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The reservoir of the M oilfield in Tarim Basin is an unconventional fracture-cave carbonate rock, encompassing various reservoir types like fractured, fracture-cave, and cave, exhibiting significant spatial heterogeneity. Despite the limited pore space in fractures, they can serve as seepage pathways, complicating the connectivity between reservoirs. High-precision fracture prediction is critical for the effective development of these reservoirs. The conventional post-stack seismic attribute-based approach, however, is limited in its ability to detect small-scale fractures. To address this limitation, a novel pre-stack fracture prediction method based on azimuthal Young's modulus ellipse fitting is introduced. Offset Vector Tile (OVT) gather is utilized, providing comprehensive information on azimuth and offset. Through analyzing azimuthal anisotropies, such as travel time, amplitude, and elastic parameters, smaller-scale fractures can be detected. First, the original OVT gather data are preprocessed to enhance the signal-to-noise ratio. Subsequently, these data are partially stacked based on different azimuths and offsets. On this basis, pre-stack inversion is carried out for each azimuth to obtain the Young's modulus in each direction, and, finally, the ellipse fitting algorithm is used to obtain the orientation of the long axis of the ellipse and the ellipticity, indicating the fracture orientation and density, respectively. The fracture prediction results are consistent with the geological structural features and fault development patterns of the block, demonstrating good agreement with the imaging logging interpretations. Furthermore, the results align with the production dynamics observed in the production wells within the block. This alignment confirms the high accuracy of the method and underscores its significance in providing a robust foundation for reservoir connectivity studies and well deployment decisions in this region. [ABSTRACT FROM AUTHOR]

Under global warming, the summer surface air temperature (SAT) change signal in the northern mid‐latitudes is generally the most significant, while the SAT change in North China (NC) shows distinct local characteristics. Using simulations from the Coupled Model Intercomparison Project Phase 6 and observation from Berkeley Earth Surface Temperature, this study reveals an unusually weak signal of summer SAT change in NC since the 1960s. This uniquely weak signal can be attributed to the small net contribution of external forcings, mainly from anthropogenic greenhouse gases (GHG) and aerosols (AA). Compared to other land regions in the same latitudinal band, the GHG‐induced warming was weaker and AA‐induced cooling was stronger in NC, resulting in the weakest SAT change signal and thus the lowest signal‐to‐noise ratio. This weaker GHG‐induced warming plays a more important role in the SAT change difference between NC and other land regions in the same latitudinal zone. Under different emission scenarios in the future, the signal‐to‐noise ratio in NC will become as large as those in the other land regions in the same latitudinal band and the northern hemisphere, which is partly due to the smaller relative differences in the SAT change signal between NC and the other two regions. The projections of SAT change indicate that climate change in NC will probably become more violent and vulnerable. [ABSTRACT FROM AUTHOR]

A multi‐slit very small angle neutron scattering (MS‐VSANS) instrument has been finally accepted at the China Spallation Neutron Source (CSNS). It is the first spallation neutron source based VSANS instrument. MS‐VSANS has a good signal‐to‐noise ratio and can cover a wide scattering vector magnitude range from 0.00028 to 1.4 Å−1. In its primary flight path, a combined curved multichannel beam bender and sections of rotary exchange drums are installed to minimize the background downstream of the instrument. An exchangeable multi‐slit beam focusing system is integrated into the primary flight path, enabling access to a minimum scattering vector magnitude of 0.00028 Å−1. MS‐VSANS has three modes, namely conventional SANS, polarizing SANS and VSANS modes. In the SANS mode, three motorized high‐efficiency 3He tube detectors inside the detector tank cover scattering angles from 0.12 to 35° simultaneously. In the polarizing SANS mode, a double‐V cavity provides highly polarized neutrons and a high‐efficiency 3He polarization analyser allows full polarization analysis. In the VSANS mode, an innovative high‐resolution gas electron multiplier detector covers scattering angles from 0.016 to 0.447°. The absolute scattering intensities of a selection of standard samples are obtained using the direct‐beam technique; the effectiveness of this method is verified by testing the standard samples and comparing the results with those from a benchmark instrument. The MS‐VSANS instrument is designed to be flexible and versatile and all the design goals have been achieved. [ABSTRACT FROM AUTHOR]

In some unconventional gas enrichment regions, the topography undergoes extreme undulation, and the surface lithology is considerably altered. This, in turn, has a great impact on seismic exploration. The main difficulty in the acquisition stage has been the selection of effective resonant frequencies and receiving parameters. This study applies a method blending micro logging and refraction to achieve a fine examination of shallow surface structures, as well as to determine a sufficient excitement layer according to the micro logging data, and thus ensure that the grain on the base or consolidated clay layer is generated. The results of this study show that the excitement and reception parameters selected can suppress interference waves, such as surface waves and multiple reflections, and in turn resolve the problem of the low signal-to-noise ratio (SNR) in the mountainous areas of the region, particularly low-noise areas. [ABSTRACT FROM AUTHOR]

Geographic information system-based mineral prospectivity mapping (MPM) aims to generate targets by combining multiple proxy layers containing geology, geochemistry, and geophysics information based on an available understanding of geological processes and translating it into critical targeting criteria. However, factors such as an imperfect geological understanding with numerous heuristic natures and intrinsic biases, the inaccuracy and sparsity of datasets, and multiple selections of predictive methods adversely affect the results of MPM and jeopardize the reliability of decision-making in exploration. Thus, a series of knowledge-driven and data-driven MPM approaches to counterbalance these disadvantages have been proposed. Uncertainty is defined as a metric of the various scales of the likelihood and consequences, which is helpful to quantitatively represent the above risks. In this paper, the uncertainty in the final three-dimensional prospectivity map is analyzed and interpreted in terms of quantification, visualization, and comparison of different predictive approaches, and a novel technology is proposed based on a (1 + ε) approximate global optimum strategy derived from the truth discovery society. It outputs the globally optimal truth (p*) as the overall mathematical expectation and a set of weights w i as the representation of reliability. Here, a previous study of the Haoyaoerhudong gold deposit, which is one of the largest black-rock-series-type gold mines in China, was reevaluated. The method demonstrated the following advantages: (i) sorted the reliability of potential models built by multiple predictive variables and different mathematical methods, (ii) provided a "best-guess-decision" prospectivity result by combining the best reliability model from w i and the signal-to-noise ratio (SNR) of the risk–return model, and (iii) provided a statistically final uncertainty model by combining p* and risk information. [ABSTRACT FROM AUTHOR]

To overcome the interference of noise on the exploration effectiveness of the controlled-source electromagnetic method (CSEM), we improved the deep learning algorithm by combining the denoising convolutional neural network (DnCNN) with the residual network (ResNet), and propose a method based on the residual denoising convolutional neural network (ResDnCNN) and shift-invariant sparse coding (SISC) for denoising CSEM data. Firstly, a sample library was constructed by adding simulated noises of different types and amplitudes to high-quality CSEM data collected. Then, the sample library was used for model training in the ResDnCNN, resulting in a network model specifically designed for denoising CSEM data. Subsequently, the trained model was employed to denoise the measured data, generating preliminary denoised data. Finally, the preliminary denoised data was processed using SISC to obtain the final denoised high-quality data. Comparative experiments with the ResNet, DnCNN, U-Net, and long short-term memory (LSTM) networks demonstrated the significant advantages of our proposed method. It effectively removed strong noise such as Gaussian, impulse, and square wave, resulting in an improvement of the signal-to-noise ratio by nearly 20 dB. Testing on CSEM data from Sichuan Province, China, showed that the apparent resistivity curves plotted using our method were smoother and more credible. [ABSTRACT FROM AUTHOR]

Climate change adaptation and relevant policy-making need reliable projections of future climate. Methods based on multi-model ensemble are generally considered as the most efficient way to achieve the goal. However, their efficiency varies and inter-comparison is a challenging task, as they use a variety of target variables, geographic regions, time periods, or model pools. Here, we construct and use a consistent framework to evaluate the performance of five ensemble-processing methods, i.e., multi-model ensemble mean (MME), rank-based weighting (RANK), reliability ensemble averaging (REA), climate model weighting by independence and performance (ClimWIP), and Bayesian model averaging (BMA). We investigate the annual mean temperature (Tav) and total precipitation (Prcptot) changes (relative to 1995–2014) over China and its seven subregions at 1.5 and 2 °C warming levels (relative to pre-industrial). All ensemble-processing methods perform better than MME, and achieve generally consistent results in terms of median values. But they show different results in terms of inter-model spread, served as a measure of uncertainty, and signal-to-noise ratio (SNR). ClimWIP is the most optimal method with its good performance in simulating current climate and in providing credible future projections. The uncertainty, measured by the range of 10th-90th percentiles, is reduced by about 30% for Tav, and 15% for Prcptot in China, with a certain variation among subregions. Based on ClimWIP, and averaged over whole China under 1.5/2 °C global warming levels, Tav increases by about 1.1/1.8 °C (relative to 1995–2014), while Prcptot increases by about 5.4%/11.2%, respectively. Reliability of projections is found dependent on investigated regions and indices. The projection for Tav is credible across all regions, as its SNR is generally larger than 2, while the SNR is lower than 1 for Prcptot over most regions under 1.5 °C warming. The largest warming is found in northeastern China, with increase of 1.3 (0.6-1.7)/2.0 (1.4-2.6) °C(ensemble's median and range of the 10th–90th percentiles) under 1.5/2 °C warming, followed by northern and northwestern China. The smallest but the most robust warming is in southwestern China, with values exceeding 0.9 (0.6–1.1)/1.5 (1.1–1.7) °C. The most robust projection and largest increase is achieved in northwestern China for Prcptot, with increase of 9.1%(-1.6–24.7%)/17.9% (0.5–36.4%) under 1.5/2 °C warming. Followed by northern China, where the increase is 6.0%(-2.6–17.8%)/11.8% (2.4–25.1%), respectively. The precipitation projection is of large uncertainty in southwestern China, even with uncertain sign of variation. For the additional half-degree warming, Tav increases more than 0.5 °C throughout China. Almost all regions witness an increase of Prcptot, with the largest increase in northwestern China. [ABSTRACT FROM AUTHOR]

External interference in ionospheric sounding seriously degrades the quality of echo signals and data; thus, it should be eliminated. This paper presents a method for suppressing interference using chaotic coding with a set of Bernoulli map sequences; compared with other commonly used coding methods such as Barker code, complementary code, and Barker-like codes, through simulation, the ambiguity function (AF) of Bernoulli map codes has better performance in terms of peak sidelobe level (PSL), integral sidelobe ratio (ISL), noise suppression (NS), and signal-to-noise ratio (SNR). Experimental tests were performed using a vertical ionosonde in Yinchuan, Ningxia Hui Autonomous Region, China, and the ionosonde was operated by alternating 40-bit Barker-like coding and 40-bit Bernoulli map coding each day to compare the effectiveness of interference suppression. The results showed that using Bernoulli map coding could remove interference and improve SNR significantly, thereby improving the data quality of the resulting ionograms. [ABSTRACT FROM AUTHOR]

On July 20, 2012, the Ms 4.9 Baoying Earthquake occurred near the junction of Baoying County and Gaoyou City in Jiangsu Province, eastern China. Due to no obvious surface rupture and limited observation of earthquake sequence, the seismogenic structure of the Ms 4.9 Baoying Earthquake is still unclear. In this study, 80 earthquakes provided by China Earthquake Network Center (CENC) are first relocated; and then the relocated 75 events with high signal-to-noise ratios as templates are utilized to scan through continuous waveform data (July 11 to August 31, 2012) using graphics processing unit-based match and locate (GPU-M&L) technique. Then the DeepDenoiser, a deep-learning-based noise reduction technique, is used to further confirm some newly detected events; and the double-difference relocation (HypoDD) algorithm is used to relocate the earthquakes. We detect and relocate more than twice as many events as the CENC routine catalog, which includes 15 fore-shocks and 230 aftershocks. The results show that the foreshocks are mainly distributed in the NW direction along the extended SE section of the blind Xiagonghe fault (XF), which is orthogonal to the strike of the seismogenic fault of the Ms 4.9 Baoying Earthquake (Yangchacang-Sangshutou fault, named YSF). Most of the aftershocks are generally distributed along the NNE-trending YSF and illuminate a steeply dipping plane. This study reveals detailed spatiotemporal evolution of the earthquake sequence and suggests that the buried XF extends southeastward and cuts through the NNE-trending seismogenic YSF. [ABSTRACT FROM AUTHOR]

To enrich the understanding of the dynamic evolution of the water resources in North China, terrestrial water storage anomalies (TWSA) from January 2003 to June 2017 are derived using the new GRACE time-variable gravity field model Tongji-GraceCom. Additionally, the spatiotemporal characteristics of terrestrial water fluxes (TWF) at multiple time scales are analyzed based on the water budget theory in conjunction with hydrometeorological and statistical data. The results show that the quality of the Tongji-GraceCom model is superior to the state-of-art spherical harmonic models (CSR RL06 and JPL RL06), with the signal-to-noise ratio improving by 10–16%. After correcting the leakage errors with a reliable correction method, the inferred TWSA in North China presents a significant downward trend, amounting to −1.61 ± 0.05 cm/yr, with the most serious TWSA depletion mainly clustering in the south-central area. The TWFs derived from GRACE and from hydrometeorological elements are in good agreement and both exhibit significant seasonal fluctuations induced by tracking the periodic movements of meteorological factors. However, unlike precipitation which manifests in an increasing trend, both TWFs reflect the obvious decreasing trends, indicating that North China is suffering from severe water deficits, which are mainly attributed to the enhanced evaporation and extensive groundwater pumping for agricultural irrigation. [ABSTRACT FROM AUTHOR]

Objectives: On July 31, 2020, China's BeiDou-3 satellite navigation system (BDS-3), which operates independently, has been fully completed and officially opened for service. The signal system of BDS-3 has been redesigned to provide public service signals of five frequencies: B1I, B3I, B1C, B2a and B2b. Methods: Based on the observations of international global navigation system monitoring and assessment service and multi-GNSS experiment (MGEX) tracking stations, this paper analyzes the characteristics of pseudoranges multipath error, signal to noise ratio, geometry-free ionosphere-free phase(GFIFP) combined observations of the new signal system, as well as the precise orbit determination (POD) performance evaluation of BDS-3 satellites. Results and Conclusions: The results show that the multipath noise level of BDS-3 satellites signal is better than that of BeiDou-2 navigation satellite system satellites, and there is no systematic deviation related to altitude angle, B1C is more significantly affected by multipath and noise. The GFIFP sequences of different signal combinations of BDS-3 satellites show periodic systematic error related to satellite, and the peak value is about 2 cm. For BDS-3 satellites, the one-step POD method is used. The two frequencies ionospheric free combination of B1I & B3I and B1C & B2a is adopted respectively. The orbit boundary discontinuity and satellite laser ranging carried out an orbit accuracy check, and the results show that when the number of available observations is less than B1I & B3I, the orbit accuracy of B1C & B2a is equivalent to that of B1I & B3I, and the radial internal coincidence accuracy is 6.1 cm and 6.6 cm respectively. [ABSTRACT FROM AUTHOR]

In this study, the quantitative precipitation estimation (QPE) capability of three X-band dual-polarization phased array radars (PAR) in Guangzhou, South China, was demonstrated, with an S-band operational dual-polarization radar as the benchmark. Rainfall rate (R) estimators based on the specific differential phase (KDP) for summer precipitation for both X-band and S-band radars were derived from the raindrop size distributions (DSDs) observed by a 2-dimensional video disdrometer (2DVD) in South China. Rainfall estimates from the radars were evaluated with gauge observations in three events, including pre-summer rainfall, typhoon precipitation, and local severe convective precipitation. Observational results showed that radar echoes from the X-band PARs suffered much more severely from attenuation than those from the S-band radar. Compared to S-band observations, the X-band echoes can disappear when the signal-to-noise ratio drops to a certain level due to severe attenuation, resulting in different estimated rainfall areas for X- and S-band radars. The attenuation corrected by KDP had good consistency with S-band observations, but the accuracy of attenuation correction was affected by DSD uncertainty and may vary in different types of precipitation. The QPE results demonstrated that the R(KDP) estimator produced better rainfall accumulations from the X-band PAR observations compared to the S-band observations. For both the X-band and S-band radars, the estimates of hourly accumulated rainfall became more accurate in heavier rainfall, due to the decreases of both the DSD uncertainty and the impact of measurement errors. In the heavy precipitation area, the estimation accuracy of the X-band radar was high, and the overestimation of the S-band radar was obvious. Through the analysis of the ZH-ZDR distribution in the three weather events, it was found that the X-band PAR with the capability of high spatiotemporal observations can capture minute-level changes in the microphysical characteristics, which help improve the estimation accuracy of ground rainfall. [ABSTRACT FROM AUTHOR]

Aeromagnetic gradient data have higher horizontal resolution on shallow sources, a magnetic anomaly that can better reflect the features of deeper sources. Therefore, we used a joint survey of aeromagnetic and gradient data to obtain the distribution of sources with different depths. In this paper, we propose an intersection constraint weighting (ICW) method based on aeromagnetic and gradient data for original and gradient anomalies with inconsistent high-low variation characteristics. The ICW method can effectively improve the resolution of inversion results and can more accurately obtain the distribution of magnetic bodies via cross-gradient by gradually adding a gradient component and applying a normalized property weighting function. Our theoretical model tests indicate that the distribution of the recovered magnetic susceptibility model of the ICW method was similar to that of the true model. In addition, the anomaly containing noise with different signal-to-noise ratios verified that the ICW method had a stronger anti-noise ability than other methods. We also inverted real data in the Zhurihe area of the Inner Mongolia Autonomous Region in northern China. The inversion result showed that the main trend of high magnetic bodies was in the northeast direction, that the shallowest depth of high magnetic bodies was 100 m, and that the greatest depth was 960 m. [ABSTRACT FROM AUTHOR]

Receiver function (RF) analysis is an indispensable method that is widely utilized to image the deep structure of the crust and upper mantle. Although the P -wave receiver function (PRF) has the advantages of a higher signal-to-noise ratio and higher resolution than S -wave receiver function, the information about P -to- S converted (Ps) phases from velocity discontinuities of the crust and upper mantle is usually obstructed by multiples from shallower crustal interfaces. Sometimes it is difficult to identify useful information about lithospheric discontinuities. In this paper, we propose a method for suppressing multiples and isolating the Ps phases of RFs. This task is accomplished by exploiting the differences in arrival times resulting from the slowness between the conversion and the multiples that occur at the same interface in the PRFs and by separating them in the Radon domain, which enables removal of crustal and sedimentary multiples. This method can effectively remove multiples and isolate the useful signals of Ps phases contained in the PRFs. We test the method on synthetic PRFs and demonstrate that crustal multiples can be effectively eliminated or suppressed and that the Ps phase of lithospheric discontinuities can be coherently traced. Next, we apply the method to real PRF data collected from the seismic station of the China Array seismic experiment (Phase II and Phase III) in the Ordos block and its adjacent area, and successfully obtain an improved common conversion point stacking image of lithospheric discontinuity structures in the depth domain, particularly for detecting the lithosphere–asthenosphere boundary. [ABSTRACT FROM AUTHOR]

GNSS radio occultation (RO) plays an important role in ionospheric electron density inversion and sounding of sporadic E layers. As China's first electromagnetic satellite, China Seismo-Electromagnetic Satellite (CSES) has collected the RO data from both GPS and BDS-2 satellites since March 2018. In this study, we extracted the signal-to-noise ratio (SNR) data of CSES and calculated the standard deviation of normalized SNR. A new criterion is developed to determine the Es events, that is, when the mean value of the absolute value of the difference between the normalized SNR is greater than 3 times the standard deviation. The statistics show that sporadic E layers have strong seasonal variations with highest occurrence rates in summer season at middle latitudes. It is also found that the occurrence height of Es is mainly located at 90–110 km, and the period 14:00–20:00 LT is the high incidence period of Es. In addition, the geometric altitudes of a sporadic E layer detected in CSES radio occultation profiles and the virtual heights of a sporadic E layer obtained by the Wuhan Zuoling station (ZLT) ionosonde show three different space-time matching criteria. Our results reveal that there is a good agreement between both parameters which is reflected in the significant correlation. [ABSTRACT FROM AUTHOR]

The electron spin resonance (ESR) method has been successfully applied to dating hydrothermal barite; however, there have been few studies of modern continental barite, such as that generated by fault movement or in sedimentary deposits. To better understand the geological processes involved in the formation of continental barite, its thermal characteristics and age firstly need to be defined. In this study, one fault barite sample and two sedimentary barite samples were obtained from continental sites in China for ESR signal thermal stability experiments. Microwave-power experiments indicate that 0.5 mW produces the maximum ESR signal intensity and the highest signal-to-noise ratio. Stepwise-heating results reveal that ESR signal intensities remain stable below 100 °C then show an increasing trend that peaks at ∼180 °C, following which they decrease rapidly between 180 and 320 °C and disappear at ∼380 °C. Isothermal heating results show that ESR signal intensities remain stable within a temperature range of 100–200 °C but show a decreasing trend for temperatures of 240–320 °C. These results indicate that the thermal decay of the ESR signal intensity for the three studied continental barites follows second-order decay kinetics. The thermal lifetimes calculated for the three samples are 6.3 × 108, 7.5 × 107, and 8.7 × 106 a, respectively. Thus, barite ESR dating can be used to date related geological events since early Pleistocene. • 0.5 mW gives the max measured ESR signal intensity. • ESR signal disappear at ∼380 °C for 15 min. • Thermal decay follows second-order decay kinetics. • Date modern continental barite for more than 15,000 ka. [ABSTRACT FROM AUTHOR]

China has taken the lead in exploring the construction of large-scale public cultural parks. By restoring the relics of the Long March, we can further promote the spirit of the Red Army, inherit the red gene, contribute to national pride, and contribute to local economic development. A new community will be built with culture, education, tourism, and leisure as the main contents. System aberration, human interference, motion, and system noise can all lead to image quality degradation. Wavelet enhancement technique is to use Wiener filtering in the Fourier region, using other properties of wavelets for filtering. The wavelet analysis method was used to recover the images within the Long March National Park, and the corresponding processing was carried out to achieve a better recovery effect. Through comparative tests, it was found that the algorithm had an average reduction of 223 iterations and an average increase of 11.264 in signal-to-noise ratio when iterating, and the number of iterations was also greatly improved. The higher the wavelet coefficients are, the higher the noise is. This paper introduces a new wavelet transform-based image restoration technique for national parks. [ABSTRACT FROM AUTHOR]

Continuous Global Positioning Systems (GPS) coordinate time series with a high spatiotemporal resolution, and provide a great opportunity to study their noise models and common mode errors (CMEs), thus making it possible to detect and analyse spatiotemporal characteristics of tectonic and non-tectonic signals in time series, and further to estimate a reliable and accurate velocity field of crustal movement in a region by removing CMEs and using the optimal noise model. In this paper, we used GPS coordinate time series from the Crustal Movement Observation Network of China (CMONOC) with an approximate decadal period from 2010 to 2020, to construct optimal noise models by fitting them with several noise combinations according to the Akaike information criterion (AIC). We further adopted independent component analysis (ICA) to extract CMEs and analysed their spatiotemporal characteristics, and then evaluated their effects on noise models and velocity uncertainties, and finally estimated a decennial velocity field of crustal movement with a higher signal-to-noise ratio (SNR) by applying the CME filtering and considering the optimal noise model in Mainland China. Our results show that optimal noise models are dominated by white noise (WN) plus flicker noise (FN) for both east and north components, and WN plus power law noise (PN) with spectral index close to −1 for up component, respectively. ICA filtering can remove the highly spatially correlated CMEs and decrease the mean RMSEs of the residual time series by about 40–60%, providing a more accurate velocity field with a higher SNR in Mainland China, accordingly. [ABSTRACT FROM AUTHOR]

Controlled source audio magnetotelluric (CSAMT) has good depth penetration and high data quality. However, the Cagniard apparent resistivity calculated in the near- field zone and transition zone is distorted, and collecting electric field components in some specific landscapes requires a high cost, such as desert, permafrost, and water areas. The magnetic field y-component (Hy) is not restricted by bad electrode grounding conditions, and the signal level is greater than that of the magnetic field z-component (Hz), which can be used to obtain the ground resistivity. A simple algorithm was used to calculate the apparent resistivity defined by Hy, and the response characteristics and measurement range were analysed by model calculation. The results show that the Hy full-field apparent resistivity has no obvious distortion. This method is applied to geological surveys in the Xiong'an New Area, China. The results indicate that the detection depth of the Hy full-field apparent resistivity is better than that of electric field x-component (Ex), and the signal-to-noise ratio is better than that of Hz. Moreover, the 1D and 2D inversion results are in good agreement with the known geological conditions. This method can extend the observational conditions and range of CSAMT. [ABSTRACT FROM AUTHOR]

Robust detection of patterns at low signal-to-noise ratios (SNRs) is a fundamental challenge of analysing high-frequency data, particularly in water quality monitoring. When conducting water quality data analysis, an indispensable step is to clean the data noise. In this paper, a new method named ADAPTIVE-EWT-MFE, based on empirical wavelet transform (EWT) and multiscale fuzzy entropy (MFE), is proposed to implement time series data cleaning. EWT-MFE can decompose the spectrum into different intrinsic mode functions (IMFs). According to different characteristics of the IMFs, an adaptive and adjustable parameter based on MFE, which reflects the intrinsic characteristics, is introduced into the threshold function to improve the performance of noise cleaning. Finally, this hybrid data cleaning method is designed to filter the high-frequency noise on the IMFs. Results show that our proposed method not only has great potential to improve the noise-cleaning performance but also does not distort noise-free data. [ABSTRACT FROM AUTHOR]

Traditional magnetotelluric (MT) impedance estimations are based on Fourier theory and carried out in the frequency domain, which has a strict stationarity requirement for the analyzed signal. However, the stationarity assumption cannot be satisfied when the data possess a low signal-to-noise ratio (SNR) and/or a short observation period. These shortcomings can cause significant errors in the MT impedance estimations, especially in the low-to-medium frequency bands. The alternating direction method of multipliers (ADMMs) and polarization analysis of the electromagnetic signal can be attached to the time-domain MT impedance estimation to address these shortcomings. This time-domain technique calculates the impedance in the time domain without Fourier transformation, and the ADMM and polarization analysis are applied to further improve the stability and convergence of the impedance estimation. Here, we present an ADMM-based method for MT impedance estimations (ADMM-MT). Various noise are added to a noise-free MT signal to test the performance of ADMM-MT. The results show that ADMM-MT yields impedance estimates with relative recovery errors below 0.2, even when the SNR of the data is 0 dB and the observation period is 60 min. We then apply ADMM-MT to field data in Inner Mongolia, China. The results indicate that the apparent resistivity curves obtained by ADMM-MT using a short time series are smooth over the 0.001–1-Hz band, which is consistent with the remote reference (RR) processing results obtained using a long time series. In contrast, the curves obtained by traditional robust estimation method are strongly biased. [ABSTRACT FROM AUTHOR]

Surface monitoring of microseismic monitoring events is generally challenging because microseismic data have a low signal-to-noise ratio (SNR). Traditional event-detection methods struggle to detect weak microseismic events. A variance fractal dimension (VFD) method for automatic microseismic event detection via multitrace energy envelope stacking (MTEES) is introduced. In the first stage, we propose a processing microseismic data method based on the MTEES method. It increases the energy of weak microseismic data to avoid missed and false microseismic detection. Furthermore, it can greatly improve computational efficiency to satisfy real-time processing requirements. In the second stage, the VFD algorithm is applied to the data processed in the first stage to improve the feasibility and validity of microseismic event detection. A simulation test with perforation data shows the reliability of the new method in the automatic detection of microseismic events. In addition, we demonstrate that analogous results can be obtained when perforation data are not available by introducing a novel approach based on synthetic correction time. The new approach is particularly useful when perforation data are not recorded, representing a significant advantage over previous approaches. We describe the application of the novel method to a real microseismic data example from monitoring hydraulic fracture treatments in Shanxi Province, China, with and without perforation data. The new method yields improvement in microseismic event detection for microseismic monitoring. Therefore, we find a wide range of applications requiring analysis of microseismic data. [ABSTRACT FROM AUTHOR]

As a hyperspectral imager aboard the orbiter "HX-1" of China's first Mars mission, the Mars Mineralogical Spectrometer (MMS) is designed with hyperspectral and multispectral operation modes to survey the mineral types and their distribution on the surface of Mars, and to study the overall chemical composition and evolution history of Mars. The multispectral modes of MMS are different from hyperspectral modes on the bands selection, spatial and spectral resolution, Signal-to-Noise Ratio (SNR) etc. So the spectral detection capability of each mode of MMS is also different. The ground validation experiment of MMS is conducted to evaluate the hyperspectral and multispectral data quality and detection capabilities. The main conclusions include: (1) The measured hyperspectra of typical mineral samples obtained by MMS agree well with the data acquired by the Standard Comparison Spectrometers (SCS) under the same measurement conditions, and the spectral uncertainty between MMS and SCS is less than 7% in the key spectral ranges (0.7 ∼ 2.2 μm ). For some typical minerals, the absorption band positions deviation between MMS and SCS are within 0.69 ∼ 14.86 nm , which are within the spectral resolution limits of MMS. (2) The six sets of band combinations designed for MMS multispectral modes are slightly superior to CRISM's multispectral mode in terms of spectral resolutions and bands selection, the water-containing minerals will be more accurately distinguished and identified, such as montmorillonite and kaolinite. Besides, the SNR of each multispectral mode is greater than 400 in the 500–2600 nm spectral range, which meets the requirements for the subtle spectral characteristics of water-containing minerals. (3) Benefiting from the MMS ground validation experiment and the experience of the OMEGA and CRISM, it is recommended that MMS first adopt the spatial continuous 52-sample or 104-sample (spatial resolution is about 0.53 ∼ 1.06 km ) multispectral operation mode for typical minerals global mapping and finding target areas of interest. Then the 208-sample multispectral mode (spatial resolution is about ∼ 265 m ) or 26-sample hyperspectral mode can be used to survey target areas of interest for the subtle mineral types characteristics and distribution. At last, 26-sample hyperspectral mode could be used to monitor the atmospheric composition of Mars by limb observations. [ABSTRACT FROM AUTHOR]

Micro‐seismic monitoring is one of the most critical technologies that guide hydraulic fracturing in hot dry rock resource development. Micro‐seismic monitoring requires high precision detection of micro‐seismic events with a low signal‐to‐noise ratio. Because of this requirement, we propose a recurrent neural network model named gated recurrent unit and support vector machine (GRU_SVM). The proposed model ensures high accuracy while reducing the parameter number and hardware requirement in the training process. Since micro‐seismic events in hot dry rock produce large wave amplitudes and strong vibrations, it is difficult to reverse the onset of each individual event. In this study, we utilize a support vector machine (SVM) as a classifier to improve the micro‐seismic event detection accuracy. To validate the methodology, we compare the simulation results of the short‐term‐average to the long‐term‐average (STA/LTA) method with GRU_SVM method by using hot dry rock micro‐seismic event data in Qinghai Province, China. Our proposed method has an accuracy of about 95% for identifying micro‐seismic events with low signal‐to‐noise ratios. By ignoring smaller micro‐seismic events, the detection procedure can be processed more efficiently, which is able to provide a real‐time observation on the types of hydraulic fracturing in the reservoirs. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the vibration signals of the hydrogenerator unit are nonlinear and nonstationary and it is difficult to extract the signal features due to strong background noise and complex electromagnetic interference, this paper proposes a dual noise reduction method based on intrinsic time-scale decomposition (ITD) and permutation entropy (PE) combined with singular value decomposition (SVD). Firstly, the vibration signals are decomposed by ITD to obtain a series of PRC components, and the permutation entropy of each component is calculated. Secondly, according to the set permutation entropy threshold, the PRC components are selected for reconstruction to achieve a noise reduction effect. On this basis, SVD is carried out, and the appropriate reconstruction order is selected according to the position of the singular value difference spectrum mutation point for reconstruction, so as to achieve the secondary noise reduction effect. The proposed method is compared with the LMD-PE-SVD and EMD-PE-SVD dual noise reduction method by simulation, taking the correlation coefficient and signal-to-noise ratio to evaluate the noise reduction performance and finding that the ITD-PE-SVD noise reduction has good noise reduction and pulse effect. Furthermore, this method is applied to the analysis of the upper guide swing data in the X-direction and Y-direction of a unit in a hydropower station in China, and it is found that this method can effectively reduce noise and accurately extract signal features, thus determining the vibration cause, which is helpful to improve the turbine fault recognition rate. [ABSTRACT FROM AUTHOR]

In seismic data processing, low-frequency random noise with non-Gaussian and non-stationary characteristics heavily contaminates the reflected signals in Tarim area, which brings great difficulties in interpretation of seismic records in northwest China. To achieve more satisfied resolution, more greater fidelity, together with much higher increased signal-to-noise ratio (SNR), this paper proposes a SNR enhancement method based on the combination of variational mode decomposition (VMD) and Semi-soft Go Decomposition (Semi-Soft GoDec), named VMD-SSGoDec, which can realize the simplification of low-rank extraction in time–frequency representation (TFR) domain. Firstly, each trace of the rough seismic record is decomposed into several modes to reconstruct a component matrix by VMD. Due to the semi-low rank or approximate low-rank character of the desert low-frequency noise component matrix in TFR domain, secondly, we apply the Semi-soft GoDec, a low-rank matrix estimation to extract the low-frequency random noise components from the VMD results obtained in the first step. Repeating the above single-trace procedure to each trace rather than decomposing the entire record but use low-rank estimation once can lead to a more reduced dimension of the component matrix, and thus simplify the low-rank selection in Semi-soft GoDec. Finally, with the extracted random noise results in the second step, we can obtain the denoised record by making a difference with the original input. The proposed algorithm is tested by both synthetic record and field desert seismic data. Experimental results show outstanding advantages in low-frequency noise attenuation comparing with those of f-x deconvolution and SSWT-OptShrink. Both low-frequency random noise and surface waves are almost thoroughly attenuated by the proposed method, while the reflected signals are left nearly intact, revealing a significant enhancement in SNR. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is difficult to extract the characteristics of the draft tube pressure fluctuation signal under the background of strong noise, this study proposes a dual noise reduction method based on adaptive local iterative filtering (ALIF) and singular value decomposition (SVD). First, perform ALIF decomposition of the signal to be decomposed to obtain a series of IMF components, calculate the sample entropy of each component, select some IMF components to reconstruct according to the set sample entropy threshold, and then perform SVD decomposition on the reconstructed signal, and according to the location of the singular value difference spectrum mutation point, the appropriate number of reconstructions is selected for reconstruction, so as to achieve the double noise reduction effect. The ALIF-SVD dual noise reduction method proposed in this study is compared with the single ALIF, EMD, and EMD-SVD dual noise reduction method through simulation, and the correlation coefficient, signal-to-noise ratio, and mean square error are used to evaluate the noise reduction. It is found that the ALIF-SVD dual noise reduction method avoids the phenomenon of modal aliasing in the decomposition process, effectively removes the noise, and can retain the useful information of the original signal, and the noise reduction effect is better. A unit of a hydropower station in China is further selected as the research object, and its draft tube pressure fluctuation data were analyzed for noise reduction. It was found that this method can accurately extract the signal characteristics under strong noise background, so as to determine the type of pressure fluctuation of the unit, which is helpful to improve the fault recognition rate of hydraulic turbines. And it provides some technical support for the safe and stable operation of hydropower units and the promotion of condition-based maintenance strategy and improves the intelligent level of hydropower station operation management. [ABSTRACT FROM AUTHOR]

Low-count PET is an efficient way to reduce radiation exposure and acquisition time, but the reconstructed images often suffer from low signal-to-noise ratio (SNR), thus affecting diagnosis and other downstream tasks. Recent advances in deep learning have shown great potential in improving low-count PET image quality, but acquiring a large, centralized, and diverse dataset from multiple institutions for training a robust model is difficult due to privacy and security concerns of patient data. Moreover, low-count PET data at different institutions may have different data distribution, thus requiring personalized models. While previous federated learning (FL) algorithms enable multi-institution collaborative training without the need of aggregating local data, addressing the large domain shift in the application of multi-institutional low-count PET denoising remains a challenge and is still highly under-explored. In this work, we propose FedFTN, a personalized federated learning strategy that addresses these challenges. FedFTN uses a local deep feature transformation network (FTN) to modulate the feature outputs of a globally shared denoising network, enabling personalized low-count PET denoising for each institution. During the federated learning process, only the denoising network's weights are communicated and aggregated, while the FTN remains at the local institutions for feature transformation. We evaluated our method using a large-scale dataset of multi-institutional low-count PET imaging data from three medical centers located across three continents, and showed that FedFTN provides high-quality low-count PET images, outperforming previous baseline FL reconstruction methods across all low-count levels at all three institutions. • We propose a novel personalized federated learning framework for low-count PET denoising. • We collected large-scale multi-institutional low-count PET data across the USA, China, and Europe. • We conducted the first real-world study on federated learning for low-count PET imaging. • We demonstrated that FedFTN can provide high-quality low-count PET across sites and low-count settings. [ABSTRACT FROM AUTHOR]

Removing motion blur has been an important issue in computer vision literature. Motion blur is caused by the relative motion between the camera and the photographed object. However, in recent years, some achievements have been made in the research of image deblurring by using deep learning algorithms. In this paper, an enhanced adversarial network model is proposed. The proposed model can use the weight of feature channel to generate sharp image and eliminate draughtboard artefacts. In addition, the mixed loss function enables the network to output high-quality image. The proposed approach is tested using GOPRO datasets and Lai datasets. In the GOPRO datasets, the peak signal-to-noise ratio of the proposed approach is up to 28.674, and DeblurGAN is 27.454. And the structural similarity measure can be achieved up to 0.969, and DeblurGAN is 0.939. Furthermore, the images were obtained from China's Chang'e 3 Lander to test the new algorithm. Due to the elimination of the chessboard effect, the deblurred image has a better visual appearance. The proposed method achieved higher performance and efficiency in qualitative and quantitative aspects using the benchmark dataset experiments. The results also provided various insights into the design and development of the camera pointing system, which was mounted on the Lander for capturing images of the moon and rover for Chang'e space mission. [ABSTRACT FROM AUTHOR]

New strategies and metrological characteristics with an instrumented wheelset are here discussed to obtain more precise measurement and higher signal-to-noise ratio. The paper describes the loads test program performed on new high-speed train running in China. A high-speed wheelset was instrumented on the axle and on the wheels with strain gauges and that signals were acquired by digital radio telemetry systems. The reliable and precise instrumented wheelset being developed went through a special calibration procedure that utilised a wheelset roller rig on which known load time histories were applied generating running conditions similar to those encountered in service and providing a more realistic condition to perform the calibration as result. The calibration of the measuring system was also improved by following a minimisation approach to estimate the optimal transfer function between the strain measurements and the wheel/rail contact forces. A field test was performed on new high-speed line and the measurements integrated contact loads and axle stresses results with GPS and gyroscope information. A specific program was prepared for data processing to obtain load spectra. The developed system has been verified to assure sufficient durability for continuous measurement on in-service trains and sufficient accuracy after various stand tests. [ABSTRACT FROM AUTHOR]

With the advantages of the little destruction to the deployment site and high repeatability compared with explosive sources, the controlled accurate seismic source (CASS) has many potential applications with respect to the investigation of the crustal structure and seismic wave velocities. However, the signal generated by the CASS rapidly attenuates with the increasing distance because of its poor signal-to-noise ratio (SNR). Consequently, the difficulties in identifying specific seismic phases from the CASS data limit its application and popularization. The aim of this study is to present a new method to improve the accuracy of traveltime estimation and to identify more seismic phases travelling through the crust. We adopt the global seismic phase scanning algorithms (GSPSA) combined with an optimized narrowband time-varying filter, whose central frequency corresponds to the instantaneous frequency of the linear frequency modulation (LFM) signals produced by the CASS. Using the seismic data from the 40-ton CASS in a field experiment around Xinfengjiang reservoir in southeast China, we attain the seismic phases such as Pg, Sg, PmP and SmS at epicentral distances of more than 200 km with GSPSA. To identify and verify these seismic phases information, we also calculate synthetic waveforms. The results demonstrate that the GSPSA method is an effective tool for seismic phase identification of CASS data. [ABSTRACT FROM AUTHOR]

Pomegranates are one of the economic fruits in China. The timely detection of pomegranate diseases and the corresponding preventive measures are important to increase crop yields and reduce economic losses. To tackle the issues that traditional edge detection operators usually resulted in low accuracy of the detection of pomegranate diseases and its contour, low anti-noise capability, and created false edges, this study presented an improved Prewitt operator with an adaptive threshold. Firstly, in the image pre-processing stage, the pending image was enhanced by high-frequency emphasize filter, and the high-frequency component, which represented to the details of the pomegranate sample in the image, was increased by the filter. On the contrary, the low-frequency component, which represented to the background of the pomegranate sample, was attenuated to facilitate the following image processing. Since the most original images contained the Gaussian noise, bilateral filtering was used to process the noise present in the image. The weighted average of the brightness values of adjacent pixels was used to represent the intensity of a pixel. The weighted average method was used based on Gaussian distribution. The weight calculation took into account both the Euclidean distance between the pixels and the radiation difference in the pixel range domain to better maintain edge feature information. Secondly, a fifth-order convolutional mask was proposed. The weights of the elements in the mask were set according to the properties of the Gaussian noise probability distribution to reduce the effect of noise on the algorithm. The weight of the central element of the convolutional mask was increased so that the edge information of the image had higher contrast. In terms of gradient calculation, eight direction templates were used to perform the convolutional operation of the image, then the gradient values of each direction were calculated. After that, the corresponding gradient values were obtained, and the gradient values of eight directions were combined into eight groups according to the rule of orthogonality. As a result, there was 90 degrees difference between each group of gradients. Then calculated the L2 norm of each set of gradients, and used the largest value of L2 norm as the gradient of the current pixel. It was shown that it was only necessary to calculate the convolutions in half the direction due to the convolutional results in opposite directions were inverse to each other. The gradients of the rest of the direction could be obtained by its symmetric property. The adaptive threshold was implemented through the minimum error method to decrease the probability of false detection and prune irrelevant details. The mean and variance of the target and background were calculated, meanwhile, the minimum error objective function was obtained according to the principle of the minimum error classification. The value that minimizes the objective function was taken as the optimal threshold. To demonstrate the effectiveness of the method in this paper, 607 test images were manually collected as samples in the natural environment from different angles and different illumination conditions. To further reduce the interference of light changes and suppress background noise, the pending images were converted into grayscale images. Therefore, the algorithm was tested using the converted grayscale images. The experimental results showed that the algorithm proposed in this study achieved a better definition at the edge of the lesion. Compared with the traditional edge detection operator, it achieved a higher recognition accuracy and lower running time. The peak signal to noise ratio of the obtained image was higher, and the obtained edge was complete and accurate. The algorithm proposed in this paper could quickly and accurately detect the area of pomegranate lesions, providing a fundamental reference for the future prevention of pomegranate diseases. [ABSTRACT FROM AUTHOR]

Conventional surface seismic exploration in areas with complex surfaces such as karst landforms has been faced with the problem of poor excitation and reception conditions. RVSP (reverse vertical seismic profile) seismic exploration adopts a geometry in which the sources are downhole and receivers are on the ground which can reduce the influence of complex surfaces on seismic wave propagation (to some extent). Through numerical simulations and real data analysis, it was noted that in areas with complex surfaces and large numbers of underground karst caves, seismic waves generated in shallow boreholes are easily affected by various surface and multiple waves as well as by scattering from karst bodies. Therefore, the quality of the reflected seismic data is extremely low. Also, it is difficult to improve the signal to noise ratio (SNR) with conventional noise filtering methods. However, when the source depth is increased, the quality of the reflected waves can be improved. This is exactly what the RVSP method accomplishes. Besides, for the RVSP method, due to its particular geometry, the apparent velocities of the reflected waves and most interference waves are quite different, which can help to filter most noise to further improve the SNR of the reflected signals. In this study, a 3D-RVSP exploration study using 8-hole joint acquisition was conducted in a typical karst landform. The results show that the 3D-RVSP method can obtain higher quality seismic data for complex surface conditions that have large numbers of underground karst caves. Furthermore, multi-hole joint acquisition for 3D-RVSP has higher data collection efficiency and better uniformity of underground coverage. Therefore, in this study, 38 faults were accurately revealed and at high resolution based on the 3D-RVSP imaging results. [ABSTRACT FROM AUTHOR]

As one of the major regions of carbonate rock oil–gas exploration in western China, Tazhong area of the Tarim Basin has severe environment and complex ground surface conditions, hence the signal to noise ratio (SNR) of the field seismic data is extremely low. To improve the SNR of desert seismic data is a crucial step in the following work. However, the random noise in desert seismic characterizes by non-stationary, non-gaussian, non-linear and low frequency, which are very different from the random Gaussian noise. In addition, the effective signals of desert seismic generally share the same frequency band with strong random noise. These all make some traditional denoising methods cannot suppress it well. Therefore, a new noise suppression framework based on improved PSO–SVM is proposed in this paper. First, we extract the correlation of noisy desert seismic data to form feature vector. Subsequently, the model of improved PSO–SVM was built to classify the extracted feature, thereby identifying the position of the seismic events. Finally, second-order TGV filter was applied for obtaining denoised results. We perform tests on synthetic and field desert seismic record and the denoising results show that the proposed method can effectively preserve effective signals and eliminate random noise. [ABSTRACT FROM AUTHOR]

Double-row stabilizing piles are widely used to stabilize large-scale landslides. The construction process of double-row stabilizing piles is often accompanied by constructional time delay (CTD), which is defined as the time interval between the installation of front-row and rear-row stabilizing piles. The CTD is often selected based on the designer's experience and the construction arrangement due to the lack of design guidelines for double-row stabilizing piles. In this paper, the CTD is considered as a design parameter and optimized based on the robust design concept. The signal-to-noise ratio, which is a function of the mean and standard deviation of factors of safety (FOS) of the stabilizing piles, is used as a measure of the design robustness. The FOS of the double-row stabilizing piles are computed using an analytical model that considers the CTD. A framework based on the concept of robust design is proposed for determining the most preferred CTD considering multiple objectives, including safety, cost, and design robustness. This framework is illustrated with a case study, the Hongyan landslide project, Taizhou, Zhejiang, China. Based on the outcome of this study, the most preferred CTD is obtained. [ABSTRACT FROM AUTHOR]

Projecting regional rainfall changes in a warmer climate attracts ongoing attention. However, large uncertainty still exists in multi-model projection. In this study, we introduce a bias-corrected method to correct the multi-model projection of changes in East Asian summer monsoon (EASM) rainfall based on the historical and RCP8.5 runs of 25 models from phase 5 of Coupled Model Intercomparison Project. Firstly, the total rainfall changes are separated into the thermodynamic component due to increased specific humidity and the dynamic component due to circulation changes. The thermodynamic component is corrected using the observed present-day rainfall and the increase rate of specific humidity based on the wet-get-wetter mechanism. On the other hand, the dynamic component with the circulation changes is corrected based on a "spatial emergent constraint" method, which is further validated by the perfect model approach. Together, these corrections give an integrated projection for EASM rainfall changes under global warming. Such an approach can improve the signal-to-noise ratio of projection effectively, from the original 0.73 of the multimodel mean to around 1.9. The corrected projection of EASM rainfall changes shows a pronounced increase in southern China, the northwest Pacific and a belt from northern China to northeastern China, and a weak increase in other EASM regions. [ABSTRACT FROM AUTHOR]

Urban geophysics ups the ante in the world of applied geophysics, which requires innovative thinking and seemingly off-the-wall approaches, if for no other reason than the settings. Ambient-noise-tomography (ANT) can play a pivotal role in yielding subsurfa2ce information in urban areas, which is capable of dealing with challenges related to these scenarios (e.g., human activities and low signal-to-noise ratio). In this study, the ANT was conducted to investigate the near-surface shear-velocity structure in the surrounding area of the Baotu Spring Park in downtown Jinan, Shandong Province, China. Quiet clear Rayleigh waves have been obtained by the cross-correlation, which indicates that strong human activities, such as moving vehicles and municipal engineering constructions, can produce approximately isotropic distribution of noise sources for high-frequency signals. The direct surface-wave tomographic method with period-dependent ray-tracing was used to invert all surface-wave dispersion data in the period band 0.2-1.5 s simultaneously for 3D variations of shear-velocity (Vs) structure. Our results show a good correspondence to the geological features with thinner Quaternary sediments, the geological structural characteristic of the limestone surrounded by the igneous which has the highest velocity than that of the limestone in the study area, and several concealed faults of which specific location has been detected at depth. The results demonstrate that it is possible to successfully use ANT with high-frequency signal in an urban environment provided a detailed planning and execution is implemented. [ABSTRACT FROM AUTHOR]

In this study, we report a Rayleigh and sodium lidar system, which was recently upgraded at the University of Science and Technology of China (USTC) in Hefei, China (31.5 ∘ N, 117 ∘ E). The lidar system features high temporal and vertical resolutions, a high signal-to-noise ratio (SNR) and mobility. Using the time-division and wavelength-division multiplexing methods, only one piece of photomultiplier tube is used in the optical receiver, which makes the system compact and robust. Wideband filtering and narrowband filtering are both used in the lidar system to obtain high SNR data under city lights. The lidar system was established on 24 September 2016 and has run stably for 2 years. Meteor trail events that lasted for only a few seconds were extracted from the high resolution, high SNR observational data. The sodium observational data in 2017 were fitted annually and semiannually, and the results were similar to those obtained in previous studies. The monthly average atmospheric temperature showed semiannual variations. Stratospheric aerosols were observed for two consecutive days during the observations. [ABSTRACT FROM AUTHOR]

Chinese fir (Cunninghamia lanceolata (Lamb) Hook.) in the Dagangshan region of Jiangxi Province in southern China was selected to explore the impact of climatic factors on tree ring width growth. Results showed that the signal-to-noise ratio (SNR) and mean sensitivity (MS) were large while the first order autocorrelation coefficient (FOAC) was small, and the chronology contains abundant climatic information. The tree ring width index of Chinese fir was significantly positively correlated with the precipitation in December of the previous year and June of the current year, and significantly negatively correlated with that in the current May and August. The tree ring width index was significantly positively correlated with the temperature in April and May of the current year, but significantly negatively correlated with that in July of the current year. The tree ring width index had a good change consistency with the warmth index (Wi ) and humidity index (Hi ). The response function of Chinese fir ring width analysis shows that the warmth index is the main factor affecting tree ring growth, followed by the humidity index, mean annual precipitation, and mean annual temperature. The comprehensive effect of temperature and precipitation factors have significant influence on the tree ring width growth of Chinese fr. Results can provide a scientific basis for studying the effect of climatic factors on tree growth in sub-tropical regions in China and many other parts of the world. [ABSTRACT FROM AUTHOR]

The first time of flight diffractometer at the China Spallation Neutron Source (CSNS), General Purpose Powder Diffractometer (GPPD), has entered the user program in 2018. GPPD is a flexible and versatile instrument to study the crystallographic and magnetic structures of polycrystalline materials. After more than 3 years of debugging and operation, the high performance of the diffractometer has been achieved for a good instrumental resolution 0.15% and a wide d-space detection range 0.05–50.48 Å together with the desirable signal-to-noise ratio characteristics, enabling a large number of user experiments and achievements. The typical scientific applications of GPPD demonstrate its outstanding potential for unraveling the precise structure of crystals. [ABSTRACT FROM AUTHOR]

Investigating geological structures has fundamental significance in engineering construction and the development of the urban economy. Limited by the circumstance related to human activities including the poor signal-to-noise ratio, buildings restricting accessibility, and surface conditions weakening sensor coupling, conventional geophysical methods are difficult to acquire high-precision geological structures, which is the premise and foundation of subway construction. The Passive surface waves method shows its preponderance in urban area surveys compared to conventional geophysical methods, especially in complex urbanized environments. Ambient noise caused by human activities can be considered as satisfying signals to perform surface wave dispersion energy calculation and explore shear wave velocity structure. In this study, 218 short-period seismometers were deployed as a four-line array crossing the planning subway of Line 22 in Guangzhou, Guangdong Province, south China. The spatial autocorrelation (SPAC) method, one of the passive surface-wave methods that can extract the dispersion curves from ambient noise data, is used to explore the distribution of the Guangsan Fault across the study area. The inverted velocity structure reveals that the linear array applied in the SPAC method with long-time seismic ambient noise record can retrieve reliable dispersion information to image subsurface geological structure. The three-dimensional result illustrated the distribution and characteristics of the Guangsan Fault matching well with previous geological references and revealed the Enping-Xinfeng Fault across the study area. The passive surface waves method has great potential for urban near-surface hidden fault investigation and can meet the demands of three-dimensional geological structure imaging with high precision. • The SPAC method has great potential for urban subsurface geological investigation. • Linear array in SPAC method with all azimuths data performs reliable inversion. • Near-surface faults in urban areas are detected by the passive surface waves method. [ABSTRACT FROM AUTHOR]

• Micro-logging and small refraction were conducted to determine observation system and static correction models. • The post-stack wave equation for the PR splitting finite difference was used for migration imagery. • Imaging section was converted into geological model by seismic interpretation technologies. • The favorable areas of karst fissure heat storage and exploration holes were calibrated. The seismic exploration was used to explore the potential geothermal resource and geological structure in Xian County, N China. Micro-logging was used to conduct surveys on the velocity structure near the surface, the static correction models and the observation system was determined by this method. By testing different borehole depths and different quantities of explosives, the best experimental parameters were obtained in a series of test locations and in two test sections. The surface differences were eliminated by the static correction, and an interference wave survey was conducted to improve the data signal to noise ratio (SNR). The post-stack wave equation for the PR splitting finite difference was used for migration imagery, and post-stack, underground imaging profiles were obtained. The corrected seismic signals were then interpreted, and converted into geological information. The results showed that the burial depths and morphology in each layer had been successfully obtained. The areas favorable for heat storage in karst fissures were mainly in the Jixian Formation and the Cambrian–Ordovician. Our investigation allowed us to predict and calibrate favorable locations for two geothermal energy exploration holes. [ABSTRACT FROM AUTHOR]

Mined-out areas, caves, voids and cavities usually appear as diffracted waves on ground penetrating radar (GPR) profiles. Therefore, the complete extraction of diffracted waves forms the foundation of the efficient usage of the GPR technique in geological surveys. We propose a method of enhancing GPR diffracted waves via singular value decomposition (SVD) filtering and establish an effective GPR data processing flowchart. First, the shallow and deep signal energies were controlled within a certain dynamic range by energy scaling in the traces. Next, the SVD filtering process was employed to suppress air waves and multiples with better transverse coherence and to extract GPR diffracted waves. Third, background noise was suppressed via band-pass filtering to further improve the signal-to-noise ratio (SNR) of the GPR data. Finally, fitting a diffraction time-distance hyperbola allow us to obtain a diffraction velocity. Constant velocity migration processing for the diffracted waves was based on the Kirchhoff migration technique. The feasibility and effectiveness of this GPR processing technique were verified with the discovery of geological flaws beneath the Mengshan Giant Buddha in China during a cavity survey. Our proposed flowchart efficiently extracts GPR diffracted waves and increases the data SNR. The resulting images are more readily interpreted within the local geological context. [ABSTRACT FROM AUTHOR]

Whistles emitted by Indo-Pacific humpback dolphins in Zhanjiang waters, China, were collected by using autonomous acoustic recorders. A total of 529 whistles with clear contours and signal-to-noise ratio higher than 10 dB were extracted for analysis. The fundamental frequencies and durations of analyzed whistles were in ranges of 1785–21 675 Hz and 30–1973 ms, respectively. Six tonal types were identified: constant, downsweep, upsweep, concave, convex, and sine whistles. Constant type was the most dominant tonal type, accounting for 32.51% of all whistles, followed by sine type, accounting for 19.66% of all whistles. This paper examined 17 whistle parameters, which showed significant differences among the six tonal types. Whistles without inflections, gaps, and stairs accounted for 62.6%, 80.6%, and 68.6% of all whistles, respectively. Significant intraspecific differences in all duration and frequency parameters of dolphin whistles were found between this study and the study in Malaysia. Except for start frequency, maximum frequency and the number of harmonics, all whistle parameters showed significant differences between this study and the study conducted in Sanniang Bay, China. The intraspecific differences in vocalizations for this species may be related to macro-geographic and/or environmental variations among waters, suggesting a potential geographic isolation among populations of Indo-Pacific humpback dolphins. [ABSTRACT FROM AUTHOR]

In the areas where carbonate rocks expose to the near surface, there are several intractable issues in conventional surface seismic, including (1) weak reflection energy, (2) complex wave field and (3) serious static correction. Therefore, the seismic imaging result suffers significantly. However, RVSP is able to achieve reflected data with high quality since it generates seismic waves in borehole and receives seismic waves at the surface. In order to verify the applicability of RVSP technique in complex areas, this study carried out a 3D-RVSP seismic experiment in Wulunshan coal field, southwest China. Compared with the surface seismic data, RVSP data show higher signal-to-noise ratio, wider frequency band and weaker surface wave interference. In addition, two imaging methods (conventional CDP transform stack and novel equivalent-surface conversion) were implemented for RVSP data imaging. The imaging results show that the smaller and deeper structures can be revealed better by equivalent-surface conversion method than by CDP transform stack method. Hence, this study demonstrates that RVSP is an efficient method applied in the area with complex surface condition. [ABSTRACT FROM AUTHOR]

ABSTRACT: Using daily output from 29 climate models provided by the Coupled Model Intercomparison Project Phase 5, we project signals in 12 extreme temperature indices and 12 extreme precipitation indices relative to 1986–2005 over China associated with a 2 °C global warming above pre‐industrial levels under representative concentration pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). The model output reflects the following projected changes: (1) It is robust and statistically significant that warm extremes are more frequent, more persistent, and more intense than those during the baseline period of 1986–2005, and local signals emerge from natural internal variability over most of China. In particular, southern China faces severe heat stress in summer based on warm extreme indices. (2) It is robust and statistically significant that there are fewer cold extremes in China. Most models show no significant changes in the longest duration and intensity of most cold extremes in southern China and northwest China. (3) The multi‐model median shows that more frequent and more intense wet extremes that deliver greater amounts of extreme precipitation occur in China, with a regional mean increase of 16.7–42.8 mm (8–42%) in total amount of annual wet extremes, but these changes are not significant and do not exceed natural internal variability over most of the country. Spatially, the Tibetan Plateau and northeast China have robust and significant changes in part of precipitation extremes, and some changes begin to emerge from natural internal variability at local scale. There are benefits to limiting global warming for China, including less frequent and less persistent warm extremes when comparing 1.5 °C with 2 °C of global warming and a later occurrence of significant changes in climate extremes when compared an intermediate mitigation scenario RCP4.5 with a high emission scenario RCP8.5. [ABSTRACT FROM AUTHOR]

In this paper, an independently developed device system called Surface Electromagnetic Prospecting (SEP) system was introduced through a CSAMT test at Dongguashan copper mine, east of Tonglin, Anhui province. In this area exists a strong electromagnetic interference including mineral and other human interferences, so there is a big challenge for electromagnetic exploration field work. In order to test the anti-interference ability of our system and ensure the quality of data, we applied both spectral analysis and temporal filter methods to improve the signal-to-noise ratio. After data processing, we obtained better results in our geophysical models and showed that the SEP system is able to obtain stable and reliable data in a complex and noisy environment. Consequently, the anti-interference capability of the SEP system is capable to undertake complicated exploration tasks. [ABSTRACT FROM AUTHOR]

Southern China is a favorable area for shale gas exploration and development, however the steep terrain and complex geological structures make development difficult. Using logging data, seismic data and Wide Field Electromagnetic Method (WFEM) data, this paper studies the distribution of mudstone and shale and assesses the effects of different geophysical techniques used in the Chengkou (CK) block, in the Sishang-Chengkou area, which has typical shale gas exploration conditions found in Southern China. The results indicate that while a requirement for obtaining precise, high resolution lithologic information, logging has limited value for obtaining structural information in the CK block. Logging is most useful for verifying the results of seismic and WFEM studies. Currently available seismic methods were also found to be unreliable for making layer selections and designing a fracturing plan due to the complex structure and resulting high signal-to-noise ratio (S/N). WFEM methods did provide information about strata distribution, geological structures, and fracture zones to reveal the prospect of hydrocarbons. WFEM was found to have great value for shale gas exploration and development in this geologic environment and allowed for the identification of a large volume with high gas yield potential. [ABSTRACT FROM AUTHOR]

We measured shear wave splitting from SKS data recorded by the transcontinental NECESSArray in NE China to constrain lithosphere deformation and sublithospheric flows beneath the area. We selected several hundreds of high quality SKS/SKKS waveforms from 32 teleseismic earthquakes occurring between 09/01/2009 and 08/31/2011 recorded by 125 broadband stations. These stations cover a variety of tectonic terranes, including the Songliao basin, the Changbaishan mountain range and Zhangguancai range in the east, the Great Xing'an range in the west and the Yanshan orogenic belt in the southwest. We assumed each station is underlaid by a single anisotropic layer and employed a signal-to-noise ratio (SNR) weighted multi-event stacking method to estimate the two splitting parameters (the fast polarization direction φ , and delay time, δt ) that gives the best fit to all the SKS/SKKS waveforms recorded at each station. Overall, the measured fast polarization direction lies more or less along the NW–SE direction, which significantly differs from the absolute plate motion direction, but is roughly consistent with the regional extension direction. This suggests that lithosphere deformation is likely the general cause of the observed seismic anisotropy. The most complicated anisotropic structure is observed beneath the southern Great Xing'an range and southwest Songliao basin. The observed large variations in splitting parameters and the seismic tomographic images of the area are consistent with ongoing lithospheric delamination beneath this region. [ABSTRACT FROM AUTHOR]