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Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 CMAS)
Citation:
Luo, H., M. Astitha, S. Rao, C. Hogrefe, R. Mathur, AND N. Kumar. Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 CMAS). 16th CMAS Conference, Chapel Hill, North Carolina, October 23 - 25, 2017.
Impact/Purpose:
By comparing observed and CMAQ-simulated long term changes in ozone, the work in this study addresses the question of how well CMAQ performs when applied to simulate the effects of changing emissions and meteorological variability on ozone. Results reinforce the notion inherent in current air quality planning applications that CMAQ is better at predicting changes in ozone changes than at simulating absolute ozone levels. Moreover, results also show that ozone exceedances depend on the magnitude of long-term forcing and that a better simulation of long-term forcing results in a better prediction of ozone extremes. This implies that model development efforts directed at improving the characterization of long-term ozone fluctuations and their changes over time would be expected to yield benefits for air quality planning applications.
Description:
Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and/or emissions are also evaluated during the same timeframe using spectral decomposition of observed and modeled ozone time series with the aim of identifying the underlying forcing mechanisms that control ozone exceedances and making informed recommendations for the optimal use of regional-scale air quality models. During the earlier 11-yr period (1990-2000), the simulated and observed trends are not statistically significant. During the more recent 2000-2010 period, all observed trends are statistically significant and WRF-CMAQ captures the observed downward trend in the Southwest and Midwest but under-predicts the downward trends in observations for the other regions. Observational analysis reveals that it is the magnitude of the long-term forcing that dictates the maximum ozone exceedance potential; there is a strong linear relationship between the long-term forcing and the 4th highest or the average of the top10 ozone concentrations in both observations and model output. This finding indicates that improving the model’s ability to reproduce the long-term component will also enable better simulation of ozone extreme values.
