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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

BICEP/Keck. XVII. Line-of-sight Distortion Analysis: Estimates of Gravitational Lensing, Anisotropic Cosmic Birefringence, Patchy Reionization, and Systematic Errors

We present estimates of line-of-sight distortion fields derived from the 95 and 150 GHz data taken by BICEP2, BICEP3, and the Keck Array up to the 2018 observing season, leading to cosmological constraints and a study of instrumental and astrophysical systematics. Cosmological constraints are derived from three of the distortion fields concerning gravitational lensing from large-scale structure, polarization rotation from magnetic fields or an axion-like field, and the screening effect of patchy reionization. We measure an amplitude of the lensing power spectrum ${A}_{L}^{\phi \phi }=0.95\pm 0.20$. We constrain polarization rotation, expressed as the coupling constant of a Chern–Simons electromagnetic term g aγ ≤ 2.6 × 10 -2 /H I , where H I is the inflationary Hubble parameter, and an amplitude of primordial magnetic fields smoothed over 1 Mpc B 1Mpc ≤ 6.6 nG at 95 GHz. We constrain the rms of optical depth fluctuations in a simple "crinkly surface" model of patchy reionization, finding A τ < 0.19 (2σ) for the coherence scale of L c = 100. We show that all of the distortion fields of the 95 and 150 GHz polarization maps are consistent with simulations including lensed ΛCDM, dust, and noise, with no evidence for instrumental systematics. In some cases, the EB and TB quadratic estimators presented here are more sensitive than our previous map-based null tests at identifying and rejecting spurious B-modes that might arise from instrumental effects. Finally, we verify that the standard deprojection filtering in the BICEP/Keck data processing is effective at removing temperature to polarization leakage.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Very long baseline IPS observations of the solar wind speed in the fast polar streams

Observations of intensity scintillation (IPS) with two or more spaced antennas have been widely used to measure the solar wind velocity. Such methods are particularly valuable in regions which spacecraft have not yet penetrated, but they are also very useful in improving the spatial temporal sampling of the solar wind, even in regions where spacecraft data are available. The principle of the measurement is to measure the time delay tau(sub d) between the scintillations observed with an antenna baseline b. The velocity estimate is just V = b/tau(sub d). The error in estimation of the time delay delta tau(sub d) is independent of the baseline length, thus the error in the velocity estimate delta V given by delta(V)/V approximately equals to (delta tau(sub d))/tau(sub d) is inversely proportional to tau(sub d) and hence to b. However the use of a long baseline b has a less obvious advantage; it provides a means for separating fast and slow contributions when both are present in the scattering region. Here we will present recent observations made using the large cylinder antenna at Ooty in the Nilgiri Hills of South India, and one of the 45 m dishes of GMRT near Pune in West-Central India. The baseline of 900 km is, by a considerable margin, the longest ever used for IPS and provides excellent velocity resolution. These results compared with the ULYSSES observations and other IPS measurements made closer to the sun with higher frequency instruments such as EISCAT and the VLBA will provide a precise measure of the velocity profile of the fast north-polar stream.

Rao, A. Pramesh↗
NASA NTRS1987

Recent data quality and earth science results from the Landsat thematic mapper

The results of the NASA Landsat Image Data Quality Analysis (LIDQA) program are reviewed. Landsat-4 and Landsat-5 TM data quality with regard to image geometry and radiometry are discussed. The results indicate that the TM provides excellent imagery that can be used in the form of satellite image maps meeting cartographic standards at scales of 1:100,000 or smaller. These data can be used to locate features or guide the revision or updating of maps for scales up to 1:24,000. The TM sensor is also providing data of good radiometric quality and stability, with radiometric uncertainties of 1 percent or smaller. The temperature dependence in the absolute radiometry is on the order of 1 to 5 percent of full scale. In terms of bidirectional reflectance estimated at the satellite, the error is estimated at under 6 percent and commonly 3 percent. Preliminary results also corroborate the utility of the TM data for geological or geographical studies.

Salomonson, Vincent V.↗
NASA NTRS1993

Orbit determination covariance analysis for the Deep Space Program Science Experiment mission

To define an appropriate orbit support procedure for the DSPSE mission, detailed permission orbit determination covariance analyses have been performed for the translunar and trans-Geographos mission phases. Preliminary analyses were also performed for the lunar mapping mission phase. These analyses are designed to assess the tracking patterns and the amount of tracking data needed to obtain orbit solutions of required accuracy for each mission phase and before and after each major orbit perturbation, such as orbit maneuvers and flybys of the Earth and Moon. In addition to operational orbit determination procedures, these analyses identify major error sources, estimate their contribution to orbital errors, and address possible strategies to reduce orbit determination error. For the lunar orbit phase, several lunar gravity error modeling approaches have been investigated. The covariance analysis results presented in this paper will serve as a guide for providing orbit determination support for the DSPSE mission.

Beckman, M.↗
NASA NTRS2002

Global Surface Temperature Change and Uncertainties Since 1861

The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

Shen, Samuel S. P.↗
NASA NTRS2012

Achievable Precision for Optical Ranging Systems

Achievable RMS errors in estimating the phase, frequency, and intensity of a direct-detected intensity-modulated optical pulse train are presented. For each parameter, the Cramer-Rao-Bound (CRB) is derived and the performance of the Maximum Likelihood estimator is illustrated. Approximations to the CRBs are provided, enabling an intuitive understanding of estimator behavior as a function of the signaling parameters. The results are compared to achievable RMS errors in estimating the same parameters from a sinusoidal waveform in additive white Gaussian noise. This establishes a framework for a performance comparison of radio frequency (RF) and optical science. Comparisons are made using parameters for state-of-the-art deep-space RF and optical links. Degradations to the achievable errors due to clock phase noise and detector jitter are illustrated.

estimation theory↗
NASA NTRS1980

The relative importance of noise level and number of events on human reactions to noise: Community survey findings and study methods

The data from seven surveys of community response to environmental noise are reanalyzed to assess the relative influence of peak noise levels and the numbers of noise events on human response. The surveys do not agree on the value of the tradeoff between the effects of noise level and numbers of events. The value of the tradeoff cannot be confidently specified in any survey because the tradeoff estimate may have a large standard error of estimate and because the tradeoff estimate may be seriously biased by unknown noise measurement errors. Some evidence suggests a decrease in annoyance with very high numbers of noise events but this evidence is not strong enough to lead to the rejection of the conventionally accepted assumption that annoyance is related to a log transformation of the number of noise events.

Fields, J. M.↗
NASA NTRS1994

Estimating Antenna-Pointing Error Using A Focal-Plane Array

Common method of determining residual errors in pointing of paraboloidal-reflector microwave antennas involves constantly dithering antenna mechanically about estimated direction of source. For cases where expense of additional focal-plane collecting horns (and their amplifiers) justified, new method eliminates mechanical dithering. Outputs of multiple receiving feed horns processed to extract phase information indicative of direction of arrival of signal received from distant source.

Zohar, Shalhav↗
NASA NTRS2016

On the Calculation of Uncertainty Statistics with Error Bounds for CFD Calculations Containing Random Parameters and Fields

This chapter discusses the ongoing development of combined uncertainty and error bound estimates for computational fluid dynamics (CFD) calculations subject to imposed random parameters and random fields. An objective of this work is the construction of computable error bound formulas for output uncertainty statistics that guide CFD practitioners in systematically determining how accurately CFD realizations should be approximated and how accurately uncertainty statistics should be approximated for output quantities of interest. Formal error bounds formulas for moment statistics that properly account for the presence of numerical errors in CFD calculations and numerical quadrature errors in the calculation of moment statistics have been previously presented in [8]. In this past work, hierarchical node-nested dense and sparse tensor product quadratures are used to calculate moment statistics integrals. In the present work, a framework has been developed that exploits the hierarchical structure of these quadratures in order to simplify the calculation of an estimate of the quadrature error needed in error bound formulas. When signed estimates of realization error are available, this signed error may also be used to estimate output quantity of interest probability densities as a means to assess the impact of realization error on these density estimates. Numerical results are presented for CFD problems with uncertainty to demonstrate the capabilities of this framework.

Uncertainty↗
NASA NTRS2010

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Simon, Donald L.↗
NASA NTRS1983

On the error in crop acreage estimation using satellite (LANDSAT) data

The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

Chhikara, R.↗
NASA NTRS1985

A water-vapor radiometer error model

The water-vapor radiometer (WVR) is used to calibrate unpredictable delays in the wet component of the troposphere in geodetic microwave techniques such as very-long-baseline interferometry (VLBI) and Global Positioning System (GPS) tracking. Based on experience with Jet Propulsion Laboratory (JPL) instruments, the current level of accuracy in wet-troposphere calibration limits the accuracy of local vertical measurements to 5-10 cm. The goal for the near future is 1-3 cm. Although the WVR is currently the best calibration method, many instruments are prone to systematic error. In this paper, a treatment of WVR data is proposed and evaluated. This treatment reduces the effect of WVR systematic errors by estimating parameters that specify an assumed functional form for the error. The assumed form of the treatment is evaluated by comparing the results of two similar WVR's operating near each other. Finally, the observability of the error parameters is estimated by covariance analysis.

Beckman, B.↗
NASA NTRS1988

Digital phase-lock loop having an estimator and predictor of error

A digital phase-lock loop (DPLL) which generates a signal with a phase that approximates the phase of a received signal with a linear estimator. The effect of a complication associated with non-zero transport delays related to DPLL mechanization is then compensated by a predictor. The estimator provides recursive estimates of phase, frequency, and higher order derivatives, while the predictor compensates for transport lag inherent in the loop.

Statman, Joseph I.↗
NASA NTRS2013

Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.

Remotely sensed soil moisture validation↗
NASA NTRS1975

Stochastic process approximation for recursive estimation with guaranteed bound on the error covariance

An approach, is proposed for the design of approximate, fixed order, discrete time realizations of stochastic processes from the output covariance over a finite time interval, was proposed. No restrictive assumptions are imposed on the process; it can be nonstationary and lead to a high dimension realization. Classes of fixed order models are defined, having the joint covariance matrix of the combined vector of the outputs in the interval of definition greater or equal than the process covariance; (the difference matrix is nonnegative definite). The design is achieved by minimizing, in one of those classes, a measure of the approximation between the model and the process evaluated by the trace of the difference of the respective covariance matrices. Models belonging to these classes have the notable property that, under the same measurement system and estimator structure, the output estimation error covariance matrix computed on the model is an upper bound of the corresponding covariance on the real process. An application of the approach is illustrated by the modeling of random meteorological wind profiles from the statistical analysis of historical data.

Menga, G.↗
NASA NTRS1994

Profile shape dependence in backscattered ultraviolet satellite retrievals of total ozone

Total ozone operational algorithms use climatological mean ozone profiles. When the actual ozone profiles have significantly different shapes versus the climatology and the solar zenith angles are large, retrieved total ozone will have an error. Recalibrated SBUV profiles are used to estimate this error. Preliminary results suggest that, on the average, the change and variation in significant profiles shapes can to a large degree be estimated by the SBUV derived profiles. Preliminary results suggest the average error in the report algorithm ozone trend (trend in reported ozone) from profile shape is relatively small during the north hemisphere winter (less than 2 percent) for solar zenith angles less than 82 degrees (for 60 degrees North Latitude).

Taylor, S. L.↗
NASA NTRS2014

Development, Validation, and Application of OSSEs at NASA-GMAO

The GMAO OSSE framework has two general classes of applications. One is to estimate the potential improvements to weather forecasting and analysis by using new proposed instruments that are not as yet built or deployed. This exploits the simulated nature of the OSSE. The other is to assess various aspects of the GMAO data assimilation system. This exploits the availability of truth provided by the OSSE. Two examples of the first class of application will be offered. One concerns deployment of constellations of passive MW sounders on small CUBESATs placed in very low orbits. The other concern is increasing the frequency of radiosonde observations to 4-times daily at all current stations. Several examples of the second class will also be presented. One is an estimation of analysis error characteristics. Another is a comparison between covariances directly determined from explicitly known background errors and those estimated by computing differences between lagged forecasts using the NMC-method prior to tuning. A third is a comparison of effects of model and observation errors on analysis and forecast skill. The last is an examination of spectra of forecast errors in a study of predictability. This latter is an ongoing study.

OSSE↗
NASA NTRS1993

Spectral characteristics of time-dependent orbit errors in altimeter height measurements

A mean reference surface and time-dependent orbit errors are estimated simultaneously for each exact-repeat ground track from the first two years of Geosat sea level estimates based on the Goddard Earth model (GEM)-T2 orbits. Motivated by orbit theory and empirical analysis of Geosat data, the time-dependent orbit errors are modeled as 1 cycle per revolution (cpr) sinusoids with slowly varying amplitude and phase. The method recovers the known 'bow tie effect' introduced by the existence of force model errors within the precision orbit determination (POD) procedure used to generate the GEM-T2 orbits. The bow tie pattern of 1-cpr orbit errors is characterized by small amplitudes near the middle and larger amplitudes (up to 160 cm in the 2 yr of data considered here) near the ends of each 5- to 6-day orbit arc over which the POD force model is integrated. A detailed examination of these bow tie patterns reveals the existence of daily modulations of the amplitudes of the 1-cpr sinusoid orbit errors with typical and maximum peak-to-peak ranges of about 14 cm and 30 cm, respectively. The method also identifies a daily variation in the mean orbit error with typical and maximum peak-to-peak ranges of about 6 and 30 cm, respectively, that is unrelated to the predominant 1-cpr orbit error. Application of the simultaneous solution method to the much less accurate Geosat height estimates based on the Naval Astronautics Group orbits concludes that the accuracy of POD is not important for collinear altimetric studies of time-dependent mesoscale variability (wavelengths shorter than 1000 km), as long as the time-dependent orbit errors are dominated by 1-cpr variability and a long-arc (several orbital periods) orbit error estimation scheme such as that presented here is used.

Chelton, Dudley B.↗