the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measuring diameters and velocities of artificial raindrops with a neuromorphic dynamic vision sensor disdrometer
Jan Steiner
Kire Micev
Asude Aydin
Jörg Rieckermann
Abstract. Hydrometers that can measure size and velocity distributions of precipitation are needed for research and corrections of rainfall estimates from weather radars and microwave links. Existing video disdrometers measure drop size distributions, but underestimate small raindrops and are impractical for widespread always-on IoT deployment. We propose an innovative method of measuring droplet size and velocity using a neuromorphic event camera. These dynamic vision sensors asynchronously output a sparse stream of pixel brightness changes. Droplets falling through the plane of focus create events generated by the motion of the droplet. Droplet size and speed are inferred from the stream of events. Using an improved hard disk arm actuator to reliably generate artificial raindrops, our experiments show small errors of 7 % (maximum mean absolute percentage error) for droplet sizes from 0.3 to 2.5 mm and speeds from 1.3 m/s to 8.0 m/s. Each droplet requires the processing of only a few hundred to thousands of events, potentially enabling low-power always-on disdrometers that consume power proportional to the rainfall rate.
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Jan Steiner et al.
Status: open (until 07 Jun 2023)
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RC1: 'Comment on egusphere-2023-215', Anonymous Referee #1, 29 Apr 2023
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The authors present a new technique for measuring size and velocity distributions of artificial raindrops. Overall, I think this is a worthwhile contribution to the field, but the paper needs clarifications in a few places. Further, the paper would benefit from comparisons to other instrumentation for field components of the paper.
The authors show small errors in droplet size and velocity. The technique used is simple in its concept, although there are issues that need to be addressed before it is ready to be used by the broader scientific community.
I recommend publication after a number of major issues are addressed in light of the comments below.
- Uncertainty in measurements, size, and velocity in natural/unnatural environments turbulence levels is missing. “In the limitation of experiments, occlusion would be a problem due to the optical arrangement, but the droplet tracks could merge or overlap”. What are the upper boundaries of raindrops concentration/turbulence where this technique work?
- The authors compare specifications of DVSD, 2DVD, and PARSIVEL, but my biggest concern with the paper is missed opportunity to compare DVSD to other (2DVD and PARSIVEL) common measurements in natural environmental conditions.
- If I understand correctly, Droplets must pass through the plane of focus Rectangle to measure size. Is there any analysis to estimate the percentage of droplets that missed the target (plane of focus)? What possible measurements if droplets move in the normal direction to the camera (0)?
- If you have additional scatter light by small particles, for example, fog particles. Will the measurements affected by it?
- As you mentioned that droplets must be fully inside of Fov for measurements. If droplets are partially inside the FoV, what is the logic to reject this, and how does this affect the uncertainty?
- Can you explain the logic of different sampling rates for different sizes? And is the sampling rate adjust itself in real time?
Minor comments:
Line 25-30: The other instruments for particle/rain droplet size distribution in all environmental conditions might be worth highlighting.
DEID disdrometer:
Dhiraj K Singh, S. Donovan, E.R. Pardyjak, and T. J. Garrett: A differential emissivity imaging technique for measuring hydrometeor mass and type, Atmos. Meas. Tech., 14, 6973–6990, https://doi.org/10.5194/amt-14-6973-2021, 2021, highlight article.
- N. Rees, Dhiraj K Singh, E.R. Pardyjak, and T. J. Garrett: Mass and density of individual frozen hydrometeors, Atmos. Chem. Phys., 14235–14250, https://doi.org/10.5194/acp-21-14235, 2021.
MASC: size and fall velocity of hydrometeors
Fitch, K. E., Hang, C., Talaei, A., and Garrett, T. J., 2020: Arctic observations and numerical simulations of surface wind effects on Multi-Angle Snowflake Camera measurements, Atmos. Meas. Tech., 14, 1127–1142.
Citation: https://doi.org/10.5194/egusphere-2023-215-RC1 -
RC2: 'Comment on egusphere-2023-215', Anonymous Referee #2, 29 May 2023
reply
This paper presents an innovative prototype that aims at measuring size and velocity of falling drops. The topic is relevant for the community and worth publication. However, I believe that some improvements are needed on the current version of the manuscript before publication. I identified three major issues: (i) comparison with measurements obtained with existing devices would greatly strengthen the described results. (ii) I found the paper sometimes hard to follow, while actually findind most of the answers in the supplementary material… hence I would suggest to transfer part of the content in the main document. (iii) A description of what occurs when multiple drops fall through the sampling area would be interesting. There is a picture on the supplementary material, but no clear description. Rough estimates of the potential frequency of such event given the sampling volume would also be relevant for the discussion.
Please find below more detailed comments:
- Section 2.1: I found this section rather difficult to read and believe that the content of the S1 (and maybe S3) would be better in the main manuscript to help the reader. The idea of waist of the hourglass shape of the outcome is clear, but I did not understand well how this shape is obtained from the actual output of the DVS. Some clarification would be helpful. Please also clarify how the drop velocity is assessed.
- Section 2.2: presenting at least briefly the IVDG here would be relevant for reader. Also, adding some details on the uncertainties associated with the size of the generated drops would be interesting (and not only in the supplementary material).
- I would suggest to transfer the content of S4 within the main document since it is very helpful for the reader to grasp how the experiment was actually conducted.
- l. 93-94 why only these drop sizes were tested and not also an intermediate one at 1-1.5 mm ?
- Figure 2: this might be a detail but I found the word “Ground truth” quite confusing since it corresponds to the expected size form a mass decrease of the water source in the drop generator which is actually (and obviously !) located at the “top” of the experiment and not on the ground… May be something like “size of generated drop” would reflect more the experiment.
- l. 163-166: It would be interesting to show how can better results be obtained via corrections to alpha and M estimates.
- Effect of the wind: the potential effect of wind in real outdoor conditions is briefly mentioned, but I believe that it should be better quantified so that the reader can better understand the real potential of this prototype.
- Section 3.1: this section would be much more relevant if it included some comparison with actual measurements from the prototype and the other disdrometers mentioned (or at least one of them).
Citation: https://doi.org/10.5194/egusphere-2023-215-RC2
Jan Steiner et al.
Data sets
Data Jan Steinera, Kire Miceva, Asude Aydin, Joerg Rieckermann, Tobi Delbruck https://drive.google.com/drive/folders/153C2YDQh-AFjdBd1kromg9BBv2esfq8e
Model code and software
Code Jan Steinera, Kire Miceva, Asude Aydin, Joerg Rieckermann, Tobi Delbruck https://drive.google.com/drive/folders/153C2YDQh-AFjdBd1kromg9BBv2esfq8e
Video supplement
Videos & Photos Jan Steinera, Kire Miceva, Asude Aydin, Joerg Rieckermann, Tobi Delbruck https://drive.google.com/drive/folders/153C2YDQh-AFjdBd1kromg9BBv2esfq8e
Video abstract
Project Website Jan Steinera, Kire Miceva, Asude Aydin, Joerg Rieckermann, Tobi Delbruck https://sites.google.com/view/dvs-disdrometer/home
Jan Steiner et al.
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