Radial Power Spectrum Research Articles

A Practical Approach for Determining Multi-Dimensional Spatial Rainfall Scaling Relations Using High-Resolution Time–Height Doppler Data from a Single Mobile Vertical Pointing Radar

The rescaling of rainfall requires measurements of rainfall rates over many dimensions. This paper develops one approach using 10 m vertical spatial observations of the Doppler spectra of falling rain every 10 s over intervals varying from 15 up to 41 min in two different locations and in two different years using two different micro-rain radars (MRR). The transformation of the temporal domain into spatial observations uses the Taylor “frozen” turbulence hypothesis to estimate an average advection speed over an entire observation interval. Thus, when no other advection estimates are possible, this paper offers a new approach for estimating the appropriate frozen turbulence advection speed by minimizing power spectral differences between the ensemble of purely spatial radial power spectra observed at all times in the vertical and those using the ensemble of temporal spectra at all heights to yield statistically reliable scaling relations. Thus, it is likely that MRR and other vertically pointing Doppler radars may often help to obviate the need for expensive and immobile large networks of instruments in order to determine such scaling relations but not the need of those radars for surveillance.

Transformations between rotational and translational invariants formulated in reciprocal spaces

Correlation functions play an important role in the theoretical underpinnings of many disparate areas of the physical sciences: in particular, scattering theory. More recently, they have become useful in the classification of objects in areas such as computer vision and our area of cryoEM. Our primary classification scheme in the cryoEM image processing system, EMAN2, is now based on third order invariants formulated in Fourier space. This allows a factor of 8 speed up in the two classification procedures inherent in our software pipeline, because it allows for classification without the need for computationally costly alignment procedures.In this work, we address several formal and practical aspects of such multispectral invariants. We show that we can formulate such invariants in the representation in which the original signal is most compact. We explicitly construct transformations between invariants in different orientations for arbitrary order of correlation functions and dimension. We demonstrate that third order invariants distinguish 2D mirrored patterns (unlike the radial power spectrum), which is a fundamental aspects of its classification efficacy. We show the limitations of 3rd order invariants also, by giving an example of a wide family of patterns with identical (vanishing) set of 3rd order invariants. For sufficiently rich patterns, the third order invariants should distinguish typical images, textures and patterns.

Preliminary Statistical Characterizations of the Lowest Kilometer Time–Height Profiles of Rainfall Rate Using a Vertically Pointing Radar

A realistic approach for gathering high-resolution observations of the rainfall rate, R, in the vertical plane is to use data from vertically pointing Doppler radars. After accounting for the vertical air velocity and attenuation, it is possible to determine the fine, spatially resolved drop size spectra and to calculate R for further statistical analyses. The first such results in a vertical plane are reported here. Specifically, we present results using MRR-Pro Doppler radar observations at resolutions of ten meters in height over the lowest 1.28 km, as well as ten seconds in time, over four sets of observations using two different radars at different locations. Both the correlation functions and power spectra are useful for translating observations and numerical model outputs of R from one scale down to other scales that may be more appropriate for particular applications, such as flood warnings and soil erosion, for example. However, it was found in all cases that, while locally applicable radial power spectra could be calculated, because of statistical heterogeneity most of the power spectra lost all generality, and proper correlation functions could not be computed in general except for one 17-min interval. Nevertheless, these results are still useful since they can be combined to develop catalogs of power spectra over different meteorological conditions and in different climatological settings and locations. Furthermore, even with the limitations of these data, this approach is being used to gain a deeper understanding of rainfall to be reported in a forthcoming paper.

Gaussian Process Regression for foreground removal in H i Intensity Mapping experiments

ABSTRACT We apply for the first time Gaussian Process Regression (GPR) as a foreground removal technique in the context of single-dish, low redshift H i intensity mapping, and present an open-source python toolkit for doing so. We use MeerKAT and SKA1-MID-like simulations of 21 cm foregrounds (including polarization leakage), H i cosmological signal, and instrumental noise. We find that it is possible to use GPR as a foreground removal technique in this context, and that it is better suited in some cases to recover the H i power spectrum than principal component analysis (PCA), especially on small scales. GPR is especially good at recovering the radial power spectrum, outperforming PCA when considering the full bandwidth of our data. Both methods are worse at recovering the transverse power spectrum, since they rely on frequency-only covariance information. When halving our data along frequency, we find that GPR performs better in the low-frequency range, where foregrounds are brighter. It performs worse than PCA when frequency channels are missing, to emulate RFI flagging. We conclude that GPR is an excellent foreground removal option for the case of single-dish, low-redshift H i intensity mapping in the absence of missing frequency channels. Our python toolkit gpr4im and the data used in this analysis are publicly available on GitHub.

Traces of Anisotropic Quasi-Regular Structure in the SDSS Data

The aim of this study is to search for quasi-periodical structures at moderate cosmological redshifts z ≲ 0.5. We mainly use the SDSS DR7 data on the luminous red galaxies (LRGs) with redshifts 0.16 ≤ z ≤ 0.47. At first, we analyze features (peaks) in the power spectra of radial (shell-like) distributions using separate angular sectors in the sky and calculate the power spectra within each sector. As a result, we found some signs of a large-scale anisotropic quasi-periodic structure detectable through 6 sectors out of a total of 144 sectors. These sectors are distinguished by large amplitudes of dominant peaks in their radial power spectra at wavenumbers k within a narrow interval of 0.05 < k < 0.07 h Mpc−1. Then, passing from a spherical coordinate system to a Cartesian one, we found a special direction such that the total distribution of LRG projections on it contains a significant (≳5σ) quasi-periodical component. We assume that we are dealing with a signature of a quasi-regular structure with a characteristic scale 116 ± 10 h−1 Mpc. Our assumption is confirmed by a preliminary analysis of the SDSS DR12 data.

Geophysical interpretation for delineating groundwater and subsurface structure in the East of Cairo City, Egypt

This study aimed to delineate groundwater and the structural trends in the East of Cairo City. For this aim, we carried out different geophysical approaches such as gravity, magnetic, and electric methods. For the gravity and magnetic data analysis, we used filtering, Euler deconvolution, and radially power spectrum techniques. In addition, 3-D modeling was performed on the magnetic data only. The radial power spectrum technique shows that the depths of the surface anomalies corresponding to the short wavelength are 0.48 and 0.5 km. While, the depths of the surface anomalies corresponding to the long wavelength are ranging from 2.74 to 2.33 km from gravity and magnetic interpretation, respectively. The Euler deconvolution revealed that the investigation area was under the effect of several fault trends; a major NW-SE trend and NE-SW and NW-SE as minor trends for gravity data. While the fault trends are in N-S and NE-SW directions for RTP magnetic data. The 3-D modeling results show that the basement depth was fluctuating between 1.186 to 1.657 Km. The principal tectonic deformations of the investigating area are towards the E-W, N-S, and NE-SW trends. The gravity and magnetic techniques in this study revealed that different faults dissect the area of trends NE-SW matching the Gulf of Aqaba direction, NW-SE matching the Gulf of Suez, N-S matching the River Nile system, and E-W matching the Mediterranean tectonics. The geo-electrical method was used to investigate groundwater presence. Regarding the seismicity, the area can be considered moderate to highly active. Most of the area faults are active except in the area's southern part. So, this part can be considered the most suitable and safe part for construction.

Hydrological subsurface investigation using geophysical electrical and magnetic methods in and around Valliyar river basin, India

The focus of the present study is to identify potential groundwater zones using resistivity Schlumberger array and magnetic method for mapping hidden lineaments in and around the Valliyar river basin situated in the tail of Southern India. Estimation by 2-D radial power spectrum indicates that the maximum depth at which the magnetic source is present is about 700 m to 800 m. In case of shallow depth magnetic source rock, it is about 40 m to 45 m. The results of magnetic data have revealed the presence of a major magnetic lineament trending in NW to SE direction. The electrical resistivity survey in our study area gives information on sub-surface layers like the weathered zone, aquifer resistivity and aquifer thickness. The locations corresponding to ves-35, ves-40, and ves-47 have weathered and fracture layers having a thickness greater than 20 m, situated in the magnetic major lineament trend. Regarding master curves for layer analysis, H and HA type curves are generally observed in the hard rock region. The interpretation of results from the present study endorses that the coastal region of the study area has good groundwater potential.

Evaluation of geothermal potential in some parts of Bida Basin of Nigeria using Curie point depths and heat flow from spectral analysis of aeromagnetic data.

The Centroid method of Spectral Depth analysis was used to evaluate the Curie point depth (CPD), Geothermal Gradient and Heat Flow in some parts of the Bida Basin of Nigeria with a view to determining the energy potential of the area. The reduced-to-pole aeromagnetic data was divided into 16 overlapping ensembles and Fast Fourier Transformed to decompose the anomalies into their energy and wavenumber components using Oasis montaj software. The radial power spectrum was calculated for each of the grid points with the locations of the centres of the ensembles and a plot of Energy spectrum versus frequency was carried out to generate two different gradients: s<sub>1</sub> and s<sub>2</sub> representing different depth source models. These gradients were used to evaluate the average depth to the top of the deepest crustal block, Z<sub>t</sub>, depth to the centroid of the deepest crustal block, Z<sub>0</sub>, CPD, Geothermal Gradient and Heat flow. From the results obtained, the CPD varied from 2.59 to 8.23 Km while the thermal gradient and heat flow in the area revealed values ranging from 70.45 to 224.15 <sup>o</sup>CKm<sup>-1</sup> and 176.13 to 560.37mWm<sup>-2 </sup>respectively. The results of the contouring in conjunction with the CPD, geothermal gradient and the heat flow values have shown that the area has a greater energy potential in the south-eastern block of Katonkarfi, with shallow CPD and high geothermal gradient and heat flow. These results could be incorporated in the GIS and available geological, geophysical and geochemical information of the area to facilitate selection of the optimum site for energy exploration.

Propagation of Alfvén Waves in the Expanding Solar Wind with the Fast–Slow Stream Interaction

Abstract We carry out two-dimensional magnetohydrodynamic simulations of an ensemble of Alfvénic fluctuations propagating in a structured, expanding solar wind including the presence of fast and slow solar wind streams. Using an appropriate expanding box model, the simulations incorporate the effects of fast–slow stream shear and compression and rarefaction self-consistently. We investigate the radial and longitudinal evolution of the cross helicity, the total and residual energies and the power spectra of outward and inward Alfvénic fluctuations. The stream interaction is found to strongly affect the radial evolution of Alfvénic turbulence. The total energy in the Alfvén waves is depleted within the velocity shear regions, accompanied by the decrease of the normalized cross helicity. The presence of stream compression facilitates this process. Residual energy fluctuates around zero due to the correlation and de-correlation between the inward/outward waves but no net growth or decrease of the residual energy is observed. The radial power spectra of the inward/outward Alfvén waves show significant longitudinal variations. Kolmogorov-like spectra are developed only inside the fast and slow streams and when both the compression and shear are present. On the other hand, the spectra along the longitudinal direction show clear Kolmogorov-like inertial ranges in all cases.

Interface depth modelling of gravity data and altitude variations: a Bayesian neural network approach

Modelling of anomalous geological source from the gravity data is vital for understanding the crustal/sub-crustal interface depths and associated hazard assessment. Two-dimensional radial power spectra have usually been used to infer average depth of protuberant geological structures, which lack details of dimensional comprehension of lateral interfaces. Here in this study, we implement jointly scaled conjugate gradient-based Bayesian neural network (SCG-BNN) scheme with variogram modelling to carve out shallow and deeper interfaces of complex geological terrain of Eastern Indian Shield, India, using Bouguer gravity anomaly (BGA) and altitude variations data. Our “learner codes” uses the SCG-BNN optimization algorithm to build up a statistical model involving appropriate control parameters for the modelling of shallow and deeper interfaces. We have also compared the proposed SCG-BNN modelling results with the results of both conventional artificial neural networks (ANNs) schemes (e.g. conjugate gradient-based ANNs (CG-ANN) and SCG-ANN) and support vector regression (SVR) modelling to demonstrate the robustness of the underlying method. Comparative analysis suggests that the SCG-BNN model produced superior results than the results of CG-ANN, SCG-ANN and SVR models. The results based on SCG-BNN analysis and variogram modelling have identified the existence of three conspicuous fault structures, namely Malda–Kishanganj Fault, Munger–Saharsha Ridge Marginal Fault and Katihar Fault. The analyses also significantly minimize prediction error in three independent datasets (viz. training, validation and test), enhancing the precision of estimated shallow and deeper interface depths and thereby extenuating feasibility of “SCG-BNN” learner code. We, therefore, conclude that the underlying approach is robust to model various interface depths and generate precisely variation in the shallow and deeper interfaces with appropriate input data from altitude variation and BGA. The “SCG-BNN learner scheme” may potentially be used to exploit interface depths from several other complex tectonic regions.

Structural framework from gravity and magnetic data in the paleo/mesoproterozoic Araí rift-sag Basin, Central Brazil

The Araí Basin comprises a paleo/mesoproterozoic rift-sag basin inverted in a thick-skinned regime during the Brasiliano Orogeny. Its depth to basement, geometry, and lateral extension remain unknown. We have aimed to determine this information based on geophysical/geologic data to clarify its main structures and gain an evolutional understanding. Gravity and magnetic data allowed us to delineate the rift system — its major faults and adjacent postrift sedimentary structures — over its entire length. The geophysical investigation included radial power spectrum analysis and Euler deconvolution alongside the application of edge structure enhancement filters on magnetic anomaly and matched filter grids. A 2.5D forward gravity model was generated using all results, with geophysical sources at depths of 35–42, 20.9–22.6, 11–15.6, 9.68, 8–2.3, and 0.37–0.54 km, respectively, interpreted as the Mohorovičić Discontinuity, Curie Surface, Conrad Discontinuity, granitic intrusions, basement depths, and superficial faults. The main interpreted tectonic framework of the entire area showed a preferential direction in N40E, comprising structures related to the Transbrasiliano Lineament and its reactivations. The basin magnetic signature trends N50-80E, with structures generated essentially in the Brasiliano Orogeny and those related to extensional rift faults reactivations (belonging to São Jorge-Alto Paraíso-Cormari, Cavalcante-Teresina, and Teresina-Nova Roma systems). These fault systems exhibit a magnetic signature at the average depth of 6 km, converging to a single fault detected up to 21.8 km. The main rift faults are in accordance with the Euler solutions and the matched filter interpretation, confirmed by mapped alluvial fans conglomerates. The current structural framework of the basin goes back to the Brasiliano Orogeny, when its sedimentary filling was limited by crustal blocks with distinct compositional, rheologic, and magnetic characteristics. These intrinsic characteristics of each block along with the resulting kinematics were responsible for delimiting the shape and depth of the basin.

Curie point depth in the SW Caribbean using the radially averaged spectra of magnetic anomalies

We have estimated the Curie Point Depth (CPD) using the average radial power spectrum in a tectonically complex area located in the SW Caribbean basin. Data analyzed came from the World Digital Magnetic Anomaly Map, and three methods have been used to compare results and evaluate uncertainties: Centroid, Spectral Peak, and Forward Modeling. Results show a match along the three methods, suggesting that the CPD values in the area ranging between 6km and 50km. The results share the following characteristics: A) High values (>30km) are in continental regions; B) There is a trend of maximum CPD values along the SW-NE direction, starting from the Central Cordillera in Colombia to the Maracaibo Lake in Venezuela; C) There is a maximum CPD at the Sierra Nevada de Santa Marta (Colombia) as well as between Costa Rica - Nicaragua and Nicaragua - Honduras borders. The lowest CPD values (<20km) are associated with the coastal regions and offshore. We also tested results by estimating the geothermal gradient and comparing measured observations of the study area. Our results suggest at least five thermal terrains in the SW Caribbean Basin: A) The area that is comprising the Venezuela Basin, the Beata Ridge and the Colombia Basin up to longitude parallel to the Providencia Throat. B) The area that includes zones to the north of the Cocos Ridge and Panam Basin up to the trench. C) The orogenic region of the northern Andes and including areas of the Santa Marta Massif. D) The continental sector that encompasses Nicaragua, northern Costa Rica and eastern of Honduras. E) Corresponds to areas of the northern Venezuela and Colombia, NW of Colombia, the Panamanian territory and the transition zones between the Upper and Lower Nicaragua Rise.

Geophysical prospecting for iron ore deposit around Tajimi village, Lokoja, North–Central Nigeria

Abstract Ground magnetic and electrical resistivity survey were undertaken to investigate the occurrence and geometry of iron ore deposit around Tajimi village, Lokoja, North-Central Nigeria. The generated residual map of the ground-magnetic data acquired at 250 stations along 15 traverses revealed numerous prominent anomalies, mostly trending in the N-S direction. The radial power spectrum revealed the depth to magnetic sources between 6 m to 20 m. The interpreted VES data characterized the area into three subsurface layers: top soil, presumably iron ore layer and weathered/fresh basement. The result of vertical electrical sounding curves showed a sudden drop in resistivity (42-241 Ωm) over high magnetic response. The geo-electric section revealed that the study area is generally characterized with thin overburden (0.5-1.7 m) and the thickness of the second layer (presumed to be the iron ore layer) ranged between 6.2-25.1 m. The study concluded that areas of high magnetic intensity showed a sudden drop in resistivity value for the VES points, which give an indication of the presence of an electrically conductive structure presumed to be iron ore deposits.

A new reference model for 3D inversion of airborne magnetic data in hilly terrain — A case study from northern Sweden

The inherent nonuniqueness in modeling magnetic data can be partly reduced by adding prior information, either as mathematical constructs or simply as bounds on magnetization obtained from laboratory measurements. If a good prior model can be used as a reference model, then the quality of estimated models through an inverse approach can be greatly improved. But even though data on magnetic properties of rocks might exist, their distribution may often be quite irregular on local and regional scales, so that it is difficult to define representative classes of rock types suitable for constraining geophysical models of magnetization. We have developed a new way of constructing a reference model that varies only laterally and is confined to the part of the terrain that lies above the lowest topography in the area. To obtain this model, several estimated 2D magnetization distributions were constructed by data inversion as a function of the iteration number. Then, a suitable 2D model of the magnetization in the topography was chosen as a starting point for constructing a 3D reference model by modifying it with a vertical decay such that its average source depth was the same for all horizontal positions. The average source depth of the reference model was chosen to satisfy the average source depth obtained from analyzing the radial power spectrum of the area studied. Finally, the measured magnetic data were inverted in three dimensions using the given reference model. For a selected reference model, shallow structures indicated a better overall correlation with large remanent magnetizations measured on rock samples from the area. Throughout the entire model, the direction of magnetization was allowed to vary freely. We found that the Euclidean norm of the estimated model was reduced compared with the case where the magnetization direction was fixed.

Magnetic depths to basalts: extension of spectral depths method

Although spectral depth determination has played a role in magnetic interpretation for over four decades, automating the procedure has been inhibited by the need for manual intervention. This paper introduces the concept of a slope spectrum of an equivalent layer, to be used in an automated depth interpretation algorithm suitable for application to very large datasets such as the complete Northern Territory aeromagnetic grid.In order to trace the extensive basalts across the Northern Territory, profiles of spectral depths have been obtained at 5 km intervals across the NT stitched grid of total magnetic intensity (TMI). Each profile is a graph from 0 to 1000 m of the probability of a magnetic layer occurring at each depth. Automating the collection of the 50 000 profiles required the development of a formula that relates slopes along the power spectrum to depths to an equivalent magnetic layer. Model slabs were populated with a large number of randomly located dipoles and their power spectra correlated with modelled depth to provide the formula. Depth profiles are too noisy to be used singly, but when a series of depth profiles are lined up side-by-side as a transect, significant magnetic layers can be traced for large distances. Transects frequently show a second layer. The formula is quite general in its derivation and would apply to any mid-latitude area where significant magnetic bodies can be modelled as extensive layers.Because the method requires a radial power spectrum, it fails to provide signal at depths much shallower than the flight line spacing. The method is convenient for a fast first pass at depth estimation, but its horizontal resolution is rather coarse and errors can be quite large.

Estimating depth to the bottom of magnetic sources at Wikki Warm Spring region, northeastern Nigeria, using fractal distribution of sources approach

Abstract: The Wikki Warm Spring (WWS) is located on the Kerri-Kerri formation of tertiary age. This forms part of the Benue Basin, which links up with the Chad Basin in the north and extends southwest to the Anambra Basin in Nigeria. The stratigraphy of the WWS region consists of alluvium, the Kerri-Kerri formation, the Gombe formation, the Pindiga formation, the Yolde formation, the Bima formation, and basement rocks as the oldest. We estimate the depth to the bottom of magnetic sources (DBMS) in the WWS region using the fractal sources distribution approach on aeromagnetic data to identify the geothermal system of the WWS region. The adopted computational method is based on statistical methods of depth determination from the radial power spectrum assuming a fractal distribution of magnetic sources. The average estimated DBMS at the WWS source location is 10.72 ± 0.54 km. The obtained results imply an average thermal gradient of 54.11 °C km-1 and heat flow value of 135.28 mW/m2. Generally, shallow DBMS values are obtained in the northeastern region of the WWS area and these increase towards the southwestern region when regional variation patterns of estimated depths are considered. The generally shallow DBMS obtained in the study area is attributed to magmatic intrusion or diapirism in the subsurface and emphasizes the effects of large-scale tectonic events, particularly the basin-initiating event, as major influences on the thermal history. Results will contribute to decisions on where to drill boreholes for further geothermal energy exploration in the region.

Blue noise sampling with controlled aliasing

In this article we revisit the problem of blue noise sampling with a strong focus on the spectral properties of the sampling patterns. Starting from the observation that oscillations in the power spectrum of a sampling pattern can cause aliasing artifacts in the resulting images, we synthesize two new types of blue noise patterns: step blue noise with a power spectrum in the form of a step function and single-peak blue noise with a wide zero-region and no oscillations except for a single peak. We study the mathematical relationship of the radial power spectrum to a spatial statistic known as the radial distribution function to determine which power spectra can actually be realized and to construct the corresponding point sets. Finally, we show that both proposed sampling patterns effectively prevent structured aliasing at low sampling rates and perform well at high sampling rates.

Evaluation of Errors in the Measurement of Surface Roughness at High Spatial Frequency by Atomic Force Microscopy on a Thin Film

Factors such as sample deformation, which comes from the applied force, and the probe shape, which results in image dilation, lead to the errors in the measurement of roughness by atomic force microscopy (AFM). We explored the roughness errors that result from the applied imaging force, different probe materials, and the probe radius in the roughness measurements of a polysilicon film surface. Structures with high spatial frequencies, which are strongly affected by the probe shape, were separated by comparing radial power spectrum density curves. A geometrical model was established to describe the roughness–probe radius relationship, which was compared with experimental results under optimized imaging conditions. For a surface with a small correlation length WCL = 14.1 nm comparable to the radius of a commercial probe (Rt<10 nm), a probe with a 7 nm radius contributes an error of around 43.7%. To achieve a precise measurement of the roughness of such a surface, it is important to develop a suitable model that describes the roughness distribution well.

Mapping Curie temperature depth in the western United States with a fractal model for crustal magnetization

We have revisited the problem of mapping depth to the Curie temperature isotherm from magnetic anomalies in an attempt to provide a measure of crustal temperatures in the western United States. Such methods are based on the estimation of the depth to the bottom of magnetic sources, which is assumed to correspond to the temperature at which rocks lose their spontaneous magnetization. In this study, we test and apply a method based on the spectral analysis of magnetic anomalies. Early spectral analysis methods assumed that crustal magnetization is a completely uncorrelated function of position. Our method incorporates a more realistic representation where magnetization has a fractal distribution defined by three independent parameters: the depths to the top and bottom of magnetic sources and a fractal parameter related to the geology. The predictions of this model are compatible with radial power spectra obtained from aeromagnetic data in the western United States. Model parameters are mapped by estimating their value within a sliding window swept over the study area. The method works well on synthetic data sets when one of the three parameters is specified in advance. The application of this method to western United States magnetic compilations, assuming a constant fractal parameter, allowed us to detect robust long‐wavelength variations in the depth to the bottom of magnetic sources. Depending on the geologic and geophysical context, these features may result from variations in depth to the Curie temperature isotherm, depth to the mantle, depth to the base of volcanic rocks, or geologic settings that affect the value of the fractal parameter. Depth to the bottom of magnetic sources shows several features correlated with prominent heat flow anomalies. It also shows some features absent in the map of heat flow. Independent geophysical and geologic data sets are examined to determine their origin, thereby providing new insights on the thermal and geologic crustal structure of the western United States.

Regional gravity anomaly separation using wavelet transform and spectrum analysis

In this paper, we propose the separation of the regional gravity anomaly using wavelet multi-scale analysis and choose rational decomposition results based on the spectrum analysis and their depth estimation results. The isotropic, symmetrical and low-pass wavelet filter, Halo wavelet, is used for wavelet transform and regional anomaly separation. The anomaly separation method is verified by the synthetic model of combined cuboids. It has also been used for regional gravity separation and deep structure study in the Dagang area, North China. The regional anomalies are obtained from large-scale wavelet decomposition results. The average depths estimated from the radial power spectrum and the stratum density are used to establish the relationship between the separation anomaly and buried geologic units. The results from seismic data and magnetotellurics inversion are used to assist the regional anomaly interpretation. From the wavelet analysis and spectrum comparisons, the regional anomalies caused by Moho and Cenozoic basement are given for further deep structure analysis.