Abstract

<p>The 3 IASI instruments on-board the Metop satellites have been sounding the atmospheric composition since 2006. Up to ~30 atmospheric gases can be measured from IASI spectra, allowing the improvement of weather forecasting, and the analysis and monitoring of atmospheric chemistry and climate variables.</p><p>The early detection of extreme events such as fires, pollution episodes, volcanic eruptions, industrial accidents, is key to take appropriate decisions regarding safety to protect inhabitants and the environment in the target areas. With IASI providing global observations twice a day in near real time, a new way for the systematic and continuous detection of exceptional atmospheric events to support operational decisions is possible.</p><p>In this work, we explore and improve a method for the detection and characterization of extreme events using the recorded spectra, which relies on the principal component analysis (PCA) method. We assess this PCA-based system by analysing IASI raw and reconstructed spectra along with their differences (residuals) for various past and documented extreme events. The benefits and limitations of this approach are discussed with comparison with available CO and SO<sub>2</sub> IASI products. A methodological innovation, based on the refined analysis of extreme residuals (outliers) for the detection of fires, volcanic eruptions and pollution event is proposed, and could be used for the automatic and systematic detection of unexpected events.</p>

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