This session focuses on the transport of momentum, heat, and moisture across spatial and temporal scales of the atmosphere. It will link sub-grid processes, such as boundary-layer turbulence, convection, and drag, to larger-scale circulation features, including, for example, jets, cyclones, and mesoscale convective systems.
We welcome theoretical, observational, and modelling contributions using both conventional methods and emerging AI or hybrid approaches. Topics include (but are not limited to):
- Transport processes associated with turbulence, convection, and subgrid variability
- Representation of boundary-layer and lower-tropospheric dynamics
- Challenges in modelling scale-aware and partially resolved processes
- Interactions between local transport and large-scale atmospheric dynamics
- Data-driven, statistical, and machine learning approaches
- Diagnostics and evaluation of transport processes across model scales and frameworks
Overall, this session aims to bring together communities working on the dynamics, physics, and machine learning of transport processes, to foster cross-scale understanding and improve modelling across weather and climate timescales, as well as process-based understanding.