Global radiant flux from active volcanoes: the 2000–2019 MIROVA database

Abstract

Since 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS) has acquired infrared images of the Earth’s surface daily. These data have made it possible to measure the thermal energy radiated by the world’s most famous volcanoes and also to discover and track eruptions in remote and poorly monitored regions. In this work, we present the database of Volcanic Radiative Power (VRP, in W) time series, recorded by the MIROVA (Middle Infrared Observation of Volcanic Activity) system over 2 decades of MODIS observations (2000–2019) at 111 active volcanoes. The database reveals that globally, the number of thermally active volcanoes each year varies between 60 and 80, almost equally partitioned between volcanoes with a basic (50%) and intermediate (45%) composition, while only 5% is represented by volcanoes erupting acidic lavas. Within the investigated period, the global-scale heat flux was almost stationary, and occasionally punctuated by peaks associated with the largest effusive eruptions (e.g., Bardarbunga and Kilauea). The Volcanic Radiative Energy (VRE, in J) emitted by basic volcanoes (∼1.8 × 1018 J) in 20 years constitutes 91% of the total, while intermediates and acids contribute only 8% (∼1.8 × 1017 J) and 1% (∼1.7 × 1016 J), respectively. A comparison with the volume of lava erupted effusively by the same volcanoes reveals that this difference is attributed to the lower efficiency in radiating thermal energy of increasingly acidic (viscous) lava bodies. Each compositional group is associated with a specific relationship between VRE and erupted volume which characterises most of the effusive volcanoes. On the other hand, some open-vent volcanoes reveal that much more heat is released than that theoretically radiated by the erupted lava. This imbalance (hereby called excess radiation) is attributed to an additional heat source, likely associated with an underlying convective magma column and/or to outgassing through a permeable conduit. We are convinced that the database presented in this work will be useful to support new emerging studies on global-scale volcanism and will contribute to a better understanding of each volcanic system.

The use of high-resolution satellite topographic data to quantify volcanic activity at Raung volcano (Indonesia) from 2011 to 2021

“…2) characterized by mild explosive volcanic activity, with only tephra emission, Raung experienced a Magnitude ≥ 4 and a Magnitude > 3.0 eruption in seven years, with the production of lavas. Time series of high resolution DEMs derived from satellite data provide therefore a powerful tool to quantify masses erupted by Magnitude ≥ 3 eruptions, which can be used in future studies to develop physics-based models coupling extrusion rates with other monitoring parameters, like deformation and thermal data, to further improve the knowledge of the magmatic systems and the volcanic activity at Raung and to try forecasting its future eruptive rates (Anderson and Segall 2011;Coppola et al 2023).…”

“…Constraining recent erupted masses at Raung would provide, at a local scale, information about the frequency and size distribution of the recent eruptions, while at a regional scale would allow to better constrain the recent regional eruptive rates of Java volcanic arc. In addition, erupted masses of Raung could be used in future studies to develop physics-based models coupling extrusion rates at effusive erupting volcanoes with other monitoring parameters, like deformation and thermal data, to further improve the knowledge of the magmatic system and activity at Raung and to try forecasting its future eruptive rates (Anderson and Segall 2011;Coppola et al 2023). Thus, here we use DEMs derived from optical and SAR data, acquired from 2011 to 2021, to quantify the erupted masses at Raung volcano, especially during the two effusive eruptions that occurred in November 2014 -August 2015 and January-April 2021.…”

Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: the hotspot learning and identification network

“…Automating the detection and quantification of volcanic hotspots can provide near-real time information to volcano observatory scientists to inform decision-making and provide a mechanism to generate long time series of thermal activity for volcanoes around the world. Time series observations are useful for determining baseline activity, identifying periods of volcanic unrest, characterizing the thermal evolution of ongoing eruptions, and retrospectively studying eruptive histories and processes (Dehn et al, 2002;Wright, 2016;Girona et al, 2021;Chevrel et al, 2023;Coppola et al, 2023).…”

“…The ability of each algorithm to distinguish hotspots from background pixels depends on how successful their index is in separating the two classes and the accuracy and precision of the threshold set for that index. MODVOLC and MIROVA have successfully generated decades long time series of hotspots at volcanoes across the globe, which has allowed for detection and monitoring of eruptions in near-real time and the study of thermal output from different eruptions and volcanic systems (Wright, 2016;Coppola et al, 2023). Still, both datasets contain false detections and missed hotspots, due to the fact that there will inevitably be non-volcanic thermal signals exceeding the set thresholds, and real volcanic signals lower than the detection thresholds.…”