Many types of extreme atmospheric events can be identified:
high pollution episode generated by large fires
high pollution peaks on large urban areas
major industrial accident
Objective and approach
This study aimed to define a method for the detection and the characterisation of exceptional atmospheric events, like those listed above,
and to develop a software able to process IASI data in near real-time.
Two methods based on Principal Component Analysis (PCA) were implemented and assessed: i) standard PCA of spectra based upon reference database
optimized for detection of extreme events; ii) innovative approach combining PCA and technique of principal angles, exploiting jointly
simulated and measured reference databases.
The prototype was evaluated against two IASI datasets: i) few cases of atmospheric events for validating the method; ii) one year of global IASI data, including clearly identified episodes of reference, for assessing the software performance.