Mathematics – Probability
Scientific paper
Sep 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008epsc.conf..331h&link_type=abstract
European Planetary Science Congress 2008, Proceedings of the conference held 21-25 September, 2008 in Münster, Germany. Online a
Mathematics
Probability
Scientific paper
Introduction Several thousand seismic events were recorded by the Apollo seismic network from 19691977. Different types of events can be distinguished: meteoroid impacts, thermal quakes and internally caused moonquakes. The latter subdivide into shallow (100 to 300km) and deep moonquakes (700 to 1100km), which are by far the most common events. The deep quakes would be no immediate danger to inhabitated stations on the Earth's Moon because of their relatively low magnitude and great depth. However, they bear important information on lunar structure and evolution, and their distribution probably reflects their source mechanism. In this study, we reinvestigate location patterns of deep lunar quakes. LOCSMITH The core of this study is a new location method (LOCSMITH, [1]). This algorithm uses time intervals rather than time instants as input, which contain the dedicated arrival with probability 1. LOCSMITH models and compares theoretical and actual travel times on a global scale and uses an adaptive grid to search source locations compatible with all observations. The output is a set of all possible hypocenters for the considered region of repeating, tidally triggered moonquake activity, called clusters. The shape and size of these sets gives a better estimate of the location uncertainty than the formal standard deviations returned by classical methods. This is used for grading of deep moonquake clusters according to the currently available data quality. Classification of deep moonquakes As first step, we establish a reciprocal dependence of size and shape of LOCSMITH location clouds on number of arrivals. Four different shapes are recognized, listed here in an order corresponding to decreasing spatial resolution: 1. "Balls", which are well defined and relatively small types of sets resembling the commonly assumed error ellipsoid. These are found in the best cases with many observations. Locations in this shape are obtained for clusters 1, 18 or 33, these were already well located by earlier works [2,3]. 2. The next best shape of a location set is the "banana" as found for clusters 5, 39 or 53 [Fig. 1]. In this case, only limited depth resolution is available, and the solution spreads over a large volume. The size of a "banana" could be minimized by either finding a not yet discovered shear wave arrival or estimating a S arrival time interval by considering the coda instead of a clear S arrival. 3. Shape of clouds we call "cones" are formed by clusters for which no compressional wave arrivals, but three S arrivals were picked. Such solutions were found for clusters 35, 201 or 218 [Fig. 2]. A depth limitation is given only by the surface of the Moon's far side. In previous works, locations of these clusters were usually determined with a fixed depth, thus neglecting all depth uncertainty [2]. 4. The fourth and worst class shows a "disc"like shape with no depth resolution and almost no latitude resolution. Clusters of this class, like 4, 23 or 43, were not located so far. From class 1 ("ball") to 4 ("disc") the amount of possible hypocenters increases. So we also found a correlation between size and shape of volumes containing possible hypocenter solutions. Aim We classified all clusters according to the solution set scheme by using arrival times of [2] with an estimated error of ±10s as input for LOCSMITH. We reprocess selected clusters of each class to come up with the special requirements and possibilities of this new location method. As said above, one of the requirements of LOCSMITH is the definition of a time interval instead of a time instant for input, and an interesting option is using an estimated S arrival time interval derived from coda and scattering model, lacking a clear S arrival. We try to find fully automated methods for each processing step, dependent on the quality of data. Methods For despiking we merged methods by [4] and [5] and achieve very good results even for worst case as already presented in [6]. Prior to stacking we developed a complex multiparameter correlation algorithm to calculate the optimum time shift. Results We present relocations of selected deep moonquakes in context of data availability and quality. Previous locations are often contained in our location clouds, but realistic location uncertainties allow large deviations from the best fitting solutions, including locations on the far side of the Moon. Perspective By developing new methods for data processing and using the LOCSMITH locating algorithm we hope to reduce the location uncertainty sufficiently to make sure that all sources are on the near side, or to prove a far side origin of some of them. This would answer questions of hemispheric symmetry of lunar deep seismicity and the Moon's internal structure. References [1] Knapmeyer (2008) accepted to GJI. [2] Nakamura (2005) JGR, 110, E01001. [3] Lognonné (2003) EPSL, 211, 2744. [4] Bulow (2005) JGR, 110, E10003. [5] Sonnemann (2005) EGU05A07960. [6] Hempel, Knapmeyer, Oberst (2008) EGU2008A07989.
Hempel Stefanie
Knapmeyer Martin
Oberst Jürgen
Sens-Schönfelder Christoph
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