the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Two new multirotor UAVs for glaciogenic cloud seeding and aerosol measurements within the CLOUDLAB project
Anna J. Miller
Fabiola Ramelli
Christopher Fuchs
Nadja Omanovic
Robert Spirig
Huiying Zhang
Ulrike Lohmann
Zamin A. Kanji
Jan Henneberger
Abstract. Uncrewed Aerial Vehicles (UAVs) have become widely used in a range of atmospheric science research applications. Because of their small size, flexible range of motion, adaptability, and low cost, multirotor UAVs are especially well-suited for probing the lower atmosphere. However, their use so far has been limited to conditions outside of clouds, first because of the difficulty of flying beyond visual line of sight, and second because of the challenge of flying in icing conditions in supercooled clouds. Here, we present two UAVs for cloud microphysical research: one UAV (the measurement UAV) equipped with a Portable Optical Particle Spectrometer (POPS) and meteorological sensors to probe the aerosol and meteorological properties in the boundary layer, and one UAV (the seeding UAV) equipped with seeding flares to produce a plume of particles that can initiate ice in supercooled clouds. A propeller heating mechanism on both UAVs allows for operating in supercooled clouds with icing conditions. These UAVs are an integral part of the CLOUDLAB project in which glaciogenic cloud seeding of supercooled low stratus clouds is utilized for studying aerosol-cloud interactions and ice crystal formation and growth. In this paper, we first show validations of the POPS onboard the measurement UAV, demonstrating that the rotor turbulence has a negligible effect on aerosol measurements. We exemplify its applicability for profiling the planetary boundary layer, as well as for sampling and characterizing aerosol plumes, in this case, the seeding plume. We explain the different flight patterns that are possible for both UAVs, namely horizontal or vertical leg patterns or hovering, with an extensive and flexible parameter space for designing the flight patterns according to our scientific goals. Finally, we show two examples of seeding experiments: first characterizing an out-of-cloud seeding plume with the measurement UAV flying horizontal transects through the plume, and second, characterizing an in-cloud seeding plume with downstream measurements with POPS on a tethered balloon. Particle concentrations and size distributions of the seeding plume from the experiments reveal that we can successfully produce and measure the seeding plume, both in-cloud and out-of-cloud. The methods presented here will be useful for probing the lower atmosphere, for characterizing aerosol plumes, and for deepening our cloud microphysical understanding through cloud seeding experiments, all of which have the potential to benefit the atmospheric science community.
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Anna J. Miller et al.
Status: open (until 27 Sep 2023)
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RC1: 'Comment on amt-2023-157', Anonymous Referee #1, 12 Sep 2023
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General comment
In the presented manuscript, Miller et al. showed the feasibility of initiating and observing an aerosol particle plume with uncrewed platforms that are intended for cloud seeding experiments. One of two newly developed uncrewed aerial vehicles (UAVs) handles the burning of flares used as the particle source for cloud seeds. Another UAV serves as a platform for measuring the released aerosol particles with an optical particle size spectrometer (OPSS). The major novelty of the two UAVs is their capability to be operational inside clouds and under icing conditions. An additional tethered balloon system was used as a second reference for measuring the aerosol plume created by the flares with another OPSS of the same type as the one onboard the UAV. It was successfully demonstrated that the measurement UAV and the TBS system captured the particles sourced by the seeding UAV inside and outside of clouds. The manuscript is generally well-written, has a good structure, and the figures are well-illustrated. Therefore, the work adds a valuable contribution to the atmospheric measurement community and is suitable for publication in AMT with minor revisions.
However, more emphasis should be given to the aerosol sampling methods with the OPSS onboard the UAV and the TBS. There are generalized conclusions about the negligible impact of the UAV rotors on aerosol sampling that are not entirely demonstrated and doubtful. The two aerosol properties particle number concentration (N) and particle number size distribution (PNSD) provided by the OPSS are partly mixed, leading to conclusions that are true for one but not for the other variable. The authors need to consider that the PNSD covers several orders of magnitude in N from the smallest to the largest size bin. Losses of larger particles do not have a large effect on N but on the PNSD and its derivatives volume and mass size distribution. These derivatives are highly relevant for optical closure studies with remote sensing observations or for air quality measures. Therefore, the authors need to clearly separate and specify when speaking of measurement uncertainties. In this context, an essential characterization of inlet sampling efficiencies for varying particle diameters depending on wind speed and UAV ascent/descent rate or horizontal speeds needs to be added.
Detailed comments
Title: the general recommendation is to avoid abbreviations in titles
Line 11 – 12: The negligible effect of rotor turbulence was not sufficiently demonstrated for particle number size distribution measurements and the statement is contradictory to Liu et al. 2021
Line 17 -18: please specify here and in the following as particle number concentration and particle number size distribution
Line 24- 25: airborne observations are certainly not needed to calibrate remote sensing measurements
Line 47: please remove the URL of Meteomatics and transfer it to the references
Line 52: only the year of the publications should be in brackets
Line 64: the acronym CLOUDLAB needs to be introduced
Line 83: 90 km h-1 is the common abbreviation used at Copernicus
Line 113: 5 cm above rotor level seems low in comparison to other studies to avoid turbulence sufficiently. Please discuss your design in comparison with other studies and provide an analytical sampling efficiency estimation of the inlet for typical wind speed, ascent/descent rates, and horizontal velocity above ground
Line 173: What means instrument variability? Uncertainty in particle number concentration measurements against reference instruments or inter-unit variability? To what time resolution does it refer, 1 Hz data? If the uncertainty refers to particle number concentration, it cannot be derived from average deviations across each size bin as presented in Appendix A1. Particle numbers at small sizes are orders of magnitude higher compared to larger sizes. Thus the uncertainty per bin has to be set in relation to the number concentration in each bin. It is better to compare integrated particle numbers across the whole size range.
Line 174-175: The method presented in Appendix A2 seems not sufficient to derive a general uncertainty of 50 % for each size bin. Please discuss the difference in your findings from other studies e.g. Liu et al. 2021 or Pilz et al. 2022
Line 188-190: the turbulence created by hovering is certainly different from that created during ascent/descent or horizontal movement of the UAV, thus the conclusion seems not sufficiently supported
Line 194-195: the difference are hard to derive on a logarithmic scale, but it seems that deviations between sampling with and without rotors near the inlet are up to a factor of two for particle diameters above 800 nm. This could become relevant when deriving particle properties from the number size distribution, e.g. volume size distribution for optical closure studies e.g. Düsing et al. 2021 (https://doi.org/10.5194/acp-21-16745-2021)
Line 201: ascending/descending rates of 10 ms-1 can significantly reduce sampling efficiency of supermicron particles depending on the inlet geometry. Please provide an analytical estimate
Line 218: rotor downwash does not appear neglectable in general, it rather depends on averaging altitude range and ascending/descending rates. Also, the variations in particle number concentration in Fig. B1 appear somewhat higher during descent than during ascent, thus indicating effects from downwash
Line 219-225: that appears as a valuable extension of the POPS usage and should therefore be part of the main manuscript
Fig. 6 (b): please specify particle number concentration on x-axis
Line 242: please briefly discuss the uncertainty of the POPS, e.g. relation of sampling frequency of 1 Hz and ascent/descent rate of 10 ms-1 including measurement uncertainty for 1 Hz data. Is the ascent/descent rate appropriate for profiling? Would it be useful to average ascent and descent profiles of particle number concentration to one profile like for temperature and humidity (which are sampled at 10 Hz)
Line 241: can the measurement UAV really characterize a ceilometer? It is rather a complementary method
Fig. 9: please specify particle number concentration on y-axis
Fig 10 (a): the plot would benefit from an additional line showing the time-height series of the balloon with the height scale on the right y-axis
Line 319: The cloud droplets appear quite small if they are measured by the POPS. Are there measures that support this hypothesis, e.g. cloud droplet diameter derived from the cloud radar, or relative humidity measurements of the POPS sample stream
Line 326: please provide additional information on the inlet of the POPS TBS . Airborne particle measurements should assure sample air relative humidity below 40 % to provide the dry particle diameter by heating or using a dryer
Line 334-335: this conclusion is not sufficiently supported
Line 339: particle number size distributions during profiling were not shown
Line 344: without proper estimations of uncertainties for particle number size distribution measurements and information about the sample air relative humidity, the system can certainly not serve as a “benchmark” to validate remote sensing retrievals
Line 361: it was not shown that microphysical changes within the plume can be assessed
Line 371: PSL suspensions (not solutions) should only be produced with distilled water
Line 377-378: The comparison to the findings by Pilz et al. 2022 is methodologically wrong. They reported comparisons of total particle number concentration measured by a POPS against a reference CPC for specific PSL sizes filtered by a DMA and not the uncertainties in single size bins measured at undefined aerosols. Pilz et al. concluded average uncertainties for particle number concentration in the range of Gao and Mynard and not up to 110%.
Line 385: how are the corresponding particle diameters are selected from the SMPS and APS? The geometric centers of each bin are certainly different across the instruments
Line 407: was the flow rate of 0.9 cm³ s-1 used for all measurements? This very low flow has certainly an effect on the sampling efficiency of supermicron particles
Citation: https://doi.org/10.5194/amt-2023-157-RC1
Anna J. Miller et al.
Anna J. Miller et al.
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