Rain drop size distributions estimated from NOAA Snow-Level Radar data

Using NOAA’s S-band High Power Snow-Level Radar, HPSLR, a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized Gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion, w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter, Dm, from the measured reflectivity, Z, produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. This estimation technique was applied to 19 h of observations from Hankins, NC. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

Frequency-Domain Characteristics Response to Passive Exercise in Patients With Coronary Artery Disease

Purpose: The enhanced external counterpulsation (EECP), a kind of passive exercise, is a novel non-invasive therapy used to improve peripheral perfusion in patients with coronary artery disease (CAD). However, whether frequency-domain characteristics of peripheral hemodynamics may benefit from passive exercise needs to be verified.Methods: We recruited 21 patients with CAD and 21 healthy controls in this study. Ultrasonic blood flow velocity spectrum in left carotid (LC) and right carotid (RC) common arteries, and right brachial (RB) and right femoral (RF) arteries was monitored using an ultrasonic Doppler. Frequency-domain characteristics before, during, and after passive exercise were extracted from ultrasonic spectrum images. The first and second peak amplitudes/frequencies (y1, y2, x1, x2) and power spectral energy ratio (PSER) in the 0–2.05 Hz/0.87 Hz (p5, p6) were calculated by fast Fourier transform and power spectrum density analysis.Results: For the amplitude and frequency characteristics of the spectrum, y1 in the LC of patients with CAD was significantly decreased during exercise (p = 0.036), whereas, y2 was significantly decreased immediately after passive exercise (p = 0.038). Besides those, y1 only in the RC and RB of controls was significantly decreased during exercise. Immediately after exercise, y2 in the LC of control was significantly lower than at the baseline (p = 0.014). For the energy ratio characteristics of the spectrum, there was an opposite response in the two groups that p6 was significantly reduced and elevated in the LC of controls and in the RB of patients with CAD during exercise (both p < 0.05).Conclusions: Passive exercise reduces amplitude and frequency characteristics of carotid arteries, while there was an opposite response of energy ratio characteristics in the LC and RB arteries to passive exercise between CAD patients and controls. Additionally, energy ratio characteristics of spectrum in the brachial artery were markedly elevated in CAD patients during passive exercise. Moreover, passive exercise only reduces amplitude characteristics of LC artery in the control group.

Use of the Velocity Intensity Spectrum to Characterize Transient Data

This paper introduces and develops the Velocity Intensity Spectrum as an analytical tool for examining transient data in the frequency domain. The Velocity Intensity Spectrum is then compared with three common alternatives: the Shock Response Spectrum, the Pseudo Velocity Spectrum, and the lesser-known Shock Intensity Spectrum, upon which it is based. The various techniques are applied to an experimental data set and compared and discussed in a practical manner.

Azimuthal multiple signal classification of dispersive and aliased surface waves recorded in 3D seismic acquisition

Irregular acquisition geometry causes discontinuities in the appearance of surface wave events, and a large offset causes seismic records to appear as aliased surface waves. The conventional method of sampling data affects the accuracy of the dispersion spectrum and reduces the resolution of surface waves. At the same time, ”mode kissing” of the low-velocity layer and inhomogeneous scatterers requires a high-resolution method for calculating surface wave dispersion. This study tested the use of the multiple signal classification (MUSIC) algorithm in 3D multichannel and aliased wavefield separation. Azimuthal MUSIC is a useful method to estimate the phase velocity spectrum of aliased surface wave data, and it represent the dispersion spectra of low-velocity and inhomogeneous models. The results of this study demonstrate that mode-kissing affects dispersion imaging, and inhomogeneous scatterers change the direction of surface-wave propagation. Surface waves generated from the new propagation directions are also dispersive. The scattered surface wave has a new dispersion pattern different to that of the entire record. Diagonal loading was introduced to improve the robustness of azimuthal MUSIC, and numerical experiments demonstrate the resultant effectiveness of imaging aliasing surface waves. A phase-matched filter was applied to the results of azimuthal MUSIC, and phase iterations were unwrapped in a fast and stable manner. Aliased surface waves and body waves were separated during this process. Overall, field data demonstrate that azimuthal MUSIC and phase-matched filters can successfully separate aliased surface waves.

Verification of a Stiffness-Variable Control System with Feed-Forward Predictive Earthquake Energy Analysis

Semi-active isolation systems with controllable stiffness have been widely developed in the field of seismic mitigation. Most systems with controllable stiffness perform more robustly and effectively for far-field earthquakes than for near-fault earthquakes. Consequently, a comprehensive system that provides comparable reductions in seismic responses to both near-fault and far-field excitations is required. In this regard, a new algorithm called Feed-Forward Predictive Earthquake Energy Analysis (FPEEA) is proposed to identify the ground motion characteristics of and reduce the structural responses to earthquakes. The energy distribution of the seismic velocity spectrum is considered, and the balance between the kinetic energy and potential energy is optimized to reduce the seismic energy. To demonstrate the performance of the FPEEA algorithm, a two-degree-of-freedom structure was used as the benchmark in the numerical simulation. The peak structural responses under two near-fault and far-field earthquakes of different earthquake intensities were simulated. The isolation layer displacement was suppressed most by the FPEEA, which outperformed the other three control methods. Moreover, superior control on superstructure acceleration was also supported by the FPEEA. Experimental verification was then conducted with shaking table test, and the satisfactory performance of the FPEEA on both isolation layer displacement and superstructure acceleration was demonstrated again. In summary, the proposed FPEEA has potential for practical application to unexpected near-fault and far-field earthquakes.

Seismic activity in the focus of the Uglegorsk earthquakes, Sakhalin Island in relevance to intensive development of coal deposits

Induced seismicity is an increase in seismic activity caused by the human engineering. An example of such activity is the mineral exploration, large water reservoirs construction, exploitation of underground oil and gas storages, etc. The authors studied the seismicity in the Uglegorsky district of Sakhalin region, where the Solntsevskoye brown coal field is located, which is the most promising in the island. Its area is over 100 sq. km, and productive strata of the Verkhneduiskaya formation with a thickness of up to 600 m contains 12 coal seams, 8 of which are working. Active mining of brown coal is carried out at the Solntsevsky coal mine, and blasting operations are performed on a large scale, that, as a result, does not exclude the relation of the seismic process to technogenic seismicity. The earthquake recurrence curves for two decades beginning from 2000 to the present were constructed in the work to compare the characteristics of the seismic regime in the studied area. The difference in the slope angle of recurrence graph during the period of 2011-2020 (the period of the most active development of the Solntsevsky coal mine) from the previous decade is quite significant. The maps of spatiotemporal distribution of seismic events epicenters in the vicinity of Solntsevsky coal mine are constructed. The contraction of zones of seismic events concentration to the mining areas, first of all to the Solntsevsky coal mine, have been found. Such a combination allows us to talk about an increase in seismicity of the region during the last years and change in its character from the natural to a mixed natural and technogenic. The focal mechanisms of the largest earthquakes occurred in the Uglegorsky district have been constructed in order to prove the change in seismicity character and reasons for the earthquake occurrence in the studied area. The mechanisms of seismic events of 2020 are classified as strike-slip faults, that is not character for the most earthquakes on the territory of Sakhalin Island. The authors made an attempt to determine the regularities of the parameters of the produced blasts and earthquakes through dynamic parameters of the seismic events foci by means of studying the frequency content of earthquakes and blasts in order to determine a corner frequency from the focal velocity spectrum.

Near Surface Velocity Estimation Using GPR Data: Investigations by Numerical Simulation, and Experimental Approach with AVO Response

The velocity of near-surface materials is one of the most important for Ground-Penetrating Radar (GPR). In the study, we evaluate the options for determining the GPR velocity to measure the accuracy of velocity approximations from the acquired GPR data at an experimental site in Hangzhou, China. A vertical profile of interval velocities can be estimated from each common mid-point (CMP) gather using velocity spectrum analysis. Firstly, GPR data are acquired and analyzed using the popular method of hyperbola fitting which generated surprisingly high subsurface signal velocity estimates while, for the same profile, the Amplitude variation with offset (AVO) analysis of the GPR data (using the same hyperbola fitting method) generate a more reasonable subsurface signal velocity estimate. Several necessary processing steps are applied both for CMP and AVO analysis. Furthermore, experimental analysis is conducted on the same test site to get velocities of samples based on dielectric constant measurement during the drilling process. Synthetic velocities generated by AVO analysis are validated by the experimental velocities which confirmed the suitability of velocity interpretations.

A Superior Seismic Data Preprocessing Technique to Improve the Resolution of Surface wave Velocity Spectrums

A high-resolution surface wave velocity spectrum, also known as dispersion image, is of paramount importance for any seismic survey to accurately predict subsurface earth’s properties. The presence of diversified noise in the field acquisition and dissimilar attenuation due to mechanical and radial damping makes it challenging for different wavefield transformation algorithm to produce a detailed and precise velocity spectrum. Standard seismic data preprocessing technique like trace normalisation or bandpass filter fails to address all issues appropriately. Here we have presented a new superior preprocessing technique that can eradicate most of the shortcomings adequately. Experimental field data and published results are used to demonstrate the accuracy of the proposed method. The proposed method also found to produce superior results when compared against the popular commercially available software package Surfseis 6. Overall, the proposed method improves the quality of the velocity spectrum significantly, and it produces a sharper dispersion image even for the extremely noisy data. The work presented here enhances our ability to interpret the surface wave data precisely and help explore accurate properties of the subsurface earth.