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Special Issue "Radar Polarimetry—Applications in Remote Sensing of the Atmosphere"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmosphere Remote Sensing".

Deadline for manuscript submissions: 31 January 2019

Special Issue Editors

Guest Editor
Dr. Haonan Chen

NOAA Earth System Research Laboratory, 325 Broadway, Boulder, CO 80305, USA
E-Mail
Interests: radar remote sensing; radar polarimetry; radar and satellite data fusion; precipitation microphysics; precipitation classification and quantification using multiparameter weather radar
Guest Editor
Prof. V. Chandrasekar

Colorado State University, 1373 Campus Delivery, Fort Collins, CO 80523, USA
Website | E-Mail
Interests: radar meteorology; radar system and networking; polarimetric analysis and signal processing; wave propagation and remote sensing
Guest Editor
Dr. Sanghun Lim

Korea Institute of Civil Engineering and Building Technology, 283 Goyangdae-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do 10223, Republic of Korea
E-Mail
Interests: quantitative precipitation estimation and hydrometeor classification using dual-polarization radar measurements and weather observation using automotive sensors
Guest Editor
Prof. Tomoo Ushio

Department of Aeronautics and Astronautics, Tokyo Metropolitan University, 1 Chome-1 Minamiosawa, Hachioji, Tokyo 192-0364, Japan
Website | E-Mail
Interests: radar-based remote sensing, passive and active remote sensing of atmosphere from spaceborne platforms, and atmospheric electricity

Special Issue Information

Dear Colleagues,

Radar has been widely used for remote sensing of weather, climate, hydrology, and the environment. Over the past 30 years, numerous radar techniques and algorithms have been developed for measuring, modeling, simulating and forecasting the Earth’s atmosphere state. In particular, polarization diversity has great potential to characterize precipitation microphysics and different atmospheric properties. The ground-based polarimetric radar can also be used for validation of satellite (i.e., passive or active space-borne sensors) observations and products. This Special Issue focuses on recent advances in polarimetric radar applications in geoscience and remote sensing. Contributions are welcome from all areas of active remote sensing of the atmosphere. Submissions are solicited covering, but not limited to, the following topics:

  • Concept of wave propagation and polarization
  • Radar remote sensing of environment
  • Advances in polarimetric radar hardware, signal processing, and data quality control
  • Scanning and vertically pointing cloud and precipitation radars
  • Identification of hydrometeor phase using polarimetric and Doppler spectra radar measurements
  • Remote sensing precipitation measurement, validation, and applications
  • The International Workshop on Small Weather Radars (ISWR 2018)

Dr. Haonan Chen  
Prof. V. Chandrasekar
Dr. Sanghun Lim
Prof. Tomoo Ushio
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Quantitative remote sensing
  • Polarization theory/application
  • Atmospheric sensing
  • Polarimetric Radar
  • Satellite
  • Precipitation retrieval, validation and application

Published Papers (2 papers)

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Research

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Open AccessArticle An Inverse Model for Raindrop Size Distribution Retrieval with Polarimetric Variables
Remote Sens. 2018, 10(8), 1179; https://doi.org/10.3390/rs10081179
Received: 7 May 2018 / Revised: 15 July 2018 / Accepted: 17 July 2018 / Published: 26 July 2018
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Abstract
This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function
[...] Read more.
This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function to generate a pseudo training dataset by considering the maximum drop diameter in a truncated Gamma model for DSD. With the pseudo training data, a nearest-neighborhood method is optimized in terms of mass-weighted diameter and liquid water content. Finally, the inverse model is evaluated with simulated and real radar data, both of which yield better agreement with disdrometer observations compared to the existing Bayesian approach. In addition, the rainfall rate derived from the DSD by the inverse model is also improved when compared to the methods using the power-law relations. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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Other

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Open AccessTechnical Note On the Use of Bright Scatterers for Monitoring Doppler, Dual-Polarization Weather Radars
Remote Sens. 2018, 10(7), 1007; https://doi.org/10.3390/rs10071007
Received: 1 May 2018 / Revised: 14 June 2018 / Accepted: 21 June 2018 / Published: 25 June 2018
PDF Full-text (720 KB) | HTML Full-text | XML Full-text
Abstract
“Bright” scatterers are useful for monitoring modern weather radars. In order to be “bright”, a point target with deterministic backscattering properties should be present at a near range and be hit by the antenna beam axis. In this note, a statistical characterization of
[...] Read more.
“Bright” scatterers are useful for monitoring modern weather radars. In order to be “bright”, a point target with deterministic backscattering properties should be present at a near range and be hit by the antenna beam axis. In this note, a statistical characterization of the echoes from a metallic tower located on Cimetta, at an 18 km range and at the same altitude as the Monte Lema radar, is presented. The analysis is based on five clear sky days (1440 samples with a spatial resolution of 1° × 1° × 83.33 m). The spectral and polarimetric signatures are striking: The spectrum width is perfectly stable; the mean radial velocity is very stable; the radar reflectivity is also quite stable, with the vertical (V) polarization being more variable than the horizontal (H) one. As far as the polarimetric information is concerned, the daily average of the differential reflectivity is approximately 1 ± 0.9 dB. The copolar correlation coefficient between H and V is remarkably large (0.9962, on average) and stable. It is believed that these unique and stable ground clutter signals could be used to monitor operational dual-polarization weather radars. Full article
(This article belongs to the Special Issue Radar Polarimetry—Applications in Remote Sensing of the Atmosphere)
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