Disdrometer

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

Polarimetric Measurements of Ice Pellets and Aggregated Snow

Abstract: The recent upgrade of the National Weather Service WSR-88D radar network to polarimetric capabilities provides the abundance of information about the precipitation microphysics. Even with the plethora of polarimetric measurements at our disposal, use of this essential information regarding the microphysical processes is underutilized. For example, there is no polarimetric relation for snow estimation. The focus of this study is to improve the existing state of polarimetric data usage for discrimination between the ice pellets and freezing rain if their occurrence is away from the radar (patchy, no radar-centric structure), and more importantly the development of the polarimetric relations for snow quantification. Observations and analysis of an ice-liquid phase precipitation event, collected with an S-band polarimetric KOUN radar and a two-dimensional video disdrometer in central Oklahoma are presented. Using the disdrometer measurements, precipitation is classified either as ice pellets or rain/freezing rain. The ice pellets were challenging to detect by looking at conventional polarimetric radar data due to the localized and patchy nature of the ice phase and occurrence close to the ground. In this study, a new, unconventional way of looking at polarimetric radar data is introduced: Slanted Vertical Profiles SVPs at low (0° - 1°) radar elevations. From the analysis of the localized and patchy structures using SVPs, the polarimetric refreezing signature, reflected in local enhancement in ZDR and reduction in ZH and ρhv, became much more evident. Model simulations of sequential drop freezing using Marshal-Palmer DSDs along with the disdrometer observations suggest that preferential freezing of small drops may be responsible for the refreezing polarimetric signature. Accurate measurements of snow amounts by radar are very difficult to achieve. The inherent uncertainty in radar snow estimates based on the radar reflectivity factor Z is caused by the variability of snow particle size distributions and snow particle density as well as large diversity of snow growth habits. In this study, a novel methodology for snow quantification based on the joint use of radar reflectivity Z and specific differential phase KDP is introduced. An extensive dataset of 2D video disdrometer measurements of aggregated snow in central Oklahoma is used to derive polarimetric relations for liquid-equivalent snowfall rate S and ice water content IWC in the forms of bivariate power-law relations. The physical basis of these relations is explained. Their multipliers are sensitive to variations in the width of the canting angle distribution, and to lesser extent particles’ aspect ratios and densities, whereas the exponents are practically invariant. This novel approach is tested against the S(Z) relation using snow disdrometer measurements in three geographical regions (Oklahoma, Colorado, and Canada). Similarly, the new approach is tested on polarimetric radar data at three localities, Oklahoma, Virginia, and Colorado. Polarimetric relations…

Correcting method for measuring errors of laser raindrop disdrometer

Abstract: The invention discloses a correcting method for measuring errors of a laser raindrop disdrometer. The correcting method can be used for overcoming the measuring errors due to a photoelectric technology adopted by the exiting laser raindrop disdrometer, remarkably improving rainfall quantitative measurement precision of the laser raindrop disdrometer, and obviously improving radar reflectivity factor calculating accuracy, so that the quantitative application field of the laser raindrop disdrometer is expanded. The correcting method can be used for optical rain gauges adopting other similarity principles.

Variability of the Rain Drop Size Distributions within a Storm

Abstract: The variability of drop size distributions (DSDs) within a storm lasted for 14 hours in Montreal, Canada, is investigated utilizing 1) 840 one-minute DSDs observed by a disdrometer, and 2) vertical profiles of reflectivity (Z) and vertical Doppler velocity (Vr) from a vertically pointing radar. Vertical Doppler velocity indicates that riming exists throughout the rain event. Based on the vertical structures of Z and Vr, we have identified three periods as a function of the degree of riming and examine the characteristics of the DSD variability. The fluctuation of the rain intensity shows the coherent structure with the decorrelation time of about 40 minutes. This emphasizes the nonstationary nature of the rain field. When riming and aggregation coexist, DSDs are narrower and show the pivoting around smaller diameters. As the degree of riming increases, DSDs become broader and then steeper when strong updraft appears. In addition, the average DSD shows peaks in small diameters associated with break-up of large raindrops. The exponent of R-Z relationships decrease with increasing degree of riming. The decorrelation time of the R-Z uncertainty is about 20 minutes. When aggregation and riming coexist, the characteristic number density N' 0 and diameter D' m are small. D' m increases rapidly and N' 0 remains its value when riming is dominant. Finally, when strong updraft exists, N' 0 dramatically increases whereas D' m slightly decreases.

Effect of disdrometer sampling area and time on the precision of precipitation rate measurement

Abstract: . Due to the discretized nature of rain, the measurement of a continuous precipitation rate by disdrometers is subject to statistical sampling errors. Here, Monte Carlo simulations are employed to obtain the precision of rain detection and rate as a function of disdrometer collection area and compared with World Meteorological Organization guidelines for a one-minute sample interval and 95 \% probability. To meet these requirements, simulations suggest that measurements of light rain with rain rates R l 0.50 mm h−1 require a collection area of at least 6 cm × 6 cm, and for R > 1 mm h−1, the minimum collection area is 10 cm × 10 cm. For R = 0.01 mm h−1, a collection area of 2 cm × 2 cm is sufficient to detect a single drop. Simulations are compared with field measurements using a new hotplate device, the Differential Emissivity Imaging Disdrometer. The field results suggest an even larger plate may be required to meet the stated accuracy, although for reasons that remain to be determined.