Rain, snow, and volcanic ash clouds contain particles generated by different physical and chemical processes. When electromagnetic radiation interacts with particle distribution, causing absorption and scattering, the backscattered power enables the retrieval of useful geophysical parameters of particle distribution. This is the measurement principle of microwave weather (meteorological) radar, monostatic remote sensing that can exploit Rayleigh and Mie backscattering to remotely probe atmospheric clouds. This article is an overview of weather radar systems and data processing for rain, snow, and volcanic ash clouds. We describe ground-based weather radars along with other platforms, such as airborne and spaceborne configurations. Signal processing of single-polarization weather radar systems in addition to more advanced schemes, such as those that enable Doppler and dual-polarization capability, are discussed. Additionally, we describe Doppler weather radars with narrow beams, which are used to detect low-level wind shear during rain, microbursts, and gusts. Multifrequency radar for snowfall retrieval is also presented, with an emphases on estimation and classification of the microphysical properties of particles. Finally, future directions for signal processing and applications for microwave weather radar systems are presented.

Weather radar data processing and atmospheric applications: An overview of tools for monitoring clouds and detecting wind shear / Falconi, M. T.; Marzano, F. S.. - In: IEEE SIGNAL PROCESSING MAGAZINE. - ISSN 1053-5888. - 36:4(2019), pp. 85-97. [10.1109/MSP.2019.2890934]

Weather radar data processing and atmospheric applications: An overview of tools for monitoring clouds and detecting wind shear

Marzano F. S.
2019

Abstract

Rain, snow, and volcanic ash clouds contain particles generated by different physical and chemical processes. When electromagnetic radiation interacts with particle distribution, causing absorption and scattering, the backscattered power enables the retrieval of useful geophysical parameters of particle distribution. This is the measurement principle of microwave weather (meteorological) radar, monostatic remote sensing that can exploit Rayleigh and Mie backscattering to remotely probe atmospheric clouds. This article is an overview of weather radar systems and data processing for rain, snow, and volcanic ash clouds. We describe ground-based weather radars along with other platforms, such as airborne and spaceborne configurations. Signal processing of single-polarization weather radar systems in addition to more advanced schemes, such as those that enable Doppler and dual-polarization capability, are discussed. Additionally, we describe Doppler weather radars with narrow beams, which are used to detect low-level wind shear during rain, microbursts, and gusts. Multifrequency radar for snowfall retrieval is also presented, with an emphases on estimation and classification of the microphysical properties of particles. Finally, future directions for signal processing and applications for microwave weather radar systems are presented.
2019
atmospheric chemistry; clouds; data handling; doppler radar
01 Pubblicazione su rivista::01a Articolo in rivista
Weather radar data processing and atmospheric applications: An overview of tools for monitoring clouds and detecting wind shear / Falconi, M. T.; Marzano, F. S.. - In: IEEE SIGNAL PROCESSING MAGAZINE. - ISSN 1053-5888. - 36:4(2019), pp. 85-97. [10.1109/MSP.2019.2890934]
File allegati a questo prodotto
File Dimensione Formato  
Falconi_Weather-radar_2019.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.49 MB
Formato Adobe PDF
2.49 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1428954
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? 6
social impact