Kim, Hyun Cheol, National Oceanic and Atmospheric
Administration/ARL, Songyou Hong, Yonsei University, Fantine Ngan, and Pius
Lee, NOAA/ARL
We investigated the
impacts of meteorology downscaling in regional air quality simulation. Multiple
global (or semi-global) meteorology simulations have been utilized to initiate
regional meteorology simulations, and their impacts on regional air quality
simulations are studied. Weather Research and Forecasting (WRF) modeling system
is used to simulated regional meteorology using initializations from North
American Mesoscale Model (NAM), Global Forecast System (GFS), and
Global/Regional Integrated Model system (GRIMs), and Community Multi-scale Air
Quality/Sparse Matrix Operator Kernel Emission (CMAQ/SMOKE) modeling system is
used to simulated regional air quality. Impacts of meteorological variables
(e.g. surface temperature, wind speed,
boundary layer, precipitation, and frontal activities) on forecast
pollutant concentrations were investigated using surface observations from numerous
observational sources, including the Meteorological Assimilation Data Ingest
System (MADIS), the EPA AirNOW/AQS, the Interagency Monitoring of Protected
Visual Environments (IMPROVE), and Continuous Ambient Monitoring Stations
(CAMS). Results show that the variance of key meteorological parameters, such
as synoptic wind patterns and surface temperature, have strong correlation with
a pollutantŐs variation and the modelŐs forecast performance (e.g. ozone bias).
We present how the differences in frontal passage location and timing affect
production and removal of regional air pollutants. For the eastern US,
locations of surface temperature bias are also well associated with surface
ozone bias, implying potential explanation for the surface ozone bias during
summertime in this region. Analysis of multi-year trend revealed a one-degree
change of surface temperature was associated with up to 10% increase of
afternoon ozone.