Disdrometer

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

A Stochastic Raindrop Time Distribution Model

Abstract: A disdrometer simultaneously measuring time of arrival and size of raindrops was set up in the Paris, France, area. Data collected over a period of 25 months (May 1992 to May 1994) are presented and analyzed to derive a long-term temporal model governed by a renewal process whose survival law is a Bi-Pareto law of the third kind. The model thus found allows nearly nine orders of magnitude of the time intervals between raindrops to be mathematically represented at the same time using only six parameters. The analysis presented here does not consider rainfall intensity and the nature of rain (convective, stratiform, etc.) as classification parameters. This approach, which may at first sight seem objectionable, is justified by the quality of the statistical inferences that can be made from the model. Two such applications are described—namely, the prediction of the total fallen-water height and the conversion between various rain gauge integration times, which are often necessary for telecommunicati...

Comparison of Polarimetric Radar Drop Size Distribution Retrieval Algorithms

Abstract: Recently, two physically based algorithms, the “beta” (β) method and the “constrained-gamma” method, have been proposed for retrieving the governing parameters of the gamma drop size distribution (DSD) from polarimetric radar measurements. The β method treats the drop axis ratio as a variable and computes drop shape and DSD parameters from radar reflectivity (Z), differential reflectivity (ZDR), and specific differential phase (KDP). The constrained-gamma method assumes that the axis ratio relation is fixed and computes DSD parameters from reflectivity, differential reflectivity, and an empirical relation between the DSD slope and shape parameters. In this paper, the two approaches are evaluated by comparing retrieved rain DSD parameters with disdrometer observations and examining derived fields for consistency. Error effects on the β method retrievals are analyzed. The β approach is found to be sensitive to errors in KDP and to be inconsistent with observations. Large retrieved β values are foun...

Correction of raindrop size distributions measured by Parsivel disdrometers, using a two-dimensional video disdrometer as a reference

Abstract: . The raindrop size distribution (DSD) quantifies the microstructure of rainfall and is critical to studying precipitation processes. We present a method to improve the accuracy of DSD measurements from Parsivel (particle size and velocity) disdrometers, using a two-dimensional video disdrometer (2DVD) as a reference instrument. Parsivel disdrometers bin raindrops into velocity and equivolume diameter classes, but may misestimate the number of drops per class. In our correction method, drop velocities are corrected with reference to theoretical models of terminal drop velocity. We define a filter for raw disdrometer measurements to remove particles that are unlikely to be plausible raindrops. Drop concentrations are corrected such that on average the Parsivel concentrations match those recorded by a 2DVD. The correction can be trained on and applied to data from both generations of OTT Parsivel disdrometers, and indeed any disdrometer in general. The method was applied to data collected during field campaigns in Mediterranean France for a network of first- and second-generation Parsivel disdrometers, and on a first-generation Parsivel in Payerne, Switzerland. We compared the moments of the resulting DSDs to those of a collocated 2DVD, and the resulting DSD-derived rain rates to collocated rain gauges. The correction improved the accuracy of the moments of the Parsivel DSDs, and in the majority of cases the rain rate match with collocated rain gauges was improved. In addition, the correction was shown to be similar for two different climatologies, suggesting its general applicability.

Errors in Estimating Raindrop Size Distribution Parameters Employing Disdrometer and Simulated Raindrop Spectra

Abstract: There have been debates and differences of opinion over the validity of using drop size distribution (DSD) models to characterize precipitation microphysics and to retrieve DSD parameters from multiparameter radar measurements. In this paper, simulated and observed rain DSDs are used to evaluate moment estimators. Seven estimators for gamma DSD parameters are evaluated in terms of the biases and fractional errors of five integral parameters: radar reflectivity (ZH), differential reflectivity (ZDR), rainfall rate (R), mean volume diameter (Dm), and total number concentration (NT). It is shown that middle-moment estimators such as M234 (using the second-third-fourth moments) produce smaller errors than lower- and higher-moment estimators if the DSD follows the gamma distribution. However, if there are model errors, the performance of M234 degrades. Even though the DSD parameters can be biased in moment estimators, integral parameters are usually not. Maximum likelihood (ML) and L-moment (LM) estima...

A Methodology to Derive Radar Reflectivity–Liquid Equivalent Snow Rate Relations Using C-Band Radar and a 2D Video Disdrometer

Abstract: The objective of this work is to derive equivalent radar reflectivity factor–liquid equivalent snow rate (Ze–SR) power-law relations for snowfall using the C-band King City operational weather radar and a 2D video disdrometer (2DVD). The 2DVD provides two orthogonal views of each snow particle that falls through its 10 cm × 10 cm virtual sensor area. The “size” parameter used here for describing the size distribution is based on the “apparent” volume computed from the two images, and an equivolume spherical diameter Dapp is defined. The determination of fall speed is based on matching two images corresponding to the same particle as it falls through two light planes separated by a precalibrated separation distance. A new “rematching” algorithm was developed to improve the quality of the fall speed versus Dapp as compared with the original matching algorithm provided by the manufacturer. The snow density is parameterized in the conventional power-law form , where α and β are assumed to be variable...