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Journal Article

Inference of raindrop size distribution from rain attenuation statistics at 12, 35, and 82 GHz

25 Apr 1984-IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (The Institute of Electronics, Information and Communication Engineers)-Vol. 67, Iss: 4, pp 211-217
About: This article is published in IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.The article was published on 1984-04-25 and is currently open access. It has received 15 citations till now.
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Journal ArticleDOI
TL;DR: Microwave attenuation measurements made on a 2.3-km microwave link are employed to estimate drop size distributions (DSD), rainfall rate, and rainfall accumulation to develop a dual-wavelength analytical technique to invert two parameters of a path-average gamma DSD.
Abstract: Microwave attenuation measurements at 25 and 38 GHz made on a 2.3-km microwave link are employed to estimate drop size distributions (DSD), rainfall rate, and rainfall accumulation. A theoretical model for the propagation of microwaves in a link system sets forth the basis for the development of a dual-wavelength analytical technique to invert two parameters of a path-average gamma DSD. The DSDs obtained from the technique are evaluated in conjunction with point measurements performed with a 2-D video disdrometer. Additionally, the DSDs yield path-average rainfall rates and rainfall accumulation which are compared with path-average measurements from a network of optical and tipping bucket rain gauges located beneath the link path, and with estimates based on empirical power law relations.

68 citations

Journal ArticleDOI
TL;DR: In this paper, a detailed review of the most literature referred theories and parameterisations to describe the below-cloud scavenging by rain in air quality modelling is presented, and a great care is recommended in the choice of the RSD with respect to the type of rain and sampling duration involved (e.g. thunderstorm, widespread, shower, etc.; long or instantaneous sampling duration).

51 citations

Journal ArticleDOI
TL;DR: The main advantage of using radar for precipitation estimation is that measurements can be made over large areas, with either fairly high temporal and spatial resolution or extensive spatial coverage (about 10 000 km2 for ground-based radar and an order of magnitude more for space-based radars) as mentioned in this paper.
Abstract: The detection and measurement of precipitation by radar has been pursued since its introduction as a meteorological tool. The main advantage of using radar for precipitation estimation is that measurements can be made over large areas, with either fairly high temporal and spatial resolution or extensive spatial coverage (about 10 000 km2 for ground-based radars and an order of magnitude more for space-based radars). To sample the area covered by a typical ground-based radar, substituting each radar spatial sample with a rain gauge, would require about a quarter-million gauges. Using a similar analogy to space radars, nearly one-half-million gauges would be required per orbit. Since the radar transmitter and receiver normally use the same antenna (monostatic operation), the measurements are sent to a central location at the speed of light by “natural wireless networks.” In addition, radars can provide fairly rapid updates of the three-dimensional structure of precipitation. Because of these advantages, radar measurements of precipitation have enjoyed widespread use for meteorological applications, independent of the accuracy or the type of algorithm used to derive precipitation estimates.

27 citations

Journal ArticleDOI
TL;DR: In this article, a comparison between the model of specific attenuation currently adopted by the International Radio Consultative Committee (CCIR) and that based on the raindrop-size distribution derived from previous propagation experiments at 11.5, 34.5 and 81.8 GHz is made.
Abstract: Millimeter-wave rain attenuation measurements have been made at 50.4, 81.8, 140.7, and 245.5 GHz on a terrestrial path of 0.81 km. On the basis of these experimental results, a comparison between the model of specific attenuation currently adopted by the International Radio Consultative Committee (CCIR) and that based on the raindrop-size distribution derived from our previous propagation experiments at 11.5, 34.5, and 81.8 GHz is made. For the Japanese climate, it is found that the CCIR model underestimates the rain attenuation at frequencies above 80 GHz and that our specific attenuation model is effective for the prediction of rain attenuation in the whole millimeter-wave region.

27 citations

Journal ArticleDOI
TL;DR: In this paper, the distribution of raindrop sizes, in terms of the lognormal and modified gamma distribution, from multi-wavelength rain attenuation measurements at millimeter and infrared wave bands have been demonstrated.
Abstract: Techniques for modeling the distribution of raindrop sizes, in terms of the lognormal and modified gamma distribution, from multiwavelength rain attenuation measurements at millimeter and infrared wave bands have been demonstrated. In order to obtain the three-parameter lognormal distribution, three experimental measurements are required, which can be attenuations at two frequencies and rain rate. Three measurements are used to form three equations, which are treated as nonlinear and are solved using a numerical technique to obtain the distribution parameters. The gamma distribution is treated as a two-parameter distribution, taking a fixed value of 2 for the index. The two parameters of the gamma distribution are obtained from measurements of rain rate and infrared attenuation following the technique described by Maitra and Gibbins [1995]. From an analysis of two rain events it is found that the measured attenuations at millimeter wavelengths show somewhat better agreement with the calculated attenuations obtained from the lognormal distribution than from the modified gamma distribution. The gamma model gives higher number densities for small drops than those given by the lognormal model.

14 citations