Overview

This site presents the current research of Freddy Aldersons.

Publications

2014

Aldersons, F., and Z. Ben-Avraham (2014)
The Seismogenic Thickness in the Dead Sea Area.
In: Garfunkel, Z., Ben-Avraham, Z., Kagan, E. (Eds.) The Dead Sea Transform: Reviews. Modern Approaches in Solid Earth Sciences. Volume 6. Springer, Dordrecht. pp. 53-89.

Four independent distributions of seismicity in the Dead Sea area underline the occurrence of lower-crustal seismic activity down-to at least 27 km and possibly as deep as 33.6 km. From these distributions, the seismogenic thickness is estimated to be 28.4 ± 2.2 km . The existence of a seismogenic zone extending deep into the lower crust is consistent with an average heat flow of only 40 - 45 mWm-2 over most regions of Israel, and around 40 mWm-2 in the Dead Sea area in particular. The seismogenic thickness in the Dead Sea area is thus nearly twice the average seismogenic thickness of 15 km observed in southern California. The fact that some seismic activity occurs down-to the Moho in the Dead Sea area suggests that the state of fully plastic deformation is probably not reached in the crust under the seismogenic zone. The ISC-GEM (Storchak et al., 2013) relocation of the Mw 6.3 earthquake of 11 July 1927 from regional and teleseismic instrumental data resulted in a well-constrained epicenter located in the Jordan Valley, not far from the epicenter reported in the 1927 bulletin of the ISS. Since the causative fault of this earthquake is likely to be the Dead Sea transform, we propose a preferred epicenter at 31.92 º N - 35.56 º E. The focal depth determined instrumentally by the ISC-GEM relocation is 15 ± 6 km, and we found an average macroseismic depth of 21.5 ± 2.5 km. Our results as a whole underline also the seismogenic importance of the transition between the upper and the lower crust in the Dead Sea area for moderate and probably also for large earthquakes.

2009

Aldersons, F., Chiaraluce, L., Di Stefano, R., Piccinini, L., and L. Valoroso (2009)
Automatic Detection, and P- and S-wave Picking Algorithm: an application to the 2009 L'Aquila (Central Italy) earthquake sequence.
Eos Trans. AGU , 90(52), Fall Meet. Suppl., Abstract U23B-0045.

In order to process as quickly as possible the enormous amount of digital waveforms continuously recorded at permanent and temporary seismic stations in Italy, we implemented a semi-automatic procedure in order to identify local earthquakes and to provide consistently-weighted P- and S-wave arrival times. Local earthquake detection is obtained by a STA / LTA ratio-based algorithm applied to 3-component seismograms from individual stations. A minimum of 4 triggered stations are required to declare a seismic event. This setting proved to be extremely effective to detect a large number of very-low magnitude earthquakes (ML > 1.5) with a small number of false alarms. The automatic picking system Mannekenpix (Aldersons, 2004), originally working on vertical component data, has been expanded to tackle 3-component data. In order to increase the reliability of P-wave and S-wave picking, the system is now virtually capable of discriminating among noise samples, P-wave samples and S-wave samples. This Identification is performed by a C5 decision tree (Quinlan, 1993) derived from training data. Five groups of predicting variables are included: Energy, Polarization, Spectral Power, Skewness and Kurtosis. In addition, the SEDSL algorithm (Magotra et al., 1989) is also used as a predictor. The picking procedure requires a preliminary calibration derived from a reference subset of high-quality manual picks. After calibration, the picking system is statistically able to mimic the picking by a human analyst and to provide consistent uncertainty estimates translated into picking weights. We illustrate very satisfying results of the automatic procedure showing P- and S-phase automatic readings for the L'Aquila 2009 sequence. The readings are fully comparable to those of a good human analyst, allowing high-quality earthquake locations of low-magnitude events in an extremely short amount of time. For a full day of continuous recording, we obtain around 2,600 triggers, from which 75% lead to high-quality located events (mean RMS ~0.1s) with at least 25 phase readings.

Diehl, T., Kissling, E., Husen, S., and F. Aldersons (2009)
Consistent phase picking for regional tomography models: application to the greater Alpine region.
Geophysical Journal International, 176, 542-554.

The resolution and reliability of tomographic velocity models strongly depends on quality and consistency of available traveltime data. Arrival times routinely picked by network analysts on a day-to-day basis often yield a high level of noise due to mispicks and other inconsistencies, particularly in error assessment. Furthermore, tomographic studies at regional scales require merging of phase picks from several networks. Since a common quality assessment is not usually available for phase data provided by different networks, additional inconsistencies are introduced by the merging process. Considerable improvement in the quality of phase data can only be achieved through complete repicking of seismograms. Considering the amount of data necessary for regional high-resolution tomography, algorithms combining accurate picking with an automated error assessment represent the best tool to derive large suitable data sets. In this work, we present procedures for consistent automated and routine picking of P-wave arrival times at local to regional scales including consistent picking error assessment. Quality-attributed automatic picks are derived from the MPX picking system. The application to earthquakes in the greater Alpine region demonstrates the potential of such a repicking approach. The final data set consists of more than 13,000 high-quality first-arrivals and it is used to derive regional 1-D and preliminary 3-D P-wave models of the greater Alpine region. The comparison with a tomographic model based on routine phase data extracted from the ISC Bulletin illustrates effects on tomographic results due to consistency and reliability of our high-quality data set.

2006

Di Stefano, R., Aldersons, F., Kissling, E., Baccheschi, P., Chiarabba, C., and D. Giardini (2006)
Automatic seismic phase picking and consistent observation error assessment: Application to the Italian seismicity.
Geophysical Journal International, 165, 121-134.

Accuracy of seismic phase observation and consistency of timing error assessment define the quality of seismic waves arrival times. High-quality and large data sets are prerequisites for seismic tomography to enhance the resolution of crustal and upper mantle structures. In this paper we present the application of an automated picking system to some 600,000 seismograms of local earthquakes routinely recorded and archived by the Italian national seismic network. The system defines an observation weighting scheme calibrated with a hand-picked data subset and mimics the picking by an expert seismologist. The strength of this automatic picking is that once it is tuned for observation quality assessment, consistency of arrival times is strongly improved and errors are independent of the amount of data to be picked. The application to the Italian local seismicity documents that it is possible to automatically compile a precise, homogeneous and large data set of local earthquake Pg and Pn arrivals with related polarities. We demonstrate that such a data set is suitable for high-precision earthquake location, focal mechanism determination and high-resolution seismic tomography.

2004

Aldersons, F. (2004)
Toward a Three-Dimensional Crustal Structure of the Dead Sea region from Local Earthquake Tomography.
Ph.D. thesis, Tel-Aviv University, pp. 123.

Within the framework of local earthquake tomography, a new automatic picking system called MannekenPix has been developed in order to collect a high-quality set of picking data from the Dead Sea region. In another work, this data set would then become the input of a high-resolution travel-time tomographic study of the crustal structure of the basin. In the first step of MannekenPix, the seismograms are filtered by a high-fidelity Wiener filter in order to increase the signal-to-noise ratio of the P-wavetrain before picking. The Wiener filter of MannekenPix uses the Maximum Entropy Method (MEM) to estimate power spectral densities, a method particularly well adapted to short data segments. The picking is performed in the second step by the robust and versatile Baer-Kradolfer (Baer and Kradolfer, 1987) picking engine. If a valid pick has been found, adaptive delay corrections are applied in the third step in order to reduce the inherent lag of the Baer-Kradolfer algorithm arrivals. In the fourth step, the weighting engine provides a statistical estimate of the picking uncertainty. For each data set, the weighting engine has to be calibrated first by a Multiple Discriminant Analysis (MDA) performed on user-supplied reference picks and weights.

By using MannekenPix to pick the seismograms from well-constrained earthquakes of the Dead Sea region, 526 (99.1 %) out of 531 earthquakes are locatable by automatic picking. Out of 15,250 seismograms, 6,889 (45.2 %) were routinely picked and 7,089 (46.5 %) were automatically picked. On the calibration data set, the average discrepancy between the routine picking and the reference picking is –0.037 sec, with a standard deviation of 0.121 sec. The average discrepancy of the automatic picking is +0.007 sec with a standard deviation of only 0.066 sec. For the complete data set, 3,058 phases (43.1 %) of the 7,089 automatic P picks fall into predicted weight 1 (absolute uncertainty not greater than 40 msec), 1,173 (16.5 %) fall into class 2 (absolute uncertainty between 40 msec and 80 msec), 1,554 (21.9 %) fall into class 3 (absolute uncertainty between 80 msec and 140 msec) and 1,304 (18.4 %) fall into class 4 (absolute uncertainty greater than 140 msec). The results from a totally out-of-sample set of reference picks and weights confirm the stability of predicted weights on unseen data

2003

Aldersons, F., Ben-Avraham, Z., Hofstetter, A., Kissling, E., and T. Al-Yazjeen (2003)
Lower-crustal strength under the Dead Sea basin from local earthquake data and rheological modeling.
Earth and Planetary Science Letters, 214, 129-142.

We studied the local seismicity of the Dead Sea basin for the period 1984-1997. Sixty percent of well-constrained microearthquakes (ML ≤ 3.2) nucleated at depths of 20-32 km and more than 40 percent occurred below the depth of peak seismicity situated at 20 km. With the Moho at 32 km, the upper mantle appeared to be aseismic during the 14-year data period. A relocation procedure involving the simultaneous use of three regional velocity models reveals that the distribution of focal depths in the Dead Sea basin is stable. Lower-crustal seismicity is not an artifact created by strong lateral velocity variations or data-related problems. An upper bound depth uncertainty of ± 5 km is estimated below 20 km, but for most earthquakes depth mislocations should not exceed ± 2 km. A lithospheric strength profile has been calculated. Based on a surface heat flow of 40 mWm-2 and a quartz-depleted lower crust, a narrow brittle to ductile transition might occur in the crust around 380°C at a depth of 31 km. For the upper mantle, the brittle to ductile transition occurs in the model at 490ºC and at 44 km depth. The absence of micro-seismicity in the upper mantle remains problematic.


Seismological Software developed by Freddy Aldersons

1. MannekenPix (Production-Mode Automatic Picking)

MannekenPix is an advanced single-trace automatic picking system for first P-wave arrivals recorded at local, regional and teleseismic distances. MPX is a turn-key solution that does not require much tuning from an experienced user before a true production mode can be reached. Most automatic picks produced by the program are comparable to those of a good human analyst. MPX includes also a weighting mechanism rigorously calibrated on Reference picks and weights provided by the user. The weighting mechanism of MPX attempts to predict the same uncertainties as those that would be estimated by a human analyst. As such, it acts as an extension of the manual approach and not as a totally independent method possibly in conflict with the legacy.

2. Visual Picker (Manual and Automatic Visual Picking)

Visual Picker is a MS-Windows companion program to MannekenPix. The main use of Visual Picker is to build a Reference subset of hand-picked arrival times and weights necessary to calibrate the weighting engine of MannekenPix on a particular data set. Since Visual Picker integrates the Wiener filter of MPX and visual tools for the determination of the Reference picking uncertainty, it is the recommended software for building the Reference set of an MPX project. Visual Picker can also be used to quickly get a feeling about how the filtering and picking routines of MPX behave on a particular data set, and to help finding appropriate values for the MPX parameters.

3. Twins Merge (Accurate Network Extender)

Twins Merge is an application allowing to accurately merge seismograms from neighbour networks whose clocks are occasionally or permanently out-of-sync with the clock of a given network. The capability of accurately synchronizing and merging seismograms can be of significant importance to the seismic monitoring coverage of regional and international borders, and at global scale. It is also quite relevant to the integration of seismograms from temporary networks.

Besides the central property of accurately synchronizing and merging seismograms, Twins Merge provides also for two related networks the automatic recognition of common events, and an automatic recognition of common stations for each common event. These beneficial side-effects also increase the overall quality of merged databases of seismograms compared to any manual approach of the synchronization problem.

Existing Seismological Software ported to PC (Windows and Linux)