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COMBINING EMPIRICAL ORTHOGONAL FUNCTION AND EXTREME VALUE THEORY METHODS TO CHARACTERIZE OBSERVED AND FUTURE CHANGES IN EXTREME U.S. AIR POLLUTION EVENTS
Impact/Purpose:
We will identify and characterize changes in extreme ozone and particulate matter events and their underlying meteorological drivers (including associated feedbacks) leading to extreme air pollution events over the past several decades (with observations and models), as well as for a variety of future climate and emission scenarios. Since particulate matter depends on precipitation (the major sink), we will also examine changes in extreme precipitation events (intensity and duration) and extended periods with minimal precipitation (extreme drought), to provide information on two of the key hazards affecting water quality.
Description:
The occurrence of meteorological conditions associated with poor air quality (i.e. elevated levels of ozone and particulate matter) that are classified as extreme events at present are expected to increase in a warmer climate. Using state-of-the-art statistical techniques, we will construct (for several U.S. regions) probability tables and simple statistical models which will translate future climate model projections under different pollutant emission scenarios into statistical forecasts of extreme events.