4.6 Article

Meteorological Conditions During an Ozone Episode in Dallas-Fort Worth, Texas, and Impact of Their Modeling Uncertainties on Air Quality Prediction

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 124, Issue 4, Pages 1941-1961

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2018JD029791

Keywords

inherent meteorology uncertainty; ensemble air quality forecasting; stationary front; ozone; Dallas-Fort Worth

Funding

  1. National Key R&D Program of China [2016YFC0201900]
  2. NASA [NNX17AG11G]
  3. NSF [AGS-0941491, AGS-1046171, AGS-1046081, AGS-1261776]
  4. NASA [1001536, NNX17AG11G] Funding Source: Federal RePORTER

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The Southern Great Plains experiences an unhealthy level of ozone (O-3) at times. The formation mechanisms contributing to these O-3 events are not always clear and in some cases are related to particular atmospheric circulation patterns. A severe O-3 pollution event on 27 August 2011 in the Dallas-Fort Worth (DFW) area is investigated with a combination of observations and simulations using the Weather Research and Forecasting model with Chemistry (WRF/Chem). During the O-3 episode, a stationary front with a stagnant zone at the leading edge persisted to the west of DFW. At the time, Hurricane Irene was located in western Atlantic, displacing the Bermuda Subtropical High and affecting the circulations over the Southern Great Plains. The stagnant zone confined the pollutant plume originating from DFW, leading to accumulation of primary pollutants and prominent O-3 formation. Emission sources from a few urban areas east of DFW as well as power plants near Mount Pleasant and Carthage also contributed to this DFW O-3 pollution episode. This scenario is different from the typical summer days over the Southern Great Plains when southerly winds prevail along the west edge of the Bermuda High and the pollutant plumes from DFW are advected downstream, resulting in low O-3. Ensemble WRF/Chem predictions driven by the operational Short-Range Ensemble Forecast outputs are conducted to examine the impact of meteorological uncertainties (particularly transport uncertainties) on air quality forecasting. The ensemble mean gives a better prediction in terms of plume directions than individual members.

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