The performance of the OTT second-generation Particle Size Velocity (PARSIVEL2) laser weather sensor is evaluated by comparing it with a collocated two-dimensional video disdrometer (2DVD) and rain gauges using data collected over a total of 36 rain events. A comparison of raindrop size distributions (DSDs) between the 2DVD and two PARSIVEL2 reveals good agreement for weak rainfall rates below approximately 10 mm h−1 and for midsize drops with diameters between 0.6 and 4.0 mm irrespective of rainfall rates, whereas the PARSIVEL2 produces overestimations of large drops with diameters above 4 mm during heavy rainfall above approximately 20 mm h−1. The resultant DSD parameters of the PARSIVEL2 present overestimations of the mean diameter Dm in the normalized gamma function and the maximum drop diameter Dmax, and underestimations of the intercept parameter Nw and total number of drops NT. Furthermore, how the characteristics of DSDs from the PARSIVEL2 affect the polarimetric radar variables, such as differential reflectivity ZDR and specific differential phase KDP, is examined, as well as how these characteristics affect empirical relations required in radar hydrometeorological applications such as quantitative rainfall estimations. Based on these examinations, it can be concluded that the OTT PARSIVEL2 still produces overestimations of large drops and underestimations of small drops during heavy rainfall, similar to older models of PARSIVEL, despite significant improvements to the PARSIVEL2 system, and furthermore that the uses of PARSIVEL2 measurements can act as a source of error in radar hydrometeorological applications such as radar rainfall estimations.

The Ministry of Land, Infrastructure and Transport (MOLIT) of South Korea operates two S-band dual-polarimetric radars, as of 2013, to manage water resources through quantitative rainfall estimations at the surface level. However, the radar measurements suffer from range ambiguity. In this study, an algorithm based on fuzzy logic is developed to identify range overlaid echoes using seven inputs: standard deviations of differential reflectivity SD(ZDR), differential propagation phase SD(ϕDP), correlation coefficient SD(ρHV) and spectrum width SD(συ), mean of ρHV and συ, and difference of ϕDP from the system offset ΔϕDP. An examination of the algorithm’s performance shows that these echoes can be well identified and that echoes strongly affected by second trip are highlighted by high probabilities, over 0.6; echoes weakly affected have probabilities from 0.4 to 0.6; and those with low probabilities, below 0.4, are assigned as echoes without range ambiguity. A quantitative analysis of a limited number of cases using the usual skill scores shows that when the probability of 0.4 is considered as a threshold for identifying the range overlaid echoes, they can be identified with a probability of detection of 90%, a false alarm rate of 6%, and a critical success index of 84%.