An Overview of RSTASH Performance in Detecting and Tracking Ash Clouds Using Polar and Geostationary Satellite Data

RST_ASH is an ash detection method based on the Robust Satellite Techniques (RST) multi-temporal approach. This algorithm, which was originally developed using AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data, uses two local variation indices in combination to identify ash clouds. The first one analyses the signal measured in the TIR region (Thermal Infrared) at around 11 µm and 12 µm wavelengths. The second one analyses the brightness temperature difference of the signal measured in the MIR (Medium Infrared) and TIR bands. Several studies showed that RST_ASH is capable of performing better than traditional BTD techniques. In particular, they showed that RST_ASH is capable of guaranteeing a performance comparable to other established ash detection techniques (e.g. water vapour corrected BTD procedure) without requiring ancillary data. Recently, RST_ASH has been implemented on MTSAT-2 (Multi-Functional Transport Satellite-2) and MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) geostationary satellites. Moreover, an optimized configuration of this algorithm has been developed and tested, showing further improvements in the discrimination capabilities of ash from meteorological clouds in daylight conditions. In this study, we present some recent RST_ASH results achieved studying some important volcanic eruptions like that of Eyjafjallajökull (Iceland) volcano of April-May 2010 and of Mt. Shinmoedake (Japan) of 26-27 January 2011. The work shows that RST_ASH, whose products may be integrated with those provided by operational ash detection techniques for better mapping areas affected by ash, may give an important contribution for supporting activities aiming at mitigating impact of ash clouds on air traffic.