Arellano, Ave, University of Arizona
We present the
development and application of an ensemble-based data assimilation system for
regional air quality studies. The
system includes the community model, WRF-Chem and the community software, DART.
This system is built upon the broad experience, within the WRF-Chem development
and user community in simulating radiatively- and chemically-active atmospheric
constituents, as well as, within the WRF/DART community on their experience in
assimilating meteorological observations for local to regional studies. Here,
we apply WRF-Chem/DART to explore the utility of satellite-derived measurements
of atmospheric constituents (i.e. O3, aerosols, CO, and CO2) in improving the
predictive capability of WRF-Chem in simulating the distribution of these
constituents and their interaction with meteorology. In this talk, we will show
results of assimilating MODIS aerosol optical depth, MOPITT CO, IASI O3, or the
ACOS XCO2 satellite retrievals, on top of assimilating meteorological
observations in WRF-Chem. In this manner, the system mimics a numerical weather
prediction with chemistry, which then offers a useful tool in assessing the
value of these retrievals to chemical weather forecasting and analysis.