SEARCH · Engineering Papers

Results for “bias correction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

NASA NTRS2015

Helium Mass Spectrometer Leak Detection: A Method to Quantify Total Measurement Uncertainty

In applications where leak rates of components or systems are evaluated against a leak rate requirement, the uncertainty of the measured leak rate must be included in the reported result. However, in the helium mass spectrometer leak detection method, the sensitivity, or resolution, of the instrument is often the only component of the total measurement uncertainty noted when reporting results. To address this shortfall, a measurement uncertainty analysis method was developed that includes the leak detector unit's resolution, repeatability, hysteresis, and drift, along with the uncertainty associated with the calibration standard. In a step-wise process, the method identifies the bias and precision components of the calibration standard, the measurement correction factor (K-factor), and the leak detector unit. Together these individual contributions to error are combined and the total measurement uncertainty is determined using the root-sum-square method. It was found that the precision component contributes more to the total uncertainty than the bias component, but the bias component is not insignificant. For helium mass spectrometer leak rate tests where unit sensitivity alone is not enough, a thorough evaluation of the measurement uncertainty such as the one presented herein should be performed and reported along with the leak rate value.

error analysis↗

NASA NTRS1986

Correcting for Nonlinearity in a Photodetector

Simple positive-feedback circuit varies bias voltage as necessary. Ideal detector biased with constant voltage, detector current proportional to photon flux plus constant offset. Detector connected between inverting input and ground, and feedback from operational amplifier through feedback resistor Rf make voltage at inverting input equal to noninverting input. Bias voltage held constant. Principle applied to linearizing mercury cadmium telluride infrared detectors in Fourier-transform spectrometers and other spectral and imaging instruments.

Schindler, R. A.↗

NASA NTRS1991

On the sea-state bias of the Geosat altimeter

The sea-state bias in a satellite altimeter's range measurement is caused by the influence of ocean waves on the radar return pulse; it results in an estimate of sea level that is too low according to some function of the wave height. This bias is here estimated for Geosat by correlating collinear differences of altimetric sea-surface heights with collinear differences of significant wave heights (H1/3). Corrections for satellite orbit error are estimated simultaneously with the sea-state bias. Based on twenty 17-day repeat cycles of the Geosat Exact Repeat Mission, the solution for the sea-state bias is 2.6 + or - 0.2 percent of H1/3. The least-squares residuals, however, show a correlation with wind speed U, so the traditional model of the bias has been supplemented with a second term: H1/3 + alpha-2H1/3U. This second term produces a small, but statistically significant, reduction in variance of the residuals. Both systematic and random errors in H1/3 and U tend to bias the estimates of alpha-1 and alpha-2, which complicates comparisons of the results with ground-based measurements of the sea-state bias.

Ray, Richard D.↗

NASA NTRS1994

Impact of Uncertainties and Errors in Converting NWS Radiosonde Hygristor Resistances to Relative Humidity

A set of 2,600 6-second, National Weather Service soundings from NASA's FIRE-II Cirrus field experiment are used to illustrate previously known errors and new potential errors in the VIZ and SDD ) brand relative humidity (RH) sensors and the MicroART processing software. The entire spectrum of RH is potentially affected by at least one of these errors. (These errors occur before being converted to dew point temperature.) Corrections to the errors are discussed. Examples are given of the effect that these errors and biases may have on numerical weather prediction and radiative transfer. The figure shows the OLR calculated for the corrected and uncorrected soundings using an 18-band radiative transfer code. The OLR differences are sufficiently large to warrant consideration when validating line-by-line radiation calculations that use radiosonde data to specify the atmospheric state, or when validating satellite retrievals. in addition, a comparison of observations of RH during FIRE-II derived from GOES satellite, raman lidar, MAPS analyses, NCAR CLASS sondes, and the NWS sondes reveals disagreement in the RH distribution and underlines our lack of an understanding of the climatology of water vapor.

Westphal, Douglas L.↗

NASA NTRS1994

Impact of Uncertainties and Errors in Converting NWS Radiosonde Hygristor Resistances to Relative Humidity

A set of 2,600 6-second, National Weather Service soundings from NASA's FIRE-II Cirrus field experiment are used to illustrate previously known errors and new potential errors in the VIZ and SDD brand relative humidity (RH) sensors and the MicroART processing software. The entire spectrum of RH is potentially affected by at least one of these errors. (These errors occur before being converted to dew point temperature.) Corrections to the errors are discussed. Examples are given of the effect that these errors and biases may have on numerical weather prediction and radiative transfer. The figure shows the OLR calculated for the corrected and uncorrected soundings using an 18-band radiative transfer code. The OLR differences are sufficiently large to warrant consideration when validating line-by-line radiation calculations that use radiosonde data to specify the atmospheric state, or when validating satellite retrievals. In addition, a comparison of observations of RE during FIRE-II derived from GOES satellite, raman lidar, MAPS analyses, NCAR CLASS sondes, and the NWS sondes reveals disagreement in the RH distribution and underlines our lack of an understanding of the climatology of water vapor.

Westphal, Douglas L.↗

NASA NTRS1979

Intercomparison of GEOS 3 tracking systems

Measurements and time biases of the GEOS 3 tracking systems in the Atlantic calibration area were determined in relation to the Goddard lasers. In collocation tests the lasers agreed with each other to about 10 cm. Early RAMLAS laser data contained an apparent time bias of 647 microsec. Later, in a laser collocation test, RAMLAS differed from MOBLAS 2 by +11.3 cm and -28 microsec. An overlooked correction reduced the -28 microsec to -8 microsec. The geoceivers initially had range rate biases of 3-6 m/s and constant time biases of several milliseconds. During the first month of GEOS 3 operations the range rate biases decreases monotonically by 2.5 + or - 1.0 m/s. The C band radar biases relative to the lasers were usually within several meters and several tenths of milliseconds. The unified S band system relative biases were usually within + or - 4 mm/s and + or - 0.1 ms. The average and scatter of the altimeter biases recovered on 18 laser reference arcs was - 5.3 + or - 0.6 m.

Berbert, J. H.↗

NASA NTRS1990

Corrections for the effects of significant wave height and attitude on Geosat radar altimeter measurements

Range estimates from a radar altimeter have biases which are a function of the significant wave height (SWH) and the satellite attitude angle (AA). Based on results of prelaunch Geosat modeling and simulation, a correction for SWH and AA was already applied to the sea-surface height estimates from Geosat's production data processing. By fitting a detailed model radar return waveform to Geosat waveform sampler data, it is possible to provide independent estimates of the height bias, the SWH, and the AA. The waveform fitting has been carried out for 10-sec averages of Geosat waveform sampler data over a wide range of SWH and AA values. The results confirm that Geosat sea-surface-height correction is good to well within the original dm-level specification, but that an additional height correction can be made at the level of several cm.

Hayne, G. S.↗

NASA NTRS2015

MISR Calibration Issues in High-Contrast Scenes, and Empirical Corrections

We diagnose the potential causes for the Multi-angle Imaging SpectroRadiometer's (MISR) persistent high aerosol optical depth (AOD) bias at low AOD with the aid of coincident MODerate-resolution Imaging Spectroradiometer (MODIS) imagery from NASA's Terra satellite. Internal reflections within the MISR instrument are responsible for a large portion of the high AOD bias in high-contrast scenes, which are especially common as broken-cloud situations over ocean. Discrepancies between MODIS and MISR nadir-viewing near-infrared (NIR) images are used to optimize nine parameters, along with a background reflectance modulation term (that was modeled separately), to represent the observed features. Independent, surface-based AOD measurements from the AErosol RObotic NETwork (AERONET) and the Marine Aerosol Network (MAN) are compared with MISR Research Algorithm (RA) AOD retrievals for 1118 coincidences to validate the corrections when applied to the nadir and off-nadir cameras. Additionally, the calibration coefficients for the red and NIR channels used for MISR over-water aerosol retrievals were reassessed with the RA to be consistent on a camera-by-camera basis. With these corrections, plus the baseline RA corrections applied (except enhanced cloud screening), the median AOD bias in the mid-visible (green) band decreases from 0.010 to 0.002, the RMSE decreases by approx. 10%, and the slope and correlation of the MISR vs. sun photometer Ångström Exponent improves. For AOD558 nm < 0.10 and with additional cloud screening, the median bias for the RA-retrieved AOD in the green band decreases from 0.011 to 0.003, compared to ~ 0.023 for the Standard Algorithm (SA). RMSE decreases by ~ 20% compared to the baseline (uncorrected) RA and by 17-53% compared to the SA. After all corrections and cloud screening are implemented, for AOD558 nm < 0.10, which includes about half the validation data, 68% absolute AOD errors for the RA have dropped to < 0.02 (approx. 0.018).

MISR↗

NASA NTRS1984

LANDSAT-4 MSS Geometric Correction: Methods and Results

An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.

Brooks, J.↗

NASA NTRS1982

Crustal interpretation of the MAGSAT data in the continental United States

The processing of MAGSAT scalar data to construct a crustal magnetic anomaly map over the continental U.S. involves removal of the reference field model, a path-by-path subtraction of a low order polynomial through a least-squares fit to reduce orbital offset errors, and a two dimensional spectral filtering to mitigate the spectral bias induced by the path-by-path orbital correction scheme. The resultant anomaly map shows reasonably good correlations with an aeromagnetic map derived from the project MAGNET. Prominent satellite magnetic anomalies are identified in terms of geological provinces and age boundaries. An inversion method was applied to MAGSAT data which produces both the Curie depth topography and laterally varying magnetic susceptibility of the crust. A contoured Curie depth map thus derived shows general agreements with a crustal thickness map based on seismic data.

Won, I. J.↗

NASA NTRS1984

Experimental studies of scaling laws for plasma collection at high voltages

Current-voltage characteristics were determined for stainless steel in a laboratory with a simulated ionospheric environment of 5 x 10 to the 11th to 2.5 x 10 to the 12th electrons/cu m. Panels with areas differing by a factor of up to 100 were biased between 0 and -2300 V. Secondary emission was corrected for using experimental data. The results indicate that the current-voltage characteristics are almost linear and that for voltages above about -500 V the current scales with characteristic panel length as L exp 1.2. Comparison with some theoretical predictions is discussed. Because of orbital velocity associated ion ram effects, the results of this study must be used with caution when applied to an orbiting spacecraft.

Konradi, A.↗

NASA NTRS1993

What determines the stellar mass functions in globular clusters?

We analyze the dependence of stellar mass function slopes for a sample of 17 globular clusters on a variety of cluster parameters. The principal novelty of our approach is the use of appropriate multivariate statistical methods to disentangle the complex situation which is present in this problem: the slopes depend simultaneously on more than one variable, and many cluster parameters are mutually correlated. We find that the mass function slopes in the range M/M(solar) = 0.5-0.8 are largely determined by the position in the Galaxy and to a lesser extent by the cluster metallicity. Clusters closer to the Galactic center or plane have shallower mass function slopes. At a given distance to the Galactic center, clusters closer to the Galactic plane have shallower mass function slopes. At a given R(GC) and/or Z(GP), more metal-rich clusters have shallower mass function slopes. Thus, the monovariate correlations with the position or metallicity are both correct, but only partial, and in terms of slopes, biased descriptions of the situation. We present trivariate least-squares solutions where the mass function slopes can be predicted within the measurement accuracy. This relation can serve as a powerful observational constraint for theories of globular cluster formation and evolution, and it is one of the tightest correlations between globular cluster properties now known.

Djorgovski, S.↗

NASA NTRS2000

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

A method is developed to retrieve surface ground temperature (T(sub g)) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing longwave radiation (CLR) is sensitive to upper level moisture (q(sub l)) over wet regions and (T(sub g)) over dry regions The clear sky window flux from 800 to 1200/cm (RadWn) is sensitive to low level moisture (q(sub t)) and T(sub g). Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub l) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in T(sub g), q(sub h) and q(sub l). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing Delta(T(sub g)) and broad layer Delta(q(sub l) from .500 hPa to surface and Delta(q(sub h)) from 200 to .300 hPa provides a good approximation to the full radiative transfer calculations. typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for Delta(T(sub g)) to about 20% for Delta(q(sub l)). Our initial application of the methodology employed an early CERES-TRMM data set (CLR and Radwn) to assess the quality of the GEOS2 data. The results showed that over the tropical and subtropical oceans GEOS2 is, in general, too wet in the upper troposphere (mean bias of 0.99 mm) and too dry in the lower troposphere (mean bias of -4.7 min). We note that these errors, as well as a cold bias in the T(sub g). have largely been corrected in the current version of GEOS-2 with the introduction of a land surface model, a moist turbulence scheme and the assimilation of SSM/I total precipitable water.

Wu, Man Li C.↗

NASA NTRS2003

Towards Automating Spacecraft Attitude Sensor Calibration

With a view towards reducing cost and complexity for spacecraft early mission support at the NASA Goddard Space Flight Center (GSFC), efforts are being made to automate the attitude sensor calibration process. This paper addresses one of the major components needed by such a system. The beneficiaries of an improved calibration process are missions that demand moderate to high precision attitude knowledge or that need to perform accurate attitude slews. Improved slew accuracy reduces the time needed for re-acquisition of fine-pointing after each attitude maneuver, Rapid target acquisition can be very important for astronomical targeting or for off-nadir surface feature targeting by Earth-oriented spacecraft. The normal sequence of on-orbit calibration starts with alignment calibration of the star trackers and possibly the Sun sensor. Their relative alignment needs to be determined using a sufficiently large data set so their fields of view are adequately sampled. Next, the inertial reference unit (IRU) is calibrated for corrections to its alignment and scale factors. The IRU biases are estimated continuously by the onboard attitude control system, but the IRU alignment and scale factors are usually determined on the ground using a batch-processing method on a data set that includes several slews sufficient to give full observability of all the IRU calibration parameters. Finally, magnetometer biases, alignment, and its coupling to the magnetic torquers are determined in order io improve momentum management and occasionally for use in the attitude determination system. The detailed approach used for automating calibrations will depend on whether the automated system resides on the ground or on the spacecraft with an ultimate goal of autonomous calibration. Current efforts focus on a ground-based system driving subsystems that could run either on the ground or onboard. The distinction is that onboard calibration should process the data sequentially rather than in a single large batch since onboard computer data storage is limited. Very good batch- processing calibration utilities have been developed and used extensively at NASA/GSFC for mission support but no sequential calibration utilities are available. To meet this need, this paper presents the mathematical description of a sequential IRU calibration system. The system has been tested using flight data from the Rossi X-ray Timing Explorer (RXTE) during a series of attitude slews. The paper also discusses the current state of the overall automated system and describes plans for adding sequential alignment calibration and other additions that will reduce the amount of analyst time and input.

Sedlak, Joseph↗

NASA NTRS2004

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to atmosphere. We anticipate future improvements in the AIRS retrieval algorithm will lead to improved understanding of the exchange of sensible and latent heat from ocean to atmosphere, and more realistic near-surface lapse rates.

cold air outbreak↗

NASA NTRS2007

First Impressions of CARTOSAT-1

CARTOSAT-1 RPCs need special handling. Absolute accuracy of uncontrolled scenes is poor (biases > 300 m). Noticeable cross-track scale error (+/- 3-4 m across stereo pair). Most errors are either biases or linear in line/sample (These are easier to correct with ground control).

Lutes, James↗

NASA NTRS2021

Simulation of Radon-222 with the GEOS-Chem Global Model: Emissions, Seasonality, and Convective Transport

Radon-222 (Rn-222) is a short-lived radioactive gas naturally emitted from land surfaces and has long been used to assess convective transport in atmospheric models. In this study, we simulate Rn-222 using the GEOS-Chem chemical transport model to improve our understanding of Rn-222 emissions and surface concentration seasonality and characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, the Modern-Era Retrospective analysis for Research and Applications (MERRA) and GEOS Forward Processing (GEOS-FP). We evaluate four global Rn-222 emission scenarios by comparing model results with observations at 51 surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with surface observations globally (68.9 % of data within a factor of 2) and a large underestimate of winter surface Rn-222 concentrations at Northern Hemisphere midlatitudes and high latitudes due to an oversimplified formulation of Rn-222 emission fluxes (1 atom cm−2 s−1 over land with a reduction by a factor of 3 under freezing conditions). We compose a new global Rn-222 emission scenario based on Zhang et al. (2011) and demonstrate its potential to improve simulated surface Rn-222 concentrations and seasonality. The regional components of this scenario include spatially and temporally varying emission fluxes derived from previous measurements of soil radium content and soil exhalation models, which are key factors in determining Rn-222 emission flux rates. However, large model underestimates of surface Rn-222 concentrations still exist in Asia, suggesting unusually high regional Rn-222 emissions. We therefore propose a conservative upscaling factor of 1.2 for Rn-222 emission fluxes in China, which was also constrained by observed deposition fluxes of 210Pb (a progeny of Rn-222). With this modification, the model shows better agreement with observations in Europe and North America (> 80 % of data within a factor of 2) and reasonable agreement in Asia (close to 70 %). Further constraints on Rn-222 emissions would require additional concentration and emission flux observations in the central United States, Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed Rn-222 vertical profiles in northern midlatitude summer and from three short-term airborne campaigns. While simulations with both GEOS products are able to capture the observed vertical gradient of Rn-222 concentrations in the lower troposphere (0–4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared with GEOS-FP, MERRA leads to stronger convective transport of Rn-222, which is partially compensated for by its weaker large-scale vertical advection, resulting in similar global vertical distributions of Rn-222 concentrations between the two simulations. This has important implications for using chemical transport models to interpret the transport of other trace species when these GEOS products are used as driving meteorology.

Bo Zhang↗

NASA NTRS2022

Validation of IMERG Oceanic Precipitation over Kwajalein

The integrated Multi-satellitE Retrievals for GPM (IMERG) Version V05B and V06B precipitation products from the Global Precipitation Measurement (GPM) mission are validated against ground-based observations from the Kwajalein Polarimetric S-band Weather Radar (KPOL) deployed at Kwajalein Atoll in the central Pacific Ocean. Such a validation is particularly important as comprehensive surface measurements over the oceans are practically infeasible, which hampers the identification of possible errors, and improvement of future versions of IMERG and other satellitebased retrieval algorithms. The V05B and V06B IMERG products are validated at their native 0.1°, 30 min resolution from 2014 to 2018 based on both volumetric and categorical metrics. This validation study indicates that precipitation rates from both IMERG V05B and V06B are underestimated with respect to radar surface estimates, but the underestimation is much reduced from V05B IMERG V06B outperforms V05B with reduced systematic bias and improved precipitation detectability. The IMERG performance is further traced back to its individual sensors and morphing-based algorithms. The overall underestimation in V05B is mainly driven by the negative relative biases from morphing-based algorithms which are largely corrected in V06B. Imagers perform generally better than sounders because of the usage of low-frequency channels in imagers which can better detect emission signals by the hydrometeors. Among imagers, the GPM Microwave Imager (GMI) and Advanced Microwave Scanning Radiometer Version 2 (AMSR2) are the best, followed by Special Sensor Microwave Imager/Sounder (SSMIS). Among sounders, the Microwave Humidity Sounder (MHS) is the best, followed by Advanced Technology Microwave Sounder (ATMS) and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) for V06B. Among all categories, morph-only and IR+morph only perform better than SAPHIR. SAPHIR shows the worst performance among all categories, likely due to its limited channel selection. It is envisaged that these results will improve our understanding of IMERG performance over oceans and aid in the improvement of future versions of IMERG.

KPOL↗