A variety of statistical methods for meteorological adjustment of ozone hav
e been proposed in the literature over the last decade for purposes of fore
casting, estimating ozone time trends, or investigating underlying mechanis
ms from an empirical perspective. The methods can be broadly classified int
o regression, extreme value, and space-time methods. We present a critical
review of these methods, beginning with a summary of what meteorological an
d ozone monitoring data have been considered and how they have been used fo
r statistical analysis. We give particular attention to the question of tre
nd estimation, and compare selected methods in an application to ozone time
series From the Chicago area. We conclude that a number of approaches make
useful contributions to the field, but that no one method is most appropri
ate for all purposes and all meteorological scenarios. Methodological issue
s such as the need for regional-scale analysis, the nonlinear dependence of
ozone on meteorology, and extreme value analysis for trends are addressed.
A comprehensive and reliable methodology for space-time extreme value anal
ysis is attractive but lacking. Published by Elsevier Science Ltd.