Dome Collapse Interaction With the Atmosphere

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Modeling Volcanic Eruption Parameters by Near-Source Internal Gravity Waves

Volcanic explosions release large amounts of hot gas and ash into the atmosphere to form plumes rising several kilometers above eruptive vents, which can pose serious risk on human health and aviation also at several thousands of kilometers from the volcanic source. However the most sophisticate atmospheric models and eruptive plume dynamics require input parameters such as duration of the ejection phase and total mass erupted to constrain the quantity of ash dispersed in the atmosphere and to efficiently evaluate the related hazard. The sudden ejection of this large quantity of ash can perturb the equilibrium of the whole atmosphere triggering oscillations well below the frequencies of acoustic waves, down to much longer periods typical of gravity waves. We show that atmospheric gravity oscillations induced by volcanic eruptions and recorded by pressure sensors can be modeled as a compact source representing the rate of erupted volcanic mass. We demonstrate the feasibility of using gravity waves to derive eruption source parameters such as duration of the injection and total erupted mass with direct application in constraining plume and ash dispersal models

Influence of chronotype and habitual training time-of-day on rating of perceived exertion in young adults

INTRODUCTION: To date, there has been little agreement on circadian variation in sports performance. It seems that both chronotype and habitual training time-of-day (HTT) need to be considered when assessing diurnal variation in performance [1]. Therefore, the aim of this study was to evaluate if chronotype and HTT may influence the rating of perceived exertion (RPE) after two different intensity trials performed in three times of day. METHODS: The chronotype of participants (N56: age 23.8±2.1 yrs, BMI 22.1±2.0 kg/m2, V’O2max 40.1±9.1 ml/kg/min) was assessed using the Morningness Eveningness Questionnaire (MEQ) [2] and their maximal oxygen uptake (V’O2max) was determined via direct gas analysis (Fitmate-Pro, Cosmed, Italy) on a cycle ergometer (LC6, Monark, Sweden) using a submaximal exercise-based protocol. Subjects’ HTT was objectively evaluated using an activity monitor (Lifecorder Plus, Kenz, Japan) worn for one week. Participants performed two 6-minute bouts of exercise on cycle ergometer at 60% and 90% of V’O2max at 8.30am (morning trial, MT), at 1.00pm (afternoon trial, AT) and at 5.30pm (evening trial, ET) in a randomised order. Training sessions were interspersed by 48 hours. After each session, participants reported their RPE (CR10) [3]. RESULTS: Distributions of chronotype and HTT were 27% of Morning-types (M-type), 59% of Neither-types (N-type) and 14% of Eveningtypes (E-type) and 21% of subjects trained in the morning, 55% in the afternoon and 23% in the evening, respectively. When the RPE of all the subjects were examined as a whole, there was no difference between the MT, the AT and the ET (60% V’O2max MT: 3.0±1.5, AT: 2.9±1.4, ET: 2.8±1.5; 90% V’O2max MT: 7.3±2.4, AT: 7.1±2.4, ET: 7.0±2.3). No time-by-group interaction effect on RPE was observed when participants were grouped by chronotype (60% V’O2max p=0.2931; 90% V’O2max p=0.7653) or HTT (60% V’O2max p=0.9370; 90% V’O2max p=0.9862). However, M-type reported lower RPE scores post MT and E-type post ET both at moderate (60% V’O2max Mtype_MT: 2.6±1.1, AT: 3.3±1.7, ET: 3.1±1.5; E-type_ MT: 3.3±2.0, AT: 2.7±0.9, ET: 2.6±1.8) and vigorous (90% V’O2max M-type_MT: 6.8±2.7, AT: 7.3±2.8, ET: 7.4±2.1; E-type_ MT: 7.4±2.2, AT: 7.0±1.9, ET: 6.4±2.5) exercise intensity. Interestingly, the same trend was not observed for RPE and HTT. CONCLUSION: In contrast to previous study findings [1], neither chronotype nor HTT have significantly influenced diurnal variation in RPE. Nevertheless, the lowest RPE scores found post MT for M-type and post ET for E-type, regardless of their HTT, seem to suggest that only chronotype might influence RPE. Future research needs to confirm this hypothesi

Monitoring unstable parts in the ice-covered Weissmies northwest face

The glacierized northwest face of Weissmies in the Saas valley (Switzerland) recently became unstable due to climate-induced glacier thinning of the supporting Triftgletscher below. In the case of a large break-off of ice, human infrastructure in the Saas valley is exposed to the danger of an ice/snow avalanche. A monitoring campaign was initiated with the goal of detecting precursory signals to the break-off. Interferometric and Doppler radar, optical imaging as well as GPS sensors provide measurements of surface displacements. Infrasound and seismometer arrays monitor acoustic and seismic emissions of ice avalanches and englacial fracture development. Here we discuss the monitoring methods and the results obtained so far. The unstable glacier mass did not undergo a large-scale break-off event, in fact it decelerated during the unusually warm summer months. An explanation remains elusive but likely involves subglacial processes and bedrock topography. Nevertheless, our results allow us to draw important conclusions regarding the suitability of different approaches to monitoring unstable glaciers