121e Effect of Temporal Averaging of Vertical Eddy Diffusivity on the Forecast Quality of Surface Zone Concentration of the National Air Quality Forecast Capability

Pius C. Lee1, Youhua Tang1, Jeff McQueen1, Hochun Huang1, Sarah Lu1, Marina Tsidulko1, Rohit Mathur2, Jon Pleim2, Tanya Otte2, George Pouliot2, Ken Schere2, and Paula Davidson3. (1) Emc/ncep/noaa, NOAA, 5200 Auth Rd, Camp Springs, MD 20746, (2) Atmospheric Modeling Division, NOAA, US EPA, Rtp, NC 27711, (3) Nws/noaa, Office of Science and Technology, 1327 East West Hwy, Silver Spring, MD 20910

Air Quality forecast models are employed to provide numerical guidance for forecasters to issue timely ozone and particulate matter concentration forecast pertinent to human health exposures to the communities they serve. The National Centers for Environmental Prediction (NCEP), National Weather Service Weather Research and Forecasting Non-hydrostatic Mesoscale Model (WRF/NMM) has been coupled with the EPA Community Multi-scale Air Quality (CMAQ) model to form the National Air Quality Forecast Capability (NAQFC). It provides such guidance for the majority part of the U.S. since 2006. This capability first provided forecast coverage over the northeastern U.S. in 2004 with WRF predecessor, the Eta model, as the meteorological driver. Both the earlier and the current capabilities are off line systems. Coupling of the turbulent mixing processes of the meteorological driver and CMAQ has been a challenge. Both Eta and WRF/NMM use the Mellor-Yamada-Janjic (MYJ) turbulence mixing scheme in the boundary layer. The option of directly using MYJ provided vertical eddy diffusivity to calculate turbulent mixing of the atmospheric constituents in CMAQ has been tested. This study investigated the effect of various temporal averaging treatments of vertical eddy diffusivity in redistributing ozone in the boundary layer. Model predicted concentration structures of ozone resulting from these various temporal treatments of vertical eddy diffusivity have been studied and verified using AIRNOW, an EPA surface ozone concentration network, and ozone-sonde data.