Universal fluctuations in tropospheric radar measurements

Andrea Barucci (1); Giovanni Macaluso (1); Daniele Mecatti (1),; Linhsia Noferini (1); Duccio Fanelli (2); Angelo Facchini (3); Massimo; Materassi (4); Massimiliano Pieraccini (1); Carlo Atzeni (1). ((1) Department; of Electronics; Telecommunications; University of Florence; Firenze,; Italy; EU; (2) Dipartimento di Energetica S.Stecco; University of Florence; ans INFN; Firenze; Italy; EU; (3) Department of Information Engineering and; Center for the Study of Complex Systems; University of Siena; Siena; Italy,; EU; (4) Istituto dei Sistemi Complessi ISC-CNR; Sesto Fiorentino; Italy; EU.)

arXiv:1002.3276·cond-mat.stat-mech·February 18, 2010

Universal fluctuations in tropospheric radar measurements

Andrea Barucci (1), Giovanni Macaluso (1), Daniele Mecatti (1),, Linhsia Noferini (1), Duccio Fanelli (2), Angelo Facchini (3), Massimo, Materassi (4), Massimiliano Pieraccini (1), Carlo Atzeni (1). ((1) Department, of Electronics, Telecommunications, University of Florence

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TL;DR

This study demonstrates that radar signal statistics encode atmospheric turbulence, with probability distributions fitting generalized Gumbel distributions, revealing a relation between wind strength and signal profile shape.

Contribution

It introduces the use of generalized Gumbel distributions to model radar data affected by atmospheric turbulence, establishing a link between wind fluctuations and signal statistics.

Findings

01

Radar data follow generalized Gumbel distributions

02

Wind strength correlates with the shape parameter of G(a)

03

Gaussian profiles emerge with decreasing wind fluctuations

Abstract

Radar data collected at an experimental facility arranged on purpose suggest that the footprint of atmospheric turbulence might be encoded in the radar signal statistics. Radar data probability distributions are calculated and nicely fitted by a one parameter family of generalized Gumbel (GG) distributions, G(a). A relation between the wind strength and the measured shape parameter "a" is obtained. Strong wind fluctuations return pronounced asymmetric leptokurtic profiles, while Gaussian profiles are eventually recovered as the wind fluctuations decrease. Besides stressing the crucial impact of air turbulence for radar applications, we also confirm the adequacy of G(a) statistics for highly correlated complex systems.

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Taxonomy

TopicsPrecipitation Measurement and Analysis · Meteorological Phenomena and Simulations · Radio Wave Propagation Studies