Preprints
https://doi.org/10.5194/egusphere-2023-215
https://doi.org/10.5194/egusphere-2023-215
17 Apr 2023
 | 17 Apr 2023

Measuring diameters and velocities of artificial raindrops with a neuromorphic dynamic vision sensor disdrometer

Jan Steiner, Kire Micev, Asude Aydin, Jörg Rieckermann, and Tobi Delbruck

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.

Jan Steiner et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-215', Anonymous Referee #1, 29 Apr 2023
    • AC1: 'Reply on RC1', Tobi Delbruck, 21 Sep 2023
  • RC2: 'Comment on egusphere-2023-215', Anonymous Referee #2, 29 May 2023
    • AC2: 'Reply on RC2', Tobi Delbruck, 21 Sep 2023
  • AC3: 'Comment on egusphere-2023-215', Tobi Delbruck, 19 Oct 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-215', Anonymous Referee #1, 29 Apr 2023
    • AC1: 'Reply on RC1', Tobi Delbruck, 21 Sep 2023
  • RC2: 'Comment on egusphere-2023-215', Anonymous Referee #2, 29 May 2023
    • AC2: 'Reply on RC2', Tobi Delbruck, 21 Sep 2023
  • AC3: 'Comment on egusphere-2023-215', Tobi Delbruck, 19 Oct 2023

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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Short summary
This paper reports a novel rain droplet measurement device that uses a neuromorphic event camera to measure droplet sizes and speeds as they fall through a shallow plane of focus. Experimental results report accuracy similar to state-of-the-art video disdrometers. Because these measurements are driven by event camera activity, this approach could enable the economical deployment of ubiquitous networks of solar-powered disdrometers.