scholarly journals Seismic Precursors to the Whakaari 2019 Phreatic Eruption detected in Five Other Volcanoes

2021 ◽  
Author(s):  
Alberto Ardid ◽  
David Dempsey ◽  
Corentin Caudron ◽  
Shane Cronin
Keyword(s):  
New Zealand ◽  
Amplitude Ratio ◽  
Volcanic Tremor ◽  
Volcanic Eruptions ◽  
Geophysical Monitoring ◽  
Seal Failure ◽  
Seismic Amplitude ◽  
Seismic Precursor ◽  
Eruption Precursors ◽  
Short Term Forecasting

Abstract Volcanic eruptions that occur without warning can be deadly in touristic and populated areas. Even with real-time geophysical monitoring, forecasting sudden eruptions is difficult because their precursors are hard to recognize and can vary between volcanoes. Here, we describe a general seismic precursor signal for gas-driven eruptions, identified through correlation analysis of 18 well-recorded eruptions in New Zealand, Alaska and Kamchatka. We show that the displacement seismic amplitude ratio, a ratio between high and medium frequency volcanic tremor, has a characteristic rise in the days prior to eruptions that likely indicates formation of a hydrothermal seal that enables rapid pressurization. Applying this model to the fatal 2019 eruption at Whakaari (New Zealand), we identify pressurization in the week before the eruption, and cascading seal failure in the 16 hours prior to the explosion. This method for identifying and proving generalizable eruption precursors can help improve short term forecasting systems.

Investigation of the pre-eruptive processes of the 2014/15 Holuhraun eruption based on extracted volcanic tremor signals

2021 ◽  
Author(s):  
Zahra Zali ◽  
Eva Eibl ◽  
Matthias Ohrnberger ◽  
Frank Scherbaum
Keyword(s):  
Amplitude Ratio ◽  
Ground Deformation ◽  
Volcanic Tremor ◽  
Simultaneous Occurrence ◽  
Generation Process ◽  
Glacier Surface ◽  
Aerial Photos ◽  
Seismic Amplitude ◽  
Subglacial Eruptions ◽  
Eruption Precursors

<p>During volcanic unrest, multiple subsurface processes can happen simultaneously and may lead to an eruption. The analysis of seismic records in an unrest period before an eruption reveals information about the pre-eruptive processes and might be able to provide hints for a possible future eruption.</p><p>The 2014–2015 Holuhraun eruption was the largest one in Iceland in 230 years. It was extensively monitored and studied in a variety of multidisciplinary research approaches. Intense seismicity and ground deformation were interpreted as magma propagation from Bárðarbunga volcano 48 km laterally at ∼6 km depth over two weeks before an eruption started at Holuhraun. Different processes including vertical and lateral magma migration, dike propagation, caldera subsidence, and subglacial eruptions happened in this period and some models linking these processes are suggested. In the two-week interval preceding the eruption, there is still no clear connection between the observed tremor and pre-eruptive processes. Both the tremor source location and tremor generation process are not well understood yet. While cauldrons as a sign of subglacial eruptions were identified on the glacier surface from aerial photos, these cauldrons might have been formed earlier and there is hence an uncertainty of a few days. A tremor location might help to constrain these dates. However, the simultaneous occurrence of intense seismicity and tremor hinders the study and location of tremor. Here, we use a recent volcanic tremor extraction algorithm (Zali et al., 2020) and extract pre-eruptive tremor signals in order to better locate them using the Seismic Amplitude Ratio Analysis (SARA) method. Furthermore, the occurrence of the tremor could open new insights into ascending magma and fluid migration as well as the timing and duration of the subglacial eruptions.</p><p>We also observed short-lived tremors before the eruptions on August 29 and 31, which could be considered as eruption precursors. The primary investigation on the extracted tremor signals is promising while further analysis is on-going.</p>

scholarly journals A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Corentin Caudron ◽  
Társilo Girona ◽  
Arthur Jolly ◽  
Bruce Christenson ◽  
Martha Kane Savage ◽  
...  
Keyword(s):  
New Zealand ◽  
Seismic Data ◽  
Seismic Velocity ◽  
Amplitude Ratio ◽  
Volcanic Tremor ◽  
Active Volcano ◽  
Shallow Subsurface ◽  
The North ◽  
Phreatic Eruptions ◽  
White Island

AbstractThe Whakaari/White Island volcano, located ~ 50 km off the east coast of the North Island in New Zealand, has experienced sequences of quiescence, unrest, magmatic and phreatic eruptions over the last decades. For the last 15 years, seismic data have been continuously archived providing potential insight into this frequently active volcano. Here we take advantage of this unusually long time series to retrospectively process the seismic data using ambient noise and tremor-based methodologies. We investigate the time (RSAM) and frequency (Power Spectral Density) evolution of the volcanic tremor, then estimate the changes in the shallow subsurface using the Displacement Seismic Amplitude Ratio (DSAR), relative seismic velocity (dv/v) and decorrelation, and the Luni-Seismic Correlation (LSC). By combining our new set of observations with the long-term evolution of earthquakes, deformation, visual observations and geochemistry, we review the activity of Whakaari/White Island between 2007 and the end of 2018. Our analysis reveals the existence of distinct patterns related to the volcano activity with periods of calm followed by cycles of pressurization and eruptions. We finally put these results in the wider context of forecasting phreatic eruptions using continuous seismic records.

Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms

2021 ◽  
Author(s):  
Zahra Zali ◽  
Matthias Ohrnberger ◽  
Frank Scherbaum ◽  
Fabrice Cotton ◽  
Eva P. S. Eibl
Keyword(s):  
Amplitude Spectrum ◽  
Volcanic Tremor ◽  
Volcanic Eruptions ◽  
Detection Algorithm ◽  
Transient Signal ◽  
Volcanic Origin ◽  
Time Frequency ◽  
Reconstructed Signal ◽  
Single Station ◽  
Transient Events

Abstract Volcanic tremor signals are usually observed before or during volcanic eruptions and must be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contribute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic–percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect transient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time–frequency domain, we decompose the signal into two separate spectrograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contributing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of transient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectrogram over frequency at each time frame. Considering transient events like earthquakes, 78% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014–2015 eruption in Iceland with the bulletin presented in Ágústsdóttir et al. (2019). Our single station event detection algorithm identified 84% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number of the bulletin events.

The adaptive capacity of New Zealand communities to wildfire

2012 ◽  
Vol 21 (6) ◽  
pp. 764 ◽  
Author(s):  
Pamela J. Jakes ◽  
E. R. (Lisa) Langer
Keyword(s):  
New Zealand ◽  
Natural Disasters ◽  
Adaptive Capacity ◽  
Local Knowledge ◽  
Expert Knowledge ◽  
Volcanic Eruptions ◽  
Institutional Capacity ◽  
Process Elements

When we think of natural disasters in New Zealand, we tend to think of earthquakes or volcanic eruptions. However, a series of events is placing New Zealand communities at greater risk of wildfire. In a case study of a rural New Zealand community that experienced wildfire, process elements such as networks and relationships among locals, development and application of local knowledge and experience, and access to and application of expert knowledge and institutional capacity helped build adaptive capacity for disasters.

scholarly journals Forecasting COVID-19 Cases Using Alpha-Sutte Indicator: A Comparison with Autoregressive Integrated Moving Average (ARIMA) Method

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
A. M. C. H. Attanayake ◽  
S. S. N. Perera
Keyword(s):  
South Africa ◽  
New Zealand ◽  
Transmission Rate ◽  
Moving Average ◽  
Specific Treatment ◽  
Study Data ◽  
Percentage Error ◽  
The Usa ◽  
Short Term Forecasting ◽  
Modelling Approach

COVID-19 is a pandemic which has spread to more than 200 countries. Its high transmission rate makes it difficult to control. To date, no specific treatment has been found as a cure for the disease. Therefore, prediction of COVID-19 cases provides a useful insight to mitigate the disease. This study aims to model and predict COVID-19 cases. Eight countries: Italy, New Zealand, the USA, Brazil, India, Pakistan, Spain, and South Africa which are in different phases of COVID-19 distribution as well as in different socioeconomic and geographical characteristics were selected as test cases. The Alpha-Sutte Indicator approach was utilized as the modelling strategy. The capability of the approach in modelling COVID-19 cases over the ARIMA method was tested in the study. Data consist of accumulated COVID-19 cases present in the selected countries from the first day of the presence of cases to September 26, 2020. Ten percent of the data were used to validate the modelling approach. The analysis disclosed that the Alpha-Sutte modelling approach is appropriate in modelling cumulative COVID-19 cases over ARIMA by reporting 0.11%, 0.33%, 0.08%, 0.72%, 0.12%, 0.03%, 1.28%, and 0.08% of the mean absolute percentage error (MAPE) for the USA, Brazil, Italy, India, New Zealand, Pakistan, Spain, and South Africa, respectively. Differences between forecasted and real cases of COVID-19 in the validation set were tested using the paired t -test. The differences were not statistically significant, revealing the effectiveness of the modelling approach. Thus, predictions were generated using the Alpha-Sutte approach for each country. Therefore, the Alpha-Sutte method can be recommended for short-term forecasting of cumulative COVID-19 incidences. The authorities in the health care sector and other administrators may use the predictions to control and manage the COVID-19 cases.

scholarly journals Development of a multi-method chronology spanning the Last Glacial Interval from Orakei maar lake, Auckland, New Zealand

Geochronology ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 367-410
Author(s):  
Leonie Peti ◽  
Kathryn E. Fitzsimmons ◽  
Jenni L. Hopkins ◽  
Andreas Nilsson ◽  
Toshiyuki Fujioka ◽  
...  
Keyword(s):  
New Zealand ◽  
High Resolution ◽  
Large Scale ◽  
Volcanic Eruptions ◽  
Climate System ◽  
Luminescence Dating ◽  
Reference Curve ◽  
Auckland Volcanic Field ◽  
Last Glacial ◽  
Maar Lake

Abstract. Northern New Zealand is an important location for understanding Last Glacial Interval (LGI) palaeoclimate dynamics, since it is influenced by both tropical and polar climate systems which have varied in relative strength and timing. Sediments from the Auckland Volcanic Field maar lakes preserve records of such large-scale climatic influences on regional palaeo-environment changes, as well as past volcanic eruptions. The sediment sequence infilling Orakei maar lake is continuous, laminated, and rapidly deposited, and it provides a high-resolution (sedimentation rate above ∼ 1 m kyr−1) archive from which to investigate the dynamic nature of the northern New Zealand climate system over the LGI. Here we present the chronological framework for the Orakei maar sediment sequence. Our chronology was developed using Bayesian age modelling of combined radiocarbon ages, tephrochronology of known-age rhyolitic tephra marker layers, 40Ar∕39Ar-dated eruption age of a local basaltic volcano, luminescence dating (using post-infrared–infrared stimulated luminescence, or pIR-IRSL), and the timing of the Laschamp palaeomagnetic excursion. We have integrated our absolute chronology with tuning of the relative palaeo-intensity record of the Earth's magnetic field to a global reference curve (PISO-1500). The maar-forming phreatomagmatic eruption of the Orakei maar is now dated to > 132 305 years (95 % confidence range: 131 430 to 133 180 years). Our new chronology facilitates high-resolution palaeo-environmental reconstruction for northern New Zealand spanning the last ca. 130 000 years for the first time as most NZ records that span all or parts of the LGI are fragmentary, low-resolution, and poorly dated. Providing this chronological framework for LGI climate events inferred from the Orakei sequence is of paramount importance in the context of identification of leads and lags in different components of the Southern Hemisphere climate system as well as identification of Northern Hemisphere climate signals.

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