Volcanology - Multidisciplinary science for a versatile campus

Dr. Simon Carn was nominated by Dr. John Gierke and selected from a highly competitive pool of candidates as the Spring 2017 Distinguished Lecturer. His lecture, Volcanology — Multidisciplinary Science for a Versatile Campus, was presented in April 2017. Volcanology – the study of volcanoes – is a truly multidisciplinary endeavor that encompasses numerous fields including geology, physics, chemistry, material science and social science. Arguably, Michigan Tech owes its very existence to volcanic activity, which is ultimately responsible for the area’s rich copper deposits and the development of mining in the Keweenaw.https://digitalcommons.mtu.edu/lecture-series/1001/thumbnail.jp

Improving automated global detection of volcanic SO2 plumes using the Ozone Monitoring Instrument (OMI)

Volcanic eruptions pose an ever-present threat to human populations around the globe, but many active volcanoes remain poorly monitored. In regions where ground-based monitoring is present the effects of volcanic eruptions can be moderated through observational alerts to both local populations and service providers such as air traffic control. However, in regions where volcano monitoring is limited satellite-based remote sensing provides a global data source that can be utilized to provide near real time identification of volcanic activity. This paper details the development of an automated volcanic plume detection method utilizing daily, global observations of sulphur dioxide (SO2) by the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite. Following identification and classification of known volcanic eruptions in 2005-2009, the OMI SO2 data are analysed using a logistic regression analysis which permits the identification of volcanic events with an overall accuracy of over 80%, and consistent plume identification when the volcanic plume SO2 loading exceeds ~400 tons. The accuracy and minimal user input requirements of the developed procedure provide a basis for the creation of an automated SO2 alert system providing volcanic alerts in regions where ground based volcano monitoring capabilities are limited. The technique could easily be adapted for use with satellite measurements of volcanic SO2 emissions from other platforms

Mapping lava flows from Nyamuragira volcano (1967-2011) with satellite data and automated classification methods

The volume, location and extent of historical lava flows are important when assessing volcanic hazards, as well as the productivity or longevity of a volcanic system. We use a Landsat/Hyperion/ALI dataset and automated classification methods to map lava flows at Nyamuragira volcano (1967-2011) in the Democratic Republic of the Congo. The humid tropical climate ofNyamuragira is advantageous because its lava flows are emplaced onto heavily forested flanks, resulting in strong contrast between lava and vegetation, which contributes to efficient flow mapping. With increasing age, there is an increase in Landsat band-4 reflectance, suggesting lava flow revegetation with time. This results in a distinct spectral contrast to delineate overlapping flows emplaced ~ 5 years apart. Areal extents of the flows are combined with published lava flow thicknesses to derive volumes. The Landsat/Hyperion/ALI dataset is advantageous for mapping future flows quickly and inexpensively, particularly for volcano observatories where resources are limited

Volcano monitoring from space using high-cadence planet CubeSat images applied to Fuego Volcano, Guatemala

Fuego volcano (Guatemala) is one of the most active and hazardous volcanoes in the world. Its persistent activity generates lava flows, pyroclastic density currents (PDCs), and lahars that threaten the surrounding areas and produce frequent morphological change. Fuego’s eruption deposits are often rapidly eroded or remobilized by heavy rains and its constant activity and inaccessible terrain makes ground-based assessment of recent eruptive deposits very challenging. Earth-orbiting satellites can provide unique observations of volcanoes during eruptive activity, when ground-based techniques may be too hazardous, and also during inter-eruptive phases, but have typically been hindered by relatively low spatial and temporal resolution. Here, we use a new source of Earth observation data for volcano monitoring: high resolution (~3 m pixel size) images acquired from a constellation of over 150 CubeSats (‘Doves’) operated by Planet Labs Inc. The Planet Labs constellation provides high spatial resolution at high cadence (\u3c1–72 h), permitting space-based tracking of volcanic activity with unprecedented detail. We show how PlanetScope images collected before, during, and after an eruption can be applied for mapping ash clouds, PDCs, lava flows, or the analysis of morphological change. We assess the utility of the PlanetScope data as a tool for volcano monitoring and rapid deposit mapping that could assist volcanic hazard mitigation efforts in Guatemala and other active volcanic regions

First synoptic analysis of volcanic degassing in Papua New Guinea

We report the first satellite-based survey of volcanic sulphur dioxide (SO2) degassing in Papua New Guinea, using Ozone Monitoring Instrument (OMI) data. OMI is sensitive to low-level passive degassing. These observations are useful for volcano monitoring, hazard assessment (particularly aviation hazard) and assessment of arc geochemical budgets and are of immense value in remote regions with little ground-based instrumentation, such as Papua New Guinea. We identify Bagana, Manam, Rabaul, Ulawun and Langila as the active sources of volcanic SO2 in Papua New Guinea, with Bagana being the largest source. We present an OMI SO2 time series for 2005–2008 and a total detected regional output of ∼1.8 × 109 kg SO2. About 40% of emissions were released by major eruption events at Manam (January 2005), Bagana (June 2006) and Rabaul (October 2006). Over the past century however, we estimate that major explosive eruptions contribute <5% of the arc-scale SO2 emission budget. Ground-based DOAS measurements of SO2 degassing at five of Papua New Guinea's volcanoes are compared with our OMI observations. The total OMI SO2 output is only ∼20% of the total extrapolated from DOAS, a discrepancy which we demonstrate is consistent with other volcanic arcs. Therefore, the true total regional SO2 output may be considerably higher than that detected by OMI. Uncertainties in the OMI SO2 data include the effects of in-plume chemical processing and dilution of SO2 prior to the satellite overpass, OMI's reduced sensitivity to low levels of SO2 in the planetary boundary layer and interference by meteorological clouds

Atmospheric processes affecting the separation of volcanic ash and SO2 in volcanic eruptions: inferences from the May 2011 Grímsvötn eruption

The separation of volcanic ash and sulfur dioxide (SO2) gas is sometimes observed during volcanic eruptions. The exact conditions under which separation occurs are not fully understood but the phenomenon is of importance because of the effects volcanic emissions have on aviation, on the environment, and on the earth’s radiation balance. The eruption of Grímsvötn, a subglacial volcano under the Vatnajökull glacier in Iceland during 21–28 May 2011 produced one of the most spectacular examples of ash and SO2 separation, which led to errors in the forecasting of ash in the atmosphere over northern Europe. Satellite data from several sources coupled with meteorological wind data and photographic evidence suggest that the eruption column was unable to sustain itself, resulting in a large deposition of ash, which left a low-level ash-rich atmospheric plume moving southwards and then eastwards towards the southern Scandinavian coast and a high-level predominantly SO2 plume travelling northwards and then spreading eastwards and westwards. Here we provide observational and modelling perspectives on the separation of ash and SO2 and present quantitative estimates of the masses of ash and SO2 that erupted, the directions of transport, and the likely impacts. We hypothesise that a partial column collapse or “sloughing” fed with ash from pyroclastic density currents (PDCs) occurred during the early stage of the eruption, leading to an ash-laden gravity intrusion that was swept southwards, separated from the main column. Our model suggests that water-mediated aggregation caused enhanced ash removal because of the plentiful supply of source water from melted glacial ice and from entrained atmospheric water. The analysis also suggests that ash and SO2 should be treated with separate source terms, leading to improvements in forecasting the movement of both types of emissions

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54–58 days), with this multi-week feature attributable to episodes of dome growth. The ~ 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7–8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems

First observations of volcanic eruption clouds from the L1 Earth-Sun Lagrange point by DSCOVR/EPIC

Volcanic sulfur dioxide (SO2) emissions have been measured by ultraviolet sensors on polar‐orbiting satellites for several decades but with limited temporal resolution. This precludes studies of key processes believed to occur in young (~1–3 hr old) volcanic clouds. In 2015, the launch of the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) provided an opportunity for novel observations of volcanic eruption clouds from the first Earth‐Sun Lagrange point (L1). The L1 vantage point provides continuous observations of the sunlit Earth, offering up to eight or nine observations of volcanic SO2 clouds in the DSCOVR/EPIC field of view at ~1‐hr intervals. Here we demonstrate DSCOVR/EPIC\u27s sensitivity to volcanic SO2 using several volcanic eruptions from the tropics to midlatitudes. The hourly cadence of DSCOVR/EPIC observations permits more timely measurements of volcanic SO2 emissions, improved trajectory modeling, and novel analyses of the temporal evolution of volcanic clouds

New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: Algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (∼1700 kt total SO2/ and Sierra Negra in 2005 (\u3e 1100DU maximum SO2/, OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments

The Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP): motivation and experimental design

The Stratospheric Sulfur and its Role in Climate (SSiRC) Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulfur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present four co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The Background (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The Transient Aerosol Record (TAR) experiment will explore the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulfur emissions, and transport processes over the period 1998–2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulfate aerosol evolution after major volcanic eruptions. The Historical Eruptions SO2 Emission Assessment (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the Pinatubo Emulation in Multiple models (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt Pinatubo eruption