Articles | Volume 12, issue 11
Atmos. Meas. Tech., 12, 5845–5861, 2019
Atmos. Meas. Tech., 12, 5845–5861, 2019
Research article
08 Nov 2019
Research article | 08 Nov 2019

The Disdrometer Verification Network (DiVeN): a UK network of laser precipitation instruments

Ben S. Pickering et al.

Related authors

The NCAS mobile dual-polarisation Doppler X-band weather radar (NXPol)
Ryan R. Neely III, Lindsay Bennett, Alan Blyth, Chris Collier, David Dufton, James Groves, Daniel Walker, Chris Walden, John Bradford, Barbara Brooks, Freya I. Addison, John Nicol, and Ben Pickering
Atmos. Meas. Tech., 11, 6481–6494,,, 2018
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Instruments and Platforms
Instabilities, Dynamics, and Energetics accompanying Atmospheric Layering (IDEAL): high-resolution in situ observations and modeling in and above the nocturnal boundary layer
Abhiram Doddi, Dale Lawrence, David Fritts, Ling Wang, Thomas Lund, William Brown, Dragan Zajic, and Lakshmi Kantha
Atmos. Meas. Tech., 15, 4023–4045,,, 2022
Short summary
Infrasound measurement system for real-time in situ tornado measurements
Brandon C. White, Brian R. Elbing, and Imraan A. Faruque
Atmos. Meas. Tech., 15, 2923–2938,,, 2022
Short summary
Quantifying the coastal urban surface layer structure using distributed temperature sensing in Helsinki, Finland
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432,,, 2022
Short summary
On the quality of RS41 radiosonde descent data
Bruce Ingleby, Martin Motl, Graeme Marlton, David Edwards, Michael Sommer, Christoph von Rohden, Holger Vömel, and Hannu Jauhiainen
Atmos. Meas. Tech., 15, 165–183,,, 2022
Short summary
Idealized simulation study of the relationship of disdrometer sampling statistics with the precision of precipitation rate measurement
Karlie N. Rees and Timothy J. Garrett
Atmos. Meas. Tech., 14, 7681–7691,,, 2021
Short summary

Cited articles

Abel, S. J., Cotton, R. J., Barrett, P. A., and Vance, A. K.: A comparison of ice water content measurement techniques on the FAAM BAe-146 aircraft, Atmos. Meas. Tech., 7, 3007–3022,, 2014. a
Adolf Thies GmbH & Co. KG: Laser Precipitation Monitor – Instruction for Use, Tech. rep., Adolf Thies GmbH & Co. KG, Hauptstraße 76, 37083 Göttingen, Germany, 2011. a
Agnew, J.: Chilbolton Facility for Atmospheric and Radio Research (CFARR) Campbell Scientific PWS100 present weather sensor data, NCAS British Atmospheric Data Centre, available at: (last access: 7 August 2019), 2013. a
Al-Sakka, H., Boumahmoud, A. A., Fradon, B., Frasier, S. J., and Tabary, P.: A new fuzzy logic hydrometeor classification scheme applied to the french X-, C-, and S-band polarimetric radars, J. Appl. Meteorol. Climatol., 52, 2328–2344,, 2013. a
Chandrasekar, V., Bringi, V., Balakrishnan, N., and Zrnić, D.: Error structure of multiparameter radar and surface measurements of rainfall, Part III: Specific differential phase, J. Atmos. Ocean Tech., 7, 621–629,<0621:ESOMRA>2.0.CO;2, 1990. a
Short summary
A new network of precipitation instruments has been established for the UK. The instruments are capable of detecting the fall velocity and diameter of each particle that falls through a laser beam. The particle characteristics are derived from the duration and amount of decrease in beam brightness as perceived by a receiving diode. A total of 14 instruments make up the network and all instruments upload 60 s frequency data in near-real time to a publicly available website with plots.