Disdrometer

About: Disdrometer is a research topic. Over the lifetime, 930 publications have been published within this topic receiving 23092 citations.

Increasing the Rainfall Kinetic Energy of Spray Nozzles by using Meshes

Abstract: Rainfall simulators are an important tool in studying soil erosion, which is a key process contributing to land degradation. The kinetic energy of simulated rain is central to these studies and it is used as an indicator of the raindrops' ability to detach particles from the soil surface. The main purpose of this experimental work was to explore the usefulness of incorporating meshes underneath pressurised nozzles' rain simulators that intercept the drops sprayed out by the nozzles and change the simulated rain characteristics, namely by increasing the rainfall kinetic energy. The laboratory experiments included testing four types of spray nozzles (discharge from 2·3 to 11·9 L min−1), combined with a high-density polyethylene mesh (square aperture of 20 mm). The effect of the mesh was studied for three vertical distances between the nozzle and the mesh (0·20, 0·40 and 0·60 m). A laser disdrometer was used to measure the diameter and fall speed of the simulated raindrops. For the mesh-free simulations, the nozzles produced drops having on average a mean equivalent diameter of around 0·6 mm and a mean fall speed of about 1·5 m s−1. The mesh increased the formation of bigger drops (>2·5 mm) and, consequently, increased the rainfall kinetic energy of the simulated rain; the magnitude of this increase varied with the spray produced by the nozzles. Results show that meshes can be useful for increasing the kinetic energy of the rainfall simulated by nozzles within soil erosion studies. Copyright © 2015 John Wiley & Sons, Ltd.

Snow Particle Size Distribution From a 2-D Video Disdrometer and Radar Snowfall Estimation in East China

Abstract: In this study, as part of an effort to study snowfall characteristics and quantify winter precipitation in East China, we investigated the microphysical properties of snowfall, including size, shape, density, and terminal velocity using a 2-D video disdrometer (2-DVD) and a weighing precipitation gauge in Nanjing (NJ), East China during the winters of 2015–2019. We obtained larger snow density and terminal velocity values than those reported in the literature for this region. Higher snow density could account for higher snowflake terminal velocity, after removing the effects of observation altitude and surface temperature. We then fit the snow particle size distributions (PSDs) to the gamma model and explored the interrelationships among the model parameters and snowfall rate (SR). The relationship between radar reflectivity factor ( $Z_{e}$ ) and SR was derived based on snow PSD measurements and the snow density relation. Using this $Z_{e}-\mathrm {SR}$ relationship, the estimated liquid-equivalent SRs are obtained from S-band NJ radar data collected during several snowfall events. Radar-inferred SRs showed reasonable agreement with those measured on the ground, with a mean absolute error of 16% for the collected snowfall events in NJ.

Estimating radar reflectivity - snowfall rate relationships and their uncertainties over Antarctica by combining disdrometer and radar observations

Abstract: Abstract Snowfall rate (SR) estimates over Antarctica are sparse and characterised by large uncertainties. Yet, observations by precipitation radar offer the potential to get better insight in Antarctic SR. Relations between radar reflectivity (Ze) and snowfall rate (Ze-SR relations) are however not available over Antarctica. Here, we analyse observations from the first Micro Rain Radar (MRR) in Antarctica together with an optical disdrometer (Precipitation Imaging Package; PIP), deployed at the Princess Elisabeth station. The relation Ze = A*SR B was derived using PIP observations and its uncertainty was quantified using a bootstrapping approach, randomly sampling within the range of uncertainty. This uncertainty was used to assess the uncertainty in snowfall rates derived by the MRR. We find a value of A = 18 [11–43] and B = 1.10 [0.97–1.17]. The uncertainty on snowfall rates of the MRR based on the Ze-SR relation are limited to 40%, due to the propagation of uncertainty in both Ze as well as SR, resulting in some compensation. The prefactor (A) of the Ze-SR relation is sensitive to the median diameter of the snow particles. Larger particles, typically found closer to the coast, lead to an increase of the value of the prefactor (A = 44). Smaller particles, typical of more inland locations, obtain lower values for the prefactor (A = 7). The exponent (B) of the Ze-SR relation is insensitive to the median diameter of the snow particles. In contrast with previous studies for various locations, shape uncertainty is not the main source of uncertainty of the Ze-SR relation. Parameter uncertainty is found to be the most dominant term, mainly driven by the uncertainty in mass-size relation of different snow particles. Uncertainties on the snow particle size distribution are negligible in this study as they are directly measured. Future research aiming at reducing the uncertainty of Ze-SR relations should therefore focus on obtaining reliable estimates of the mass-size relations of snow particles.