Effect of disdrometer type on rain drop size distribution characterisation: a new dataset for south-eastern Australia

Knowledge of the full rainfall drop size distribution (DSD) is critical for characterising liquid water precipitation for applications such as rainfall retrievals using electromagnetic signals and atmospheric model parameterisation. Southern Hemisphere temperate latitudes have a lack of DSD observations and their integrated variables. Laser-based disdrometers rely on the attenuation of a beam by falling particles and are currently the most commonly used type of instrument to observe the DSD. However, there remain questions on the accuracy and variability in the DSDs measured by co-located instruments, whether identical models, different models or from different manufacturers. In this study, raw and processed DSD observations obtained from two of the most commonly deployed laser disdrometers, namely the Parsivel1 from OTT and the Laser Precipitation Monitor (LPM) from Thies Clima, are analysed and compared. Four co-located instruments of each type were deployed over 3 years from 2014 to 2017 in the proximity of Melbourne, a region prone to coastal rainfall in south-eastern Australia. This dataset includes a total of approximately 1.5 million recorded minutes, including over 40 000 min of quality rainfall data common to all instruments, equivalent to a cumulative amount of rainfall ranging from 1093 to 1244 mm (depending on the instrument records) for a total of 318 rainfall events. Most of the events lasted between 20 and 40 min for rainfall amounts of 0.12 to 26.0 mm. The co-located LPM sensors show very similar observations, while the co-located Parsivel1 systems show significantly different results. The LPM recorded 1 to 2 orders of magnitude more smaller droplets for drop diameters below 0.6 mm compared to the Parsivel1, with differences increasing at higher rainfall rates. The LPM integrated variables showed systematically lower values compared to the Parsivel1. Radar reflectivity–rainfall rate (ZH–R) relationships and resulting potential errors are also presented. Specific ZH–R relations for drizzle and convective rainfall are also derived based on DSD collected for each instrument type. Variability of the DSD as observed by co-located instruments of the same manufacturer had little impact on the estimated ZH–R relationships for stratiform rainfall, but differs when considering convective rainfall relations or ZH–R relations fitted to all available data. Conversely, disdrometer-derived ZH–R relations as compared to the Marshall–Palmer relation ZH=200R