Interactions between modes of climate variability across timescales (also known as cross-timescale interference) underpin observed weather and climate regionally and globally through teleconnective processes. Such interactions have impacts on a multitude of climate variables, such as rainfall or temperature, and can lead to events that impact health, water availability, and agriculture. This session calls for abstracts that assess the mechanisms for cross-timescale interference or explore new methods for identifying cross-timescale interference. Additionally, abstracts can investigate the linear and nonlinear interactions between modes of climate variability or examine the changes needed to improve model representation of cross-timescale interference. We also aim to highlight studies that identify modes of climate variability and teleconnections, and their cross-scale interference, that result in enhanced state-dependent predictability across timescales, or windows of forecast opportunity.