A new algorithm to detect desert dust outbreaks using MSG-SEVIRI data

The strong impact of dust outbreaks on human activities has significantly increased the interest of scientific community in developing efficient monitoring systems capable of detecting them, supporting activities devoted to mitigate their effects. In this work, the performances of an innovative algorithm for dust detection, named RSTDUST, based on the successful Robust Satellite Techniques (RST) multitemporal approach, are further assessed, analyzing some intense Saharan dust outbreaks which affected Mediterranean region in May 2008. This algorithm is further experimented here analyzing data provided by SEVIRI (Spinning Enhanced Visible and Infrared Imager), which offers the opportunity of promptly detecting dust events (close to the source) and of monitoring their space-time evolution in real time, thanks to its temporal resolution of 15 minutes. Outcomes of this study, which are compared to some independent ground- and satellite-based aerosol products, confirm that RST DUST may represent an effective tool for automatically identifying Saharan dust from space both over land and sea areas. This work encourages further experimentations of such an algorithm in different geographic regions by using different satellite sensor data, to better assess its potential in monitoring dust events in operational contexts.