Abstract:
A major issue with the analysis of data on tropospheric ozone is to establish whether observed trends in the data are real, meaning that they could be attributed to actual changes in the emissions of toxic gases into the atmosphere, or whether they are the result of meteorological changes affecting the conditions under which ozone is generated. One way of investigating this question is to construct a regression model in which the level of ozone is represented as a function of both meteorological variables and time, in order to determine the significance of the time component when the meteorological variables are taken into account. However, the conventional methods of regression analysis do not make any distinction between low and high levels of the series, whereas with ozone it is largely the high levels that are of interest and concern. This paper proposes a method of regression analysis that is based entirely on the exceedances over a high threshold, and applies the method to data from the Houston area.
Keywords:
Diagnostic model testing; Generalized Pareto distributions; Meteorological conditions; Nonhomogeneous Poisson process.
tr16.pdf