Advances in Weather Prediction and Numerical Simulation
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Air, Climate Change and Sustainability".
Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 1713
Special Issue Editors
Interests: development of numerical weather prediction models; numerical simulation of high-impact weather
Special Issues, Collections and Topics in MDPI journals
Interests: numerical simulation of severe convective weather; development of cloud microphysics scheme
Special Issue Information
Dear Colleagues,
In recent decades, great progress has been achieved in numerical weather prediction. Forecasting skills have increased significantly over the past 40 years due to the advances in observation and modeling and through the better integration of these through data assimilation and related techniques. For example, forecasts are able to be made about 3–10 days ahead of time, and this timeframe has been increasing by about one day per decade. Accurate forecasts can save lives, support emergency management, and prevent economic losses, promoting the sustainable development of the social economy.
Severe weather events, such as torrential rainfall, hailstorms, and tornadoes, are high-impact weather events that can cause great economic losses and casualties. Under the background of global warming, severe weather events have occurred frequently worldwide. However, the numerical prediction and simulation of severe weather are challenging and difficult due to the small spatial and temporal scales of these weather events. The aim of this Special Issue is to present recent advances in weather prediction and numerical simulation, especially their application in predicting high-impact severe weather events. Both original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- The numerical simulation of severe weather events, including torrential rainfall, hailstorms, tornadoes, etc.
- Analyses of the mechanisms of severe weather, such as the initiation of convection, the organization of convective systems, etc.
- The assimilation of observational data, such as satellite, weather radar, etc.
- The parameterization of physical processes, including cloud microphysical process, boundary layer process; land surface process, etc.
We look forward to receiving your contributions.
Prof. Dr. Fan Ping
Dr. Lei Yin
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. Sustainability is an international peer-reviewed open access semimonthly 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
- numerical simulation
- high-impact weather
- initiation and organization mechanisms
- parameterization of physical processes
- data assimilation
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