Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-2813-2018
https://doi.org/10.5194/gmd-11-2813-2018
Model description paper
 | 
13 Jul 2018
Model description paper |  | 13 Jul 2018

Simulating atmospheric tracer concentrations for spatially distributed receptors: updates to the Stochastic Time-Inverted Lagrangian Transport model's R interface (STILT-R version 2)

Benjamin Fasoli, John C. Lin, David R. Bowling, Logan Mitchell, and Daniel Mendoza

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Cited articles

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Short summary
The Stochastic Time-Inverted Lagrangian Transport (STILT) model is used to determine the area upstream that influences the air arriving at a given location. We introduce a new framework that makes the STILT model faster and easier to deploy and improves results. We also show how the model can be applied to spatially complex measurement strategies using trace gas observations collected onboard a Salt Lake City, Utah, USA, light-rail train.