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At least 1,171 records · Page 65

On correcting radial orbit errors for altimetric satellites using crossover analysis

A method is proposed for correcting radial orbit error in measurements of sea surface height using a satellite altimeter. Traditionally, the orbit error is modeled in terms of a Fourier series with the Fourier coefficients determined by minimizing the residual crossover difference in a least-squares sense. In this method an a priori constraint must be imposed to obtain a unique solution. It is shown that by using singular value decomposition, no such constraint is needed. This proposed method leaves the geographically dependent errors unchanged and makes only those corrections warranted by the information contained in crossover differences. Thus, the resultant ocean topography is free from any undue distortion which might be incurred by an a priori constraint. It is suggested that the method is useful for application to high-accuracy altimetric mission, because the orbit error can be reduced without compromising the accuracy of the measured mean ocean topography.

Fu, Lee-Lueng↗

Hyper Suprime-Cam Year 3 results: Cosmology from cosmic shear power spectra

Here, we measure weak lensing cosmic shear power spectra from the 3-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers 416 deg 2 of the northern sky, with a mean i-band seeing of 0.59 arcsec and an effective galaxy number density of 15 arcmin —2 within our adopted redshift range. With an i-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning 0.3 ≤ z ph ≤ 1.5 based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range 300 < ℓ < 1800. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat Λ CDM model, we find S 8 ≡ σ 8 (Ω m /0.3) 0.5 = ${0.776}_{—0.033}^{+0.032}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a ~2σ-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of S 8 by no more than ~ 0.5σ, indicating that our result is robust to such systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Modified LTR robust control for flexible structures

A procedure is developed for dealing with performance and robustness issues in the design of multi-input multi-output compensators for lightly damped flexible structures. The procedure is based upon representing errors in the plant design model as structured uncertainties, and applying a modified version of the Loop Transfer Recovery (LTR) design method. Real parameter errors, such as frequency errors, damping errors or modal displacement errors can be treated. The approach involves adjusting the cost function in the regulator problem and the process noise model in the estimator problem in a particular manner which reflects the assumed structure of the modeling errors. Numerical examples dealing with the control of a large flexible space antenna with uncertain frequencies demonstrate a considerable improvement over standard LTR methods. Convenient design parameters can be varied until a satisfactory compromise is achieved between performance and robustness.

Blelloch, P. A.↗

LANDSAT-4 horizon scanner performance evaluation

Representative data spans covering a little more than a year since the LANDSAT-4 launch were analyzed to evaluate the flight performance of the satellite's horizon scanner. High frequency noise was filtered out by 128-point averaging. The effects of Earth oblateness and spacecraft altitude variations are modeled, and residual systematic errors are analyzed. A model for the predicted radiance effects is compared with the flight data and deficiencies in the radiance effects modeling are noted. Correction coefficients are provided for a finite Fourier series representation of the systematic errors in the data. Analysis of the seasonal dependence of the coefficients indicates the effects of some early mission problems with the reference attitudes which were computed by the onboard computer using star trackers and gyro data. The effects of sun and moon interference, unexplained anomalies in the data, and sensor noise characteristics and their power spectrum are described. The variability of full orbit data averages is shown. Plots of the sensor data for all the available data spans are included.

Bilanow, S.↗

The embedded young stars in the Taurus-Auriga molecular cloud. I - Models for spectral energy distributions

We describe radiative transfer calculations of infalling, dusty envelopes surrounding pre-main-sequence stars and use these models to derive physical properties for a sample of 21 heavily reddened young stars in the Taurus-Auriga molecular cloud. The density distributions needed to match the FIR peaks in the spectral energy distributions of these embedded sources suggest mass infall rates similar to those predicted for simple thermally supported clouds with temperatures about 10 K. Unless the dust opacities are badly in error, our models require substantial departures from spherical symmetry in the envelopes of all sources. These flattened envelopes may be produced by a combination of rotation and cavities excavated by bipolar flows. The rotating infall models of Terebey et al. (1984) models indicate a centrifugal radius of about 70 AU for many objects if rotation is the only important physical effect, and this radius is reasonably consistent with typical estimates for the sizes of circumstellar disks around T Tauri stars.

Kenyon, Scott J.↗

Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations

This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by linear parabolic partial differential equations with control inputs. It is shown that quantities that are necessary for the error estimator can be either obtained exactly as the solutions of least-squares problems in a non-intrusive way from data such as initial conditions, control inputs, and high-dimensional solution trajectories or bounded in a probabilistic sense. Here, the computational procedure follows an offline/online decomposition. In the offline (training) phase, the high-dimensional system is judiciously solved in a black-box fashion to generate data and to set up the error estimator. In the online phase, the estimator is used to bound the error of the reduced-model predictions for new initial conditions and new control inputs without recourse to the high-dimensional system. Numerical results demonstrate the workflow of the proposed approach from data to reduced models to certified predictions.

97 MATHEMATICS AND COMPUTING↗

Dark Energy Survey Year 3 results: Constraints on extensions to Λ CDM with weak lensing and galaxy clustering

We constrain six possible extensions to the Λ cold dark matter (CDM) model using measurements from the Dark Energy Survey’s first three years of observations, alone and in combination with external cosmological probes. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data vectors and blind analyses of real data to validate the robustness of our results to astrophysical and modeling systematic errors. In many cases, constraining power is limited by the absence of theoretical predictions beyond the linear regime that are reliable at our required precision. The Λ CDM extensions are dark energy with a time-dependent equation of state, nonzero spatial curvature, additional relativistic degrees of freedom, sterile neutrinos with eV-scale mass, modifications of gravitational physics, and a binned σ 8 ( z ) model which serves as a phenomenological probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find ( w p , w a ) = ( - 0.9 9 - 0.17 + 0.28 , - 0.9 ± 1.2 ) at 68% confidence with z p = 0.24 from the DES measurements alone, and ( w p , w a ) = ( - 1.0 3 - 0.03 + 0.04 , - 0. 4 - 0.3 + 0.4 ) with z p = 0.21 for the combination of all data considered. Curvature constraints of Ω k = 0.0009 ± 0.0017 and effective relativistic species N eff = 3.1 0 - 0.16 + 0.15 are dominated by external data, though adding DES information to external low-redshift probes tightens the Ω k constraints that can be made without cosmic microwave background observables by 20%. For massive sterile neutrinos, DES combined with external data improves the upper bound on the mass m eff by a factor of 3 compared to previous analyses, giving 95% limits of ( Δ N eff , m eff ) ≤ ( 0.28 , 0.20 eV ) when using priors matching a comparable Planck analysis. For modified gravity, we constrain changes to the lensing and Poisson equations controlled by functions Σ ( k , z ) = Σ 0 Ω Λ ( z ) / Ω Λ , 0 and μ ( k , z ) = μ 0 Ω Λ ( z ) / Ω Λ , 0 , respectively, to Σ 0 = 0. 6 - 0.5 + 0.4 from DES alone and ( Σ 0 , μ 0 ) = ( 0.04 ± 0.05 , 0.0 8 - 0.19 + 0.21 ) for the combination of all data, both at 68% confidence. Overall, we find no significant evidence for physics beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗

A31N-03: Lower-Tropospheric CO2 from Near-Infrared ACOS-GOSAT Observations

We present two new products from near-infrared GOSAT observations: lower tropospheric (LMT, from 0-2.5 km) and upper tropospheric/stratospheric (U, above 2.5 km) carbon dioxide partial columns. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial columns significantly improve over the ACOS-GOSAT initial guess/a priori, with distinct patterns in the LMT and U seasonal cycles which match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemisphere biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and CO/CO2 emission factor consistent with published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with monthly average error of 0.8 (1.4) ppm for ocean (land). The new LMT partial column is more locally influenced than the U partial column, meaning that local fluxes can now be separated from CO2 transported from far away.

Kulawik, Susan S.↗

Assessment of Crustal Leg Uncertainties for RSTT Path-dependent Uncertainty

The Regional Seismic Travel Time (RSTT) model and software were recently updated to allow for path-dependent uncertainty (PDU) estimates for travel-time (Begnaud et al. 2021; Begnaud et al. 2020). Begnaud et al. (2021) describes the process of improving the current distance-dependent uncertainty parameterization for RSTT using a random effects model (REM) to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The REM separates the error between observed slowness and model predicted slowness into bias and random components. The PDU is calculated by integrating these mean squared errors along a seismic-phase ray path.

58 GEOSCIENCES↗

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗

Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions

Aerosol effects on clouds and radiation are the dominant contribution to uncertainty in radiative forcing relative to the pre-industrial atmosphere. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging by condensation of semi-volatile substances and coagulation among particles. These findings suggest that structural error in modeled aerosol properties contributes to the large inter-model variability in aerosol radiative forcing.

Fierce, Laura M.↗

A Logarithmic Bayesian Approach to Quantum Error Detection

We consider the problem of continuous quantum error correction from a Bayesian perspective, proposing a pair of digital filters using logarithmic probabilities that are able to achieve near-optimal performance on a three-qubit bit-flip code, while still being reasonable to implement on low-latency hardware. These practical filters are approximations of an optimal filter that we derive explicitly for finite time steps, in contrast with previous work that has relied on stochastic differential equations such as the Wonham filter. By utilizing logarithmic probabilities, we are able to eliminate the need for explicit normalization and can reduce the Gaussian noise distribution to a simple quadratic expression. The state transitions induced by the bit-flip errors are modeled using a Markov chain, which for log-probabilities must be evaluated using a LogSumExp function. We develop the two versions of our filter by constraining this LogSumExp to have either one or two inputs, which favors either simplicity or accuracy, respectively. Using simulated data, we demonstrate that the single-term and two-term filters are able to significantly outperform both a double threshold scheme and a linearized version of the Wonham filter in tests of error detection under a wide variety of error rates and time steps.

97 MATHEMATICS AND COMPUTING↗

Another Approach to Enhance Airline Safety: Using Management Safety Tools

The ultimate goal of conducting an accident investigation is to prevent similar accidents from happening again and to make operations safer system-wide. Based on the findings extracted from the investigation, the "lesson learned" becomes a genuine part of the safety database making risk management available to safety analysts. The airline industry is no exception. In the US, the FAA has advocated the usage of the System Safety concept in enhancing safety since 2000. Yet, in today s usage of System Safety, the airline industry mainly focuses on risk management, which is a reactive process of the System Safety discipline. In order to extend the merit of System Safety and to prevent accidents beforehand, a specific System Safety tool needs to be applied; so a model of hazard prediction can be formed. To do so, the authors initiated this study by reviewing 189 final accident reports from the National Transportation Safety Board (NTSB) covering FAR Part 121 scheduled operations. The discovered accident causes (direct hazards) were categorized into 10 groups Flight Operations, Ground Crew, Turbulence, Maintenance, Foreign Object Damage (FOD), Flight Attendant, Air Traffic Control, Manufacturer, Passenger, and Federal Aviation Administration. These direct hazards were associated with 36 root factors prepared for an error-elimination model using Fault Tree Analysis (FTA), a leading tool for System Safety experts. An FTA block-diagram model was created, followed by a probability simulation of accidents. Five case studies and reports were provided in order to fully demonstrate the usefulness of System Safety tools in promoting airline safety.

Lu, Chien-tsug↗

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

Comparisons of subsonic drag estimates derived from Pioneer Venus probes flight data with wind-tunnel results

Subsonic drag coefficients have been obtained from flight data for the Pioneer Venus multiprobes. The technique used to extract the information from the data consisted of utilizing in situ pressure and temperature measurements. Analysis of the major model parameter error sources indicates overall error levels of five percent or less in the flight values of the drag coefficient. Comparisons of the flight coefficients with preflight wind-tunnel test data showed generally good agreement except for the Sounder descent probe configuration. To preclude atmospheric phenomena as a possible explanation of this difference, additional wind-tunnel tests were performed on the Sounder descent probe. Special attempts were made to duplicate the probe geometry for tests in a high Reynolds number environment in order to achieve as realistic model and flight conditions as practical. Preliminary results from this testing in the NASA LaRC Low Turbulence Pressure Tunnel produced a drag coefficient of 0.68 at 0 deg angle of attack which is within the expected accuracy limits of the flight derived drag coefficient value of 0.72 + or - 0.04, thus eliminating atmospheric phenomena as the explanation for the initial difference.

Blanchard, R. C.↗

Assimilation of Satellite Ozone Observations

This talk will discuss assimilation of ozone data from satellite-borne instruments. Satellite observations of ozone total columns and profiles have been measured by a series of Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter Ultraviolet (SBUV) instruments, and more recently by the Global Ozone Monitoring Experiment. Additional profile data are provided by instruments on NASA's Upper Atmosphere Research Satellite and by occultation instruments on other platforms. Instruments on Envisat' and future EOS Aura satellite will supply even more comprehensive data about the ozone distribution. Satellite data contain a wealth of information, but they do not provide synoptic global maps of ozone fields. These maps can be obtained through assimilation of satellite data into global chemistry and transport models. In the ozone system at NASA's Data Assimilation Office (DAO) any combination of TOMS, SBUV, and Microwave Limb sounder (MLS) data can be assimilated. We found that the addition of MLS to SBUV and TOMS data in the system helps to constrain the ozone distribution, especially in the polar night region and in the tropics. The assimilated ozone distribution in the troposphere and lower stratosphere is sensitive also to finer changes in the SBUV and TOMS data selection and to changes in error covariance models. All results are established by comparisons of assimilated ozone with independent profiles from ozone sondes and occultation instruments.

Stajner, I.↗

Constraining Black Carbon Aerosol over Asia using OMI Aerosol Absorption Optical Depth and the Adjoint of GEOS-Chem

Accurate estimates of the emissions and distribution of black carbon (BC) in the region referred to here as Southeastern Asia (70degE-l50degE, 11degS-55degN) are critical to studies of the atmospheric environment and climate change. Analysis of modeled BC concentrations compared to in situ observations indicates levels are underestimated over most of Southeast Asia when using any of four different emission inventories. We thus attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem model and its adjoint for April and October of 2006. Overwhelming enhancements, up to 500%, in anthropogenic BC emissions are shown after optimization over broad areas of Southeast Asia in April. In October, the optimization of anthropogenic emissions yields a slight reduction (1-5%) over India and parts of southern China, while emissions increase by 10-50% over eastern China. Observational data from in situ measurements and AERONET observations are used to evaluate the BC inversions and assess the bias between OMI and AERONET AAOD. Low biases in BC concentrations are improved or corrected in most eastern and central sites over China after optimization, while the constrained model still underestimates concentrations in Indian sites in both April and October, possibly as a. consequence of low prior emissions. Model resolution errors may contribute up to a factor of 2.5 to the underestimate of surface BC concentrations over northern India. We also compare the optimized results using different anthropogenic emission inventories and discuss the sensitivity of top-down constraints on anthropogenic emissions with respect to biomass burning emissions. In addition, the impacts of brown carbon, the formulation of the observation operator, and different a priori constraints on the optimization are investigated. Overall, despite these limitations and uncertainties, using OMI AAOD to constrain BC sources improves model representation of BC distributions, particularly over China.

Aerosols↗

Software reliability: A comparison of results obtained from established software reliability models

Two models of the software error detection process are compared, the Jelinski-Moranda model and a Bayes inference model. Simulation techniques are used to generate software related system failure data which is analyzed by both models. Point estimates and confidence limits are compared. It is demonstrated that uncertainty may be considerable for reasonable samples sizes and should be considered in any application of these techniques. The Jelinski-Moranda model is sensitive to the failure of data to follow internal assumptions of the model, often not providing any point estimates, a factor which may limit its usefulness in many real world situations. The Bayes model is shown to respond to the introduction of additional errors in the software correction process, a condition where error counting models such as the Jelinski-Moranda generally fail to converge.

Horn, M. H.↗