Meaningful forecasting of the atmospheric concentration and ground accumulation of volcanic ash during explosive eruptions requires detailed knowledge of the eruption source parameters. However, due to the large uncertainties in observations and limitations of current models used to make inferences from these, monitoring an ongoing eruption and quantifying the mass eruption rate in real-time is a considerable challenge. Within the EU supersite project "FutureVolc", an integrated approach has been applied to develop a quasi-autonomous multi-parameter system, denoted "REFIR", for monitoring volcanic eruptions in Iceland and assessing the eruption mass flow rate by inverting the plume height information and taking account of these uncertainties. REFIR has the capability to ingest and process streaming plume-height data provided by a multitude of ground based sensors, including C- and X-band radars and web-cam based plume height tracking systems. These observational data are used with a suite of plume models that also consider the current wind and other atmospheric conditions, providing statistically assessed best estimates of plume height and mass eruption rate. Provided instrumental data is available, near real-time estimates are obtained (the delay corresponding to the scan rate of data providing instruments, presently of the order of minutes). Using the Hekla 2000, and Eyjafjallajokull 2010 eruptions in Iceland, the potential of REFIR is demonstrated and discussed through application to three scenarios. The system has been developed to provide maximum flexibility. A setup script assists the user in adapting to local conditions, allowing implementation of REFIR for any volcanic eruption site worldwide. REFIR is designed to be easily upgradable, allowing future extension of monitoring networks, learning from new events, and incorporation of new technologies and model improvements. This article gives an overview of the basic structure, models implemented, functionalities and the computational techniques of REFIR. (C) 2018 The Authors. Published by Elsevier B.V.
REFIR- A multi-parameter system for near real-time estimates of plume-height and mass eruption rate during explosive eruptions
Dioguardi, Fabio;
2018-01-01
Abstract
Meaningful forecasting of the atmospheric concentration and ground accumulation of volcanic ash during explosive eruptions requires detailed knowledge of the eruption source parameters. However, due to the large uncertainties in observations and limitations of current models used to make inferences from these, monitoring an ongoing eruption and quantifying the mass eruption rate in real-time is a considerable challenge. Within the EU supersite project "FutureVolc", an integrated approach has been applied to develop a quasi-autonomous multi-parameter system, denoted "REFIR", for monitoring volcanic eruptions in Iceland and assessing the eruption mass flow rate by inverting the plume height information and taking account of these uncertainties. REFIR has the capability to ingest and process streaming plume-height data provided by a multitude of ground based sensors, including C- and X-band radars and web-cam based plume height tracking systems. These observational data are used with a suite of plume models that also consider the current wind and other atmospheric conditions, providing statistically assessed best estimates of plume height and mass eruption rate. Provided instrumental data is available, near real-time estimates are obtained (the delay corresponding to the scan rate of data providing instruments, presently of the order of minutes). Using the Hekla 2000, and Eyjafjallajokull 2010 eruptions in Iceland, the potential of REFIR is demonstrated and discussed through application to three scenarios. The system has been developed to provide maximum flexibility. A setup script assists the user in adapting to local conditions, allowing implementation of REFIR for any volcanic eruption site worldwide. REFIR is designed to be easily upgradable, allowing future extension of monitoring networks, learning from new events, and incorporation of new technologies and model improvements. This article gives an overview of the basic structure, models implemented, functionalities and the computational techniques of REFIR. (C) 2018 The Authors. Published by Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
