Atmospheric Radar for Severe Weather Surveillance and Analysis

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: closed (15 February 2020) | Viewed by 3936

Special Issue Editor

Servei Meteorologic de Catalunya, 08029 Barcelona, Spain
Interests: severe weather; remote sensing; nowcasting; hail; heavy rain; supercells; squall lines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Severe weather (large hail, strong convective straight winds, tornadoes, heavy rainfall, all associated to intense thunderstorms) produces substantial losses in agriculture, industry, and many others human activities. Besides, casualties are also possible in some cases, depending on the intensity of the phenomena and on the vulnerability of the affected area. Severe weather phenomena occur in many areas of the world, producing substantial economic losses, as reported by the WMO. For this reason, research on this topic requires important efforts to develop efficient weather surveillance systems. One of them is remote sensing—weather radar in particular—for detecting, diagnosing, and forecasting severe weather producing thunderstorms. Furthermore, because of the spatial and time resolutions, some radar products can help the generation of affectation maps to be used in civil protection plans or to infer the climatology of a particular area. This book is a compilation of some of the last advances in this field.

Dr. Tomeu Rigo
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.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 4321 KiB  
Article
Flash Flood Forecasting in São Paulo Using a Binary Logistic Regression Model
by Andrea Salomé Viteri López and Carlos Augusto Morales Rodriguez
Atmosphere 2020, 11(5), 473; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11050473 - 7 May 2020
Cited by 10 | Viewed by 3180
Abstract
This study presents a flash flood forecasting model that uses a binary logistic regression method to determine the occurrence of flash flood events in different watersheds in the city of São Paulo, Brazil. This study is based on two years (2015–2016) of rain [...] Read more.
This study presents a flash flood forecasting model that uses a binary logistic regression method to determine the occurrence of flash flood events in different watersheds in the city of São Paulo, Brazil. This study is based on two years (2015–2016) of rain estimates from a dual-polarization S-band Doppler weather radar (SPOL) and flood locations observed by the Climate Emergency Management Center (CGE) of São Paulo City Hall. The logistic regression model is based on daily accumulated precipitation, a maximum precipitation rate, and daily rainfall duration. The model presented a probability of detection (POD) of 46% (71%) on average for flood events (conditional), while, for events without flash flood, it reached 98% probability. Despite the low averaged POD for flash flood occurrence, the model demonstrated a good performance for watersheds located in the east of the city near the Tietê River and in the southeast with probabilities above 50%. Full article
(This article belongs to the Special Issue Atmospheric Radar for Severe Weather Surveillance and Analysis)
Show Figures

Figure 1

Back to TopTop