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CSIR Fourth Paradigm Institute

(Formerly CSIR Centre for Mathematical Modelling and Computer Simulation)

A constituent laboratory of Council of Scientific & Industrial Research (CSIR).

Ministry of Science and Technology, Government of India.

by Ramees R. Mir, Imtiyaz A. Parvez, Gabi Laske & Vinod K. Gaur 

This paper presents estimated misorientation angles of broadband seismic sensors of the Kashmir-Zanskar network and their effects on anisotropy determinations and great-circle-path deviations. The misorientations were calculated from the difference between backazimuths of Rayleigh waves and those of the great-circle-arcs connecting the source and receiver. Waveforms of global Rayleigh waves extracted from the records of 13 broadband seismographs in the Kashmir-Zanskar region of Northwestern Himalaya, and 3 others around the region, were used to evaluate misorientation errors in each of these sensor installations. Three of the 16 were found to have orientation errors between ± 5 and 10° with respect to the geographic north, 4 between 10 and 16° and the remainder with <5°. These misalignments had resulted in leakage of a substantial amount of energy in the transverse component receiver functions which, after correction, led to sharper amplitudes and polarities. Indeed, the SKS-derived azimuths of the fast component were found to be quite sensitive to instrument misalignment, suffering ~ 16° shift from a ~ 15.5° error in orientation. A notable observation revealed by misalignment corrections was the substantial, up to 20°, off-great-circle arc deviations even along shorter path arrivals from regional events, offering a qualitative ordination of the region’s heterogeneities. The paper also presents probability distribution functions of the estimated power spectral density of ambient noise at each station compared with global high and low-noise models and near-source earthquake models. The results provide a first-order assessment of small earthquake detection capability of this network, down to M1.0, also confirmed by some of the smallest events located.

Source: https://doi.org/10.1007/s10950-022-10090-z

 

 

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To synergize the strong expertise in various disciplines across CSIR and build a unified platform that embodies a rich set of big data enabling technologies and services with optimized performance to facilitate research collaboration and scientific discovery. 

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To develop reliable knowledge products for decision support in Earth, Engineering and Information sciences as well as to host centralised supercomputing facility for CSIR. 

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