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Open AccessArticle

Variability of Microwave Scattering in a Stochastic Ensemble of Measured Rain Drops

1
Earth and Space Sciences Group (ESS), Institute of Environmental Sciences (ICAM), University of Castilla-La Mancha, 45071 Toledo, Spain
2
Albacete Research Institute of Informatics (I3A), University of Castilla-La Mancha, 02071 Albacete, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 960; https://doi.org/10.3390/rs10060960
Received: 16 May 2018 / Revised: 8 June 2018 / Accepted: 14 June 2018 / Published: 15 June 2018
(This article belongs to the Special Issue Remote Sensing of Precipitation)
While it has been proved that multiple scattering in the microwave frequencies has to be accounted for in precipitation retrieval algorithms, the effects of the random arrangements of drops in space has seldom been investigated. The fact is, a single rain drop size distribution (RDSD) corresponds with many actual 3D distributions of those rain drops and each of those may a priori absorb and scatter radiation in a different way. Each spatial configuration is equivalent to any other in terms of the RDSD function, but not in terms of radiometric characteristics, both near and far from field, because of changes in the relative phases among the particles. Here, using the T-matrix formalism, we investigate the radiometric variability of two ensembles of 50 different 3D, stochastically-derived configurations from two consecutive measured RDSDs with 30 and 31 drops, respectively. The results show that the random distribution of drops in space has a measurable but apparently small effect in the scattering calculations with the exception of the asymmetry factor. View Full-Text
Keywords: precipitation; radar; radiometer; T-Matrix; microwave scattering precipitation; radar; radiometer; T-Matrix; microwave scattering
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MDPI and ACS Style

Tapiador, F.J.; Moreno, R.; Navarro, A.; Jiménez, A.; Arias, E.; Cazorla, D. Variability of Microwave Scattering in a Stochastic Ensemble of Measured Rain Drops. Remote Sens. 2018, 10, 960.

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