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Near-real time detection of unexpected atmospheric events using Principal Component Analysis on the IASI radiances.
- Source :
- EGUsphere; 12/20/2022, p1-31, 31p
- Publication Year :
- 2022
-
Abstract
- The three 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 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 for the near real time detection and characterization of unexpected events, which relies on the principal component analysis (PCA) of IASI radiance spectra. By analysing both the IASI raw and compressed spectra, we applied a PCA-granule based method on various past well documented extreme events such as volcanic eruptions, fires, anthropogenic pollutions and industrial accidents. We demonstrate that the method is well suited to detect spectral signatures for reactive and weak absorbing gases, even for sporadic events. Long-term records are also generated for fire and volcanic events, by analysing the available IASI/Metop-B data record. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- Database :
- Complementary Index
- Journal :
- EGUsphere
- Publication Type :
- Academic Journal
- Accession number :
- 160892363
- Full Text :
- https://doi.org/10.5194/egusphere-2022-1372