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At least 253 records · Page 14

A comparison of SIR-B directional ocean wave spectra with aircraft scanning radar spectra

Directional ocean wave spectra derived from Shuttle Imaging Radar-B (SIR-B) L-band imagery collected off the coast of Southern Chile on 11 and 12 October 1984 were compared with independent spectral estimates from two airborne scanning radars. In sea states with significant wave heights ranging from 3 to 5 meters, the SIR-B-derived sspectra at 18 deg and 25 deg off nadir yielded reasonable estimates of wavelengths, directions, and spectral shapes for all wave systems encountered, including a purely azimuth-traveling system. A SIR-B image intensity variance spectrum containing predominantly range-traveling waves closely resembles an independent aircraft estimate of the slope variance spectrum. The prediction of a U.S. Navy global spectral ocean wave model on 11 October 1984 exhibited no significant bias in dominant wave number but contained a directional bias of about 30 deg with respect to the mean of the aircraft and spacecraft estimates.

Beal, R. C.↗

SIR-B ocean-wave enhancement with fast Fourier transform techniques

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

Tilley, David G.↗

Phobos Ephemeris Improvement from Recent Spacecraft Observations

Despite 127 years of observations, there is still room for improvement in the ephemeris of the Martian satellite Phobos. Early in this history, Earth-based astrometric observations of Phobos and Deimos were used to estimate the mass and oblateness of Mars. As more data accumulated, it became clear that a secular acceleration in the longitude of Phobos was occurring, and this was attributed to tidal dissipation within Mars, yielding rough estimates of the tidal quality factor, or Q. At the epoch of the earliest spacecraft observations of Phobos, from Mariner 9 and the Viking Orbiters and Landers, the gravitational field of Mars, and resulting forces on Phobos, were still not particularly well known. Thus observations of natural and artificial satellite motions continued to contribute, each in their own way, to knowledge of the mass distribution within Mars. Improvements in tracking system accuracy, and the placement of satellites, like the 1996 Mars Global Surveyor and 2001 Mars Odyssey, in circular polar orbits has lead to dramatic improvements to knowledge of the Mars gravity field. The direct gravitational influence on Phobos is no longer expected to be a limiting factor in predicting its orbital motion. Despite that progress, a variety of observations of Phobos from recent orbiters and landers suggest that the best satellite ephemeris still has along-track orbit errors which are accumulating at a rate of 1.75 kilometers per year, with Phobos gaining on the predicted positions. These recent observations alone do not span sufficient time to separately resolve the positional error into changes in mean motion and changes in secular acceleration. However, combining them with earlier observations will allow improvements in both the mean motion and its first derivative. This latter parameter is particularly interesting, as it relates to tidal dissipation, and thus uniquely constrains the internal structure of Mars. The current best estimate of the secular acceleration rate of Mars implies a surprisingly low value for the tidal dissipation factor Q = (94 plus or minus 1). For the Earth, most tidal dissipation occurs within the oceans. The terrestrial mantle tidal Q is 280. An issue of interest is then: why, where, and how does Mars dissipate tidal energy so effectively.

Bills, B. G.↗

Satellite Angular Rate Estimation From Vector Measurements

This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

Azor, Ruth↗

Combined Radiometer-Radar Microphysical Profile Estimations with Emphasis on High Frequency Brightness Temperature Observations

Information about the vertical microphysical cloud structure is useful in many modeling and predictive practices. Radiometers and radars are used to observe hydrometeor properties. This paper describes an iterative retrieval algorithm that combines the use of airborne active and wideband (10 to 340 GHz) passive observations to estimate the vertical content and particle size distributions of liquid and frozen hydrometeors. The physically-based retrieval algorithm relies on the high frequencies (greater than 89 GHz) to provide details on the frozen hydrometeors. Neglecting the high frequencies yielded acceptable estimates of the liquid profiles, but the ice profiles were poorly retrieved. Airborne radar and radiometer observations from the third Convection and Moisture EXperiment (CAMEX-3) were used in the retrieval algorithm as constraints. Nadir profiles were estimated for a minute each of flight time (approximately 12.5 km along track) from an anvil, convection, and quasi- stratiform rain. The complex structure of the frozen hydrometeors required the most iterations for convergence for the anvil cloud type. The wideband observations were found to more than double the estimated frozen hydrometeor content as compared to retrievals using only 90-GHz and below. The convective and quasi-stratiform quickly reached convergence (minimized difference between observations and calculations using the estimated profiles). A qualitative validation using coincident in situ CAMEX-3 observations shows that the retrieved particle size distributions are well corroborated with independent measurements.

Gail Skofronick-Jackson↗

On Bayesian Inductive Inference & Predictive Estimation

We investigate Bayesian inference and the Principle of Maximum Entropy (PME) as methods for doing inference under uncertainty. This investigation is primarily through concrete examples that have been previously investigated in the literature. We find that it is possible to do Bayesian inference and PME inference using the same information, despite claims to the contrary, but that the results are not directly comparable. This is because Bayesian inference yields a probability density function (pdf) over the unknown model parameters, whereas PME yields point estimates. If mean estimates are extracted from the Bayesian pdfs, the resulting parameter estimates can differ radically from the PME values and also from the Maximum Likelihood values. We conclude that these differences are due to the Bayesian inference not assuming anything beyond the given prior probabilities and the data, whereas PME implicitly assumes that the given constraints are the only constraints that are operating. Since this assumption can be wrong, PME values may have to be revised when subsequent data shows evidence for more constraints. The entropy concentration previously "proved" by E. T. Jaynes is shown to be in error. Further, we show that PME is a generalized form of independence assumption, and so can be a very powerful method of inference when the variables being investigated are largely independent of each other.

Cheeseman, Peter↗

A novel multistage estimation of signal parameters

A multistage estimation scheme is presented for estimating the parameters of a received carrier signal possibly phase-modulated by unknown data and experiencing very high Doppler, Doppler rate, etc. Such a situation arises, for example, in the case of the Global Positioning Systems (GPS). In the proposed scheme, the first-stage estimator operates as a coarse estimator of the frequency and its derivatives, resulting in higher rms estimation errors but with a relatively small probability of the frequency estimation error exceeding one-half of the sampling frequency (an event termed cycle slip). The second stage of the estimator operates on the error signal available from the first stage, refining the overall estimates, and in the process also reduces the number of cycle slips. The first-stage algorithm is a modified least-squares algorithm operating on the differential signal model and referred to as differential least squares (DLS). The second-stage algorithm is an extended Kalman filter, which yields the estimate of the phase as well as refining the frequency estimate. A major advantage of the is a reduction in the threshold for the received carrier power-to-noise power spectral density ratio (CNR) as compared with the threshold achievable by either of the algorithms alone.

Kumar, Rajendra↗

Evaluation of a methodology for model identification in the time domain

A model identification methodology for structural dynamics has been applied to simulated vibrational data as a first step in evaluating its accuracy. The evaluation has taken into account a wide variety of factors which affect the accuracy of the procedure. The effects of each of these factors were observed in both the response time histories and the estimates of the parameters of the model by comparing them with the exact values of the system. Each factor was varied independently but combinations of these have also been considered in an effort to simulate real situations. The results of the tests have shown that for the chain model, the procedure yields robust estimates of the stiffness parameters under the conditions studied whenever uniqueness is ensured. When inaccuracies occur in the results, they are intimately related to non-uniqueness conditions inherent in the inverse problem and not to shortcomings in the methodology.

Beck, R. T.↗

Determination of stability derivatives from flight data using a Newton-Raphson minimization technique

A modified Newton-Raphson or quasilinearization minimization technique for determining stability derivatives from flight data was developed and compared with simple-equations, analog-matching, least-squares, and Shinbrot methods of analysis. For the data analyzed, the solutions computed by using the estimates obtained from the Newton-Raphson technique fit the data and determined coefficients adequately. A further modification to include a priori information was found to be useful. A model statistically similar to the flight data was analyzed using the same methods (excluding analog matching), and the Newton-Raphson technique was found to yield superior estimates. An approximate Cramer-Rao bound was compared with the error covariance matrix of the model and was found to provide information about the reliability of the individual estimates obtained. The technique was successfully applied to data obtained from a light airplane, a large supersonic airplane, and a lifting body vehicle. It was shown that the reliability of the estimates of a given coefficient obtained from these vehicles depends upon the data analyzed.

Iliff, K. W.↗

An entropy and viscosity corrected potential method for rotor performance prediction

An unsteady Full-Potential Rotor code (FPR) has been enhanced with modifications directed at improving its drag prediction capability. The shock generated entropy has been included to provide solutions comparable to the Euler equations. A weakly interacted integral boundary layer has also been coupled to FPR in order to estimate skin-friction drag. Pressure distributions, shock positions, and drag comparisons are made with various data sets derived from two-dimensional airfoil, hovering, and advancing high speed rotor tests. In all these comparisons, the effect of the nonisentropic modification improves (i.e., weakens) the shock strength and wave drag. In addition, the boundary layer method yields reasonable estimates of skin-friction drag. Airfoil drag and hover torque data comparisons are excellent, as are predicted shock strength and positions for a high speed advancing rotor.

Bridgeman, John O.↗

Magnectic Probing of Core Geodynamics

To better understand geomagnetic theory and observation, we can use spatial magnetic spectra for the main field and secular variation to test core dynamical hypotheses against seismology. The hypotheses lead to theoretical spectra which are fitted to observational spectra. Each fit yields an estimate of the radius of Earth s core and uncertainty. If this agrees with the seismologic value, then the hypotheses pass the test. A new way to obtain theoretical spectra extends the hydromagnetic scale analysis of Benton to scale-variant field and flow. For narrow scale flow and a dynamically weak field by the top of Earth s core, this yields a JGR-PI, and a secular variation spectrum modulated by a cubic polynomial in spherical harmonic degree n. The former passes the tests. The latter passes many tests, but does not describe rapid dipole decline and quadrupole rebound; some tests suggest it is a bit hard, or rich in narrow scale change.In a core geodynamo, motion of the fluid conductor does work against the Lorentz force. This converts kinetic into magnetic energy which, in turn, is lost to heat via Ohmic dissipation. In the analysis at length- scale l/k, if one presumes kinetic energy is converted in either eddy- overturning or magnetic free-decay time-scales, then Kolmogorov or other spectra in conflict with observational spectra can result. Instead, the rate work is done roughly balances the dissipation rate, which is consistent with small scale flow. The conversion time-scale depends on dynamical constraints. These are summarized by the magneto- geostrophic vertical vorticity balance by the top of the core, which includes anisotropic effects of rotation, the magnetic field, and the core-mantle boundary. The resulting theoretical spectra for the core- source field and its SV are far more compatible with observation. The conversion time-scale of order 120 years is pseudo-scale-invariant. Magnetic spectra of other planets may differ; however, if a transition to non-conducting fluid hydrogen in Jupiter acts as barrier to vertical flow, as well as current, then the shape of the jovi-magnetic spectrum could be remarkably Earth-like.

Voorhies, Coerte↗

Magnetic Probing of Core Geodynamics

To better understand geomagnetic theory and observation, we can use spatial magnetic spectra for the main field and secular variation to test core dynamical hypotheses against seismology. The hypotheses lead to theoretical spectra which are fitted to observational spectra. Each fit yields an estimate of the radius of Earth's core and uncertainty. If this agrees with the seismologic value, then the hypothesis passes the test. A new way to obtain theoretical spectra extends the hydromagnetic scale analysis of Benton to scale-variant field and flow. For narrow scale flow and a dynamically weak field by the top of Earth's core, this yields a generalized Stevenson-McLeod spectrum for the core-source field, and a secular variation spectrum modulated by a cubic polynomial in spherical harmonic degree n. The former passes the tests. The latter passes many tests, but does not describe rapid dipole decline and quadrupole rebound; some tests suggest it is a bit hard, or rich in narrow scale range. In a core geodynamo, motion of the fluid conductor does work against the Lorentz force. This converts kinetic into magnetic energy which, in turn, is lost to heat via Ohmic dissipation. In the analysis at length-scale 1/k, if one presumes kinetic energy is converted in either eddy-overturning or magnetic free-decay time-scales, then Kolmogorov or other spectra in conflict with observational spectra can result. Instead, the rate work is done roughly balances the dissipation rate, which is consistent with small-scale flow. The conversion time-scale depends on dynamical constraints. These are summarized by the magnetogeostrophic vertical vorticity balance by the top of the core, which includes anisotropic effects of rotation, the magnetic field, and the core-mantle boundary. The resulting theoretical spectra for the core-source field and its SV are far more compatible with observation. The conversion time-scale of order 120 years is pseudo-scale-invariant. Magnetic spectra of other planets may differ; however, if a transition to non-conducting fluid hydrogen in Jupiter acts as a barrier to vertical flow, as well as current, then the shape of the jovi-magnetic spectrum could be remarkably Earth-like.

Voorhies, Coerte V.↗

Magnetic Probing of Core Geodynamics

To better understand geomagnetic theory and observation, we can use spatial magnetic spectra for the main field and secular variation to test core dynmcal hypotheses against seismology. The hypotheses lead to theoretical spectra which are fitted to observational spectra. Each fit yields an estimate of the radius of Earth's core and uncertainty. If this agrees with the seismologic value, then the hypothes pass the test. A new way to obtain theoretical spectra extends the hydromagnetic scale analysis of Benton to scale-variant field and flow. For narrow scale flow and a dynamically weak field by the top of Earth's core, this yields a generalized Stevenson-McLeod spectrum for the core-source field, and a secular variation spectrum modulated by a cubic polynomial in spherical harmonic degree n. The former passes the tests. The latter passes many tests, but does not describe rapid dipole decline and quadrupole rebound; some tests suggest it is a bit hard, or rich in narrow scale change. In a core geodynamo, motion of the fluid conductor does work against the Lorentz force. This converts kinetic into magnetic energy which, in turn, is lost to heat via Ohmic dissipation. In the analysis at lentgh-scale l/k, if one presumes kinetic energy is converted in either eddy- overturning or magnetic free-decay time-scales, then Kolmogorov or other spectra in conflict with observational spectra can result. Instead, the rate work is done roughly balances the dissipation rate, which is consistent with small scale flow. The conversion time-scale depends on dynamical constraints. These are summarized by the magneto-geostrophic vertical vorticity balance by the top of the core, which includes anisotropic effects of rotation, the magnetic field, and the core- mantle boundary. The resulting theoretical spectra for the core-source field and its SV are far more compatible with observation. The conversion time-scale of order l20 years is pseudo-scale-invarient. Magnetic spectra of other planets may differ; however, if a transition to non-conductmg fluid hydrogen in Jupiter acts as barrier to vertical flow, as well as current, then the shape of the jovi-magnetic spectrum could be remarkably Earth-like.

Voorhies, Coerte V.↗

Reanalysis Surface Mass Balance of the Greenland Ice Sheet along K-transect (2000-2014)

Accurate estimates of surface mass balance over the Greenland ice sheet (GrIS) would contribute to understanding the cause of recent changes and would help to better estimate the future contribution of the GrIS to sea-level rise. Given the limitations of in-situ measurement, modeling, and remote sensing, it is critical to explore the opportunity to merge the available data to better characterize the spatial and temporal variation of the GrIS surface mass balance (SMB). This work utilizes a particle batch smoother data assimilation technique that yields SMB estimates that benefit from the snow model Crocus and a 16-day albedo product derived from satellite remote sensing data. Comparison of the results against in-situ SMB measurements shows that the assimilation of the albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB by 51% and reduces bias by 95%.

Greenland Ice Sheet↗

Helium abundance of the sun.

Critical review of the four methods that have been used to estimate the ratio of helium to hydrogen in the sun - the solar neutrino flux, spectral intensity of helium lines in prominences and the chromosphere, elemental abundance of solar cosmic rays, and variations of solar wind He/H. At present the measured value for the neutrino flux cannot be explained by any of the theoretical models of the sun, and thus the neutrino measurements cannot yield an estimate of He/H. Helium line intensity measurements give the most accurate values for He/H now available - i.e., 5 to 8% helium by number. However, these results refer to the chromosphere and prominences only, and questions of spatial and temporal variations of the observed quantities and of the inferred helium abundances have not yet been dealt with adequately.

Hirshberg, J.↗

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally distributed single-catchment locations for a 10-yr experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF consistently increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone, and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results additionally demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Rolf Reichle↗

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally-distributed single-catchment locations for a 10-year experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF systematically increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results also demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Soil moisture↗

A Nonlinear Reduced Order Method for Prediction of Acoustic Fatigue

The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing geometrically nonlinear random vibrations. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

Przekop, Adam↗