期刊
ATMOSPHERIC CHEMISTRY AND PHYSICS
卷 14, 期 15, 页码 7721-7739出版社
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/acp-14-7721-2014
关键词
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资金
- NSF
- NSF REU [1005042]
- NASA Modelling, Analysis, and Prediction Program [NNX13AL12G]
- Office of Science (BER) of the US Department of Energy [DE-SC0007021]
- Kavli Chair in Earth System Science
- U.S. Department of Energy (DOE) [DE-SC0007021] Funding Source: U.S. Department of Energy (DOE)
- Directorate For Geosciences [1005042] Funding Source: National Science Foundation
- Div Atmospheric & Geospace Sciences [1005042] Funding Source: National Science Foundation
- NASA [470336, NNX13AL12G] Funding Source: Federal RePORTER
From the ensemble of stations that monitor surface air quality over the United States and Europe, we identify extreme ozone pollution events and find that they occur predominantly in clustered, multiday episodes with spatial extents of more than 1000 km. Such scales are amenable to forecasting with current global atmospheric chemistry models. We develop an objective mapping algorithm that uses the heterogeneous observations of the individual surface sites to calculate surface ozone averaged over 1 degrees by 1 degrees grid cells, matching the resolution of a global model. Air quality extreme (AQX) events are identified locally as statistical extremes of the ozone climatology and not as air quality exceedances. With the University of California, Irvine chemistry-transport model (UCI CTM) we find there is skill in hindcasting these extreme episodes, and thus identify a new diagnostic using global chemistry-climate models (CCMs) to identify changes in the characteristics of extreme pollution episodes in a warming climate.
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