Measurement quality and analysis capability of infrasonic signals are both affected by background wind-noise. Physical filters, i.e., barriers and pipe arrays, are traditionally employed to reduce such noise. However, limited efficacy, site dependence, cost, requirement of space, non-portability, and frequent maintenance are some of their major drawbacks. This work proposes an adaptive filtering-based adaptive line enhancer (ALE) noise cancellation scheme as an alternative. Two infrasonic sensors (Chaparral Physics 50A), are adjacently deployed. One sensor is fitted with a conventional four-armed non-porous hose array (physical filter), while the ALE scheme is applied to the second sensor, sans physical filter. In high wind-noise conditions, the ALE scheme seems to behave as a lowpass filter (cutoff at 0.2 Hz), with a maximum attenuation of 26 dB at 8 Hz, while the physical filter provides significant attenuation only above 4 Hz with a maximum attenuation of 17 dB at 8 Hz. Generally, at other frequencies, the ALE scheme provides up to 20 dB superior noise attenuation as compared to the physical filter. The ALE also provides up to 6 dB gain in the signal-to-noise ratio as compared to the physical filter, due to non-attenuation of the infrasonic signal.

A massive snow avalanche occurred on April, 2012 at Gayari, located in NE part of Pakistan, close to India and China Border. The catastrophic avalanche killed nearly 148 people, majority of which were Pakistan army personnel destroying army base camp. To mitigate its future hazard, different triggering mechanisms have been investigated in this study. We contemplate that the avalanche was triggered due to snow pack existence on favorable slope in combination with different meteorological conditions and anomalous ground vibration. The avalanche occurrence clock was advanced by two earthquakes: M4.1 at a distance ∼ 125 km that occurred about 21 hours before and another comparatively larger (M5.6) earthquake that occurred comparatively at larger distance (∼ 370 km) and longer time (∼ 25 days) before which have significantly changed the loading conditions. The latter event (M 5.6) has imparted maximum peak dynamic stress and cumulative seismic moment a month before the avalanche. Interestingly the avalanche occurred within the seismic coda of M2.8 earthquake from Hindu Kush region, located at 560 km distance. Although the size and its expected impact on avalanche might be minor but its role in instantaneous triggering cannot be ruled out. Even smaller events at larger distance have been reported to cause snow avalanches in same environments. The presence of cracks within the avalanche, were further weaken by persistence of extremely low temperature (lowest in the past decade), causing high precipitation rate along with altering the mechanical properties of the weak layer within the snow pack. Robust wind pressure pattern highest and lowest in March and April, 2012 respectively might be responsible for abrupt changes in loading conditions.

This study presents the coherently stacked P-wave receiver functions and bouguer anomaly mapping of Western Himalayas (longitude 71°-74°E and latitude 31°-34°N ) to estimate crustal thickness. Data used for Pwave receiver function is from local seismic network of Pakistan whereas, gravity data is extracted from Topex available in public domain for research. The crust thickness and average crust Vp/Vs ratio at each station of the network is obtained by coherently stacking the Ps, PpPs, PpSs + PsPs phases of 15 seismic stations. The data used in this study was collected from 2012 to 2019, events with magnitudes mb ≥ 6 and epicenteral distances 30°to 95°were chosen. There is a significant difference in Moho depth beneath the broadband seismic stations used for the investigations. Moho depth mapping: A case study of Western HimalayasMoho depth is 36 km in the south, on average 46 km in the center, and 52 km at the northernmost seismic station of the study area. In general, the crust is dipping from South to North for the study area. In order to support this interpreted argument of moho-depth variation from P-Wave receiver function, residual calculation of bouguer anomaly data was carried out as well. The residuals showing a variation of anomalous data from -89 to 193 mGal in study area have presented a promising correlation and favored the argument of crustal dipping as suggested by P-wave function from seismic network. The trend confirms that the crustal thickening and shortening is caused by the collision of Indian and Asian plates.

This study presents the coherently stacked P-wave receiver functions and bouguer anomaly mapping ofWestern Himalayas (longitude 71◦ -74◦ E and latitude 31◦ -34◦ N ) to estimate crustal thickness. Data used for P-wave receiver function is from a local seismic network of Pakistan whereas, gravity data is extracted from Topex and available in the public domain for research. The crust thickness and average crust Vp/Vs ratio at each station of the network are obtained by coherently stacking the Ps, PpPs, PpSs + PsPs phases of 15seismic stations. The data used in this study was collected from 2012 to 2019, events with magnitudes mb ≥ 6 and epicentral distances 30◦ to 95◦ were chosen. There is a significant difference in Moho depth beneath the broadband seismic stations used for the investigations. Moho depth is 36 km in the south, on average 46 km in the center, and 52 km at the northernmost seismic station of the study area. The crust is generally dipping from South to North for the study area. In order to support this interpreted argument of moho-depth variation from the P-wave receiver function, residual calculation of Bouguer anomaly data was carried out as well. The residuals showing a variation of anomalous data from -89 to 193 mGal in the study area have presented a good correlation and favored the argument of crustal dipping as suggested by the P-wave function from the seismic network. The trend confirms that the crustal thickening and shortening are caused by the collision of Indian and Asian plates.