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Atmosphere
Special Issues
Weather Radar Observations of Severe Storms
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Weather Radar Observations of Severe Storms

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 4700

Special Issue Editor

Dr. Gianfranco Vulpiani

E-Mail Website
Guest Editor
Civil Protection Department, The Council of Ministers, 00193 Rome, Italy
Interests: operational QPE; deep convection; neural networks; data fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The technological improvements in the last few decades have supported the efforts of the scientific and operational community in facing the intrinsic issues related to the use of weather radars in a broad set of applications. In this respect, the spread of dual-polarization has enormously improved the data quality, quantitative precipitation estimation, microphysical parameters and process analysis, and discrimination of radar returns. As a result, weather radars have become an indispensable tool in the daily activities carried out by meteorological services all over the world.

Nevertheless, the delicate issue of weather, hydrogeological, and hydraulic risk management, emphasized by climate change, together with the increase in urbanization, has profound socio-economic and civil protection impacts that need to further enhance the quality and reliability of radar products. In this context, the nowcasting of precipitation and the identification of pre-convective precursors are, among others, topics requiring additional efforts for early warning purposes.

This Special Issue, while focused on the recent advancements on the analysis of severe storms, QPE, microphysical parameter estimation, processes analysis, and nowcasting, is also dedicated to data quality management, multisensors data fusion, data assimilation, radar networking, urban scale monitoring, and early warning. Recent advances on the analysis and quantification of winter storms are more than welcome.

Dr. Gianfranco Vulpiani
Guest Editor

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. Atmosphere 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 2400 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

  • Severe storms analysis, interpretation, and nowcasting
  • Quantitative precipitation estimation
  • Hydrometeor classification
  • Data quality
  • Data fusion
  • Data assimilation
  • Urban scale monitoring
  • Early warning
  • Snow detection and quantitative estimation

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Published Papers (1 paper)

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Research

21 pages, 9694 KiB  
Article
Radar-Based Automatic Identification and Quantification of Weak Echo Regions for Hail Nowcasting
by Junzhi Shi, Ping Wang, Di Wang and Huizhen Jia
Atmosphere 2019, 10(6), 325; https://doi.org/10.3390/atmos10060325 - 14 Jun 2019
Cited by 12 | Viewed by 4199
Abstract
The identification of some radar reflectivity signatures plays a vital role in severe thunderstorm nowcasting. A weak echo region is one of the signatures that could indicate updraft, which is a fundamental condition for hail production. However, this signature is underutilized in automatic [...] Read more.
The identification of some radar reflectivity signatures plays a vital role in severe thunderstorm nowcasting. A weak echo region is one of the signatures that could indicate updraft, which is a fundamental condition for hail production. However, this signature is underutilized in automatic forecasting systems due to the lack of a reliable detection method and the uncertain relationships between different weak echo regions and hail-producing thunderstorms. In this paper, three algorithms related to weak echo regions are proposed. The first is a quasi-real-time weak echo region morphology identification algorithm using the radar echo bottom height image. The second is an automatic vertical cross-section-making algorithm. It provides a convenient tool for automatically determining the location of a vertical cross-section that exhibits a visible weak echo region to help forecasters assess the vertical structures of thunderstorms with less time consumption. The last is a weak echo region quantification algorithm mainly used for hail nowcasting. It could generate a parameter describing the scale of a weak echo region to distinguish hail and no-hail thunderstorms. Evaluation with real data of the Tianjin radar indicates that the critical success index of the weak echo region identification algorithm is 0.61. Statistics on these data also show that when the weak echo region parameters generated by the quantification algorithm are in a particular range, more than 85% of the convective cells produced hail. Full article
(This article belongs to the Special Issue Weather Radar Observations of Severe Storms)
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