84th AMS Annual Meeting

Tuesday, 13 January 2004: 4:45 PM
Fully coupled “online” chemistry within the WRF model
Room 605/606
Georg A. Grell, NOAA/ERL/FSL and CIRES/ Univ. of Colorado, Boulder, CO; and S. E. Peckham, R. Schmitz, and S. A. McKeen
Poster PDF (446.2 kB)
A fully coupled “online” version of WRF-chem model has been developed. In this form, the air quality version of the model is consistent, with all transport done by the meteorology model. The same vertical and horizontal coordinates are used (no horizontal or vertical interpolation), the same physics parameterization utilized for subgrid scale transport, and no interpolation in time is performed. This allows for easy handling from a data management standpoint, and is also the most efficient with regard to overall CPU costs. Grid-scale advection in the mass coordinate WRF is mass and scalar conserving.

The Chemistry Package consists of dry deposition ( "flux-resistance" method), biogenic emission (as in Simpson, et al. 1995 and Guenther et al. 1994), the chemical mechanism from RADM2, a complex Photolysis scheme, (Madronich scheme coupled with hydrometeors), and a state of the art aerosol module (MADE/SORGAM aerosol parameterization). The aerosol module was also coupled to the photolysis routine as well as the atmospheric radiation scheme to allow for feedback from the chemistry to the meteorology.

In addition to simulating the weather or -- in its most complicated form -- the air quality, this numerical modeling system may also be used as a coupled weather prediction and chemical dispersion model in order to forecast the release and transport of atmospheric tracers (through grid and subgrid-scale transport, emissions, and deposition).

This modeling system has been evaluated with retrospective simulations on NOAA/FSL's massively parallel supercomputer with data from the 2002 New England Air Quality Study (NEAQS). It is also being run in real-time to predict air quality over the central and eastern US. In addition to describing the modeling system, we will show results from comparisons of air quality predictions to observations.

Supplementary URL: