The RSTASH algorithm is a specific configuration of the Robust Satellite Techniques (RST) multitemporal approach developed for detecting and tracking ash clouds from space. This algorithm was originally proposed and tested with success on AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data, and has been recently implemented on data provided by Japanese geostationary satellites (MTSAT). In this work, the preliminary results achieved exporting RSTASH on MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) data to study the Eyjafjallajökull eruptions of April- May 2010, which caused an unprecedented air traffic disruption in Northern and central Europe, are reported. This study was carried testing RSTASH in critical observational conditions (e.g. high view angles, cold background, frequent and diffuse cloud coverage), using for the first time an optimized configuration of this algorithm for daytime conditions, and assessing its potential in monitoring ash clouds in real time, exploiting the high temporal resolution of SEVIRI (15 minutes). Outcomes of this work show that RSTASH may be profitably used for an automated and accurate identification of ashaffected areas also at high latitude regions. Accurate detection, in fact, is a mandatory step before to characterize ash clouds from a quantitative point of view by means of retrieval analyses. These results encourage a full implementation of this algorithm on SEVIRI data, in view of a its possible usage in operational contexts.

Implementation of a Robust Satellite Technique (RST ASH) On Msg-Seviri Data for timely detection and near real- time monitoring of volcanic ash clouds from space

TRAMUTOLI, Valerio;FALCONIERI, ALFREDO
2013-01-01

Abstract

The RSTASH algorithm is a specific configuration of the Robust Satellite Techniques (RST) multitemporal approach developed for detecting and tracking ash clouds from space. This algorithm was originally proposed and tested with success on AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data, and has been recently implemented on data provided by Japanese geostationary satellites (MTSAT). In this work, the preliminary results achieved exporting RSTASH on MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) data to study the Eyjafjallajökull eruptions of April- May 2010, which caused an unprecedented air traffic disruption in Northern and central Europe, are reported. This study was carried testing RSTASH in critical observational conditions (e.g. high view angles, cold background, frequent and diffuse cloud coverage), using for the first time an optimized configuration of this algorithm for daytime conditions, and assessing its potential in monitoring ash clouds in real time, exploiting the high temporal resolution of SEVIRI (15 minutes). Outcomes of this work show that RSTASH may be profitably used for an automated and accurate identification of ashaffected areas also at high latitude regions. Accurate detection, in fact, is a mandatory step before to characterize ash clouds from a quantitative point of view by means of retrieval analyses. These results encourage a full implementation of this algorithm on SEVIRI data, in view of a its possible usage in operational contexts.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/104099
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