Comparison of assimilated meteorological inputs for use in air quality modeling during the TexAQS-II intensive study period

The Second Texas Air Quality Study (TexAQS-II) was conducted in summer 2006 to understand regional air quality problems through the comprehensive meteorological and chemical in Eastern Texas. During August 30th – September 1st, a high ozone episode occurred after passage of a front previous day. Southeastern Texas was dominant by continental high pressure system and subjected by northeasterly to easterly synoptic winds. The ozone peak concentrations continued to increase for three days from 95 ppb, 147 ppb and to 153 ppb, respectively. To understand physical and chemical processes influencing air quality, an accurate description of meteorological condition is essential. In this study, we utilized the existing objective analysis and nudging four-dimensional data assimilation (FDDA) tools in the fifth-generation Penn State/NCAR Mesoscale Model (MM5) to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates surface and upper air meteorological observations for the retrospective simulation of the TexAQS-II period. We intend to generate better initial and boundary conditions using the objective analysis and use the recursive nudging procedure to maximize the correcting capabilities of FDDA. Being used as a regional meteorological model to drive chemical simulations in a fine scale, MM5 carries on the synoptic signals from global analyses. To improve regional meteorological simulation results, three sets of analyses data including NCEP/NOAA North American Model reanalysis (NAM), North American Regional Reanalysis (NARR) and Global Forecast System (GFS) were used to initialize the model and provide lateral boundary condition. The EPA Models-3 Community Multiscale Air Quality modeling system (CMAQ) were performed with different MM5 inputs and the results were evaluated with the observations during the TexAQS-II campaign to study how different meteorological inputs affects air quality simulation.