In recent years, machine learning (ML) and artificial intelligence (AI) have emerged as powerful tools for weather forecasting and detection of extreme weather and climate events. The application of data-driven algorithms across different temporal and spatial scales has shown great promise in predicting phenomena such as hurricanes, floods, heatwaves, and droughts and improving the accuracy and timeliness of climate projections.
This session seeks contributions exploring the development and application of ML or ML-enhanced algorithms for forecasting weather and climate at multiple timescales and for detecting and forecasting extreme weather and climate events. We encourage submissions that address the use of AI for meteorological forecasts, extended-range forecasts, sub-seasonal to seasonal climate forecasts, or longer-term climate projections, spanning local to global spatial scales. We also welcome studies that integrate ML with physical mechanisms, leading to AI-driven advancements that improve the representation of climate variables in numerical models or climate datasets.
By bringing together experts from AI, data science, meteorology, and climate science, this session aims to foster interdisciplinary collaborations that push the boundaries of weather and climate forecasting and understanding extreme weather and climate events. We encourage submissions from early-career scientists, established researchers, and industry professionals alike.