Next Article in Journal / Special Issue
Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types
Previous Article in Journal / Special Issue
Biomass Burning Aerosols Observed in Northern Finland during the 2010 Wildfires in Russia
Article Menu

Export Article

Open AccessArticle
Atmosphere 2013, 4(1), 35-47;

Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data

Institute of Methodologies for Environmental Analysis, C.da S. Loya, I-85050 Tito Scalo (PZ), Italy
Author to whom correspondence should be addressed.
Received: 2 November 2012 / Revised: 26 February 2013 / Accepted: 26 February 2013 / Published: 5 March 2013
Full-Text   |   PDF [408 KB, uploaded 5 March 2013]   |  


Thanks to its observational frequency of 15 min, the Meteosat Second Generation (MSG) geostationary satellite offers a great potential to monitor dust storms. To explore this potential, an algorithm for the detection and the retrieval of dust aerosol optical properties has been tested. This is a multispectral algorithm based on visible and infrared data which has been applied to 15 case studies selected between 2007 and 2011. The algorithm has been validated in the latitude–longitude box between 30 and 50 degrees north, and −10 and 20 degrees east, respectively. Hereafter we present the obtained results that have been validated against Aerosol Robotic Network (AERONET) ground-based measurements and compared with the retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites. The dust aerosol optical depth variations observed at the AERONET sites are well reproduced, showing good correlation of about 0.77, and a root mean square difference within 0.08, and the spatial patterns retrieved by using the algorithm developed are in agreement with those observed by MODIS. View Full-Text
Keywords: dust optical depth; dust detection; MSG; SEVIRI dust optical depth; dust detection; MSG; SEVIRI

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Romano, F.; Ricciardelli, E.; Cimini, D.; Di Paola, F.; Viggiano, M. Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data. Atmosphere 2013, 4, 35-47.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Atmosphere EISSN 2073-4433 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top