Application of an inverse model in the community modeling effort results

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 1995Inverse modeling activities in oceanography have recently been intensified, aided by the oncoming observational data stream of WOCE and the advance of computer power. However, interpretations of inverse model results from climatological hydrographic data are far from simple. This thesis examines the behavior of an inverse model in the WOCE CME (Community Modeling Effort) results where the physics and the parameter values are known. The ultimate hypotheses to be tested are whether the inferred circulations from a climatological hydrographic data set (where limited time means and spatial smoothing are usually used) represent the climatological ocean general circulations, and what the inferred "diffusion" coefficients really are. The inverse model is first tested in a non-eddy resolving numerical GCM ocean. Numerical/scale analyses are used to test whether the inverse model properly represents the GCM ocean. Experiments show how biased answers could result from an incorrect model, and how a correct model must produce the right answers. When the inverse model is applied to the time-mean hydrographic data of an eddy-resolving GCM ocean in the fine grid resolution of the GCM, the estimated horizontal circulation is statistically consistent with the EGCM time means in both patterns and values. Although the flow patterns are similar, the uncertainties for the GCM time means and the inverse model estimates are different. The former are very large, such that the GCM time-mean circulation has no significance in the deep ocean. The latter are much smaller, and with them the estimated circulations are well defined. This is consistent with the concept that ocean motions are very energetic, while variations of tracers (temperature, salinity) are low frequency. The inverse model succeeded in extracting the ocean general circulation from the "climatological" hydrographic data. The estimated vertical velocities are also statistically indistinguishable from the GCM time means. However, significant differences between the estimated "diffusion" coefficients and the EGCM eddy diffusion coefficients are found at certain locations. These discrepancies are attributed to the differences in physics of the inverse model and the EGCM ocean. The "diffusion" coefficients from the inversion parameterize not only the eddy fluxes, but also (part of) the temporal variation and biharmonic terms which are not explicitly included in the inverse model. Given the essentially red spectrum of the ocean, it makes sense to look for smooth solutions. Aliasing due to subsampling on a coarse grid and the effects of spatial smoothing are addressed in the last part of this thesis. It is shown that this aliasing could be greatly reduced by spatial smoothing. The estimated horizontal circulation from the spatially smoothed time-mean EGCM hydrographic data with a coarse grid resolution (2.4° longitude by 2.0° latitude) is generally consistent with the spatially smoothed EGCM time means. Significant differences only occur at some grid points at great depths, where the GCM circulations are very weak. The conclusions of this study are different from some previous studies. These discrepancies are explained in the concluding chapter. Finally, it should be pointed out that the issue of properly representing a GCM ocean by an inverse model is not identical to the issue of represent ing the real ocean by the same inverse model, since the GCM ocean is not identical to the real ocean. Numerical calculations show that both the non-eddy resolving and the eddy-resolving GCM oceans used in this work are evolving towards a statistical equilibrium. In the real ocean, the importance of temporal variation terms in the property conservation equations should also be analyzed when a steady mverse model is applied to a limited time-mean (the climatological) data set.This research was carried out under National Science Foundation grant OCE- 90-04396

Circulation and water mass balance in the Brazil Basin

Analysis of data from the Levitus (1982) atlas shows that the application of the Montgomery streamfunction to the potential density surfaces induces an error which cannot be ignored in some regions in the ocean. The error arises from the variation of the specific volume anomaly along isopycnal surfaces. By including the major part of this effect, new streamfunctions, named the pressure anomaly and mean pressure streamfunctions, are suggested for use in potential density coordinates. By including the variations of specific volume anomaly and pressure along isopycnal surfaces, the inverse model proposed by Hogg (1987) is modified for increased accuracy and then applied to the Brazil Basin to study the circulation, diffusion and water mass balances. The system of equations with constraints of positive diffusivities and oxygen consumption rates is solved by the inverse method. By using multiple tracers and controlling the scale of variation of the diffusion coefficients we are able to construct an overdetermined system whose solution is by a least-square approach. The results indicate that the circulation in the upper ocean is consistent with previous work, but that in the deep ocean differs from some previous analyses. In the NADW depth, we find a coincidence of flow with tongues of water properties. The diffusivities and diapycnal velocities seem stronger in the region near the equator than in the south, with reasonable values. Diffusion plays an important role in the water property balances. Examples show that similar property patterns may result from different processes

Deducing dynamic properties from simulated hydrographic data: Part I. Results from a non-eddy-resolving model

Inverse models are widely used in oceanography. However, their reliability remains an open question, as comparison of inverse model results with real values of ocean parameters is difficult due to insufficient knowledge of the latter. The feasibility of extracting the ocean general circulation, mixing rates, as well as air-sea heat and freshwater fluxes from hydrographic data is studied by applying an inverse model to the CME (Community Modeling Effort) results where both the physics and parameter values are known. The inverse model assumes approximate thermal wind balance and steady state conservation laws for mass, heat, and salt, assumptions satisfied by the GCM ocean although the residuals in the tracer conservation equations are comparable to the diffusion terms in the deep ocean. Effects of errors in these equations on inverse model solutions for different variables are studied in detail. A surface layer model is designed to estimate the air-sea heat and freshwater fluxes and the results are compared to their “true” values. Experiments on various parameterizations of different variables are carried out in the hope of getting some guidance in applying the inverse model to the real ocean. The inverse model estimates for horizontal circulation are relatively robust—they are consistent with the GCM ocean circulations in most of the experiments, and effects of equation errors are more pronounced in the estimates for diffusivity and air-sea fluxes. Residuals in the equations are noisy and resemble a random distribution. In such cases, the estimates for all the parameters are very close to their true values. The conclusions of this work are different from previous works, and the discrepancies are explained

Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral features such as mel- cepstral coefficients (MCCs), which are related to human per- ception and have been widely used in VC, have not been prop- erly investigated. Instead of using one specific type of spectral feature, it is expected that VAE may benefit from using multi- ple types of spectral features simultaneously, thereby improving the capability of VAE for VC. To this end, we propose a novel VAE framework (called cross-domain VAE, CDVAE) for VC. Specifically, the proposed framework utilizes both STRAIGHT spectra and MCCs by explicitly regularizing multiple objectives in order to constrain the behavior of the learned encoder and de- coder. Experimental results demonstrate that the proposed CD- VAE framework outperforms the conventional VAE framework in terms of subjective tests.Comment: Accepted to ISCSLP 201

Consistent Right-Invariant Fixed-Lag Smoother with Application to Visual Inertial SLAM

State estimation problems without absolute position measurements routinely arise in navigation of unmanned aerial vehicles, autonomous ground vehicles, etc., whose proper operation relies on accurate state estimates and reliable covariances. Unaware of absolute positions, these problems have immanent unobservable directions. Traditional causal estimators, however, usually gain spurious information on the unobservable directions, leading to over-confident covariance inconsistent with actual estimator errors. The consistency problem of fixed-lag smoothers (FLSs) has only been attacked by the first estimate Jacobian (FEJ) technique because of the complexity to analyze their observability property. But the FEJ has several drawbacks hampering its wide adoption. To ensure the consistency of a FLS, this paper introduces the right invariant error formulation into the FLS framework. To our knowledge, we are the first to analyze the observability of a FLS with the right invariant error. Our main contributions are twofold. As the first novelty, to bypass the complexity of analysis with the classic observability matrix, we show that observability analysis of FLSs can be done equivalently on the linearized system. Second, we prove that the inconsistency issue in the traditional FLS can be elegantly solved by the right invariant error formulation without artificially correcting Jacobians. By applying the proposed FLS to the monocular visual inertial simultaneous localization and mapping (SLAM) problem, we confirm that the method consistently estimates covariance similarly to a batch smoother in simulation and that our method achieved comparable accuracy as traditional FLSs on real data.Comment: 13 pages, 4 figures, AAAI 2021 Conferenc

Input Estimation Algorithms for Reentry Vehicle Trajectory Estimation

Fast and accurate estimation of trajectory is important in tracking and intercepting reentry vehicles. Validating model is a real challenge associated with the qverall trajectory estimation problem. Input estimation technique provides a’solution to this challenge. Two input estimation algorithms were introduced based on different assumptions about the input applied to the model. This investigation presents approaches consisting of an extended Kahnan filter and two input estimation algorithms to identify the reentry vehicle trajectory in its terminal phase using data from a single radar source. Numerical simulations with data generated from two models demonstrate superior capabilities as measured by accuracy compared to the extended Kalman filter. Evaluation using real flight data provides the consistent results. The comparison between two input estimation algorithms is also presented. The trajectory estimation approaches based on two algorithms are effective in solving the reentry vehicle tracking problem

Phase structure in the baryon density-dependent quark mass model

The properties of phase diagram of strange quark matter in equilibrium with hadronic matter at finite temperature are studied, where the quark phase and hadron phase are treated by baryon density-dependent quark mass model and hadron resonance gas model with hard core repulsion factor, respectively. Our results indicate that the strangeness fraction fs, perturbation parameter C, and confinement parameter D have strong influence on the properties of phase diagram and the formation of strangelets, where a large fs, small C and D favor the formation of strangelets. Consider the isentropic expansion process, we found that the initial entropy per baryon is about 5, which gives a large probability for the formation of strangelets. Furthermore, as the strangeness fraction fs and one gluon-exchange interaction strength C decrease and confinement parameter D increases, the reheating effect becomes more significant, reducing the possibility of forming strangelets. The new phase diagram could support a massive compact star with the maximum mass exceeding twice the solar mass and have a significant impact on the mass-radius relationship for hybrid stars

Dense Polarized Positrons from Laser-Irradiated Foil Targets in the QED Regime

Dense positrons are shown to be effectively generated from laser-solid interactions in the strong-field quantum electrodynamics (QED) regime. Whether these positrons are polarized has not yet been reported, limiting their potential applications. Here, by QED particle-in-cell simulations including electron-positron spin and photon polarization effects, we investigate a typical laser-solid setup that an ultraintense linearly polarized laser irradiates a foil target with $\mu$m-scale-length preplasma. We find that once the positron yield becomes appreciable with the laser intensity exceeding $10^{24}~\rm W/\rm cm^2$, the positrons are obviously polarized. The polarized positrons can acquire $>30\%$ polarization degree and $>30$ nC charge with a flux of $10^{12}\,{\rm sr}^{-1}$. The polarization relies on the deflected angles and can reach 60\% at some angles and energies. The angularly-dependent polarization is attributed to the asymmetrical laser fields positrons undergo in the skin layer of overdense plasma, where the radiative spin-flip and radiation reaction play significant roles. The positron polarization is robust and could generally appear in future 100-PW-class laser-solid experiments for various applications.Comment: 6 pages, 5 figures, with Supplemental Materia