About this Research Topic
This Research Topic is Volume III of a series and will cover all aspects of numerical weather prediction issues. The previous volumes can be found here:
Advances in Numerical Model, Data Assimilation, and Observations for Hazardous Weather Prediction
Advances in Numerical Model, Data Assimilation, and Observations for Hazardous Weather Prediction: Volume II
Regional numerical weather forecasts have made notable advancements in predicting hazardous weather events like storms, flash floods, damaging winds, and tropical cycles etc. This progress is attributed to the improved numerical weather prediction model, the data assimilation algorithms, utilization of multi-source observations, development of convective-allowing models, utilization of high-performance computers, and advancements in artificial intelligence techniques.
This Research Topic seeks submissions on the following topics that are related to the improvement of meteorology numerical modeling using multi-source observations and artificial intelligence techniques for high-impact weather events:
• Regional numerical weather prediction development and application;
• Data assimilation algorithms and coupled data assimilation;
• Application for new observation datasets;
• Advances in observation operator, observation error model Applications of machine learning and AI techniques for hazardous event prediction;
• Developments in verification methods for numerical products.
Advances in Numerical Model, Data Assimilation, and Observations for Hazardous Weather Prediction
Advances in Numerical Model, Data Assimilation, and Observations for Hazardous Weather Prediction: Volume II
Regional numerical weather forecasts have made notable advancements in predicting hazardous weather events like storms, flash floods, damaging winds, and tropical cycles etc. This progress is attributed to the improved numerical weather prediction model, the data assimilation algorithms, utilization of multi-source observations, development of convective-allowing models, utilization of high-performance computers, and advancements in artificial intelligence techniques.
This Research Topic seeks submissions on the following topics that are related to the improvement of meteorology numerical modeling using multi-source observations and artificial intelligence techniques for high-impact weather events:
• Regional numerical weather prediction development and application;
• Data assimilation algorithms and coupled data assimilation;
• Application for new observation datasets;
• Advances in observation operator, observation error model Applications of machine learning and AI techniques for hazardous event prediction;
• Developments in verification methods for numerical products.
Keywords: Numerical weather prediction, Remote sensing data assimilation, High-performance computing, Machine learning and artificial intelligence, In-depth evaluation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
