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Development of the Next Generation Air Quality Modeling System
Citation:
Pleim, Jon, R. Gilliam, David-C Wong, J. Herwehe, R. Bullock, G. Pouliot, C. Hogrefe, W. Appel, Bill Hutzell, D. Kang, L. Ran, AND H. Foroutan. Development of the Next Generation Air Quality Modeling System. 16th Annual CMAS Conference, Chapel Hill, North Carolina, October 23 - 25, 2017.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinement and online atmospheric chemistry; 2. Regional (limited area) online meteorology and chemistry; 3. Offline (sequential) regional meteorology and chemistry. A one-dimensional air quality (AQ) component, built from state of the science chemistry and aerosol modules from the Community Multiscale Air Quality (CMAQ) model will be used in all three configurations. For the Global online configuration, the AQ component will be coupled to the Model for Prediction Across Scales – Atmosphere (MPAS-A), which is a global meteorological model with seamless mesh refinement developed at the National Center for Atmospheric Research (NCAR). The regional configurations will be coupled with WRF although we may also use a regional version of MPAS that has recently been developed at NCAR. In the presentation we will describe our modifications to MPAS to improve its suitability for retrospective air quality applications and show evaluations of global and regional meteorological simulations. Our modifications include addition of physics schemes that we developed for WRF that are particularly designed for air quality applications: the Pleim surface layer (PSL), the Pleim-Xiu (PX) land surface model with fractional land use for a 40-class National Land Cover Database (NLCD40), and the Asymmetric Convective Model 2 (ACM2) planetary boundary layer scheme. We also added analysis nudging four-dimensional data assimilation (FDDA) to control error growth for long term retrospective simulations. In addition, we updated the KF scheme in MPAS to the latest version which adds subgrid-scale cumulus cloud feedback to the radiation schemes, multiple convective triggers, and a scale-aware convective time scale (Jerry Herwehe will present this work). We will also show preliminary MPAS-AQ results where we have incorporated CMAQ modules for atmospheric chemistry and deposition in MPAS.
