Retrieving Rain Drop Size Distribution Moments from GPM Dual-Frequency Precipitation Radar

A novel method for retrieving the moments of rain drop size distribution (DSD) from the dual-frequency precipitation radar (DPR) onboard the global precipitation mission satellite (GPM) is presented. The method involves the estimation of two chosen reference moments from two specific DPR products, namely the attenuation-corrected Ku-band radar reflectivity and (if made available) the specific attenuation at Ka-band. The reference moments are then combined with a function representing the underlying shape of the DSD based on the generalized gamma model. Simulations are performed to quantify the algorithm errors. The performance of methodology is assessed with two GPM-DPR overpass cases over disdrometer sites, one in Huntsville, Alabama and one in Delmarva peninsula, Virginia, both in the US. Results are promising and indicate that it is feasible to estimate DSD moments directly from DPR-based quantities.

Influence of drop size distribution and kinetic energy in precipitation modelling for laboratory rainfall simulators

It is difficult to define the hydrologic and hydraulic characteristics of rain for research purposes, especially when trying to replicate natural rainfall using artificial rain on a small laboratory scale model. The aim of this paper was to use a drip-type rainfall simulator to design, build, calibrate, and run a simulated rainfall. Rainfall intensities of 40, 60 and 80 mm/h were used to represent heavy rainfall events of 1-hour duration. Flour pellet methods were used to obtain the drop size distribution of the simulated rainfall. The results show that the average drop size for all investigated rainfall intensities ranges from 3.0–3.4 mm. The median value of the drop size distribution or known as D50 of simulated rainfall for 40, 60 and 80 mm/h are 3.4, 3.6, and 3.7 mm, respectively. Due to the comparatively low drop height (1.5 m), the terminal velocities monitored were between 63–75 % (8.45–8.65 m/s), which is lower than the value for natural rainfall with more than 90 % for terminal velocities. This condition also reduces rainfall kinetic energy of 25.88–28.51 J/m2mm compared to natural rainfall. This phenomenon is relatively common in portable rainfall simulators, representing the best exchange between all relevant rainfall parameters obtained with the given simulator set-up. Since the rainfall can be controlled, the erratic and unpredictable changeability of natural rainfall is eliminated. Emanating from the findings, drip-types rainfall simulator produces rainfall characteristics almost similar to natural rainfall-like characteristic is the main target.

Impact of hygroscopic seeding on the initiation of precipitation formation: results of a hybrid bin microphysics parcel model

A hybrid bin microphysical scheme is developed in a parcel model framework to study how natural aerosol particles and different types of hygroscopic seeding materials affect the precipitation formation. A novel parameter is introduced to describe the impact of different seeding particles on the evolution of the drop size distribution. The results of more than 100 numerical experiments using the hybrid bin parcel model show that (a) the Ostwald-ripening effect has a substantial contribution to the broadening of the drop size distribution near the cloud base. The efficiency of this effect increases as the updraft velocity decreases. (b) The efficiency of hygroscopic seeding is significant only if the size of the seeding particles is in the coarse particle size range. The presence of the water-soluble background coarse particles reduces the efficiency of the seeding, (c) The efficient broadening of the size distribution due to the seeding depends on the width of the size distribution of water drops in the control cases, but the relation is not as straightforward as in the case of the glaciogenic seeding.

Modelling Spray Pressure Effects on Droplet Size Distribution from Agricultural Nozzles

For spray applications, drop size is the most important feature as it affects all aspects of a phytosanitary treatment: biological efficacy, environmental pollution, and operator safety. In turn, drop size distribution depends on nozzle type, liquid properties, and working pressure. In this research, three nozzles were studied under ordinary working conditions and the effect of pressure on drop size distribution was assessed. The nozzles under test, all from Albuz (France), were an orange hollow cone nozzle ATR 80 (European color code), an air induction flat spray nozzle AVI 11003, and an air induction hollow cone nozzle TVI 8002. The ATR 80 and the TVI 8002 nozzles were tested at four pressure values: 0.3, 0.5, 1.0, and 1.5 MPa; the AVI 11003 nozzle was tested at 0.3 and 0.5 MPa. The drop size measurement technique was based on the liquid immersion method by using a custom-made test bench; spray quality parameters were computed by means of suitable functions written in R language. Results showed that an increase in working pressure caused an increase in drop pulverization regardless of the type of nozzle, and drop pulverization was higher for the turbulence nozzle than for the two air induction nozzles. Based on skewness and kurtosis values, the theoretical gamma distribution was the most adapt to fit the experimental data. The scale parameter showed a decreasing trend with the increase in the pressure, a clear index of higher drop pulverization.

Drop Size Distribution and Lightning Manifestations in AMMA-CATH Area

This paper analyses for the first time in tropical area, the relationship between lightning and DSD (Drop Size Distribution) parameters on rainy events that occurred during the monsoon period. The Lightning data used are collected by the LINET (Lightning Detection Network) while the DSD data were recorded by a distrometer. The correlation was computed within five circles of radius varying between to with a step of . These consecutive areas are centered on the position of the disdrometer. By taking into account only the convective spectra and remove out of the data the cases where there is rain without any lightning and vice versa, all data was computed with a time scale of one minute during each of the rainy events .The results showed that the exponential and polynomial laws fit better our data than the power and linear laws. The highest correlation coefficients are obtained within a radius of about 20 km around the distrometer location. The correlation between the parameter and is the most stable with a correlation coefficient equal to .