3 research outputs found

    High-Resolution Grain-Size Distributions: Insight into Tephra Dispersal and Sedimentation during Plinian Eruptions

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    Detailed field studies of past eruptions contribute to constraining the input parameters used to forecast tephra dispersion and mitigate potentially fatal volcanic hazards. It is thus of the utmost importance to understand the relationships between the characteristics of tephra deposits and these input Eruption Source Parameters (ESPs). In this dissertation, I determine the ESPs for the ~7.7 ka Cleetwood eruption of Mount Mazama (Crater Lake/giiwas, Oregon, USA). This eruption is an important historic eruption because it immediately preceded the climactic caldera-forming eruption, at the same location, and is similar to the only observed silicic volcanic eruptions that have transitioned from explosive to effusive activity (2008 Chaitén and 2011-2012 Cordón Caulle, [Chile]). The Cleetwood eruptive sequence consisted of two consecutive VEI 4 eruptions: the main lower Cleetwood unit and smaller upper Cleetwood units, in order from oldest to youngest. The lower Cleetwood phase alone, produced a ~14.4 km plume and emplaced ~0.85 km3 of tephra. Altogether, the explosive phase of the Cleetwood eruption deposited ~1.1 km3 (non-DRE) of material and transitioned to an effusive stage that emplaced a ~0.6 km3 rhyodacitic lava flow. Furthermore, I develop a novel approach which combines laser diffraction and dynamic image analysis to produce a continuous set of high-resolution grain-size distributions (HR-GSDs) for samples spanning a range of sizes of ejected tephra from less than a micron to a few centimeters. Through this approach, I show the ability for these HR-GSDs to provide insights into magma fragmentation and tephra transport. Next, through detailed wind analysis and the use of these ESPs as the inputs for Tephra2, a volcanic ash transport and dispersal model, I estimate the geometry and dimensions of the volcanic plume that emplaced the lower Cleetwood unit. Here, I show the standard version of Tephra2, which uses a vertical line source, does well to reproduce mass loads and grain-size distributions separately but fails to fit both simultaneously with a single set of empirical inputs. To overcome this, I adapt Tephra2 outputs to simulate deposition via an umbrella cloud. Applying this adaptation and a grid search approach over reasonable plume heights and umbrella cloud geometries gives the best results for a plume with a 4x40 km2 elliptical geometry. This approach improves overall GSDs without degrading mass loads. Lastly, I combine detailed componentry and HR-GSDs on samples I collected from the products of hybrid phase of the 2011-2012 eruption at Cordón Caulle. This analysis suggests that ash sintering after fragmentation produced a dense plug that obstructed the shallow conduit. This caused the system to re-pressurize and subsequently shatter pieces of the plug during the next explosive event. This pattern continued until permeable outgassing dominated over re-pressurization, facilitating the transition to a solely effusive stage

    Using Eruption Source Parameters and High-Resolution Grain-Size Distributions of the 7.7 ka Cleetwood Eruption of Mount Mazama (Oregon, United States) to Reveal Primary and Secondary Eruptive Processes

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    Numerical simulations of real-time volcanic ash dispersal forecasts and ensuing tephra hazard assessments rely on field-derived Eruption Source Parameters (ESPs) such as plume height, erupted volume, mass eruption rate and the Total Grain-Size Distribution (TGSD) of particles ejected from a volcano into the atmosphere. Here we calculate ESPs for the ∼7.7 ka Cleetwood eruption of Mount Mazama (Crater Lake/giiwas, Oregon, United States) that immediately preceded the caldera-forming eruption. We also introduce a novel approach to produce high-resolution grain-size distributions (GSDs) of individual samples over a wide range of particle sizes (0.00035–35 mm) by combining laser diffraction with dynamic image analysis. Detailed field analysis allows us to divide the Cleetwood eruptive sequence into a series of two distinct and consecutive VEI 4 eruptions: the lower (~0.98 km3) and upper (∼0.20 km3) Cleetwood units. The lower Cleetwood was the most intense with a plume height of ∼19 km and an average mass discharge rate of ∼3.1 × 107 kg s−1. Its TGSD yields a fractal dimension D∼3.1, like other similar eruptions. All twelve high-resolution GSDs produced in this study exhibit two systematic breaks in slope from a power-law relationship at ∼0.125 and ∼0.510 mm. These breaks in slope create three segments: S1 (<0.125 mm), S2 (0.125–0.510 mm), and S3 (>0.510 mm) that can be fit by power-law relationships with fractal dimensions of D1 = 2.5 ± 0.2, D2 = 0.5 ± 0.1, and D3 = 3.6 ± 1.1, respectively. Together with ESPs and detailed componentry, D values at various locations give insight into magma fragmentation and tephra transport. We find that D1 values are positively correlated with the median grain-size and are similar to values found in rapid decompression magma fragmentation experiments. We infer that D1 values reflect the size distribution of the primary products of magma fragmentation and could thus be used to infer the potential energy at fragmentation. We interpret the relatively low values of D2 to an increase in dense components due to particle rafting. Our work shows that comparing high-resolution GSDs at several locations on the dispersal axis can further constrain primary and secondary eruptive processes, which prove crucial to improving tephra hazard assessments and dispersal forecasting

    DataSheet1_Using Eruption Source Parameters and High-Resolution Grain-Size Distributions of the 7.7 ka Cleetwood Eruption of Mount Mazama (Oregon, United States) to Reveal Primary and Secondary Eruptive Processes.pdf

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    Numerical simulations of real-time volcanic ash dispersal forecasts and ensuing tephra hazard assessments rely on field-derived Eruption Source Parameters (ESPs) such as plume height, erupted volume, mass eruption rate and the Total Grain-Size Distribution (TGSD) of particles ejected from a volcano into the atmosphere. Here we calculate ESPs for the ∼7.7 ka Cleetwood eruption of Mount Mazama (Crater Lake/giiwas, Oregon, United States) that immediately preceded the caldera-forming eruption. We also introduce a novel approach to produce high-resolution grain-size distributions (GSDs) of individual samples over a wide range of particle sizes (0.00035–35 mm) by combining laser diffraction with dynamic image analysis. Detailed field analysis allows us to divide the Cleetwood eruptive sequence into a series of two distinct and consecutive VEI four eruptions: the lower (∼0.98 km3) and upper (∼0.20 km3) Cleetwood units. The lower Cleetwood was the most intense with a plume height of ∼19 km and an average mass discharge rate of ∼3.1×107 kg s−1. Its Total Grain-Size Distribution yields a fractal dimension D∼3.1, like other similar eruptions. All twelve high-resolution GSDs produced in this study exhibit two systematic breaks in slope from a power-law relationship at ∼0.125 mm and ∼0.510 mm. These breaks in slope create three segments: S1 (0.510 mm) that can be fit by power-law relationships with fractal dimensions of D1=2.5 ± 0.2, D2=0.5 ± 0.1, and D3=3.6 ± 1.1, respectively. Together with ESPs and detailed componentry, D values at various locations give insight into magma fragmentation and tephra transport. We find that D1 values are positively correlated with the median grain-size and are similar to values found in rapid decompression magma fragmentation experiments. We infer that D1 values reflect the size distribution of the primary products of magma fragmentation and could thus be used to infer the potential energy at fragmentation. We interpret the relatively low values of D2 to an increase in dense components due to particle rafting. Our work shows that comparing high-resolution grain-size distributions at several locations on the dispersal axis can further constrain primary and secondary eruptive processes which prove crucial to improving tephra hazard assessments and dispersal forecasting.</p
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