The wave of the Information Technology revolution is propelling us into a new era of research on atmospheric and environmental sciences. New techniques including Artificial Intelligence/Machine Learning (AI/ML) are enabling a deeper understanding of the complex atmospheric and environmental systems, as well as the interactions between weather/climate, air quality, public health, and social-economics. At the same time, Cloud Computing, GPU Computing, and Digital Twin have greatly facilitated much faster and more accurate earth system modeling, especially the weather/climate and air quality modeling and forecasting. These cutting-edge techniques are therefore playing an increasingly important role in atmospheric, climate, and environmental research and governance.
In this session, we welcome submissions addressing the latest progress in new techniques applied to research on all aspects of atmospheric, climate, and environmental sciences, including but not limited to,
- The application of AI/ML and other techniques for:
• Advancing the understanding of the complex earth system, especially the underlying mechanisms of weather/climate system, atmospheric environmental system, and their interactions
• Facilitating faster and more accurate weather/climate/air quality modeling and forecasting, especially for extreme weather, climate change, and air pollution episodes
• Shedding new insights into the mechanisms of atmospheric chemistry and physics
• Achieving air pollution tracing and source attribution
• Assisting policymakers on decisions towards environmental sustainability (e.g., considering interactions between extreme weather, climate change, air quality, socio-economics, and public health
- The adaptation and development of AI/ML and other techniques by proposing:
• Explainable AI (XAI)
• Hybrid methods (e.g., hybrid ML, physics-integrated ML)
• Transfer learning
• New algorithms
• Advanced model frameworks
We believe that exchanges across research fields could help breaking down the limitations of thinking and enabling technological innovations. Therefore, contributions from fields other than atmospheric, climate, and environmental sciences are also encouraged.
In this session, we welcome submissions addressing the latest progress in new techniques applied to research on all aspects of atmospheric, climate, and environmental sciences, including but not limited to,
- The application of AI/ML and other techniques for:
• Advancing the understanding of the complex earth system, especially the underlying mechanisms of weather/climate system, atmospheric environmental system, and their interactions
• Facilitating faster and more accurate weather/climate/air quality modeling and forecasting, especially for extreme weather, climate change, and air pollution episodes
• Shedding new insights into the mechanisms of atmospheric chemistry and physics
• Achieving air pollution tracing and source attribution
• Assisting policymakers on decisions towards environmental sustainability (e.g., considering interactions between extreme weather, climate change, air quality, socio-economics, and public health
- The adaptation and development of AI/ML and other techniques by proposing:
• Explainable AI (XAI)
• Hybrid methods (e.g., hybrid ML, physics-integrated ML)
• Transfer learning
• New algorithms
• Advanced model frameworks
We believe that exchanges across research fields could help breaking down the limitations of thinking and enabling technological innovations. Therefore, contributions from fields other than atmospheric, climate, and environmental sciences are also encouraged.