- 2Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
- 1ZX Lidars, The Old Barns, Fairoaks Farm, Hollybush, Ledbury, HR8 1EU, U.K.
- 2Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Abstract. Atmospheric visibility, or meteorological optical range (MOR), is governed by light extinction by aerosols. State-of-the-art visibility sensors, such as employed in meteorological observatories and airports, infer MOR by either measuring transmittance or scattering. While these sensors yield robust measurements with reasonable accuracy (10 % to 20 %), they measure in situ. MOR from these sensors may thus not be representative of MOR further away, for example, under conditions with stratified aerosol types. This includes off-shore sites near the sea surface during conditions with advection fog, sea spray or mist. Elastic backscatter lidar can be used to measure light extinction and has previously demonstrated to be a powerful method to infer visibility. Lidar can measure visibility not just near the instrument, but further away (remotely) and single-ended, whilst capable of measuring profiles of MOR along atmospheric slant paths. Continuous-wave (CW) Doppler wind lidar systems make up one of the most widespread type of elastic backscatter lidar and are typically used in wind resource assessment. Using these existing platforms for remote and single-ended measurement of MOR-profiles could allow for new and valuable applications. However, the low light extinction associated with this type of lidar excludes the use of the extinction coefficient for MOR retrieval, but leaves the backscatter coefficient as a possible proxy for MOR, though with an accuracy expected to be inferior to the former method. We analysed backscatter data from CW wind lidar and co-measured MOR from visibility sensors from two campaigns (Cabauw, Netherlands and Pershore, United Kingdom) and found backscatter from CW wind lidar to be a viable proxy of MOR if calibrated against a visibility sensor. The expected accuracy of the method is low and of order of few kilometres. This means MOR from CW wind lidar could be used in safety uncritical problems, such as assessment of visibility of man-made objects, including wind turbines. The high sensitivity of the lidar backscatter to aerosol type and size distribution could open up additional applications, such as volcanic plume monitoring.
Manuel Queißer et al.
Status: open (until 10 Aug 2022)
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RC1: 'Comment on amt-2022-132', Anonymous Referee #2, 15 Jul 2022
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Here, visibility is estimated from a continuous-wave (CW) Doppler lidar and compared with visibility sensors at two locations: Cabauw, Netherlands and Pershore, United Kingdom. Retrieving visibility or aerosol backscatter from CW Doppler lidars would enable further studies with a widely-spread instrument type, which is currently not utilised to retrieve aerosol-related parameters. Therefore, I consider this manuscript within the scope of AMT.
Unfortunately, agreement between the CW Doppler lidar and visibility sensor is not very good, and it is questionable how useful this method would be. What is missing, is a more detailed analysis into the reasons for the observed discrepancy.
Major comments
I am not convinced that the observed differences are due to aerosol properties for the most part. Especially, since the backscatter coefficient retrieved from the CW Doppler lidar is not corrected for range, focus or attenuation. For instance, attenuated backscatter from ceilometers is considered to require calibration before use (e.g. Kotthaus et al., 2016; Hopkin et al., 2019). Also pulsed Doppler lidars require substantial post-processing for aerosol parameter retrievals (e.g. Vakkari et al., 2019; Pentikäinen et al., 2020). Please compare attenuated backscatter from CW Doppler lidar with attenuated backscatter from a reference instrument (e.g. ceilometer with proper post-processing).
Lines 218-220 “Towards lower visibilities, the dependence becomes increasingly nonlinear. Only visibilities of at least 4 km are considered, which helps to select a data range with reasonably linear correlation between backscatter and inverse visibility and excludes the impact of fog or cloud on the visiometer readings.” In my opinion, the low visibility end of the spectrum is even more interesting than > 4km range (e.g. fog detection). Please include <4km visibility in the analysis.
Specific comments
83-85 “The backscatter coefficient has a higher sensitivity to the size of the aerosols along the beam path and hence to the aerosol size distribution (SD) than the extinction coefficient.” Please provide reference.
103-105 “Due to the longer wavelength (~1550 nm) of most CW wind lidars compared with visible backscatter lidars described above, at normal working ranges (up to 300 m), the return signal is not sensitive to atmospheric extinction, but is practically governed by the backscatter coefficient only.” If visibility is low, I’d expect extinction to substantial. And for many applications low visibility is the interesting part. Can you indicate a visibility range when extinction can be ignored?
134-135 How good is the cloud removal algorithm? Has it been compared with a ceilometer for instance?
137 Please define “pi”.
180-181 “As stated above, the backscatter coefficients from the wind lidars are time series in units of 1.3×10-6 m-1 sr-1.” Please give backscatter in units of [m-1 sr-1] throughout the paper. Scaling by 1.3 x 10^6 makes it hard to follow the results.
Figure 2c seems identical to a photo in Knoop et al. (2021). Please indicate source and license to reproduce it.
204-205 “A typical value for ð¼ has been empirically determined as 1.4 for visibilities between 6 and 20 km (Nebuloni et al., 2005), which is adopted here.” Yet, on line 252-253 Angstrom exponent is changed to 2.0. Please give some more references to justify the selected Angstrom exponent and lidar ratio. At least Baars et al. (2016) and Illingworth et al. (2015) give some values for a few aerosol types, but there are probably better (and more recent) references.
209 Please check “Figure 3 3 shows”
225-226 “The nonlinearity of the visibility with backscatter could be attributed to different contributions to the average aerosol size distribution (Curcio et al., 1958).” I don’t quite understand what are the “different contributions” here, please clarify.
Figure 3: Please plot backscatter on logarithmic scale without the scaling factor.
265-269 Please provide a literature overview of lidar-retrieved Angstrom exponent and lidar ratio at Cabauw and Pershore, or similar environments, if measurements are not available for these sites.
279 “The lidar backscatter coefficient can be quite dynamic, changing by several factors within minutes.” Please specify which factors.
Figure 5 and 6 captions: please define “BS”.
309-310 “general observations of a vertically weakly exponential decrease in lidar signal strength (hence backscatter) that becomes significant above ~100 m agl.” Is this due to lack of range correction in the backscatter retrieval?
345-346 “A backscatter minimum around July has been measured with different CW wind lidars in other locations in the Northern Hemisphere.” Please add reference.
433-438 Are there any other studies that report similar seasonality for backscatter?
455-457 and 462-464 See e.g. Illingworth et al. (2015) and Baars et al. (2016) for range of values associated with different aerosol types. Please also check if you can find better references on the topic.
525-527 “For Cabauw, lidar backscatter derived visibility was found to be height dependent (Fig. 8), in line with the observation that under cloud free conditions backscatter from CW-wind lidar usually tends to slightly decrease with height in the lower part of the planetary boundary layer.” Is this due to lack of range correction in the backscatter retrieval?
References
Baars, H., Kanitz, T., Engelmann, R., Althausen, D., Heese, B., Komppula, M., Preißler, J., Tesche, M., Ansmann, A., Wandinger, U., Lim, J.-H., Ahn, J. Y., Stachlewska, I. S., Amiridis, V., Marinou, E., Seifert, P., Hofer, J., Skupin, A., Schneider, F., Bohlmann, S., Foth, A., Bley, S., Pfüller, A., Giannakaki, E., Lihavainen, H., Viisanen, Y., Hooda, R. K., Pereira, S. N., Bortoli, D., Wagner, F., Mattis, I., Janicka, L., Markowicz, K. M., Achtert, P., Artaxo, P., Pauliquevis, T., Souza, R. A. F., Sharma, V. P., van Zyl, P. G., Beukes, J. P., Sun, J., Rohwer, E. G., Deng, R., Mamouri, R.-E., and Zamorano, F.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, 2016.
Hopkin, E., Illingworth, A. J., Charlton-Perez, C., Westbrook, C. D., and Ballard, S.: A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds, Atmos. Meas. Tech., 12, 4131–4147, https://doi.org/10.5194/amt-12-4131-2019, 2019.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation, Bull. Amer. Meteor. Soc., 96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1, 2015.
Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, https://doi.org/10.5194/amt-14-2219-2021, 2021.
Kotthaus, S., O’Connor, E., Münkel, C., Charlton-Perez, C., Haeffelin, M., Gabey, A. M., and Grimmond, C. S. B.: Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers, Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, 2016.
Pentikäinen, P., O’Connor, E. J., Manninen, A. J., and Ortiz-Amezcua, P.: Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar, Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, 2020.
Vakkari, V., Manninen, A. J., O’Connor, E. J., Schween, J. H., van Zyl, P. G. and Marinou, E.: A novel post-processing algorithm for Halo Doppler lidars, Atmos. Meas. Tech., 12(2), 839–852, doi:10.5194/amt-12-839-2019, 2019.
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AC1: 'Reply on RC1', Manuel Queisser, 05 Aug 2022
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The authors would like to thank the reviewer for the time and effort taken to review this manuscript. It is very much appreciated. Please find the response attached.
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AC1: 'Reply on RC1', Manuel Queisser, 05 Aug 2022
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RC2: 'Comment on amt-2022-132', Anonymous Referee #1, 09 Aug 2022
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The manuscript suggests correlation between visibility measurements from in-situ visiometers and backscatter coefficient measurements from a continuous-wave wind Lidar. Datasets from two measurement campaigns are used, one in Cabauw (Netherlands) and one in Pershore (UK). The study falls into the scope of AMT. Yet, there are important differences between visibility from CW wind lidar and visiometers, arising from the different aerosol properties. Also, calibration of CW wind lidar against a visibility sensor in a similar mean aerosol scene area to the one of its intended use is necessary, creating limitations to future applications.
At L 104-106 when describing the CW wind lidars, it is said that “the return signal is not sensitive to atmospheric extinction, but is practically governed by the backscatter coefficient only. This leaves the backscatter coefficient as the most obvious proxy of visibility of a CW lidar.” Thought at L43 it has been mentioned that “by measuring light extinction σ, MOR can be derived”. Basically, it looks like the most important parameter is overlooked. Could you give more details on that?
L538-539 “This can be explained by different aerosol types and size distributions at play for different backscatter coefficients” I find it hard to understand the grammar of this sentence.
I think that the small agreement between CW Doppler lidar and visibility sensor measurements, mainly for Pershore, should be mentioned in the conclusions and briefly explain the reason of these differences.
Concerning the site specific differences, it should be mentioned that if backscatter from other types of instruments (e.g.ceilometers) was used, the same differences between the two sites would have arisen and also provide an example of correspondingly data. The site specific differences are very important and every site will present different aerosol scene and properties.
Since the study assesses if backscatter from CW wind lidar can be used to retrieve visibility, a conclusion about seasonality observed for backscatter in the two sites (Fig 10), along with the MOR connection to this seasonality, would be really helpful for the reader.
Have you checked what happens if you use Ct=2% in eq. (1)? Eg. (8) would change to 4/(β(π)S(λ1/λ0)α). Would this have an important effect on the results? Also, lidar ratio S is considered constant, but as also described in the manuscript, presents strong variability depending on the aerosol type. This should also be mentioned in the conclusions (L 537-544) along with the “less linear correlation”.
Manuel Queißer et al.
Manuel Queißer et al.
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