Webley, P. W.

RED SEED stands for Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters, and combines stakeholders from the remote sensing, modelling and response communities with experience in tracking volcanic effusive events. The group first met during a three day-long workshop held in Clermont Ferrand (France) between 28 and 30 May 2013. During each day, presentations were given reviewing the state of the art in terms of (a) volcano hot spot detection and parameterization, (b) operational satellite-based hot spot detection systems, (c) lava flow modelling and (d) response protocols during effusive crises. At the end of each pre- sentation set, the four groups retreated to discuss and report on requirements for a truly integrated and operational response that satisfactorily combines remote sensors, modellers and responders during an effusive crisis. The results of collating the final reports, and follow-up discussions that have been on-going since the workshop, are given here. We can reduce our discussions to four main findings. (1) Hot spot detection tools are operational and capable of providing effusive erup- tion onset notice within 15 min. (2) Spectral radiance metrics can also be provided with high degrees of confidence. However, if we are to achieve a truly global system, more local receiving stations need to be installed with hot spot detection and data processing modules running on-site and in real time. (3) Models are operational, but need real-time input of reliable time-averaged discharge rate data and regular updates of digital elevation models if they are to be effective; the latter can be provided by the radar/photogrammetry community. (4) Information needs to be provided in an agreed and standard format following an ensemble approach and using models that have been validated and recognized as trustworthy by the responding authorities. All of this requires a sophisticated and centralized data collection, distribution and reporting hub that is based on a philosophy of joint ownership and mutual trust. While the next chapter carries out an exercise to explore the viability of the last point, the detailed recommendations behind these findings are detailed here.

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During volcanic eruptions, volcanic ash transport and dispersion models (VATDs) are used to forecast the location and movement of ash clouds over hours to days in order to define hazards to aircraft and to communities downwind. Those models use input parameters, called “eruption source parameters”, such as plume height H, mass eruption rate Ṁ, duration D, and the mass fraction m63 of erupted debris finer than about 4 or 63 μm, which can remain in the cloud for many hours or days. Observational constraints on the value of such parameters are frequently unavailable in the first minutes or hours after an eruption is detected. Moreover, observed plume height may change during an eruption, requiring rapid assignment of new parameters. This paper reports on a group effort to improve the accuracy of source parameters used by VATDs in the early hours of an eruption. We do so by first compiling a list of eruptions for which these parameters are well constrained, and then using these data to review and update previously studied parameter relationships. We find that the existing scatter in plots of H versus Ṁ yields an uncertainty within the 50% confidence interval of plus or minus a factor of four in eruption rate for a given plume height. This scatter is not clearly attributable to biases in measurement techniques or to well-recognized processes such as elutriation from pyroclastic flows. Sparse data on total grain-size distribution suggest that the mass fraction of fine debris m63 could vary by nearly two orders of magnitude between small basaltic eruptions ( 0.01) and large silicic ones (> 0.5). We classify eleven eruption types; four types each for different sizes of silicic and mafic eruptions; submarine eruptions; “brief” or Vulcanian eruptions; and eruptions that generate co-ignimbrite or co-pyroclastic flow plumes. For each eruption type we assign source parameters. We then assign a characteristic eruption type to each of the world's 1500 Holocene volcanoes. These eruption types and associated parameters can be used for ash-cloud modeling in the event of an eruption, when no observational constraints on these parameters are available.