8.5
Impact of marine boundary layer parameterization schemes on surface ozone prediction in coastal regions

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Thursday, 27 January 2011: 2:45 PM
Impact of marine boundary layer parameterization schemes on surface ozone prediction in coastal regions
3A (Washington State Convention Center)
Jianping Huang, NOAA/NWS/NCEP, Camp Springs, MD; and J. McQueen, Y. Tang, M. Tsidulko, H. C. Huang, S. Lu, C. Tassone, B. Lapenta, G. DiMego, D. W. Byun, P. Lee, Y. Choi, D. Tong, and I. Stajner

The National Air Quality Forecasting Capability (NAQFC), linking the National Centers for Environmental Prediction (NCEP)'s Weather Research and Forecasting/Non-hydrostatic Mesoscale Model (WRF/NMM) with the Community Multiscale Air Quality (CMAQ) model, provides numerical guidance for surface ozone predictions. In coastal regions the NAQFC often over-predicts surface ozone. Two of the factors that may contribute this prediction bias are considered here: the planetary boundary layer (PBL) parameterization schemes and the minimum marine PBL height. Three different planetary boundary layer height schemes are available in the NAQFC: WRF/NMM predicted turbulence kinetic energy-based (TKE) PBL height, the PBL height calculated from the bulk Richardson number, and the PBL height calculated with the Asymmetric Convective Model version 2 (ACM2) in the CMAQ pre-processor, PreMAQ. The ACM2 scheme is used in real-time NAQFC predictions. The minimum PBL height is assumed to be the first level of the model (around 40 meters over the ocean). In this study, a series of sensitivity runs including case studies and real-time simulations are conducted to examine the possible impacts of PBL parameterization schemes and varying minimum marine PBL height on surface ozone predictions in the coastal regions. The NCEP Environmental Modeling Centers (EMC) Forecast Verification System (FVS) is then used to quantify their impacts on the surface ozone predictions. Finally, recommendations such as a more realistic minimum value of marine PBL height are proposed to improve surface ozone predictions in these regions.