High-Impact Weather Events: Dynamics, Variability and Predictability
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".
Deadline for manuscript submissions: 25 September 2024 | Viewed by 1397
Special Issue Editors
2. Centre for the Research of Agroenvironmental and Biological Sciences, CITAB, Universidade de Trás-os-Montes e Alto Douro, UTAD, 5000-801 Vila Real, Portugal
Interests: windstorms; thunderstorms; tornadoes; downbursts; mountain waves and turbulence; aircraft icing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
High-Impact Weather Events are usually associated with severe thunderstorms, tropical and extra-tropical cyclones. These systems can cause hazardous weather conditions such as heavy rain, and strong winds, including tornadoes and downbursts, hail and lightning. Despite improvements made in recent years, numerical weather prediction (NWP) models operational in national meteorological services are unable to accurately predict the timing and location of such hazards. On a different time-scale, heat waves and droughts also have a significant social impact. In addition, recent studies have shown that compound events (multivariate and simultaneous extremes) with a very high impact on society have become more frequent, and this trend is expected to persist with increasing global warming. One example of a compound event with a very high impact on society is the simultaneous occurrence of heat waves and extreme wind events, which can intensify forest fires, ultimately leading to large deforestation and loss of life.
This Special Issue welcomes papers that contribute to improving the knowledge about high-impact weather, such as:
- Studies addressing the dynamic aspects and predictability of High-Impact Weather Events, focusing on ensemble forecasting systems and convection-permitting models;
- Observational and model-based studies of tropical and extra-tropical cyclones and severe convective storms;
- Nowcasting techniques, using satellite, radar, lightning systems and other observations;
- Studies quantifying the effect of climate change on the characteristics of tropical and extra-tropical cyclones, and on drought frequencies;
- Studies addressing the predictability of compound events and the impact of climate change on the frequency of the compound events.
Dr. Margarida Belo-Pereira
Dr. André Simon
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. 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
- tropical cyclones
- explosive cyclogenesis
- windstorms
- hailstorms
- tornadic storms
- squall lines
- heat waves
- climate change
- ensemble forecast
- model objective verification
