scholarly journals Processes culminating in the 2015 phreatic explosion at Lascar volcano, Chile, monitored by multiparametric data

2019 ◽  
Author(s):  
Ayleen Gaete ◽  
Thomas R. Walter ◽  
Stefan Bredemeyer ◽  
Martin Zimmer ◽  
Christian Kujawa ◽  
...  

Abstract. Small steam-driven volcanic explosions are common at volcanoes worldwide but are rarely documented or monitored; therefore, these events still put residents and tourists at risk every year. Steam-driven explosions also occur frequently (once every 2–5 years on average) at Lascar volcano, Chile, where they are often spontaneous and lack any identifiable precursor activity. Here, for the first time at Lascar, we describe the processes culminating in such a sudden volcanic explosion that occurred on October 30, 2015, which was thoroughly monitored by cameras, a seismic network, and gas (SO2 and CO2) and temperature sensors. Prior to the eruption, we retrospectively identified unrest manifesting as a gradual increase in the number of long-period (LP) seismic events in 2014, indicating an augmented level of activity at the volcano. Additionally, SO2 flux and thermal anomalies were detected before the eruption. Then, our weather station reported a precipitation event, followed by changes in the brightness of the permanent volcanic plume and (10 days later) by the sudden volcanic explosion. The multidisciplinary data exhibited short-term variations associated with the explosion, including (1) an abrupt eruption onset that was seismically identified in the 1–10 Hz frequency band, (2) the detection of a 1.7 km high white-grey eruption column in camera images, and (3) a pronounced spike in sulfur dioxide (SO2) emission rates reaching 55 kg sec−1 during the main pulse of the eruption as measured by a mini-DOAS scanner. Continuous CO2 gas and temperature measurements conducted at a fumarole on the southern rim of the Lascar crater revealed a pronounced change in the trend of the relationship between the carbon dioxide (CO2) mixing ratio and the gas outlet temperature; we believe that this change was associated with the prior precipitation event. An increased thermal anomaly inside the active crater observed through Sentinel-2 images and drone overflights performed after the steam-driven explosion revealed the presence of a fracture ~ 50 metres in diameter truncating the dome and located deep inside the active crater, which coincides well with the location of the thermal anomaly. Altogether, these observations lead us to infer that a lava dome was present and subjected to cooling and inhibited degassing. We conjecture that a precipitation event led to the short-term build-up of pressure inside the shallow dome that eventually triggered a vent-clearing phreatic explosion. This study shows the chronology of events culminating in a steam-driven explosion but also demonstrates that phreatic explosions are difficult to forecast, even if the volcano is thoroughly monitored; these findings also emphasize why ascending to the summits of Lascar and similar volcanoes is hazardous, particularly after considerable rainfall.

2020 ◽  
Vol 20 (2) ◽  
pp. 377-397 ◽  
Author(s):  
Ayleen Gaete ◽  
Thomas R. Walter ◽  
Stefan Bredemeyer ◽  
Martin Zimmer ◽  
Christian Kujawa ◽  
...  

Abstract. Small steam-driven volcanic explosions are common at volcanoes worldwide but are rarely documented or monitored; therefore, these events still put residents and tourists at risk every year. Steam-driven explosions also occur frequently (once every 2–5 years on average) at Lascar volcano, Chile, where they are often spontaneous and lack any identifiable precursor activity. Here, for the first time at Lascar, we describe the processes culminating in such a sudden volcanic explosion that occurred on 30 October 2015, which was thoroughly monitored by cameras, a seismic network, and gas and temperature sensors. Prior to the eruption, we retrospectively identified unrest manifesting as a gradual increase in the number of long-period (LP) seismic events in 2014, indicating an enhanced level of activity at the volcano. Additionally, sulfur dioxide (SO2) flux and thermal anomalies were detected before the eruption. Then, our weather station reported a precipitation event, followed by an increase in steaming and a sudden volcanic explosion at Lascar. The multidisciplinary data exhibited short-term variations associated with the explosion, including (1) an abrupt eruption onset that was seismically identified in the 1–10 Hz frequency band, (2) the detection of a 1.7 km high white-gray eruption column in camera images, and (3) a pronounced spike in SO2 emission rates reaching 55 kg s−1 during the main pulse of the eruption as measured by a mini-differential optical absorption spectroscopy (DOAS) scanner. Continuous carbon dioxide (CO2) and temperature measurements conducted at a fumarole on the southern rim of the Lascar crater revealed a pronounced change in the trend of the relationship between the CO2 mixing ratio and the gas outlet temperature; we speculate that this change was associated with the prior precipitation event. An increased thermal anomaly inside the active crater as observed in Sentinel-2 images and drone overflights performed after the steam-driven explosion revealed the presence of a ∼50 m long fracture truncating the floor of the active crater, which coincides well with the location of the thermal anomaly. This study presents the chronology of events culminating in a steam-driven explosion but also demonstrates that phreatic explosions are difficult to predict, even if the volcano is thoroughly monitored; these findings emphasize why ascending to the summits of Lascar and similar volcanoes is hazardous, particularly after considerable precipitation.


1996 ◽  
Vol 39 (2) ◽  
Author(s):  
G. Asch ◽  
K. Wylegalla ◽  
M. Hellweg ◽  
D. Seidl ◽  
H. Rademacher

During the Proyecto de Investigaciòn Sismològica de la Cordillera Occidental (PISCO '94) in the Atacama desert of Northern Chile, a continuously recording broadband seismic station was installed to the NW of the currently active volcano, Lascar. For the month of April, 1994, an additional network of three, short period, three-component stations was deployed around the volcano to help discriminate its seismic signals from other local seismicity. During the deployment, the volcanic activity at Lascar appeared to be limited mainly to the emission of steam and SO2. Tremor from Lascar is a random, «rapid-fire» series of events with a wide range of amplitudes and a quasi-fractal structure. The tremor is generated by an ensemble of independent elementary sources clustered in the volcanic edifice. In the short-term, the excitation of the sources fluctuates strongly, while the long-term power spectrum is very stationary.


2021 ◽  
Vol 13 (18) ◽  
pp. 3584
Author(s):  
Peng Liu ◽  
Yi Yang ◽  
Yu Xin ◽  
Chenghai Wang

A moderate precipitation event occurring in northern Xinjiang, a region with a continental climate with little rainfall, and in leeward slope areas influenced by topography is important but rarely studied. In this study, the performance of lightning data assimilation is evaluated in the short-term forecasting of a moderate precipitation event along the western margin of the Junggar Basin and eastern Jayer Mountain. Pseudo-water vapor observations driven by lightning data are assimilated in both single and cycling analysis experiments of the Weather Research and Forecast (WRF) three-dimensional variational (3DVAR) system. Lightning data assimilation yields a larger increment in the relative humidity in the analysis field at the observed lightning locations, and the largest increment is obtained in the cycling analysis experiment. Due to the increase in water vapor content in the analysis field, more suitable thermal and dynamic conditions for moderate precipitation are obtained on the leeward slope, and the ice-phase and raindrop particle contents increase in the forecast field. Lightning data assimilation significantly improves the short-term leeward slope moderate precipitation prediction along the western margin of the Junggar Basin and provides the best forecast skill in cycling analysis experiments.


2016 ◽  
Vol 9 (1) ◽  
pp. 431-450 ◽  
Author(s):  
A. Folch ◽  
A. Costa ◽  
G. Macedonio

Abstract. Eruption source parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D (one-dimensional) cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in the presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an effective grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the effective particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland). The modular structure of the code facilitates the implementation in the future code versions of more quantitative ash aggregation parameterization as further observations and experiment data will be available for better constraining ash aggregation processes.


Author(s):  
Ayleen Gaete ◽  
Thomas R. Walter ◽  
Stefan Bredemeyer ◽  
Martin Zimmer ◽  
Christian Kujawa ◽  
...  

2015 ◽  
Vol 8 (9) ◽  
pp. 8009-8062 ◽  
Author(s):  
A. Folch ◽  
A. Costa ◽  
G. Macedonio

Abstract. Eruption Source Parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D cross-section averaged eruption column model based on the Buoyant Plume Theory (BPT). The model accounts for plume bent over by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an "effective" grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice-versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the "effective" particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland).


2020 ◽  
Author(s):  
Yue Zheng ◽  
Ziye Zhou ◽  
Cong Fang ◽  
Jiaxi Liang ◽  
Boyang Ren ◽  
...  

<p>        Heavy rainfall is one of the most frequent and severe weather hazards in the world which becomeone of the hugest natural risks.  It has been found that during the flood season in South China, high intensive precipitation occurs very frequently due to the impact of east Asian monsoon.  An unexpected and unusual extreme precipitation event could lead to millions or billions worth of damage, wash out vehicles and houses, destroy agricultural fields, and threat people’s lives.  Determining the linkage between heavy rainfall causes, critical meteorological condition, and impacts can make it easier to classify risk level.  However, due to the insufficiencies of quantitative heavy rainfall related property damages, and low efficient precipitation forecast, the risk evaluation could not be well determined.  Therefore, we employed an improved short-term precipitation forecast based on ensemble deep learning algorithms that can provide more accurate prediction, and apply  25 years of insurance data to aid as proxy for the evaluation of short-term heavy rainfall risks, aiming to trigger in-time precautions and reduce losses. </p><p>       The improved short-term precipitation forecast is built based on combination of scale-invariant feature transform (SIFT) algorithm and ensemble model including convolutional neural network (CNN), gradient boosting decision tree (GBDT), and neural network.  The main dataset used includes radar images and station observed precipitation.  The past 1.5 hour radar reflectivity images are measured at 15 times with an interval of 6 minutes, and in 4 different heights from 0.5 km to 3.5 km with an interval of 1 km.  The hourly site precipitation is obtained from ground meteorology stations.  The SIFT is used to calculate cloud trajectory velocity, and the CNN is implemented with features including pinpoint local radar images, spatial-temporal descriptions of the cloud movement and the global description of the cloud pattern.  Weights are assigned to the ensemble model to compute the following 2-3 hours forecasting results.  Additionally, the insurance data include more than 50 thousand records provided on a geography coordinate level for the last 25 years. </p><p>       Result shows that the insurance data have a strong correlation with short-term precipitation.  It also indicates that our proposed model of short-term precipitation forecast outperforms only-deep learning-based and traditional optical flow-based methods.  The insurance data could provide a good proxy for describing heavy rainfall damage and to aid to explore the causes and impacts.  This study would greatly assist policy makers, civil protection agencies, and insurance companies to improve emergency systems and response mechanisms.</p>


2008 ◽  
Vol 71 (2) ◽  
pp. 171-183 ◽  
Author(s):  
F. Tassi ◽  
F. Aguilera ◽  
O. Vaselli ◽  
E. Medina ◽  
D. Tedesco ◽  
...  

2020 ◽  
Author(s):  
Andre Geisler ◽  
Benjamin Seelmann ◽  
Matthias Hort ◽  
Joachim Bülow ◽  
Lea Scharff ◽  
...  

<p>In February 2019 we completed the installation of a ten instrument network at Sakurajima volcano, Japan. The network includes three Doppler radar systems to record eruption velocities and amount of ejected material at Minamidake crater. Those instruments are located to the East of the volcano at a distance of about 4.5 km to the vent. We also installed three field mills to measure the electric field that is generated during an eruption due to charging of the volcanic plume. Those instruments are located to the East, North and West of the volcano at different distances. The network is completed by a weather station to monitor environmental conditions, an absolute pressure sensor for recording infrasound data, and a broadband seismometer. As an additional instrument we installed a thunderstorm detector BTD300.</p><p> </p><p>In a first step we use the infrasound data (complemented by four stations from the japanese network) to generate an event catalog. The main reason for doing this is the fact that the Japanese Meteorological Society (responsible for monitoring) only reports eruptions higher than 1000 m above the vent, but there are certainly more but smaller eruptions. The event catalog based on infrasound data is complemented by the events detected by our radar systems and the field mills. In the presentation we will discuss the detection limits of the network as well as the observed electrification of the volcanic cloud that may lead to lightning, which leaves a clear signal in the electric field data. We will present some initial numerical simulations on where the strongest electric field in an eruption column occurs and discuss the impact of charging due to fractoemission and triboelectrification. Using the measured data and our initial numerical model calculations we explore which dynamic conditions appear to be favorable for lightning to occur and which not.</p>


Sign in / Sign up

Export Citation Format

Share Document