Special Issue "Prediction, Observation, and Monitoring of Weather and Climate Extremes"
Deadline for manuscript submissions: 15 December 2023 | Viewed by 6365
Interests: climatology; climate change; extreme events; model evaluation
Special Issues, Collections and Topics in MDPI journals
Interests: meteorology; climate change; climate services; sustainable development
The increase in the intensity and frequency of weather and climate extremes is a growing concern. The resulting disasters greatly impact the natural environment and human society. Projections show a high likelihood of an increase in extreme events as a result of global warming. Therefore, the accurate prediction and timely monitoring of extreme events are of great significance in saving lives and minimizing the destruction of property.
Although extreme events have been studied extensively from univariate perspectives with varying indices developed for monitoring individual and regional events, their variation and formation mechanism on a local to regional scale is unclear, especially those that manifest concurrent occurrences. For example, the variability of Eurasian temperatures and the number of extreme-cold events are increasing under the current climate situation. In addition, the capability of monitoring and forecasting extreme events is also very limited, and the forecast time for different phenomena may differ. Although it is challenging to predict such events, efforts and progress have been made and are worth acknowledging and sharing.
To better understand regional weather and climate characteristics under global warming, we expect to know how extreme-event monitoring techniques and indices perform in different areas. For the simulation and prediction of extreme events, we expect to obtain more insights into the ability of numerical models to adequately simulate extreme events in different areas and at different time scales. To improve the skill of model simulation and prediction, we expect to understand the predictability of extreme events based on dynamic models, physical–empirical models, statistical events, dynamic–statistical models, and deep-learning approaches.
In this context, for this Special Issue of Atmosphere, we are calling for submissions related but not limited to the above questions. Articles that may contribute to a better understanding of extreme-weather/climate-event monitoring and predictions are invited.
Dr. Brian Odhiambo Ayugi
Dr. Victor Ongoma
Dr. Kenny T.C. Lim Kam Sian
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.
- weather and climate extremes
- model evaluation
- climate variability
- severe weather forecasting
- climate change projection
- extreme indices
- compound events