M20 - Role of Ocean-Atmosphere Interactions in Climate Variability, Change and Predictability

Convenors: Hisashi Nakamura, Noel S. Keenlyside
Co-convener: Mat Collins, Meghan F. Cronin, Ruiqiang, Mojib, Shoshiro Minobe, Mathieu Rouault, Tomoki Tozuka, Tim Woollings, Shang-Ping Xie 

Ocean-atmosphere interactions are an important source of climate variability and predictability. Great progress has been made during the past two decades in understanding, modeling and predicting interannual variability over the tropical oceans, including the El Niño – Southern Oscillation (ENSO) and associated global teleconnections. The role of the extratropical oceans in climate variability is less well understood with regard to its origin and multi-scale impacts. The latter especially concerns the influence of the western boundary current regions, including the Agulhas system, and associated frontal zones on the overlying atmosphere, storms and blocking and possible teleconnections. While ocean-atmosphere interaction in the tropics is better understood, its poor representation in climate models leads to large systematic errors and degrades climate predictions. Tropical-extratropical interactions and interactions between ocean basins are other areas where progress is required. As today’s climate includes a significant contribution from anthropogenic forcing, regional anomaly patterns and the role of ocean-atmosphere interactions have to be considered in the context of global climate change.

We invite contributions on topics including, but not limited to: 1) theoretical, observational and/or modeling studies on the processes involved in ocean-atmosphere interactions, in the tropics and extratropics (and their interaction), and their role in climate variability and predictability; 2) impacts of ocean variability on the coupled troposphere/stratosphere system at various spatial scales up to global; 3) the response of the ocean to multi-scale atmospheric variability; and/or 4) the evaluation and improvement of ocean-atmosphere coupling in climate models.