Starting in February 2017, a network of 14 Thies™ manufactured Laser Precipitation Monitors (LPMs) were installed at various locations around the United Kingdom to create the Disdrometer Verification Network (DiVeN). The instruments were installed for verification of radar hydrometeor classification algorithms but are valuable for much wider use in the scientific and operational meteorological community.

Every Thies LPM is able to designate each observed hydrometeor into one of 20 diameter bins from >= 0.125 mm to > 8 mm, and one of 22 speed bins from > 0.0 m s-1 to > 20.0 m s-1. A laser and diode receiver operate in tandem; a falling particle will occlude the beam. The duration of the occlusion and the maximum extent (measured by diode voltage) determines the fall velocity and diameter respectively. Using empirically-derived relationships, the instrument classifies precipitation into one of 11 possible hydrometeor classes in the form of a 'present weather code', with an associated indicator of uncertainty. To provide immediate feedback to data users, the observations are plotted in near real time (NRT) and made publicly available on a website within 7 minutes (see linked documentation section). A 'present weather code' is a World Meteorological Organisation (WMO) code used to define the present observatory weather (see linked documentation for the WMO present weather code list).

The instruments belonged to the Met Office but were loaned to the National Centre for Atmospheric Science (NCAS) for the duration of the project. NCAS handle the receiving server for real-time DiVeN data, which is the only route to this dataset. On-site collection of data are not guaranteed in all circumstances. Some of the sites rely on unreliable O2 3G dongles; whilst the Feshie instrument was solar and wind powered and the Coverhead instrument suffered from power / connectivity issues. Any missing data can be explained by these reasons, and are handled appropriately in the files. The data were collated into daily files of 1440 minutes. More information can be found in Pickering et al., 2018, see related documentation.