The AlpArray Research Seismicity-Catalogue
Bibliographic record
Abstract
Summary We take advantage of the new large AlpArray Seismic Network (AASN) as part of the AlpArray research initiative (www.alparray.ethz.ch), to establish a consistent seismicity-catalogue for the greater Alpine region (GAR) for the time period 2016 January 1–2019 December 31. We use data from 1103 stations including the AASN backbone composed of 352 permanent and 276 (including 30 OBS) temporary broad-band stations (network code Z3). Although characterized by a moderate seismic hazard, the European Alps and surrounding regions have a higher seismic risk due to the higher concentration of values and people. For these reasons, the GAR seismicity is monitored and routinely reported in catalogues by a 11 national and 2 regional seismic observatories. The heterogeneity of these data set limits the possibility of extracting consistent information by simply merging to investigate the GAR's seismicity as a whole. The uniformly spaced and dense AASN provides, for the first time, a unique opportunity to calculate high-precision hypocentre locations and consistent magnitude estimation with uniformity and equal uncertainty across the GAR. We present a new, multistep, semi-automatic method to process ∼50 TB of seismic signals, combining three different software. We used the SeisComP3 for the initial earthquake detection, a newly developed Python library ADAPT for high-quality re-picking, and the well-established VELEST algorithm both for filtering and final location purposes. Moreover, we computed new local magnitudes based on the final high-precision hypocentre locations and re-evaluation of the amplitude observations. The final catalogue contains 3293 seismic events and is complete down to local magnitude 2.4 and regionally consistent with the magnitude 3+ of national catalogues for the same time period. Despite covering only 4 yr of seismicity, our catalogue evidences the main fault systems and orogens’ front in the region, that are documented as seismically active by the EPOS-EMSC manually revised regional bulletin for the same time period. Additionally, we jointly inverted for a new regional minimum 1-D P-wave velocity model for the GAR and station delays for both permanent station networks and temporary arrays. These results provide the base for a future re-evaluation of the past decades of seismicity, and for the future seismicity, eventually improving seismic-hazard studies in the region. Moreover, we provide a unique, consistent seismic data set fundamental to further investigate this complex and seismically active area. The catalogue, the minimum 1-D P-wave velocity model, and station delays associated are openly shared and distributed with a permanent DOI listed in the data availability section.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".