Publication Date:
2013-06-21
Description:
In this paper, we develop an algorithm based on combining spectral, spatial, and temporal thresholds from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) daytime measurements to identify and track different aerosol types, primarily volcanic ash. Contemporary methods typically do not use temporal information to identify ash. We focus not only on the identification and tracking of volcanic ash during the Eyjafjallajökull volcanic eruption period beginning 14 April 2010 to May but a pixel level classification method for separating various classes in the SEVIRI images. Three case studies on 19 April, 16 May, and 17 May are analyzed in extensive detail with other satellite data including the Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Facility for Airborne Atmospheric Measurements (FAAM) BAe146 aircraft data to verify the aerosol spatial distribution maps generated by the SEVIRI algorithm. Our results indicate that the SEVIRI algorithm is able to track volcanic ash even at these high latitudes. Furthermore, the BAe146 aircraft data shows that the SEVIRI algorithm detects nearly all ash regions when AOD 〉 0.2. However, the algorithm has higher uncertainties when AOD is 〈 0.1 over water and AOD 〈 0.2 over land. The ash spatial distributions provided by this algorithm can be used as a critical input and validation for atmospheric dispersion models simulated by Volcanic Ash Advisory Centers (VAACs). Identifying volcanic ash is an important first step before quantitative retrievals of ash concentration can be made.
Electronic ISSN:
1867-8610
Topics:
Geosciences
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