A21A-0018
Multiple Sensitivity Testing for Regional Air Quality Model in summer 2014
Tuesday, 15 December 2015
Poster Hall (Moscone South)
Youhua Tang1,2, Pius Lee3, Li Pan2, Daniel Tong2, Hyun C Kim4, Min Huang5, Jun Wang6, Jeffrey McQueen6, Cheng-Hsuan Lu3 and Richard S Artz4, (1)NOAA Air Resources Laboratory, College Park, MD, United States, (2)Cooperative Institute for Climate and Satellites University of Maryland, College Park, MD, United States, (3)NOAA, Boulder, CO, United States, (4)NOAA College Park, College Park, MD, United States, (5)Jet Propulsion Laboratory, Pasadena, CA, United States, (6)NOAA, Center for Weather and Climate Prediction, National Weather Service, College Park, MD, United States
Abstract:
The NOAA Air Resources laboratory leads to improve the performance of the U.S. Air Quality Forecasting Capability (NAQFC). It is operational in NOAA National Centers for Environmental Prediction (NCEP) which focuses on predicting surface ozone and PM2.5. In order to improve its performance, we tested several approaches, including NOAA Environmental Modeling System Global Aerosol Component (NGAC) simulation derived ozone and aerosol lateral boundary conditions (LBC), bi-direction NH3 emission and HMS(Hazard Mapping System)-BlueSky emission with the latest U.S. EPA Community Multi-scale Air Quality model (CMAQ) version and the U.S EPA National Emission Inventory (NEI)-2011 anthropogenic emissions. The operational NAQFC uses static profiles for its lateral boundary condition (LBC), which does not impose severe issue for near-surface air quality prediction. However, its degraded performance for the upper layer (e.g. above 3km) is evident when comparing with aircraft measured ozone. NCEP’s Global Forecast System (GFS) has tracer O3 prediction treated as 3-D prognostic variable (Moorthi and Iredell, 1998) after being initialized with Solar Backscatter Ultra Violet-2 (SBUV-2) satellite data. We applied that ozone LBC to the CMAQ’s upper layers and yield more reasonable O3 prediction than that with static LBC comparing with the aircraft data in Discover-AQ Colorado campaign. NGAC’s aerosol LBC also improved the PM2.5 prediction with more realistic background aerosols. The bi-direction NH3 emission used in CMAQ also help reduce the NH3 and nitrate under-prediction issue. During summer 2014, strong wildfires occurred in northwestern USA, and we used the US Forest Service’s BlueSky fire emission with HMS fire counts to drive CMAQ and tested the difference of day-1 and day-2 fire emission estimation. Other related issues were also discussed.
