Cross-spectral Correlation Research Articles

A composite approach towards understanding the mechanisms and driving variables of river mouth variability: A case study of the Da Dien River mouth

ABSTRACT This research aims to present a composite approach to characterizing the intra-annual and interannual variability in inlet throat width and understanding its mechanism (how, when, and why it varies). The techniques used include remote sensing imagery analysis, spectral and cross-spectral analyses, correlation analyses, and random forest variable importance. The Da Dien River mouth (DDRM), which is located in southern Central Vietnam and experiences a strong annual signal of climate regimes, was selected as a case study to demonstrate the applicability of the approach. The results show that the narrowing/widening of the DDRM throat width is highly dynamic and variable under the significant dominant influence of wave height, tide and river flow, which seasonally and interannually vary according to the monsoon regime, El Niño/Southern Oscillation and sunspot number variations (better correlation with ENSO events). The overall throat width decreases during El Niño/the positive QBO phase and increases during La Niña periods/the negative QBO phase. The difference in river flow magnitudes is the main cause for the constriction/expansion of the DDRM throat width. The successful application of the study approach to the DDRM case study demonstrates its usefulness and ability to be applied to other case studies in tropical monsoon regions.

Sensitivity Kernels for Inferring Lorentz Stresses from Normal-mode Frequency Splittings in the Sun

Abstract Departures from standard spherically symmetric solar models, in the form of perturbations such as global and local-scale flows and structural asphericities, result in the splitting of eigenfrequencies in the observed spectrum of solar oscillations. Drawing from prevalent ideas in normal-mode-coupling theory in geophysical literature, we devise a procedure that enables the computation of sensitivity kernels for general Lorentz-stress fields in the Sun. Mode coupling due to any perturbation requires careful consideration of self- and cross coupling of multiplets. Invoking the isolated-multiplet approximation allows for limiting the treatment to purely self coupling, requiring significantly less computational resources. We identify the presence of such isolated multiplets under the effect of Lorentz stresses in the Sun. Currently, solar missions allow for precise measurements of self coupling of multiplets via “a-coefficients” and the cross-spectral correlation signal that enables the estimation of the “structure coefficients”. We demonstrate the forward problem for both self coupling (a-coefficients) and cross coupling (structure coefficients). In doing so, we plot the self-coupling kernels and estimate a-coefficients arising from a combination of deep-toroidal and surface-dipolar axisymmetric fields. We also compute the structure coefficients for an arbitrary general magnetic field (real and solenoidal) and plot the corresponding “splitting function”, a convenient way to visualize the splitting of multiplets under 3D internal perturbations. The results discussed in this paper pave the way to formally pose an inverse problem and infer solar internal magnetic fields.

Estimation of Sea Surface Current from X-Band Marine Radar Images by Cross-Spectrum Analysis

The cross-spectral correlation approach has been used to estimate the wave spectrum from optical and radar images. This work aims to improve the cross-spectral approach to derive current velocity from the X-band marine radar image sequence, and evaluate the application conditions of the method. To reduce the dependency of gray levels on range and azimuth, radar images are preprocessed by the contrast-limited adaptive histogram equalization. Two-dimensional cross-spectral coherence and phase are derived from neighboring X-band marine radar images, and the phases with large coherences are used to estimate the phase velocity and angular frequency of waves, which are first fitted with the theoretical dispersion relation by different least square models, and then the current velocity can be determined. Compared with the current velocities measured by a current meter, the root-mean-square error, correlation coefficient, bias, and relative error are 0.15 m/s. 0.88, –0.05 m/s, and 7.79% for the north-south velocity, and 0.14 m/s, 0.86, 0.06 m/s, and 10.75% for the east-west velocity in the experimental area, respectively. The preprocessing, critical coherence, and the number of images for applying the cross-spectral approach, are discussed.

The influence of low-frequency variability on tree-rings based climate reconstruction: a case study from central Italy (Roman coast).

Tree rings are among the best sources of proxy data for reconstructing past climatic records. In this study we explore for the first time what type of climatic signals can be reconstructed from stone pine ( Pinus pinea L.) based on tree-rings from central Italy (Roman coast). Samples from 112 stone pine trees from stands with different age classes were collected at two locations, Castel Fusano and Castelporziano. In determining the particular target variable for climate reconstruction we explored a wide range of climatic signals (from monthly to multiple year scale) for correlations with tree ring chronologies produced using a variety of detrending methods. We reconstructed short term (autumn-early winter) and long term (3 years precipitation) signals during the 150 years of available data using the “classical” detrending method but also methods preserving their low frequency variability (ABD and RCS) within the chronologies. By setting the best multiple year precipitation drivers at an annual scale and applying a simple percentile threshold approach, we identified the wettest and driest climatic events. The best accuracy in identifying the climatic thresholds was obtained with the ABD method, which also showed the best cross spectral correlation with a long precipitation record. Our reconstruction underpins that since ca. 1850 the Roman coast has experienced its driest conditions in terms of 2-3 year rainfall sums during the last 50 years of the 20 th Century. This finding may be used in the context of identifying the long-term natural variability of the region in relation to climate change as it is expected to affect the Mediterranean.

Coastal Monitoring Program of Bathymetry Using Video Images Technique

The objective of this research is to investigate the capabilities of optical remote sensing to monitor bathymetry in nearshore area using video images. The technique is designed to extract wave number components based on variation of intensity of brightness at each pixel in the images using cross-spectral correlation approach. This approach is based on pixel array analysis that utilizes a nonlinear inverse method ‘Levenberg-Marquardt’. The technique is applied to the data collected at Hasaki beach in Japan from August to December 2006. The results indicate that the estimate of nearshore bathymetry is proved reasonable accurate near shoreline and breaking area where the differences between estimated and survey water depth are less than 10-30 cm.

J-Resolved 1H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis.

1H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D 1H NMR spectra, we have investigated the use of 2D J-resolved (JRES) 1H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.

Wave-Packet Representation of Shock-Cell Noise for a Single Round Jet

From a viewpoint analogous to the wave-packet model, the shock-cell-noise model developed by Harper-Bourne and Fisher (“The Noise from Shock Waves in Supersonic Jets,” AGARD Rept. CP-131, 1974) is directly evaluated using unsteady pressure fields computed with a large-eddy simulation. Continuum two-point correlation functions of near-field pressure fluctuations in a single round jet are projected to acoustic fields as a boundary-value problem, and the expression is transformed into a discrete representation equivalent to the Harper-Bourne and Fisher model. In this process, the two-point correlation is reconstructed using the snapshot proper orthogonal decomposition technique in the frequency domain (namely, the cross-spectral correlation). Accordingly, hydrodynamic and acoustic fields associated with shock-cell noise are visualized for each azimuthal mode. From explicit correspondence between the Harper-Bourne and Fisher model and the cross-spectral correlation function, the validity of the model is analyzed in terms of the active shock-cell sites, the correlation length, the phase velocity, and the contributions from azimuthal modes as a function of the Strouhal number. Many aspects of the Harper-Bourne and Fisher model, such as the discrete nature and the correlation length scale, are justified; on the other hand, the importance of some missing aspects, especially the azimuthal content and the harmonic wave-number components, is found at a Strouhal number of approximately two or higher.

Cosic’s Resonance Recognition Model for Protein Sequences and Photon Emission Differentiates Lethal and Non-Lethal Ebola Strains: Implications for Treatment

The Cosic Resonance Recognition Model (RRM) for amino acid sequences was applied to the classes of proteins displayed by four strains (Sudan, Zaire, Reston, Ivory Coast) of Ebola virus that produced either high or minimal numbers of human fatalities. The results clearly differentiated highly lethal and non-lethal strains. Solutions for the two lethal strains exhibited near ultraviolet (~230 nm) photon values while the two asymptomatic forms displayed near infrared (~1000 nm) values. Cross-correlations of spectral densities of the RRM values of the different classes of proteins associated with the genome of the viruses supported this dichotomy. The strongest coefficient occurred only between Sudan-Zaire strains but not for any of the other pairs of strains for sGP, the small glycoprotein that intercalated with the plasma cell membrane to promote insertion of viral contents into cellular space. A surprising, statistically significant cross-spectral correlation occurred between the “spike” glycoprotein component (GP1) of the virus that associated the anchoring of the virus to the mammalian cell plasma membrane and the Schumann resonance of the earth whose intensities were determined by the incidence of equatorial thunderstorms. Previous applications of the RRM to shifting photon wavelengths emitted by melanoma cells adapting to reduced ambient temperature have validated Cosic’s model and have demonstrated very narrowwave-length (about 10 nm) specificity. One possible ancillary and non-invasive treatment of people within which the fatal Ebola strains are residing would be whole body application of narrow band near-infrared light pulsed as specific physiologically-patterned sequences with sufficient radiant flux density to perfuse the entire body volume.

ACOUSTIC MODELING METHOD

A cross-spectral correlation function of a structure may be determined by providing a finite element model of the structure having a plurality of elements each having a centroid. A plurality of composite centroids may be determined wherein each one of the composite centroids is based on at least one of the elements. The cross-spectral correlation function between at least one pair of the elements in the finite element model may be assigned to be the cross-spectral correlation function of the composite centroids that include the centroids of the elements. If the pair of elements is included in the same composite centroid, then the cross-spectral correlation function between the elements is assigned to be the autocorrelation function of the composite centroid that includes the pair of elements.

Observed Decadal Changes in Downward Wave Coupling between the Stratosphere and Troposphere in the Southern Hemisphere

Downward wave coupling dominates the intraseasonal dynamical coupling between the stratosphere and troposphere in the Southern Hemisphere. The coupling occurs during late winter and spring when the stratospheric basic state forms a well-defined meridional waveguide, which is bounded above by a reflecting surface. This basic-state configuration is favorable for planetary wave reflection and guides the reflected waves back down to the troposphere, where they impact wave structures. In this study decadal changes in downward wave coupling are analyzed using the Modern Era Retrospective-Analysis for Research and Applications (MERRA) dataset. A cross-spectral correlation analysis, applied to geopotential height fields, and a wave geometry diagnostic, applied to zonal-mean zonal wind and temperature data, are used to understand decadal changes in planetary wave propagation. It is found that downward wave 1 coupling from September to December has increased over the last three decades, owing to significant increases at the beginning and end of this 4-month period. The increased downward wave coupling is caused by both an earlier onset of the vertically bounded meridional waveguide configuration and a persistence of this configuration into December. The latter is associated with the observed delay in vortex breakup. The results point to an additional dynamical mechanism whereby the stratosphere has influenced the tropospheric climate in the Southern Hemisphere.

Downward Wave Coupling between the Stratosphere and Troposphere: The Importance of Meridional Wave Guiding and Comparison with Zonal-Mean Coupling

Abstract The nature of downward wave coupling between the stratosphere and troposphere in both hemispheres is analyzed using the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset. Downward wave coupling occurs when planetary waves reflected in the stratosphere impact the troposphere, and it is distinct from zonal-mean coupling, which results from wave dissipation and its subsequent impact on the zonal-mean flow. Cross-spectral correlation analysis and wave geometry diagnostics reveal that downward wave-1 coupling occurs in the presence of both a vertical reflecting surface in the mid-to-upper stratosphere and a high-latitude meridional waveguide in the lower stratosphere. In the Southern Hemisphere, downward wave coupling occurs from September to December, whereas in the Northern Hemisphere it occurs from January to March. A vertical reflecting surface is also present in the stratosphere during early winter in both hemispheres; however, it forms at the poleward edge of the meridional waveguide, which is not confined to high latitudes. The absence of a high-latitude waveguide allows meridional wave propagation into the subtropics and decreases the likelihood of downward wave coupling. The results highlight the importance of distinguishing between wave reflection in general, which requires a vertical reflecting surface, and downward wave coupling between the stratosphere and troposphere, which requires both a vertical reflecting surface and a high-latitude meridional waveguide. The relative roles of downward wave and zonal-mean coupling in the Southern and Northern Hemispheres are subsequently compared. In the Southern Hemisphere, downward wave-1 coupling dominates, whereas in the Northern Hemisphere downward wave-1 coupling and zonal-mean coupling are found to be equally important from winter to early spring. The results suggest that an accurate representation of the seasonal cycle of the wave geometry is necessary for the proper representation of downward wave coupling between the stratosphere and troposphere.

Effect of material spatial dispersion in the degree of polarization of thermal radiation emitted by a spherical source

The influence of material spatial dispersion in the degree of polarization emitted by a metallic sphere is studied by means of fluctuational electrodynamics. The corresponding cross-spectral correlation functions of the electric field are calculated on a basis of a non-local scattering T-matrix for a spherical scatterer and for non-local dielectric functions for the metal such as those provided by the hydrodynamic model and the Lindhard theory. It is shown that the main effect of the material spatial dispersion is a blue shift of the spectra of the degree of polarization which, however, diminishes as the sphere size increases. Also, at the bulk plasma frequency, a local maximum of the degree of polarization emerges as a result of the excitation of bulk plasmons which is not evident when a local dielectric function is assumed.

Infrared signatures of the NCCO radical

The first definitive infrared signatures of the elusive NCCO radical have been measured using a microwave discharge technique combined with low-temperature matrix-isolation spectroscopy, resulting in a consistent set of vibrational assignments for six isotopologues. The infrared spectra of these NCCO isotopologues were concomitantly established by rigorous variational nuclear-motion computations based on a high-level coupled-cluster quartic vibrational force field [ROCCSD(T)/cc-pCVQZ] and cubic dipole field [ROCCSD/cc-pCVTZ]. Our experimental and theoretical results for NCCO overturn the vibrational assignments in a NIST-JANAF compilation and those from a recent two-dimensional cross-spectral correlation analysis. For the parent isotopologue at 11 K in a nitrogen matrix, we find the signature bands nu(2)(CO str.) = 1889.2 cm(-1) and nu(3)(CC str.) = 782.0 cm(-1). Our variational vibrational computations reveal strong mixing of the nu(3) stretching fundamental and the nu(4) + nu(5) bending combination level for all isotopologues. These Fermi resonances manifest a clear breakdown of the simple normal-mode picture of molecular vibrations at low energies.

Nearshore Bathymetry Estimation Using Video Coastal Monitoring System

The invention of new digital technology of images from video camera systems now can provide information of the shoreward propagation of wave using pixel intensity time series that collected at cross-shore array. From this video image of intensity data, we can measure the wave speed (or, equivalent to wave number). Then the local water depth is inferred from linear wave theory dispersion relation equation. This paper describes the cross-spectral correlation approach scheme for investigating wave speed or equivalent wave number from video image data sets. The approach based on a pixel array analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency. The solution includes error predictions that can be used to evaluate sample designs (data gaps) and the signal coherence. The technique was tested using 30 days of hourly data collected at Egmond beach, Netherlands. The result showed that the method have capability to derive wave number prediction from pixel intensity time series to support bathymetry estimation in near shore area through inversion of an appropriate wave dispersion model.

Ocean Wavenumber Estimation From Wave-Resolving Time Series Imagery

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution).

Signal-to-noise enhancement in time-resolved IR emission spectra through two-dimensional correlation analysis

We have examined the relative signal-to-noise (S/N) enhancement as obtained through extraction of the diagonal elements of the synchronous correlation map following two-dimensional correlation analysis of both self- and cross-spectral correlation. In particular, comparison was made between the resulting correlation spectrum and the spectrum obtained through simple averaging. As a means of analysis, four series of synthetic spectra, containing time dependent variations in both spectral intensity and frequency as well as artificially added random noise, were generated and analyzed with correlation analysis as well as simple averaging. It is found that for a time-dependent decay in spectral intensity, the S/N enhancement achieved through correlation is marginally superior to that which is obtained through simple averaging. For all cases considered, inclusion of a frequency shift results in an overall diminished enhancement. As in the case of simple linear averaging, the effect of self- vs. cross-correlation on S/N enhancement is directly related to the number of spectra used in the analysis. Additionally, for series exhibiting a frequency shift, it is observed that correlation analysis yields spectra which are more representative of the original time-dependent data sets.

Two-dimensional cross-spectral correlation analysis and its application to time-resolved Fourier transform emission spectra of transient radicals

A spectral analysis method, based on the generalized two-dimensional (2D) vibrational spectra correlation analysis, is developed for deciphering the correlation among the spectral peaks of two different spectra. This 2D cross-spectral correlation (2DCSC) analysis is aimed at revealing the vibrational features associated with a common species in two spectra, each obtained from a system containing multiple species with at least one common species. The cross-spectral correlation is based on the premise that the spectral features of the same species should have the same time and frequency responses toward similar perturbations. The effectiveness of the cross-spectral correlation analysis is first illustrated with model systems, with spectral peaks decaying linearly or exponentially with time, before being applied to analyzing time-resolved emission spectra obtained, by a Fourier transform IR spectrometer, for samples consisting of the vibrationally excited transient cyanooxomethyl radical (OCCN). 2DCSC among the three different sets of time-resolved spectra collected following the photodissociation of three different precursor molecules of OCCN, respectively, allows the identification of the CN and CO stretching modes of this radical.

Blind cross-spectral image registration using prefiltering and Fourier-based translation detection

This paper describes a fast technique for registering image pairs from visible and infrared spectra that differ by translation, small rotations, and small changes of scale. The main result of this paper is a nonlinear prefiltering and thresholding technique that substantially enhances the cross-spectral correlation, provided that the image pairs have many features in common. We show the use of the technique in conjunction with a Fourier-based normalized correlation algorithm to perform fast cross-spectral registrations. In the absence of such prefiltering, local reversals of contrast from image to image tend, to impair the quality of correlation-based registrations. The algorithm computes the translation that maximizes the overall normalized correlation of the filtered images without examining individual image features. Small rotations and scale changes can be recovered by computing the translation displacement in several different regions of the image pairs. In an experiment on a moderate-sized database, the algorithm produced a correct registration rate of over 90% at a false positive rate of less than 10%. For a particularly difficult subset of images in the database, the correct registration rate fell to approximately 85% at a false positive rate of less than 10%. This retrieval quality is comparable to that of a mutual-information-based algorithm.

Wavelength decorrelation of laser speckle from three-dimensional diffuse objects

The wavelength dependence of laser speckle produced by scattering from 3-D diffuse objects is considered. A simple Fourier transform relationship between the cross-spectral correlation function and an object's range profile is derived.

Applications of Astrom-Gray-Markel recursions

The Astrom-Gray-Markel recursions algorithm computes the power of an ARMA model from its power spectral density. Two applications of this algorithm are shown in this paper. The first application is the derivation of some ARMA identities relating the ARMA coefficients, the reflection coefficients and the tap weights. They provide an insight about the AR spectral shape without actually plotting the spectrum. The second is an analytical evaluation of the cross-spectral correlation (CSC) between two ARMA models without any numerical integrations. The CSC is useful to identify time-varying signals of the same type when adaptive filtering techniques can be applied to these signals, as an alternative to a time-domain correlation which may require long durations of the signals.