Citation:

Appel, W., R. Gilliam, Jon Pleim, G. Pouliot, S. Roselle, AND R. Mathur. Fine-scale application of the WRF-CMAQ modeling system to the 2013 DISCOVER-AQ San Joaquin Valley study. American Meteorological Society Annual Meeting, Phoenix, AZ, January 07, 2015.

Impact/Purpose:

The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Description:

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In January/February 2013, the DISCOVER-AQ project conducted intensive air quality measurements over the San Joaquin Valley in California. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality over the same region using 4-km and 2-km horizontal grid spacings. The goal of modeling exercise is to evaluate the impact on model performance of applying the coupled WRF-CMAQ modeling system at fine scales (e.g. 4 and 2km) compared to more coarse regional scale simulations (e.g. 12km). New data assimilation techniques and high resolution input data for the WRF model that were developed as part of previous fine-scale WRF-CMAQ application over the eastern United States will be applied to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions (e.g anthropogenic heating) will be assessed. Data collected during the 2013 DISCOVER-AQ campaign, which include aircraft transects and spirals, ozonesondes, tethered balloon measurements, LIDAR measurements, and intensive ground-based site measurements are used to evaluate results from the WRF-CMAQ modeling system. The results of the comparisons of the model output to these measurements will be presented, along with results from the various sensitivity simulations examining the impact the various updates to the modeling system have on the model estimates. Finally, the results will be compared to results from previous fine-scale applications performed for California during the California Nexus (CalNex) study in 2010.

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