The variability of stratospheric ozone in a 29 year assimilated data set and sensitivity calculations

Consistent observation-based data sets of stratospheric ozone are needed in order to resolve many of the pending questions regarding stratospheric ozone. Satellite observations are available since the late 1970s; however, as most observational methods rely on backscattered sunlight, these do not provide complete long-term coverage of the stratosphere, in particular during polar night. In this PhD thesis, a 29 year data set of stratospheric ozone is introduced that has been generated from sequential assimilation of satellite observations into the Bremen 3D Chemistry Transport Model (CTM). In the method of data assimilation, a three-dimensional physical computer model is used to close the gaps between single measurements. Observations constrain the CTM where available, and at the same time the information is propagated into areas where no observations are available. Here, profile ozone observations from the Solar Backscatter UV (SBUV and SBUV/2) instruments are used, which have been in orbit continuously since 1978. The resulting assimilated data set is validated against independent observations from other satellite platforms and in-situ observations with sondes. Agreement to independent observations is excellent throughout most of the stratosphere, and the assimilated data set can thus be used as a consistent extension of the satellite record beyond the limits of data coverage. The assimilated data set, in conjunction with sensitivity calculations with the unconstrained CTM, is used to analyse the variability of stratospheric ozone during the last three decades on two distinctly different temporal and spatial domains. The first research question deals with the short-term variability of polar ozone during winter. The Arctic ozone layer is subject to large inter-annual variations during spring; although statistical connections between dynamical quantities in winter and springtime total ozone abundance are known, little is known about how ozone anomalies develop and evo