In this study, we provide a new perspective on the current state of the ozone layer using a comprehensive long-term total ozone data record which has been recently released within the framework of the European Space Agency's Climate Change Initiative. Based on a multivariate regression analysis, we disentangle various aspects of ozone change and variability on global and regional scales, thus enabling the monitoring of the effectiveness of the Montreal Protocol. Given dominant natural variability the expected midlatitude onset of ozone recovery is still not significant and would need additional 5 years of observations to be unequivocally detectable. A regional increase in the tropics is a likely manifestation of a long-term change in El Niño-Southern Oscillation intensity over the last two decades induced by strong El Niño in 1997/1998 and strong La Niña in 2010/2011.

Precise knowledge of the location and height of the volcanic sulphur dioxide (SO 2) plume is essential for accurate determination of SO 2 emitted by volcanic eruptions. Current SO 2 plume height retrieval algorithms based on ultraviolet (UV) satellite measurements are very time-consuming and therefore not suitable for near-real-time applications. In this work we present a novel method called the full-physics inverse learning machine (FP-ILM) algorithm for extremely fast and accurate retrieval of the SO 2 plume height. FP-ILM creates a mapping between the spectral radiance and the geophysical parameters of interest using supervised learning methods. The FP-ILM combines smart sampling methods, dimensionality reduction techniques, and various linear and non-linear regression analysis schemes based on principal component analysis and neural networks. The computationally expensive operations in FP-ILM are the radiative transfer model computations of a training dataset and the determination of the inversion operatorthese operations are performed off-line. The application of the resulting inversion operator to real measurements is extremely fast since it is based on calculations of simple regression functions. Retrieval of the SO 2 plume height is demonstrated for the volcanic eruptions of Mt. Kasatochi (in 2008) and Eyjafjallajökull (in 2010), measured by the GOME-2 (Global Ozone Monitoring Instrument-2) UV instrument on-board MetOp-A.

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