Orals

Understanding atmospheric transport of trace species and aerosols is a topic that critically depends on bringing modeling and observational efforts together. The purpose of this session is to enable such connections, with a secondary focus on Lagrangian modeling of the atmosphere.

Vertical and long-range transport of trace species and aerosols are key factors controlling their concentrations and variability. Various surface emissions have a strong direct influence on the upper troposphere via several vertical transport processes, especially cumulus convection and lifting associated with frontal systems (warm and cold conveyor belts). Downward transport occurs via accompanying subsidence, while precipitation scavenging is one of the key sinks for many gases and aerosols. Long-range and intercontinental transport result in measurable enhancements of gas and aerosol concentrations in populated and agricultural regions due to industrial and biomass burning emissions thousands of kilometers upstream. Even many "remote" marine regions are far from being free from the direct influence of relatively short-lived anthropogenically produced gases and aerosols produced over far away continents. Additional processes such as stratosphere-troposphere exchange and lightning can also influence the chemical composition of downwind locations. Numerous methods have been applied to study transport-related issues, including targeted and long-term in-situ measurements as well as remote sensing (ground-based and satellite) and models (cloud-scale to global).

Lagrangian models are a very important research tool in this context, yet numerous scientific issues remain. We therefore invite studies contributing to advancing Lagrangian models, including the improvement of parameterizations of atmospheric processes, the quantitative assessment of uncertainties, improving model performance, and the proper coupling of Lagrangian models to Eulerian Numerical Weather Prediction and General Circulation models. In addition we invite contributions from applied Lagrangian research, involving observational data. We specially encourage those studies which synergistically combine various types of models and observations.