"Lagrangian Particle" Modelling Approach

We are engaged in the development of a "Lagrangian particle" approach to simulate tracer transport in the atmosphere. The Lagrangian particles represent air parcels of unit mass that can be tagged with concentrations of various tracers. Depending on the specific scientific problem to be addressed, the tracer can be water, greenhouse gases such CO2 and CH4, or pollutants such as CO and mercury.

Our Lagrangian modelling approach possesses three unique characteristics:

1) The particles move with both deterministic and stochastic velocities, simulating the effects of mean wind and random eddies, respectively. This enables a much more detailed and accurate representation of atmospheric transport, paricularly in the lower atmosphere, where turbulence is strong and where the traditional approach of simulating atmospheric transport with single mean-wind trajectories can be subject to large errors.

2) By simulating particles moving backward in time from an observation location, they mark out the air parcels that comprise the observation, as well as their transport history. These air parcels provide powerful information to interpret atmospheric observations. For instance, if a plume of a pollutant is observed at a measurement site, the time-reversed simulations of particles starting at the site would reveal potential source regions that emitted the pollutant.

3) The particles can resolve sub-gridscale influences since they are not tied to grids (winds are interpolated down to the particles' locations to move them). This is particularly important in cases where strong and variable sources/sinks are found in the "near-field" of a measurement site.

The specific model that has been developed with the characteristics described above is the Stochastic Time-Inverted Lagrangian Transport (STILT) model. The paper describing the technical details of the STILT model can be found here.

Click here for an animation of a 3-D simulation from STILT.