The Experts below are selected from a list of 4488 Experts worldwide ranked by ideXlab platform
Robert E Kursinski - One of the best experts on this subject based on the ideXlab platform.
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improving gps radio occultation stratospheric Refractivity retrievals for climate benchmarking
Geophysical Research Letters, 2012Co-Authors: Anthony J Mannucci, Robert E KursinskiAbstract:[1] Global Positioning System radio occultation (GPS RO) measurements have been shown to be valuable for climate monitoring. The Refractivity retrieved from these measurements are most accurate below 25 km altitude. At higher altitudes, the atmosphere becomes increasingly tenuous, and the measurement noise becomes comparable to or exceeds the bending signal. This necessitates some form of smoothing or modeling of the bending angles at high altitudes before Abel inversion. In this paper, we introduce a new approach to reduce the systematic bias that could result from such high-altitude initialization. We show that the climatological average of Refractivity can be computed as the Abel inversion of the average bending angles with very little error in the stratosphere. By using the average bending angles, we can substantially reduce the random noise in the measurements and increase the altitude at which the initialization needs to be applied. We performed a simulation study which validated this approach and demonstrated the significant improvement in stratospheric Refractivity retrieval. Applying the method to actual COSMIC data showed a similar level of difference between our method and the conventional method above 25 km. This implies that the improvement seen in the simulation could be achievable with the real data.
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an approach for retrieving marine boundary layer Refractivity from gps occultation data in the presence of superrefraction
Journal of Atmospheric and Oceanic Technology, 2006Co-Authors: Feiqin Xie, Stig Syndergaard, Robert E Kursinski, Benjamin M HermanAbstract:Abstract The global positioning system (GPS) radio occultation (RO) technique has demonstrated the ability to precisely probe earth’s atmosphere globally with high vertical resolution. However, the lowermost troposphere still presents some challenges for the technique. Over moist marine areas, especially in subtropical regions, a very large negative moisture gradient often exists across the thermal inversion capping the marine boundary layer (MBL), which frequently causes superrefraction (SR), or ducting. In the presence of SR, the reconstruction of Refractivity from RO data becomes an ill-posed inverse problem. This study shows that one given RO bending angle profile is consistent with a continuum (an infinite number) of Refractivity profiles. The standard Abel retrieval gives the minimum Refractivity solution of the continuum and thus produces the largest negative bias, consistent with a negative bias often present in the retrieved Refractivity profiles in the moist lower troposphere. By applying a simp...
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a refractive index mapping operator for assimilation of occultation data
Monthly Weather Review, 2005Co-Authors: Stig Syndergaard, Robert E Kursinski, Benjamin M Herman, Emily M Lane, David E FlittnerAbstract:Abstract This paper describes the details of a fast, linear, forward-inverse refractive index mapping operator that can be used for assimilation of occultation data of various kinds into NWP models. Basically, the mapping consists of the integration of the refractive index along finite straight lines, mimicking the observational geometry as well as the subsequent retrieval of a refractive index profile, assuming spherical symmetry. Line integrals are discretized such that the Refractivity is evaluated along the horizontal at fixed levels that can be chosen to coincide with the pressure levels of an NWP model. Integration of the hydrostatic equation at a large number of locations is thereby avoided. The mapping operator is tested using an idealized model of a weather front with large horizontal gradients. Mapped Refractivity profiles are compared with retrieved Refractivity profiles obtained via accurate 3D ray tracing simulations of GPS radio occultation events with ray path tangent points near the weathe...
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1dvar analysis of temperature and humidity using gps radio occultation Refractivity data
Journal of Geophysical Research, 2002Co-Authors: Paul Poli, Robert E Kursinski, Joanna JoinerAbstract:[1] The constellation of Global Positioning System (GPS) satellites provides a source of continuous, phase-stable electromagnetic signals available for radio occultation observations of our planet. The atmospheric-induced bending of the transmitted rays observed during each occultation can be converted into a Refractivity profile using an Abel transform. Since Refractivity is related to temperature and humidity, it may potentially be used in global data assimilation for numerical weather prediction (NWP) and for creating climate data sets. We first compare GPS/Meteorology (GPS/MET) 1995 Refractivity with various backgrounds and verify that the best expected background presents generally the best fit with the observed Refractivity. We implement here an efficient one-dimensional variational (1DVAR) analysis of GPS Refractivity that enables retrieving temperature, humidity, and sea-level pressure using the finite volume data assimilation system background. 1DVAR analyses with GPS/MET 1995 data are compared with collocated radiosondes. They show an excellent capacity of the GPS measurements to resolve the tropopause. In the Northern Hemisphere, we demonstrate a net reduction of temperature bias and standard deviation, as compared with the background. The 1DVAR humidity presents reduced standard deviation as compared to the background between 550 and 400 hPa. However, a Refractivity bias between the observations and the background in the lower troposphere systematically shifts the 1DVAR humidity downward. A Refractivity bias over the whole profile is transformed into a 1DVAR sea-level pressure bias. This study represents a step toward using the GPS radio occultation data in data assimilation systems to improve NWP forecasts and representation of Earth's climate in models.
William S. Hodgkiss - One of the best experts on this subject based on the ideXlab platform.
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Refractivity estimation from sea clutter an invited review
Radio Science, 2011Co-Authors: Ali Karimian, William S. Hodgkiss, Peter Gerstoft, Caglar Yardim, Amalia E BarriosAbstract:[1] Non-standard radio wave propagation in the atmosphere is caused by anomalous changes of the atmospheric Refractivity index. In recent years, Refractivity from clutter (RFC) has been an active field of research to complement traditional ways of measuring the Refractivity profile in maritime environments which rely on direct sensing of the environmental parameters. Higher temporal and spatial resolution of the Refractivity profile, together with a lower cost and convenience of operations have been the promising factors that brought RFC under consideration. Presented is an overview of the basic concepts, research and achievements in the field of RFC. Topics that require more attention in future studies also are discussed.
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estimation of radio Refractivity from radar clutter using bayesian monte carlo analysis
IEEE Transactions on Antennas and Propagation, 2006Co-Authors: Caglar Yardim, Peter Gerstoft, William S. HodgkissAbstract:This paper describes a Markov chain Monte Carlo (MCMC) sampling approach for the estimation of not only the radio Refractivity profiles from radar clutter but also the uncertainties in these estimates. This is done by treating the Refractivity from clutter (RFC) problem in a Bayesian framework. It uses unbiased MCMC sampling techniques, such as Metropolis and Gibbs sampling algorithms, to gather more accurate information about the uncertainties. Application of these sampling techniques using an electromagnetic split-step fast Fourier transform parabolic equation propagation model within a Bayesian inversion framework can provide accurate posterior probability distributions of the estimated Refractivity parameters. Then these distributions can be used to estimate the uncertainties in the parameters of interest. Two different MCMC samplers (Metropolis and Gibbs) are analyzed and the results compared not only with the exhaustive search results but also with the genetic algorithm results and helicopter Refractivity profile measurements. Although it is slower than global optimizers, the probability densities obtained by this method are closer to the true distributions.
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Probability distribution of low-altitude propagation loss from radar sea clutter data
Radio Science, 2004Co-Authors: Peter Gerstoft, William S. Hodgkiss, Ted L. Rogers, Michael JableckiAbstract:This paper describes the estimation of propagation loss and its statistical properties on the basis of observations of radar sea clutter data. This problem is solved by first finding an ensemble of relevant Refractivity model parameters, and each Refractivity model is weighted according to its data likelihood function. A parabolic equation propagation model is used both in mapping from environmental model to radar clutter data and also when mapping to propagation loss. Two different methods are then used for mapping from a statistical description of Refractivity parameters to a statistical description of propagation loss. In the first approach, all of the sampled models explored in the inversion are used to give a statistical description of propagation loss. Alternatively, the environmental model is sampled from the probability for the Refractivity model parameters and then mapped into propagation loss. This can be done efficiently if we are using the one-dimensional marginal distributions instead of the full distribution for the environmental parameters.
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Refractivity estimation using multiple elevation angles
IEEE Journal of Oceanic Engineering, 2003Co-Authors: Peter Gerstoft, William S. Hodgkiss, L T Rogers, L J WagnerAbstract:Estimation of the atmospheric Refractivity is important for the prediction of radar performance. Surface or elevated trapping layers formed by the outflow of relatively dry and warm air over a cooler body of water often result in the refractive structure-supporting-convergence-zone-like behavior and multimodal effects. The propagation under such conditions can be very sensitive to even small changes in the vertical and horizontal structure of Refractivity. Obtaining in situ measurements of sufficient fidelity to estimate where intensifications in the electromagnetic field will occur is difficult. The authors previously have demonstrated the ability to infer Refractivity parameters from grazing-incidence radar sea-clutter data. The radar system was the 2.8-GHz space range radar that overlooks the Atlantic Ocean in the vicinity of Wallops Island, VA. The forward modeling consisted of the mapping of an 11-parameter environmental model via an electromagnetic propagation model into the space of the radar clutter observations. A genetic algorithm was employed to optimize the objective function. Ground truth data were atmospheric soundings obtained by a helicopter flying a saw-tooth pattern. The overall result was that the ability to estimate the propagation within the duct itself was comparable to that of in situ measurements. However, the ability to characterize the region above the duct was quite poor. Modern three-dimensional radars, however, have relatively narrow beams. Using these narrow beams at multiple elevations might resolve the ambiguity leading to the poor characterization in the region above the duct. Using radar data from the SPANDAR radar, it is demonstrated that such an approach is feasible and that more-robust estimates can be obtained by using two elevation angles and/or by constraining the solution to contain realistic Refractivity profiles.
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inversion for Refractivity parameters from radar sea clutter
Radio Science, 2003Co-Authors: Peter Gerstoft, Ted L. Rogers, J Krolik, William S. HodgkissAbstract:[1] This paper describes estimation of low-altitude atmospheric Refractivity from radar sea clutter observations. The vertical structure of the refractive environment is modeled using five parameters, and the horizontal structure is modeled using six parameters. The Refractivity model is implemented with and without an a priori constraint on the duct strength, as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the Refractivity structure into a replica field. Replica fields are compared to the observed clutter using a squared-error objective function. A global search for the 11 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on S-band radar sea-clutter data from Wallops Island, Virginia. Reference data are from range-dependent Refractivity profiles obtained with a helicopter. The inversion is assessed (1) by comparing the propagation predicted from the radar-inferred Refractivity profiles and from the helicopter profiles, (2) by comparing the Refractivity parameters from the helicopter soundings to those estimated, and (3) by examining the fit between observed clutter and optimal replica field. This technique could provide near-real-time estimation of ducting effects. In practical implementations it is unlikely that range-dependent soundings would be available. A single sounding is used for evaluating the radar-inferred environmental parameters. When the unconstrained environmental model is used, the “Refractivity-from-clutter,” the propagation loss generated and the loss from this single sounding, is close within the duct; however, above the duct they differ. Use of the constraint on the duct strength leads to a better match also above the duct.
Peter Gerstoft - One of the best experts on this subject based on the ideXlab platform.
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estimating Refractivity from propagation loss in turbulent media
Radio Science, 2016Co-Authors: Mark Wagner, Peter Gerstoft, Ted RogersAbstract:This paper estimates lower atmospheric Refractivity (M-profile) given an electromagnetic (EM) propagation loss (PL) measurement. Specifically, height independent PL measurements over a range of 10-80 km are used to infer information about the existence and potential parameters of atmospheric ducts in the lowest 1 km of the atmosphere. The main improvement made on previous Refractivity estimations is inclusion of range dependent fluctuations due to turbulence in the forward propagation model. Using this framework, the maximum likelihood (ML) estimate of atmospheric Refractivity has good accuracy, and with prior information about ducting the maximum a priori (MAP) Refractivity estimate can be found. Monte Carlo methods are used to estimate the mean and covariance of PL, which are fed into a Gaussian likelihood function for evaluation of estimated Refractivity probability. Comparisons were made between inversions performed on propagation loss data simulated by a wide angle Parabolic Equation (PE) propagation model with added homogeneous and inhomogeneous turbulence. It was found that the turbulence models produce significantly different results, suggesting that accurate modeling of turbulence is key.
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Refractivity estimation from sea clutter an invited review
Radio Science, 2011Co-Authors: Ali Karimian, William S. Hodgkiss, Peter Gerstoft, Caglar Yardim, Amalia E BarriosAbstract:[1] Non-standard radio wave propagation in the atmosphere is caused by anomalous changes of the atmospheric Refractivity index. In recent years, Refractivity from clutter (RFC) has been an active field of research to complement traditional ways of measuring the Refractivity profile in maritime environments which rely on direct sensing of the environmental parameters. Higher temporal and spatial resolution of the Refractivity profile, together with a lower cost and convenience of operations have been the promising factors that brought RFC under consideration. Presented is an overview of the basic concepts, research and achievements in the field of RFC. Topics that require more attention in future studies also are discussed.
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real time Refractivity from clutter using a best fit approach improved with physical information
Radio Science, 2010Co-Authors: Rémi Douvenot, Peter Gerstoft, Vincent Fabbro, Christophe Bourlier, Joseph SaillardAbstract:[1] Refractivity from clutter (RFC) retrieves the radio frequency refractive conditions along a propagation path by inverting the measured radar sea clutter return. In this paper, a real-time RFC technique is proposed called “Improved Best Fit” (IBF). It is based on finding the environment with best fit to one of many precomputed, modeled radar returns for different environments in a database. The method is improved by considering the mean slope of the propagation factor, and physical considerations are added: smooth variations of refractive conditions with azimuth and smooth variations of duct height with range. The approach is tested on data from 1998 Wallops Island, Virginia, measurement campaign with good results on most of the data, and questionable results are detected with a confidence criterion. A comparison between the Refractivity structures measured during the measurement campaign and the ones retrieved by inversion shows a good match. Radar coverage simulations obtained from these inverted Refractivity structures demonstrate the potential utility of IBF.
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recursive bayesian electromagnetic Refractivity estimation from radar sea clutter
Radio Science, 2007Co-Authors: S Vasudevan, Peter Gerstoft, Ted L. Rogers, Richard H Anderson, Shawn Kraut, J KrolikAbstract:[1] Estimation of the range- and height-dependent index of refraction over the sea surface facilitates prediction of ducted microwave propagation loss. In this paper, Refractivity estimation from radar clutter returns is performed using a Markov state space model for microwave propagation. Specifically, the parabolic approximation for numerical solution of the wave equation is used to formulate the Refractivity from clutter (RFC) problem within a nonlinear recursive Bayesian state estimation framework. RFC under this nonlinear state space formulation is more efficient than global fitting of Refractivity parameters when the total number of range-varying parameters exceeds the number of basis functions required to represent the height-dependent field at a given range. Moreover, the range-recursive nature of the estimator can be easily adapted to situations where the Refractivity modeling changes at discrete ranges, such as at a shoreline. A fast range-recursive solution for obtaining range-varying Refractivity is achieved by using sequential importance sampling extensions to state estimation techniques, namely, the forward and Viterbi algorithms. Simulation and real data results from radar clutter collected off Wallops Island, Virginia, are presented which demonstrate the ability of this method to produce propagation loss estimates that compare favorably with ground truth Refractivity measurements.
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estimation of radio Refractivity from radar clutter using bayesian monte carlo analysis
IEEE Transactions on Antennas and Propagation, 2006Co-Authors: Caglar Yardim, Peter Gerstoft, William S. HodgkissAbstract:This paper describes a Markov chain Monte Carlo (MCMC) sampling approach for the estimation of not only the radio Refractivity profiles from radar clutter but also the uncertainties in these estimates. This is done by treating the Refractivity from clutter (RFC) problem in a Bayesian framework. It uses unbiased MCMC sampling techniques, such as Metropolis and Gibbs sampling algorithms, to gather more accurate information about the uncertainties. Application of these sampling techniques using an electromagnetic split-step fast Fourier transform parabolic equation propagation model within a Bayesian inversion framework can provide accurate posterior probability distributions of the estimated Refractivity parameters. Then these distributions can be used to estimate the uncertainties in the parameters of interest. Two different MCMC samplers (Metropolis and Gibbs) are analyzed and the results compared not only with the exhaustive search results but also with the genetic algorithm results and helicopter Refractivity profile measurements. Although it is slower than global optimizers, the probability densities obtained by this method are closer to the true distributions.
Geoffrey F. Strouse - One of the best experts on this subject based on the ideXlab platform.
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cell based refractometer for pascal realization
Optics Letters, 2017Co-Authors: Patrick F Ega, Jacob E Ricke, Jack A Stone, Jay H Hendricks, Geoffrey F. StrouseAbstract:We describe a method for determining the density of helium via measurements of optical Refractivity. In combination with the equation of state, this allows realization of the pascal. Our apparatus is based on the integration of a gas triple-cell into a quasi-monolithic heterodyne interferometer: the stability of the interferometer is ±50 pm over 10 h. We claim the contribution of cell window thinning to pathlength uncertainty can be canceled within an uncertainty of 0.37 fm/Pa per window pass, of which for our 25 cm cell length corresponds to a fractional error of 9.3×10−6 in the measure of helium Refractivity. We report the ratio (n−1)N2 /(n−1)He=8.570354(13) at p=367.420(4) kPa, T=293.1529(13) K and λ=632.9908(6) nm, which can be used to calibrate less-accurate refractometers. By measuring helium Refractivity at known temperature and pressure, we determined the Boltzmann constant with standard uncertainty kB=1.380652(17)×10−23 JK−1.
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performance of a dual fabry perot cavity refractometer
Optics Letters, 2015Co-Authors: Patrick F Egan, Jonathan E. Ricker, Gregory E Scace, Jack A Stone, Jay H Hendricks, Geoffrey F. StrouseAbstract:We have built and characterized a refractometer that utilizes two Fabry–Perot cavities formed on a dimensionally stable spacer. In the typical mode of operation, one cavity is held at vacuum, and the other cavity is filled with nitrogen gas. The differential change in length between the cavities is measured as the difference in frequency between two helium-neon lasers, one locked to the resonance of each cavity. This differential change in optical length is a measure of the gas Refractivity. Using the known values for the molar Refractivity and virial coefficients of nitrogen, and accounting for cavity length distortions, the device can be used as a high-resolution, multi-decade pressure sensor. We define a reference value for nitrogen Refractivity as n−1=(26485.28±0.3)×10−8 at p=100.0000 kPa, T=302.9190 K, and λvac=632.9908 nm. We compare pressure determinations via the refractometer and the reference value to a mercury manometer.
Rémi Douvenot - One of the best experts on this subject based on the ideXlab platform.
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A Variational Adjoint Approach on Wide-Angle Parabolic Equation for Refractivity Inversion
IEEE Transactions on Antennas and Propagation, 2021Co-Authors: Uygar Karabaş, Youssef Diouane, Rémi DouvenotAbstract:Radar systems performance under anomalous propagation conditions can be predicted if the atmosphere is properly known. This paper introduces a tomographic approach to estimate Refractivity in the troposphere with an adjoint-based inversion method. A new adjoint model is developed for the two-dimensional wide-angle parabolic equation using variational adjoint approach, to invert Refractivity from phaseless data measured with an array of radio receivers in open-sea environment. The obtained adjoint model is validated considering propagation through range-independent medium over flat perfectly-electric-conducting surface at horizontal polarization. The ill-posedness of the regarded inverse problem is shown with the optimization landscapes. The parametric study indicates the potential use of this method as a Refractivity gradient retrieval system under certain circumstances.
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On the Use of Adjoint Methods for Refractivity Estimation in the Troposphere
2020Co-Authors: Uygar Karabaş, Youssef Diouane, Rémi DouvenotAbstract:This paper presents a preliminary study of a new inversion strategy combining the method of adjoint applied to the wide-angle parabolic equation and the method of split-step wavelet for tropospheric Refractivity estimation. Our main motivation is to use a gradient based optimization method to infer atmosphere from radio-frequency data, in an effort towards a real-time accurate Refractivity-from-clutter system. The proposed adjoint formulation is validated with the method of finite differences. The validation setup is developed for inversion using a tomographic approach.
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real time Refractivity from clutter using a best fit approach improved with physical information
Radio Science, 2010Co-Authors: Rémi Douvenot, Peter Gerstoft, Vincent Fabbro, Christophe Bourlier, Joseph SaillardAbstract:[1] Refractivity from clutter (RFC) retrieves the radio frequency refractive conditions along a propagation path by inverting the measured radar sea clutter return. In this paper, a real-time RFC technique is proposed called “Improved Best Fit” (IBF). It is based on finding the environment with best fit to one of many precomputed, modeled radar returns for different environments in a database. The method is improved by considering the mean slope of the propagation factor, and physical considerations are added: smooth variations of refractive conditions with azimuth and smooth variations of duct height with range. The approach is tested on data from 1998 Wallops Island, Virginia, measurement campaign with good results on most of the data, and questionable results are detected with a confidence criterion. A comparison between the Refractivity structures measured during the measurement campaign and the ones retrieved by inversion shows a good match. Radar coverage simulations obtained from these inverted Refractivity structures demonstrate the potential utility of IBF.
