Department of Geological and Mining Engineering and Sciences
Volcanic eruptions pose an ever-present threat to human populations around the globe, but many active volcanoes remain poorly monitored. In regions where ground-based monitoring is present the effects of volcanic eruptions can be moderated through observational alerts to both local populations and service providers, such as air traffic control. However, in regions where volcano monitoring is limited satellite-based remote sensing provides a global data source that can be utilised to provide near-real-time identification of volcanic activity. This paper details a volcanic plume detection method capable of identifying smaller eruptions than is currently feasible, which could potentially be incorporated into automated volcanic alert systems. This method utilises daily, global observations of sulfur dioxide (SO2) by the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. Following identification and classification of known volcanic eruptions in 2005-2009, the OMI SO2 data, analysed using a logistic regression analysis, permitted the correct classification of volcanic events with an overall accuracy of over 80 %. Accurate volcanic plume identification was possible when lower-tropospheric SO2 loading exceeded ∼400 t. The accuracy and minimal user input requirements of the developed procedure provide a basis for incorporation into automated SO2 alert systems.
Atmospheric Measurement Techniques
Improving global detection of volcanic eruptions using the Ozone Monitoring Instrument (OMI).
Atmospheric Measurement Techniques,
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Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License. Publisher’s version of record: https://doi.org/10.5194/amt-9-5487-2016