Cloud Correction and its Impact on Air Quality Simulations

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Wednesday, 5 February 2014: 9:00 AM
Room C206 (The Georgia World Congress Center )
Arastoo Pour Biazar, Univ. of Alabama, Huntsville, AL; and R. T. McNider, M. Khan, Y. H. Park, B. Dornblaser, and K. Doty

Clouds significantly affect tropospheric chemistry. They have a critical role in modulating photolysis rates, impact boundary-layer development, lead to deep vertical mixing of pollutants and precursors, and induce aqueous phase chemistry. Air quality simulations, used in the State Implementation Plan (SIP) attainment demonstration, rely on simulated clouds from a meteorological model. Unfortunately, numerical meteorological models still have difficulty in creating clouds in the right place and time compared to observed clouds. This is especially the case when synoptic-scale forcing is weak, as often is the case during air pollution episodes. A poor representation of clouds impacts the photochemical model's ability to correctly predict trace gas and aerosol concentrations. In this study the impact of errors in cloud prediction on air quality simulations is examined. First, the Geostationary Operational Environmental Satellite (GOES) derived cloud fields are assimilated within Weather Research and Forecasting (WRF) model to improve simulated clouds. Second, air quality simulations using the Community Multiscale Air Quality (CMAQ) with and without cloud correction are performed and evaluated against surface observations. A technique was developed to dynamically support cloud formation/dissipation within WRF based on GOES observations. Satellites provide an observational platform for defining the formation and location of clouds. The technique was implemented and tested in WRF for a month-long simulation during August 2006. The technique proved to be effective regardless of the convective parameterization scheme used. The cloud correction not only improved the spatial and temporal distribution of clouds, it also improved boundary layer temperature, humidity, and wind speed. These improvements in meteorological fields directly impacted the air quality simulations and altered trace gas concentrations. Preliminary results from air quality model evaluations will be presented.