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DOE OSTI2023

Global variance decomposition of downscaled and bias-corrected CMIP6 climate projections

This dataset provides the results of a global variance decomposition of downscaled and bias-corrected CMIP6 climate projections. The total projection variance for a set of climate metrics is partitioned into contributions from: scenario uncertainty, model/GCM uncertainty, downscaling and bias-correction uncertainty, and interannual variability. The contribution from each source is expressed as a percentage of the total variance. Seven climate metrics are analyzed: Annual average temperature (avg_tas.nc) Annual total precipitation (tot_pr.nc) Annual maximum of daily maximum temperature (max_tasmax.nc) Annual maximum 1-day precipitation (max_pr.nc) Annual number of extremely hot days (hot_days.nc) Annual number of extremely wet days (wet_days.nc) Annual number of dry days (dry_days.nc) Extremely hot/wet days are defined to occur when temperature/precipitation exceeds the local 99th percentile defined over 1980-2014. Dry days are defined to occur when daily precipitation is less than 1mm. all_metrics_timesliced.nc gives the results for all metrics averaged over three 20-year periods: 2020-2039, 2050-2069, 2080-2099. For more details on the methods, see: Lafferty & Sriver, Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6, npj Climate & Atmospheric Science (2023) An interactive visualization of this data can be found at: https://lafferty-sriver-2023-downscaling-uncertainty.msdlive.org

Lafferty, David↗

DOE OSTI2020

Biases in genome reconstruction from metagenomic data

Background Advances in sequencing, assembly, and assortment of contigs into species-specific bins has enabled the reconstruction of genomes from metagenomic data (MAGs). Though a powerful technique, it is difficult to determine whether assembly and binning techniques are accurate when applied to environmental metagenomes due to a lack of complete reference genome sequences against which to check the resulting MAGs. Methods We compared MAGs derived from an enrichment culture containing ~20 organisms to complete genome sequences of 10 organisms isolated from the enrichment culture. Factors commonly considered in binning software—nucleotide composition and sequence repetitiveness—were calculated for both the correctly binned and not-binned regions. This direct comparison revealed biases in sequence characteristics and gene content in the not-binned regions. Additionally, the composition of three public data sets representing MAGs reconstructed from the Tara Oceans metagenomic data was compared to a set of representative genomes available through NCBI RefSeq to verify that the biases identified were observable in more complex data sets and using three contemporary binning software packages. Results Repeat sequences were frequently not binned in the genome reconstruction processes, as were sequence regions with variant nucleotide composition. Genes encoded on the not-binned regions were strongly biased towards ribosomal RNAs, transfer RNAs, mobile element functions and genes of unknown function. Our results support genome reconstruction as a robust process and suggest that reconstructions determined to be >90% complete are likely to effectively represent organismal function; however, population-level genotypic heterogeneity in natural populations, such as uneven distribution of plasmids, can lead to incorrect inferences.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Some effects of bias errors in redundant flight control systems.

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, e.g., individual actuator commands, are not controllable, although the sum of the command signals is well-behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of 'nuisance trips' in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs. Results of numerical solutions confirm the problem and its solutions.

Stengel, R. F.↗

NASA NTRS1972

Some effects of bias errors in redundant flight control systems

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, or individual actuator commands, are not controllable, although the sum of the command signals is well-behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of nuisance trips in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs. Results of numerical solutions confirm the problem and its solutions.

Stengel, R. F.↗

NASA NTRS1973

Some effects of bias errors in redundant flight control systems.

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, e.g., individual actuator-commands, are not controllable, although the sum of the command signals is well behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of nuisance trips in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs.

Stengel, R. F.↗

NASA NTRS1976

Drag bias feedback for the analytic drag control entry guidance system

The Analytic Drag Control (ADC) entry guidance has been developed and baselined for the space shuttle orbiter entry. A method is presented which corrects the orbiter entry guidance commanded bank angle for biases between navigated drag and guidance computed reference drag. This is accomplished by an integral feedback technique, which uses the drag bias information to adjust the difference between navigated and reference altitude rate used by the ADC guidance. The method improves the capability of the ADC guidance system by compensating for any error source which causes a bias between the navigated drag and reference drag profile. These errors include navigated altitude rate errors, atmosphere dispersions, and roll attitude deadband effects. A discussion of the method and results of digital computer entry simulations is presented.

Kyle, H. C.↗

NASA NTRS1975

Geometrical procedures for the analysis of spacecraft attitude and bias determinability

Geometrical procedures are presented for predicting the determinability of spacecraft attitude and bias parameters. An analysis is presented on three common attitude measurements: sun angle, nadir angle, and sun-to-earth mid-scan rotation angle. First, the geometry of these measurements is considered for an arbitrary fixed location of the spacecraft; then the effect of orbital motion is analyzed. The results are summarized in a set of simple geometrical rules. The application of these rules to the Synchronous Meteorological Satellite-2 (SMS-2) is discussed. As a result of this geometrical analysis, modifications were made to the SMS-2 bias determination schedule which substantially enhanced the determinability of attitude sensor biases.

Wertz, J. R.↗

NASA NTRS1977

Evaluation of an infrared horizon scanner bias determination algorithm for earth-oriented spacecraft

An algorithm for estimating infrared horizon scanner biases for earth-oriented spacecraft is presented. A mathematical description of the proposed algorithm is given, and the algorithm is evaluated for use by two earth-oriented spacecraft: the Applications Explorer Missions-A/Heat Capacity Mapping Mission (AEM-A/HCMM) and Seasat-A. The results of this study indicate that scanner alignment and calibration errors appear as nearly constant biases in the scanner pitch and roll data and that these constant biases can be estimated to within 0.05 degree for AEM-A and 0.03 degree for Seasat-A.

Hotovy, S. G.↗

NASA NTRS1983

A separated bias identification and state estimation algorithm for nonlinear systems

A computational algorithm for the identification of biases in discrete-time, nonlinear, stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.

Caglayan, A. K.↗

NASA NTRS1983

A bias identification and state estimation methodology for nonlinear systems

A computational algorithm for the identification of input and output biases in discrete-time nonlinear stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.

Caglayan, A. K.↗

NASA NTRS1984

Electromagnetic bias of 36-GHz radar altimeter measurements of MSL

The data reduction techniques used to determine the magnitude of electromagnetic (EM) bias in radar altimeter measurements of mean sea level (MSL) area described. Particular attention is given to the bias reduction scheme developed specifically for the Surface Contour Radar (SCR) instrument of the Ocean Topography Experiment (TOPEX). The SCR makes it possible to determine the amount of the backscattered power due to EM reflectance per unit area by measuring both the return power and elevation. Variations of backscattered power for different sea states are determined as a function of displacement of the MSL. On the basis of the recent SCR observations from aircraft, a standard error due to EM bias is predicted for MSL measurements performed with a satellite altimeter radar operating at a frequency of 36 GHz. The obtained standard error was 1 percent for regions with waves 1.9-5.5 meters in height.

Walsh, E. J.↗

NASA NTRS1988

Two biased estimation techniques in linear regression: Application to aircraft

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Klein, Vladislav↗

NASA NTRS1987

A review of sea-state bias in altimetry

The accuracy of satellite altimetric measurements of sea level is limited in part by the influence by ocean waves on the altimeter signal reflected from the sea surface. This error, termed the sea-state bias, is poorly known; yet, for such altimetric satellite missions as Topex/Poseidon, it is the largest source of error exclusive of those resulting from calculation of the satellite's ephemeris. Previous observations of sea-state bias have had a large, apparently random scatter, in the range of 1-5 percent of significant wave height; and the observations are not consistent with theoretical calculations of the bias. Further theoretical and experimental studies will be required for understanding the error with an accuracy required by future altimetric satellite missions.

Stewart, Robert↗

NASA NTRS1988

Cosmology of biased discrete symmetry breaking

The cosmological consequences of spontaneous breaking of an approximate discrete symmetry are studied. The breaking leads to formation of proto-domains of false and true vacuum separated by domain walls of thickness determined by the mass scale of the model. The cosmological evolution of the walls is extremely sensitive to the magnitude of the biasing; several scenarios are possible, depending on the interplay between the surface tension on the walls and the volume pressure from the biasing. Walls may disappear almost immediately after they form, or may live long enough to dominate the energy density of the Universe and cause power-law inflation. Limits are obtained on the biasing that characterizes each possible scenario.

Gelmini, Graciela B.↗

NASA NTRS1988

A method for modeling bias in a person's estimates of likelihoods of events

It is of practical importance in decision situations involving risk to train individuals to transform uncertainties into subjective probability estimates that are both accurate and unbiased. We have found that in decision situations involving risk, people often introduce subjective bias in their estimation of the likelihoods of events depending on whether the possible outcomes are perceived as being good or bad. Until now, however, the successful measurement of individual differences in the magnitude of such biases has not been attempted. In this paper we illustrate a modification of a procedure originally outlined by Davidson, Suppes, and Siegel (3) to allow for a quantitatively-based methodology for simultaneously estimating an individual's subjective utility and subjective probability functions. The procedure is now an interactive computer-based algorithm, DSS, that allows for the measurement of biases in probability estimation by obtaining independent measures of two subjective probability functions (S+ and S-) for winning (i.e., good outcomes) and for losing (i.e., bad outcomes) respectively for each individual, and for different experimental conditions within individuals. The algorithm and some recent empirical data are described.

Nygren, Thomas E.↗

NASA NTRS1988

Intrinsic and artificial bias in the KONUS cumulative number distribution

The known biases affecting the KONUS gamma burst cumulative number distribution are discussed and categorized as intrinsic (unavoidable) and artificial (avoidable). Artificial biases are removed to obtain a revised, more faithful representation of the true KONUS log N-log Pc, where Pc is in counts (1/0.25 s). A low Pc turnover is still apparent in the revised log N-log Pc. Conflicting claims that the KONUS log N-log Pc is compatible with a nearby disk or an isotropic, homogeneous distribution are tested using the revised log N-log Pc and a rigorous treatment of the KONUS intrinsic gamma background bias. The claims are shown to be improbable. Other possibilities and problms concerning log N-log Pc are discussed, but the need for a complete explanation of the low Pc turnover remains.

Jennings, Mark C.↗

NASA NTRS1989

Geometric bias and time coincidence in 3-dimensional laser Doppler velocimeter systems

The measurement by a three-dimensional laser Doppler velocimeter of a turbulent flow has been numerically simulated. Errors associated with the probe volume geometry and the coincidence time window concept are revealed. One type of error occurs for high system data rates when multiple particles lead to system realizations. Another error occurs associated with a geometric bias discovered in the present study. This three-dimensional ldv geometric bias exists even for single-particle realizations and regardless of the system data rate. A technique for the elimination of the geometric bias is presented.

Brown, J. L.↗

NASA NTRS1989

Parametric study of statistical bias in laser Doppler velocimetry

Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.

Gould, Richard D.↗