Eulerian Simulation of Tracer Distribution during CAPTEX

Richard A. Brost National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado

Search for other papers by Richard A. Brost in
Current site
Google Scholar
PubMed
Close
,
Philip L. Haagenson National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado

Search for other papers by Philip L. Haagenson in
Current site
Google Scholar
PubMed
Close
, and
Ying-Hwa Kuo National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado

Search for other papers by Ying-Hwa Kuo in
Current site
Google Scholar
PubMed
Close
Full access

Abstract

We compared observed and model-simulated surface concentration on a spatial wale of 1100 km and a temporal scale of 36 h. The Eulerian tracer model calculated advection by the mean winds and gradient transport for subgrid-scale turbulent transfer. The simulations were evaluated by the maximum concentrations, spatial correlations between concentrations, plume sizes, and trajectory errors. We examined the following inputs and model parameters: 1) different meteorologies, including simulated, observed, and combinations of the two; 2) the spatial and temporal resolution of the observations; 3) the spatial resolution of the meteorological model; and 4) the spatial resolution of the tracer model. The best meteorology was observed horizontal winds, enhanced with additional, nonstandard rawinsondes and model-simulated eddy diffusivities. The spatial resolution of the tracer model was more important than that of the meteorological model. Meteorology from a mesoscale model could be competitive with that from standard observations. We found consistency between different measures of tracer simulation quality.

Abstract

We compared observed and model-simulated surface concentration on a spatial wale of 1100 km and a temporal scale of 36 h. The Eulerian tracer model calculated advection by the mean winds and gradient transport for subgrid-scale turbulent transfer. The simulations were evaluated by the maximum concentrations, spatial correlations between concentrations, plume sizes, and trajectory errors. We examined the following inputs and model parameters: 1) different meteorologies, including simulated, observed, and combinations of the two; 2) the spatial and temporal resolution of the observations; 3) the spatial resolution of the meteorological model; and 4) the spatial resolution of the tracer model. The best meteorology was observed horizontal winds, enhanced with additional, nonstandard rawinsondes and model-simulated eddy diffusivities. The spatial resolution of the tracer model was more important than that of the meteorological model. Meteorology from a mesoscale model could be competitive with that from standard observations. We found consistency between different measures of tracer simulation quality.

Save