vdis: Video Disdrometer

A disdrometer measures the drop size distribution and velocity of falling hydrometeors.

The 2-dimensional video-disdrometer (VDIS) comprises video cameras capable of observing individual hydrometeors from views perpendicular to each other. Two CCD line scan cameras are directed towards the measurement area. Objects passing through the measurement area—which is determined by the cross-section of the two optical paths as seen from above—obstruct the light and are detected as shadows by the cameras.

Each camera contains a small embedded computer responsible for handling the data-capture process, analysis of the data, and its conversion and compression into a format suitable for further processing. Subsequently the data are transferred to the computer used for instrument control and final analysis.

In order to identify individual precipitation particles by matching their views as seen by each of the cameras, it is necessary to synchronize the shutter and control both cameras with a synchronous line trigger signal.

To reconstruct observables like falling velocity, oblateness, etc. from the datastreams of the two cameras, the two optical paths are displaced vertically by about 6mm, typically. Measuring this distance and adjusting the background illumination are the two major calibration and maintenance tasks necessary for successful operation of the device.



  • Fixed
  • AMF1
  • AMF2
  • AMF3

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Louf V, A Protat, R Warren, S Collis, D Wolff, S Raunyiar, C Jakob, and W Petersen. 2019. "An integrated approach to weather radar calibration and monitoring using ground clutter and satellite comparisons." Journal of Atmospheric and Oceanic Technology, 36(1), 10.1175/JTECH-D-18-0007.1.
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Morrison H, M Kumjian, C Martinkus, O Prat, and M van Lier-Walqui. 2018. " A general -moment normalization method for deriving rain drop size distribution scaling relationships ." Journal of Applied Meteorology and Climatology, , 10.1175/JAMC-D-18-0060.1. ONLINE.

Kumjian M, C Martinkus, O Prat, S Collis, M van Lier-Walqui, and H Morrison. 2018. "A Moment-based Polarimetric Radar Forward Operator for Rain Microphysics." Journal of Applied Meteorology and Climatology, , 10.1175/JAMC-D-18-0121.1. ONLINE.


Tokay A, L D’Adderio, F Porcù, D Wolff, and W Petersen. 2017. "A Field Study of Footprint-Scale Variability of Raindrop Size Distribution." Journal of Hydrometeorology, 18(12), 10.1175/JHM-D-17-0003.1.

Bartholomew MJ. 2017. Two-Dimensional Video Disdrometer (VDIS) Instrument Handbook. Ed. by Robert Stafford, ARM Research Facility. DOE/SC-ARM-TR-111.

Cadeddu M, R Marchand, E Orlandi, D Turner, and M Mech. 2017. "Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities." IEEE Transactions on Geoscience and Remote Sensing, 55(11), 10.1109/TGRS.2017.2728699.

Testik FY and B Pei. 2017. "Wind Effects on the Shape of Raindrop Size Distribution." Journal of Hydrometeorology, 18(5), 10.1175/JHM-D-16-0211.1.

von Lerber A, D Moisseev, L Bliven, W Petersen, A Harri, and V Chandrasekar. 2017. "Microphysical properties of snow and their link to Ze–S relation during BAECC 2014." Journal of Applied Meteorology and Climatology, 56(6), 10.1175/JAMC-D-16-0379.1.


Giangrande SE, T Toto, MP Jensen, M Bartholomew, Z Feng, A Protat, C Williams, C Schumacher, and L Machado. 2016. "Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5." Journal of Geophysical Research: Atmospheres, 121(21), 10.1002/2016jd025303.
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Jensen MP, WA Petersen, A Bansemer, N Bharadwaj, LD Carey, DJ Cecil, SM Collis, AD Del Genio, B Dolan, J Gerlach, SE Giangrande, G Heymsfield, P Kollias, TJ Lang, SW Nesbitt, A Neumann, M Poellot, SA Rutledge, M Schwaller, A Tokay, CR Williams, DB Wolff, S Xie, and EJ Zipser. 2016. "The Midlatitude Continental Convective Clouds Experiment (MC3E)." Bulletin of the American Meteorological Society, 97(9), 10.1175/bams-d-14-00228.1.
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