Near-real-time detection of unexpected atmospheric events using principal component analysis on the Infrared Atmospheric Sounding Interferometer (IASI) radiances

The three Infrared Atmospheric Sounding Interferometer (IASI) instruments on board the Metop family of satellites have been sounding the atmospheric composition since 2006. More than 30 atmospheric gases can be measured from the IASI radiance spectra, allowing the improvement of weather forecasting and the monitoring of atmospheric chemistry and climate variables. The early detection of extreme events such as fires, pollution episodes,volcanic eruptions, or industrial releases is key to take safety measures to protect the inhabitants and the environment in the impacted areas. With its near-real-time observations and good horizontal coverage, IASI can contribute to the series of monitoring systems for the systematic and continuous detection of exceptional atmospheric events in order to support operational decisions. In this paper, we describe a new approach to the near-real-time detectionand characterization of unexpected events, which relies on the principalcomponent analysis (PCA) of IASI radiance spectra. By analyzing both theIASI raw and compressed spectra, we applied a PCA-granule-based method onvarious past, well-documented extreme events such as volcanic eruptions,fires, anthropogenic pollution, and industrial accidents. We demonstratethat the method is well suited to the detection of spectral signatures for reactive and weakly absorbing gases, even for sporadic events. Consistent long-term records are also generated for fire and volcanic events from the available IASI/Metop-B data record. The method is running continuously, delivering email alerts on a routinebasis, using the near-real-time IASI L1C radiance data. It is planned to beused as an online tool for the early and automatic detection of extremeevents, which was not done before.