Model-Based Weather Radar Remote Sensing of Explosive Volcanic Ash Eruption

• Published in: IEEE transactions on geoscience and remote sensing Vol. 48; no. 10; pp. 3591 - 3607
• Main Authors: Marzano, Frank Silvio, Marchiotto, Sara, Textor, Christiane, Schneider, David J
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied geophysics; Ash particle aggregation; ash retrieval; Ashes; Atmospheric modeling; Climatology; Clouds; Earth sciences; Earth, ocean, space; Exact sciences and technology; Explosives; Internal geophysics; inversion methods; Mathematical models; Meteorological radar; Meteorology; microwave radars; Microwave theory and techniques; numerical simulation; Radar; Reflectivity; Remote monitoring; Remote sensing; Sensitivity analysis; Volcanic ash; volcanic eruption clouds; Volcanic eruptions; Volcanoes; Weather; Augustine; Alaska; Southwestern Alaska; United States; microwaves; algorithms; sensitivity analysis; plumes; simulation; aggregation; case studies; clouds; North America; aggregate; currents; particles; numerical simulation; high resolution; volcanic ash; models; inverse problem; eruptions; tracers; ash retrieval; remote sensing; microwave radars; concentration; Ash particle aggregation; classification; backscattering; inversion methods; regression; volcanic eruption clouds; radar methods; errors
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2010.2047862

Microphysical and dynamical features of volcanic ash clouds can be quantitatively monitored by using ground-based microwave weather radars. These systems can provide data for determining the ash volume, total mass, and height of eruption clouds. In order to demonstrate the unique potential of this microwave active remote-sensing technique, the case study of the eruption of Augustine Volcano in Alaska in January 2006 is described and analyzed. Volume scan data, acquired by a NEXRAD WSR-88D S-band ground-based weather radar, are processed to automatically classify and estimate eruptive cloud particle concentration. The numerical results of the coupled model Z-reflectivity from Active Tracer High resolution Atmospheric Model (ATHAM), including particle aggregation processes and simulation of radar reflectivity from the ATHAM microphysical model, are exploited to train the inversion algorithm. The volcanic ash radar retrieval based on the ATHAM algorithm is a physical-statistical approach based on the backscattering microphysical model of volcanic cloud particles (hydrometeors, ash, and aggregates), used within a Bayesian classification and optimal regression algorithm. A sensitivity analysis is carried out to evaluate the overall error budget. The evolution of the Augustine eruption is discussed in terms of radar measurements and products, pointing out the unique features, the current limitations, and future improvements of radar remote sensing of volcanic plumes.