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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Evaluation of the Relative Contribution of Observing Systems in Reanalyses: Aircraft Temperature Bias and Analysis Innovations

Reanalyses have become important sources of data in weather and climate research. While observations are the most crucial component of the systems, few research projects consider carefully the multitudes of assimilated observations and their impact on the results. This is partly due to the diversity of observations and their individual complexity, but also due to the unfriendly nature of the data formats. Here, we discuss the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) and a companion dataset, the Gridded Innovations and Observations (GIO). GIO is simply a post-processing of the assimilated observations and their innovations (forecast error and analysis error) to a common spatio-temporal grid, following that of the MERRA analysis fields. This data includes in situ, retrieved and radiance observations that are assimilated and used in the reanalysis. While all these disparate observations and statistics are in a uniform easily accessible format, there are some limitations. Similar observations are binned to the grid, so that multiple observations are combined in the gridding process. The data is then implicitly thinned. Some details in the meta data may also be lost (e.g. aircraft or station ID). Nonetheless, the gridded observations should provide easy access to all the observations input to the reanalysis. To provide an example of the GIO data, a case study evaluating observing systems over the United States and statistics is presented, and demonstrates the evaluation of the observations and the data assimilation. The GIO data is used to collocate 200mb Radiosonde and Aircraft temperature measurements from 1979-2009. A known warm bias of the aircraft measurements is apparent compared to the radiosonde data. However, when larger quantities of aircraft data are available, they dominate the analysis and the radiosonde data become biased against the forecast. When AMSU radiances become available the radiosonde and aircraft analysis and forecast error take on an annual cycle. While this supports results of previous work that recommend bias corrections for the aircraft measurements, the interactions with AMSU radiances will also require further investigation. This also provides an example for reanalysis users in examining the available observations and their impact on the analysis. GIO data is presently available alongside the MERRA reanalysis.

Bosilovich, Michael G.↗
NASA NTRS1976

An analysis of the errors associated with the determination of atmospheric temperature from atmospheric pressure and density data

A graph was developed for relating delta T/T, the relative uncertainty in atmospheric temperature T, to delta p/p, the relative uncertainty in the atmospheric pressure p, for situations, when T is derived from the slope of the pressure-height profile. A similar graph relates delta T/T to delta roh/rho, the relative uncertainty in the atmospheric density rho, for those cases when T is derived from the downward integration of the density-height profile. A comparison of these two graphs shows that for equal uncertainties in the respective basic parameters, p or rho, smaller uncertainties in the derived temperatures are associated with density-height rather than with pressure-height data. The value of delta T/T is seen to depend not only upon delta p or delta rho, and to a small extent upon the value of T or the related scale height H, but also upon the inverse of delta h, the height increment between successive observations of p or rho. In the case of pressure-height data, delta T/T is dominated by 1/delta h for all values of delta h; for density-height data, delta T/T is dominated by delta rho/rho for delta h smaller than about 5 km. In the case of T derived from density-height data, this inverse relationship between delta T/T and delta h applies only for large values of delta h, that is, for delta h 35 km. No limit exists in the fineness of usable height resolution of T which may be derived from densities, while a fine height resolution in pressure-height data leads to temperature with unacceptably large uncertainties.

Minzner, R. A.↗
NASA NTRS1987

Results from 1984 airborne Doppler lidar wind measurement program. Flight 6: Analysis of line-of-sight elevation angle errors and apparent Doppler velocities

During the summer of 1984 the Marshall Space Flight Center's Airborne Doppler Lidar System (ADLS) made a series of wind measurements in the California Central Valley. This study quantifies the lidar beam angle errors and velocity errors through analysis of ground return signals. Line-of-sight elevation (LOSE) angle errors are under 1 deg. Apparent Doppler ground velocities, as large as 2m/s, are considerably less than in a previous flight experiment in 1981. No evidence was found of a Schuler resonance phenomenon common to inertial navigation systems (INS), however the aperiodic nature of the apparent velocities implies an error in the INS-derived ground speeds. Certain features and subtleties in the ground returns are explained in terms of atmospheric structure and characteristics of the ADLS hardware and software. Finally, least squares and low-pass filtering techniques are suggested for eliminating errors during post-processing.

Rothermel, Jeffry↗
NASA NTRS1986

Analysis of modeling errors in system identification

This paper is concerned with the identification of a system in the presence of several error sources. Following some basic definitions, the notion of 'near-equivalence in probability' is introduced using the concept of near-equivalence between a model and process. Necessary and sufficient conditions for the identifiability of system parameters are given. The effect of structural error on the parameter estimates for both deterministic and stochastic cases are considered.

Hadaegh, F. Y.↗
NASA NTRS1987

Analysis of counting errors in the phase/Doppler particle analyzer

NASA is investigating the application of the Phase Doppler measurement technique to provide improved drop sizing and liquid water content measurements in icing research. The magnitude of counting errors were analyzed because these errors contribute to inaccurate liquid water content measurements. The Phase Doppler Particle Analyzer counting errors due to data transfer losses and coincidence losses were analyzed for data input rates from 10 samples/sec to 70,000 samples/sec. Coincidence losses were calculated by determining the Poisson probability of having more than one event occurring during the droplet signal time. The magnitude of the coincidence loss can be determined, and for less than a 15 percent loss, corrections can be made. The data transfer losses were estimated for representative data transfer rates. With direct memory access enabled, data transfer losses are less than 5 percent for input rates below 2000 samples/sec. With direct memory access disabled losses exceeded 20 percent at a rate of 50 samples/sec preventing accurate number density or mass flux measurements. The data transfer losses of a new signal processor were analyzed and found to be less than 1 percent for rates under 65,000 samples/sec.

Oldenburg, John R.↗
NASA NTRS1990

Statistical analysis of modeling error in structural dynamic systems

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Hasselman, T. K.↗
NASA NTRS1996

Analysis of Drift Errors in the JPL/UCLA Micromachined Gyroscope

The model of the JPL/UCLA micromachined vibratory gyroscope will be enhanced to include time varying effects. First, they will be shown to exist through trends in the experimental results. Causes of mechanical error will be further explained by analyzing possible perturbations to the physical model.

coriolois force gyroscope gyroscope design gyrosco↗
NASA NTRS2006

Analysis of Calibration Errors for Both Short and Long Stroke White Light Experiments

This work will analyze focusing and tilt variations introduced by thermal changes in calibration processes. In particular the accuracy limits are presented for common short- and long-stroke experiments. A new, simple, practical calibration scheme is proposed and analyzed based on the SIM PlanetQuest's Micro-Arcsecond Metrology (MAM) testbed experiments.

instruments↗
NASA NTRS1985

Statistical magnetic anomalies from satellite measurements for geologic analysis

The errors of numerically averaging satellite magnetic anomaly data for geologic analysis are investigated using orbital anomaly simulations of crustal magnetic sources by Gauss-Legendre quadrature integration. These simulations suggest that numerical averaging errors constitute small and relatively minor contributions to the total error-budget of higher orbital estimates (approx. 400 km), whereas for lower orbital estimates the error of averaging may increase substantially. Least-squares collocation is also investigated as an alternative to numerical averaging and found to produce substantially more accurate anomaly estimates as the elevation of prediction is decreased towards the crustal sources.

Goyal, H. K.↗
NASA NTRS1974

Recent results on parametric analysis of differential Omega error

Previous tests of the differential Omega concept and an analysis of the characteristics of VLF propagation make it possible to delineate various factors which might contribute to the variation of errors in phase measurements at an Omega receiver site. An experimental investigation is conducted to determine the effect of each of a number of parameters on differential Omega accuracy and to develop prediction equations. The differential Omega error form is considered and preliminary results are presented of the regression analysis used to study differential error.

Baxa, E. G., Jr.↗
NASA NTRS1996

Testing and Performance Analysis of the Multichannel Error Correction Code Decoder

This report provides the test results and performance analysis of the multichannel error correction code decoder (MED) system for a regenerative satellite with asynchronous, frequency-division multiple access (FDMA) uplink channels. It discusses the system performance relative to various critical parameters: the coding length, data pattern, unique word value, unique word threshold, and adjacent-channel interference. Testing was performed under laboratory conditions and used a computer control interface with specifically developed control software to vary these parameters. Needed technologies - the high-speed Bose Chaudhuri-Hocquenghem (BCH) codec from Harris Corporation and the TRW multichannel demultiplexer/demodulator (MCDD) - were fully integrated into the mesh very small aperture terminal (VSAT) onboard processing architecture and were demonstrated.

Soni, Nitin J.↗
NASA NTRS2016

Analysis of Random Segment Errors on Coronagraph Performance

At 2015 SPIE O&P we presented "Preliminary Analysis of Random Segment Errors on Coronagraph Performance" Key Findings: Contrast Leakage for 4thorder Sinc2(X) coronagraph is 10X more sensitive to random segment piston than random tip/tilt, Fewer segments (i.e. 1 ring) or very many segments (> 16 rings) has less contrast leakage as a function of piston or tip/tilt than an aperture with 2 to 4 rings of segments. Revised Findings: Piston is only 2.5X more sensitive than Tip/Tilt

Technology↗