Description of work
Characterization of grain-size parameters, determination of mass eruption rate and assimilation of geophysical data to initialize Volcanic Ash Transport and Dispersal Models (VATDMs) {JR2.1}. A key factor in enabling prediction of ash plume dispersion and mitigating risk to air traffic is near real-time monitoring of volcanic eruption onset and the mass eruption rate (MER) over time. Both satellites and ground-based observations as well the real-time ASHER sampler, developed in the FUTUREVOLC project have potential for estimating in near -real time ash grain sizes and total fallout, leading to improved estimates of Total Grain -Size Distribution of an eruption in near real- time. The observations would be linked to measurements of physical parameters of the ash and laboratory experiments of particle aggregation and used as a multidisciplinary dataset. The assimilation of multiple data and improved physical understanding can provide the basis for improvements in modeling of volcanic plumes and their effects and help to obtain better quantification of the ash hazard, in the air (dispersal) and on the ground (fallout thickness).
Tools and techniques to rapidly combine and interpret meteorological measurements and ground-based remote sensing of volcanic ash. {JR2.2}. During volcanic eruptions an urgent priority is to characterise the proximal plume characteristics, such as mass flux, plume height, particle and gas characteristics. These data are for near real time interpretation of volcanic plume characteristics and are used to drive operational models such as those used by VAACs and agencies responsible for civil hazard warnings.
Volcano pre-eruptive detection schemes {JR2-3}. Early identification of signs that magma is moving towards the surface, timing of eruption onset, possible transitions in eruptive style, and eruption end are all very important for hazard monitoring and management, but for which automatic detection is generally not trivial. However, seismic tremor results from the FUTUREVOLC project suggest that certain characteristic changes are observed when magma moves near the surface. Furthermore infrasound arrays can detect when the eruptive vent opens to the atmosphere and magma arrives on the surface. Joint, real-time analysis and correlation of seismic and infrasound signals can provide a means for pre-eruptive early warning. Automatic algorithms for correlating such signals are to be generated and implemented.