Description:

The assessment of climate variability and change, broadly construed, is enriched by novel applications of statistics and machine learning methodologies. This session brings together a broad range of researchers in climatology, statistics, and machine learning to highlight important developments at the intersections of these fields. We welcome submissions of state-of-the-art applications of statistics and machine learning methodologies that contribute substantively to the study of climate variability and change. Areas of interest include but are not limited to: climate extremes, predictability, model evaluation, trend and internal variability assessment, and methods that combine multiple data sources.