What is the threat? Sue Loughlin and Julia Crummy British Geological Survey. NERC All rights reserved NERC All rights reserved
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1 What is the threat? Sue Loughlin and Julia Crummy British Geological Survey BATA Conference, London 15 th October 2013
2 What is a volcano?
3 Where and how many? There are more than 1500 known potentially active volcanoes onshore (<10,000 years old) There are 82 volcanoes in Europe (including 32 in Iceland) Most are not well-monitored or are not monitored at all More than 80 volcano observatories worldwide Source: Thor Thordarson
4 When do they erupt? volcanoes erupt in one year Most eruptions are short-lived (hours to days) Some erupt almost continuously (eg Etna, Stromboli) Some have long repose intervals (hundreds to thousands of years) Freysteinn Sigmundsson
5 How do they erupt? Explosive Explosive : magmatic, phreatomagmatic (magma-water interaction), phreatic Effusive : lava domes, lava flows Effusive
6 Volcano Observatories
7 Monitoring Source: Icelandic Met Office
8 What actually causes eruptions? Magma mixing - Heat and volatile addition - Pressurisation Interaction of magma with groundwater Earthquakes Plate tectonics!
9 Frequency of explosive Icelandic eruptions since 850AD (per 20 years) An eruption every 2-5 years on average From Larsen & Eiriksson (2007)
10 Icelandic Met Office / ICAO 2014 : Interactive resource on Iceland s volcanoes Iceland Catalogue
11 Laki eruption Redrawn from Thordarson and Self (2003).
12 Fissure eruptions From From
13 Eruption early warning Only about 1-3 out of 10 episodes of unrest worldwide lead to an eruption (WOVOdat) Sometimes an acceleration hours before an eruption Multiparametric monitoring needed to issue a short-term forecast Some eruptions occur with no warning Source: IMO
14 Real-time information Icelandic Met Office (Iceland s volcano observatory) Aviation Colour codes
15 Basics for ash forecast modelling
16 Real-time data requirements Height (with time) Duration Grainsize distribution Vertical mass distribution Mass flux Gudmundsson et al Sci Rep. 2012;2:572. doi: /srep00572.
17 Plume processes Proximal to distal aggregation processes Large grains >30 microns Stevenson et al J. Geophysical Res. 117 Stevenson et al J. Applied Volc. 2:3
18 What is being done - VANAHEIM! Characterisation of the near-field Eyjafjallajokull plume and its longrange influence Woodhouse et al JGR, 118. Ash Relative vorticity Relative vorticity + ash
19 FUTUREVOLC 1. Know the volcanoes - Eruption catalogue, styles, volcano evolution 2. Better forecasting - Improved monitoring, timely recognition of precursors, early warning 3. The first model run - Source parameters from historical eruptions 4. The real-time source term - Observation, new techniques, understanding of processes 5. Effective data acquisition Measurements/sampling, remote sensing development, real-time 6. Risk assessment / management / communication
20 EVOSS : global near-real time monitoring
21 Coordination and collaboration WMO-IUGG workshops Ash dispersal forecast and civil aviation Bonadonna et al Volcano Observatory Best Practice (VOBP) workshops -Short term forecasting -Communication Global Volcano Model
22 Global Volcano Model A sustainable, accessible international platform for information on volcanic hazard and risk Initiated by BGS and Bristol University Coordination Systematic data, evidence, analysis Task forces Community-led, co-production www. globalvolcanomodel.org
23 Large magnitude eruptions Deligne, Coles and Sparks (JGR,115, 2010, doi: /2009jb006554)
24 Summary Improved data collection to enable statistical models for characterizing (Icelandic) eruptions in terms of recurrence intervals, 'sizes' (magnitude, intensity, VEI), durations and frequency. Probabilistic modelling is the next step. Need to formally take account of the many and varied uncertainties. Detailed forensic analysis of eruptions. Improved numerical models for some aspects of eruption dynamics. Enhanced real-time multi-parameter monitoring at more volcanoes, development of new techniques to assist with source parameters for dispersal models. Strong multi-disciplinary collaboration, coordination and coproduction.
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