Advanced Numerical Modeling Techniques in Meteorology: Exploring the Frontier of Weather Prediction and Data Assimilation

Dear Colleagues,

The field of meteorology is undergoing a transformative phase, driven by revolutionary breakthroughs in the application of artificial intelligence (AI), advancements in numerical modeling techniques, and the burgeoning potential of quantum computing. This Special Issue of Atmosphere aims to provide a comprehensive overview of these cutting-edge methodologies, offering insights into their applications, challenges, and prospects.

Numerical modeling techniques have been the backbone of modern weather prediction. These models simulate atmospheric processes using mathematical and algorithmic expressions of physical law that drive the atmosphere and require significant computational resources. Recent advancements have enhanced the accuracy and efficiency of these models, incorporating finer spatial resolutions, improved boundary conditions, and novel algorithms. This Special Issue will delve into the latest developments, highlighting key improvements and their impact on weather forecasting.

Artificial intelligence (AI) has revolutionized various scientific domains, and meteorology is no exception. Yet still, an open frontier is how and whether, by integrating AI with traditional physics-based models, researchers can create hybrid systems that leverage the strengths of both approaches. AI algorithms can analyze vast amounts of data, identify patterns, and make predictions with unprecedented speed. When combined with the rigorous foundation of physics models, these hybrid techniques may offer a powerful tool for weather prediction and data assimilation even for situations in which they were not trained, such as extreme weather events that arise as a natural outcome of ongoing climate change. This Special Issue will explore the methodologies and case studies demonstrating the benefits of or denying the efficacy of AI-integrated physics models.

Quantum computing represents the next frontier of computational power, promising to solve complex problems that are beyond the reach of classical computers. In meteorology, quantum computing holds the potential to revolutionize data assimilation, improve model accuracy, and significantly reduce computation times. Although still in its nascent stages, the application of quantum computing in meteorology is an exciting area of research. This Special Issue will discuss the current applications of quantum computing in meteorology, and the challenges that need to be addressed for its widespread adoption.

The intersection of advanced numerical modeling techniques, hybridization of AI-integrated physics models, and quantum computing heralds a new era in meteorology. By embracing these innovative approaches, meteorologists can enhance the accuracy of weather predictions, improve data assimilation processes, and tackle previously insurmountable challenges. This Special Issue of Atmosphere aims to foster collaboration, stimulate discussion, and inspire further research in these groundbreaking areas. We invite contributions from researchers, practitioners, and experts to share their insights, findings, and visions for the future of meteorological science.

You may choose our Joint Special Issue in Atmosphere.

Dr. Miodrag Rancic
Dr. Ivana Tosic
Guest Editors

Manuscript Submission Information

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• numerical modeling
• data assimilation
• weather forecasting
• artificial intelligence (AI)
• quantum computing