In recent years, machine learning (ML) and artificial intelligence (AI) have emerged as powerful weather forecasting tools, including for weather and climate extremes and related events. Data-driven algorithms applied across different temporal and spatial scales have shown great promise in predicting phenomena such as hurricanes, floods, heatwaves, and droughts, while also 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 spatial and temporal scales and for detecting and anticipating extreme weather and climate events. We welcome studies that address the use of AI for short-and medium-range meteorological forecasts, extended-range forecasts, sub-seasonal to seasonal climate forecasts, or longer-term climate projections, spanning local to global spatial scales.
We particularly encourage submissions that connect extremes to their societal and environmental impacts, such as impacts on infrastructure, ecosystems, health, or energy systems.Contributions that integrate ML with physical mechanisms to advance the representation of climate variables in numerical models or climate datasets are also highly encouraged.
By bringing together experts from AI, data science, meteorology, climate science, and impact modelling, this session aims to foster interdisciplinary collaborations that push the boundaries of forecasting and understanding extreme weather and climate events, as well as their impacts. We encourage submissions from early-career scientists, established researchers, and industry professionals alike.