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Numerical Models and Weather Extreme Events
Topic Information
Dear Colleagues,
This Topic comprises several interdisciplinary research areas that cover the main aspects of numerical weather predictions. Every year, there are hurricanes, extreme heat waves, tornadoes, and other extreme weather events, resulting in thousands of deaths and billions of dollars in damage. The prediction of extreme weather further in advance and with increased accuracy could allow targeted regions to be better prepared in order to reduce loss of life and property damage. It is evident that climate change is increasing the intensity and frequency of extreme weather events; thus, their prompt prediction has never been more important. The development of accurate local forecasts is notoriously difficult due to the complex physics driving heavy precipitation and intense winds. Weather forecasting requires supercomputers and trained local practitioners, thus narrowing its accessibility to wealthy governments and communities. Moreover, traditional weather forecasts with a predictive scope of several days in advance are very coarse in terms of resolution and, therefore, do not capture local extreme events. One alternative developed in recent years is the usage of local observations to forecast weather up to a couple of hours in advance. In this regard, next-generation satellites bring great opportunities to further improve short-term forecasting. Artificial intelligence and machine-learning breakthroughs are changing weather forecasting such that resource-heavy, regional weather models might soon be completely replaced by machine-learning approaches. Such innovative approaches use specific networks (GANs) trained via global weather forecasts to correct for the biases that exist in current weather models. The new model downscales global forecasts to be as accurate as a local forecast, without requiring the vast amounts of computational, financial, and human resources previously required for such a small scale. Manuscripts addressing these exciting areas can be submitted.
Some examples of related subjects include:
- Current challenging areas in weather models;
- The assessment of a weather model’s ability to represent extreme weather events;
- Supercomputing applied to Weather Forecasting;
- Ensemble modeling;
- Monte Carlo simulations;
- Stochastic weather generators;
- The monitoring of weather and climate from space.
Dr. Edoardo Bucchignani
Dr. Andrea Mastellone
Topic Editors
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC |
|---|---|---|---|---|---|
Applied Sciences
|
2.5 | 5.3 | 2011 | 18.4 Days | CHF 2400 |
Atmosphere
|
2.5 | 4.6 | 2010 | 16.1 Days | CHF 2400 |
Climate
|
3.0 | 5.5 | 2013 | 19.7 Days | CHF 1800 |
Meteorology
|
- | - | 2022 | 37.6 Days | CHF 1000 |
Remote Sensing
|
4.2 | 8.3 | 2009 | 23.9 Days | CHF 2700 |
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