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Advance of Radar Meteorology and Hydrology II
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Advance of Radar Meteorology and Hydrology II

A special issue of Climate (ISSN 2225-1154). This special issue belongs to the section "Climate and Environment".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 1239

Special Issue Editors

Dr. Sanghun Lim

E-Mail Website
Guest Editor
Korea Institute of Civil Engineering and Building Technology, Goyang-si, Republic of Korea
Interests: radar meteorology/hydrology; precipitation microphysics; precipitation identification and quantitative precipitation estimation
Special Issues, Collections and Topics in MDPI journals
Dr. Seongsim Yoon

E-Mail Website
Guest Editor
Korea Institute of Civil Engineering and Building Technology, Goyang-si, Republic of Korea
Interests: hydrometeorology; quantitative precipitation estimation; quantitative precipitation forecast
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Tremendous advances have been made in the last 30 years in the science, technology, and engineering of radars. With the development of multiple polarization, multiple wavelength, and network sensing technologies, the radar has become a widely used tool in meteorological and hydrological applications. Radar can provide the information needed for weather systems, weather forecasting, flood warning, and climate surveys.
The goal of this Special Issue is to share the recent advances in radar meteorology and hydrology. Topics of interest include, but are not limited to, the following areas:

  • New radar system concept for precipitation observation;
  • Advances in radar signal processing and quality control;
  • Cloud and precipitation microphysics;
  • Remote sensing precipitation measurement;
  • Radar meteorological and hydrological applications;
  • Remote sensing applications in climatology.

You may choose our Joint Special Issue in Remote Sensing.

Dr. Sanghun Lim
Dr. Seongsim Yoon
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 submissions that pass pre-check are 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. Climate 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

  • radar system
  • radar signal processing
  • quality control
  • quantitative precipitation estimation
  • nowcasting
  • hydrological applications
  • remote sensing
  • precipitation

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Published Papers (1 paper)

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Research

16 pages, 3803 KiB  
Article
Quantitative Testing of a SOLO-Based Automated Quality Control Algorithm for Airborne Tail Doppler Radar Data
by Robert Pasken and Richard Woodford
Climate 2024, 12(9), 130; https://doi.org/10.3390/cli12090130 - 26 Aug 2024
Viewed by 831
Abstract
An automated quality control pre-processing algorithm for removing non-weather radar echoes from airborne Doppler radar data has been developed. The proposed algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data [...] Read more.
An automated quality control pre-processing algorithm for removing non-weather radar echoes from airborne Doppler radar data has been developed. The proposed algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data assimilation. As important as reducing the time required and skill level necessary to process an airborne Doppler dataset can be, the quality of the automated analysis is paramount. Retrieved wind data, recovered perturbation pressure data (with associated momentum check values) and correlation coefficients were computed. To quantitatively test the quality of the automated quality control algorithm, spatial Pearson correlation coefficients and momentum check values were computed. Four different (published) Electra Doppler Radar (ELDORA) datasets of convective echoes were used to stress the algorithm. Four distinct threshold levels for data removal in the automated quality control algorithm were applied to each of four ELDORA datasets. The algorithm threshold levels were labeled as follows: extremely low, low, medium, and high. Extremely low algorithm cases were deemed necessary during the data analyses and were added to the low, medium and high cases. A description of each case and the differences in the perturbation pressure momentum check values and correlation coefficients between the interactively edited fields were computed. These comparisons along with a subjective visual inspection show that the automated quality control algorithm can produce an analysis comparable—and in some cases superior—to an interactive analysis when used properly. A key benefit of this algorithm is that the skill level of a relatively inexperienced airborne radar meteorologist may be effectively increased by using the SOLO QC algorithm. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology II)
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