scholarly journals Waveform Relocated Earthquake Catalog for Southern California (1981 to June 2011)

2012 ◽  
Vol 102 (5) ◽  
pp. 2239-2244 ◽  
Author(s):  
E. Hauksson ◽  
W. Yang ◽  
P. M. Shearer
Keyword(s):  
Southern California ◽  
Earthquake Catalog

Southern California Earthquake Data Now Available in the AWS Cloud

2021 ◽  
Author(s):  
Ellen Yu ◽  
Aparna Bhaskaran ◽  
Shang-Lin Chen ◽  
Zachary E. Ross ◽  
Egill Hauksson ◽  
...  
Keyword(s):  
Southern California ◽  
Data Availability ◽  
First Year ◽  
Earthquake Catalog ◽  
High Data ◽  
Seismic Waveform ◽  
Challenges And Opportunities ◽  
Amazon Web Services ◽  
Computationally Intensive ◽  
Earthquake Data

Abstract The Southern California Earthquake Data Center is hosting its earthquake catalog and seismic waveform archive in the Amazon Web Services (AWS) Open Dataset Program (s3://scedc-pds; us-west-2 region). The cloud dataset’s high data availability and scalability facilitate research that uses large volumes of data and computationally intensive processing. We describe the data archive and our rationale for the formats and data organization. We provide two simple examples to show how storing the data in AWS Simple Storage Service can benefit the analysis of large datasets. We share usage statistics of our data during the first year in the AWS Open Dataset Program. We also discuss the challenges and opportunities of a cloud-hosted archive.

scholarly journals Simple statistics for complex Earthquake time distributions

2018 ◽  
Vol 25 (3) ◽  
pp. 497-510 ◽  
Author(s):  
Teimuraz Matcharashvili ◽  
Takahiro Hatano ◽  
Tamaz Chelidze ◽  
Natalia Zhukova
Keyword(s):  
Data Analysis ◽  
Calculation Method ◽  
Time Distribution ◽  
Southern California ◽  
Multiscale Entropy ◽  
Data Sets ◽  
Analysis Tool ◽  
Earthquake Catalog ◽  
Complex Data ◽  
Process Data

Abstract. Here we investigated a statistical feature of earthquake time distributions in the southern California earthquake catalog. As a main data analysis tool, we used a simple statistical approach based on the calculation of integral deviation times (IDT) from the time distribution of regular markers. The research objective is to define whether and when the process of earthquake time distribution approaches to randomness. Effectiveness of the IDT calculation method was tested on the set of simulated color noise data sets with the different extent of regularity, as well as for Poisson process data sets. Standard methods of complex data analysis have also been used, such as power spectrum regression, Lempel and Ziv complexity, and recurrence quantification analysis, as well as multiscale entropy calculations. After testing the IDT calculation method for simulated model data sets, we have analyzed the variation in the extent of regularity in the southern California earthquake catalog. Analysis was carried out for different periods and at different magnitude thresholds. It was found that the extent of the order in earthquake time distributions is fluctuating over the catalog. Particularly, we show that in most cases, the process of earthquake time distributions is less random in periods of strong earthquake occurrence compared to periods with relatively decreased local seismic activity. Also, we noticed that the strongest earthquakes occur in periods when IDT values increase.

scholarly journals Quantitative Analysis of Shallow Earthquake Sequences and Regional Earthquake Behavior: Implications for Earthquake Forecasting

2021 ◽  
Author(s):  
◽  
Katrina Maureen Jacobs
Keyword(s):  
New Zealand ◽  
Southern California ◽  
Southern Alps ◽  
Earthquake Forecasting ◽  
Double Difference ◽  
Earthquake Catalog ◽  
Slow Slip ◽  
Individual Sequences ◽  
Earthquake Sequences ◽  
Sequence Parameters

<p>This study is a quantitative investigation and characterization of earthquake sequences in the Central Volcanic Region (CVR) of New Zealand, and several regions in New Zealand and Southern California. We introduce CURATE, a new declustering algorithm that uses rate as the primary indicator of an earthquake sequence, and we show it has appreciable utility for analyzing seismicity. The algorithm is applied to the CVR and other regions around New Zealand. These regions are also compared with the Southern California earthquake catalogue. There is a variety of behavior within these regions, with areas that experience larger mainshock-aftershock (MS-AS) sequences having distinctly different general sequence parameters than those of more swarm dominated regions. The analysis of the declustered catalog shows that Lake Taupo and at least three other North Island regions have correlated variations in rate over periods of ~5 years. These increases in rate are not due to individual large sequences, but are instead caused by a general increase in earthquake and sequence occurrence. The most obvious increase in rate across the four North Island subsets follows the 1995-1996 magmatic eruption at Ruapehu volcano. The fact that these increases are geographically widespread and occur over years at a time suggests that the variations may reflect changes in the subduction system or a broad tectonic process.  We examine basic sequence parameters of swarms and MS-AS sequences to provide better information for earthquake forecasting models. Like MS-AS sequences, swarm sequences contain a large amount of decay (decreasing rate) throughout their duration. We have tested this decay and found that 89% of MS-AS sequences and 55% of swarm sequences are better fit with an Omori's law decay than a linear rate. This result will be important to future efforts to forecast lower magnitude ranges or swarm prone areas like the CVR.  To look at what types of process may drive individual sequences and may be associated with the rate changes, we examined a series of swarms that occurred to the South of Lake Taupo in 2009. We relocated these earthquakes using double-difference method, hypoDD, to obtain more accurate relative locations and depths. These swarms occur in an area about 20x20 km. They do not show systematic migration between sequences. The last swarm in the series is located in the most resistive area of the Tokaanu geothermal region and had two M =4.4 earthquakes within just four hours of each other. The earthquakes in this swarm have an accelerating rate of occurrence leading up to the first M = 4.4 earthquakes, which migrate upward in depth. The locations of earthquakes following the M = 4.4 event expand away from it at a rate consistent with fluid diffusion.  Our statistical investigation of triggering due to large global (M ≥ 7) and regional earthquakes (M ≥ 6) concludes that more detailed (waveform level) investigation of individual sequences will be necessary to conclusively identify triggering, but sequence catalogs may be useful in identifying potential targets for those investigations. We also analyzed the probability that a series of swarms in the central Southern Alps were triggered by the 2009 Dusky Sound Mw = 7.8 and the 2010 Darfield Mw = 7.1 earthquake. There is less than a one-percent chance that the observed sequences occurred randomly in time. The triggered swarms do not show a significant difference to the swarms occurring in that region at other times in the 1.5-year catalog. Waveform cross-correlation was performed on this central Southern Alps earthquake catalog by a fellow PhD student Carolin Boese, and reveals that individual swarms are often composed of a single waveform family or multiple waveform families in addition to earthquakes that did not show waveform similarities. The existence of earthquakes that do not share waveform similarity in the same swarm (2.5 km radius) as a waveform family indicates that similar waveform groups may be unique in their location, but do not necessarily necessitate a unique trigger or driver. In addition to these triggered swarms in the Southern Alps we have also identified two swarms that are potentially triggered by slow-slip earthquakes along the Hikurangi margin in 2009 and 2010. The sequence catalogs generated by the CURATE method may be an ideal tool for searching for earthquake sequences triggered by slow-slip.</p>

scholarly journals Quantitative Analysis of Shallow Earthquake Sequences and Regional Earthquake Behavior: Implications for Earthquake Forecasting

2021 ◽  
Author(s):  
◽  
Katrina Maureen Jacobs
Keyword(s):  
New Zealand ◽  
Southern California ◽  
Southern Alps ◽  
Earthquake Forecasting ◽  
Double Difference ◽  
Earthquake Catalog ◽  
Slow Slip ◽  
Individual Sequences ◽  
Earthquake Sequences ◽  
Sequence Parameters

<p>This study is a quantitative investigation and characterization of earthquake sequences in the Central Volcanic Region (CVR) of New Zealand, and several regions in New Zealand and Southern California. We introduce CURATE, a new declustering algorithm that uses rate as the primary indicator of an earthquake sequence, and we show it has appreciable utility for analyzing seismicity. The algorithm is applied to the CVR and other regions around New Zealand. These regions are also compared with the Southern California earthquake catalogue. There is a variety of behavior within these regions, with areas that experience larger mainshock-aftershock (MS-AS) sequences having distinctly different general sequence parameters than those of more swarm dominated regions. The analysis of the declustered catalog shows that Lake Taupo and at least three other North Island regions have correlated variations in rate over periods of ~5 years. These increases in rate are not due to individual large sequences, but are instead caused by a general increase in earthquake and sequence occurrence. The most obvious increase in rate across the four North Island subsets follows the 1995-1996 magmatic eruption at Ruapehu volcano. The fact that these increases are geographically widespread and occur over years at a time suggests that the variations may reflect changes in the subduction system or a broad tectonic process.  We examine basic sequence parameters of swarms and MS-AS sequences to provide better information for earthquake forecasting models. Like MS-AS sequences, swarm sequences contain a large amount of decay (decreasing rate) throughout their duration. We have tested this decay and found that 89% of MS-AS sequences and 55% of swarm sequences are better fit with an Omori's law decay than a linear rate. This result will be important to future efforts to forecast lower magnitude ranges or swarm prone areas like the CVR.  To look at what types of process may drive individual sequences and may be associated with the rate changes, we examined a series of swarms that occurred to the South of Lake Taupo in 2009. We relocated these earthquakes using double-difference method, hypoDD, to obtain more accurate relative locations and depths. These swarms occur in an area about 20x20 km. They do not show systematic migration between sequences. The last swarm in the series is located in the most resistive area of the Tokaanu geothermal region and had two M =4.4 earthquakes within just four hours of each other. The earthquakes in this swarm have an accelerating rate of occurrence leading up to the first M = 4.4 earthquakes, which migrate upward in depth. The locations of earthquakes following the M = 4.4 event expand away from it at a rate consistent with fluid diffusion.  Our statistical investigation of triggering due to large global (M ≥ 7) and regional earthquakes (M ≥ 6) concludes that more detailed (waveform level) investigation of individual sequences will be necessary to conclusively identify triggering, but sequence catalogs may be useful in identifying potential targets for those investigations. We also analyzed the probability that a series of swarms in the central Southern Alps were triggered by the 2009 Dusky Sound Mw = 7.8 and the 2010 Darfield Mw = 7.1 earthquake. There is less than a one-percent chance that the observed sequences occurred randomly in time. The triggered swarms do not show a significant difference to the swarms occurring in that region at other times in the 1.5-year catalog. Waveform cross-correlation was performed on this central Southern Alps earthquake catalog by a fellow PhD student Carolin Boese, and reveals that individual swarms are often composed of a single waveform family or multiple waveform families in addition to earthquakes that did not show waveform similarities. The existence of earthquakes that do not share waveform similarity in the same swarm (2.5 km radius) as a waveform family indicates that similar waveform groups may be unique in their location, but do not necessarily necessitate a unique trigger or driver. In addition to these triggered swarms in the Southern Alps we have also identified two swarms that are potentially triggered by slow-slip earthquakes along the Hikurangi margin in 2009 and 2010. The sequence catalogs generated by the CURATE method may be an ideal tool for searching for earthquake sequences triggered by slow-slip.</p>

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