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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon,−40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., N2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10 +/- 0.88 t/ha, and the total biomass for the country, given a total forest area of 688,096 sq km, is 3.65 +/- 0.06 Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152 Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06 Gt) by 19%.

Hybrid 3-Phase sampling↗
NASA NTRS2012

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Deloach, Richard↗
NASA NTRS1990

The stability of individual patterns of autonomic responses to motion sickness stimulation

As part of a program to develop a treatment for motion sickness based on self-regulation of autonomic nervous system (ANS) activity, this study examined the stability of an individual's pattern of ANS responses to motion sickness stimulation on repeated occasions. Motion sickness symptoms were induced in 58 people during two rotating chair test. Physiological responses measured were heart rate, finger pulse volume, respiration rate, and skin conductance. Using standard scores, stability of responses of specific magnitudes across both tests is as examined. Correlational analyses, analysis of variance, and a components of variance analysis all revealed marked, but quite stable, individual differences in ANS responses to both mild and severe motion sickness. These findings confirm the prior observation that people are sufficiently unique in their ANS responses to motion sickness provocation to make it nesessary to individually tailor self-regulation training. Further, these data support the contention that individual ANS patterns are sufficiently consistent from test to test so as to serve as an objective indicator of individual motion sickness malaise levels.

Cowings, Patricia S.↗
NASA NTRS1977

Characterization of nonGaussian atmospheric turbulence for prediction of aircraft response statistics

Mathematical expressions were derived for the exceedance rates and probability density functions of aircraft response variables using a turbulence model that consists of a low frequency component plus a variance modulated Gaussian turbulence component. The functional form of experimentally observed concave exceedance curves was predicted theoretically, the strength of the concave contribution being governed by the coefficient of variation of the time fluctuating variance of the turbulence. Differences in the functional forms of response exceedance curves and probability densities also were shown to depend primarily on this same coefficient of variation. Criteria were established for the validity of the local stationary assumption that is required in the derivations of the exceedance curves and probability density functions. These criteria are shown to depend on the relative time scale of the fluctuations in the variance, the fluctuations in the turbulence itself, and on the nominal duration of the relevant aircraft impulse response function. Metrics that can be generated from turbulence recordings for testing the validity of the local stationary assumption were developed.

Mark, W. D.↗
NASA NTRS1992

Evidence of orbital forcing in 510 to 530 million year old shallow marine cycles, Utah and western Canada

Spectral analyses of two sequences of shallow marine sedimentary cycles that were deposited between 510 and 530 million years ago were completed. One sequence is from Middle Cambrian rocks in southern Utah and the other is from Upper Cambrian rocks in the southern Canadian Rockies. In spite of the antiquity of these strata, and even though there are differences in the age, location, and cycle facies between the two sequences, both records have distinct spectral peaks with surprisingly similar periodicities. A null model constructed to test for significance of the spectral peaks and circulatory in the methodology indicates that all but one of the spectral peaks are significant at the 90 percent confidence level. When the ratios between the statistically significant peaks are measured, we find a consistent relation to orbital forcing; specifically, the spectral peak ratios in both the Utah and Canadian examples imply that a significant amount of the variance in the cyclic records is driven by the short eccentricity (approximately 109 ky) and by the precessional (approximately 21 ky) components of the Earth's orbital variations. Neither section contains a significant component of variance at the period of the obliquity cycle, however.

Bond, Gerard C.↗
DOE OSTI2025

Turbulent Parameters by airborne measurements over BNF in March 2025

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 10 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Atmosphere↗
DOE OSTI2025

CHELAX-BNF: Turbulent Parameters by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 through June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Aircraft Integrated Meteorological Measurement Sys↗
NASA NTRS1984

Estimating optimal sampling unit sizes for satellite surveys

This paper reports on an approach for minimizing data loads associated with satellite-acquired data, while improving the efficiency of global crop area estimates using remotely sensed, satellite-based data. Results of a sampling unit size investigation are given that include closed-form models for both nonsampling and sampling error variances. These models provide estimates of the sampling unit sizes that effect minimal costs. Earlier findings from foundational sampling unit size studies conducted by Mahalanobis, Jessen, Cochran, and others are utilized in modeling the sampling error variance as a function of sampling unit size. A conservative nonsampling error variance model is proposed that is realistic in the remote sensing environment where one is faced with numerous unknown nonsampling errors. This approach permits the sampling unit size selection in the global crop inventorying environment to be put on a more quantitative basis while conservatively guarding against expected component error variances.

Hallum, C. R.↗
NASA NTRS1989

The proton temperature and the total hourly variance of the magnetic field components in different solar wind speed regions

A comparison has been made between the predictions of the theory for radial variations of both Alfvenic fluctuations and solar wind proton temperatures proposed by Tu (1987, 1988) and the statistical results of hourly averaged plasma and magnetic field data observed by Helios 1 and 2 from launch through 1980 for different solar wind speed regimes. The comparison shows that for speed ranges between 500-800 km/s, the radial variation of the proton temperature between 0.3 and 1 AU can be explained by heating from the cascade energy which is determined by the radial variation of the total variance of magnetic field vector.

Tu, Chuan-Yi↗
DOE OSTI2023

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr, down to δr < 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ 2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B -mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr , down to δr < 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ 2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

U. Fuskeland↗
NASA NTRS1985

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.↗
NASA NTRS1986

Variability of earth-emitted radiation from one year of Nimbus-6 ERB data

Outgoing longwave radiation (OLR) measurements from the Nimbus-6 ERB wide field-of-view instrument are used to study daytime and nighttime radiation variability on a 15 deg regional, zonal, and global scale. An analysis of components of variance is used to determine how much of the total variability is due to between-region and within-region variance. Most of the analysis is on July and January data from one year of Nimbus-6 ERB. Different geographical scales are considered: regions within latitude zones and latitude zones within hemispheres. Results show that much of the variability is spatial, peaks in the tropics and subtropics, and is concentrated in the Northern Hemisphere. Daytime variability is generally larger than nighttime variability for July but not for January. Variance in OLR in the tropics and subtropics is largely a function of cloud variability.

Bess, T. D.↗
NASA NTRS2018

Tagging Components in the Test Complex Area

Why tag components differently? - Various methods are in place to tag different components, but not every component is tracked; - Variance in method can make it difficult to obtain component information and identify discrepancies; -Time and resources are spent on component localization and verification. Previous work of RA10 interns: - Researching more efficient asset tracking methods; - Investigating cost effective ways to localize components; - Past interns identified using QR (Quick Response) codes as a potential solution. Link QR codes to Windchill (PLM - Product Lifecycle Management system) DDMS (Design and Data Management System) after QR code is printed/etched and physically tagging it as quickly as possible

Gomez, Sarah↗
NASA NTRS2011

Current Sheets in the Heliosheath: Voyager 1, 2009

We identified all of the current sheets for which we have relatively complete and accurate magnetic field (B) data from Voyager 1 (V1) from days of year (DOYs) 1 to 331, 2009, which were obtained deep in the heliosheath between 108.5 and 111.8 AU. Three types of current sheets were found: (1) 15 proton boundary layers (PBLs), (2) 10 and 3 magnetic holes and magnetic humps, respectively, and (3) 3 sector boundaries. The magnetic field strength changes across PBL, and the profile B(t) is linearly related to the hyperbolic tangent function, but the direction of B does not change. For each of the three sector boundaries, B rotated in a plane normal to the minimum variance direction, and the component of B along the minimum variance direction was zero within the uncertainties, indicating that the sector boundaries were tangential discontinuities. The structure of the sector boundaries was not as simple as that for PBLs. The average thickness of magnetic holes and humps (approx.30 RL) was twice that of the PBLs (approx.15 RL). The average thickness of the current sheets associated with sector boundaries was close to the thickness of the PBLs. Our observations are consistent with the hypothesis that magnetic holes and humps are solitons, which are initiated by the mirror mode instability, and evolve by nonlinear kinetic plasma processes to pressure balanced structures maintained by magnetization currents and proton drift currents in the gradients of B.

Burlaga, L. F.↗
NASA NTRS2010

Analysis of Wind Tunnel Polar Replicates Using the Modern Design of Experiments

The role of variance in a Modern Design of Experiments analysis of wind tunnel data is reviewed, with distinctions made between explained and unexplained variance. The partitioning of unexplained variance into systematic and random components is illustrated, with examples of the elusive systematic component provided for various types of real-world tests. The importance of detecting and defending against systematic unexplained variance in wind tunnel testing is discussed, and the random and systematic components of unexplained variance are examined for a representative wind tunnel data set acquired in a test in which a missile is used as a test article. The adverse impact of correlated (non-independent) experimental errors is described, and recommendations are offered for replication strategies that facilitate the quantification of random and systematic unexplained variance.

Deloach, Richard↗
NASA NTRS1995

Ulysses observations of latitude gradients in the heliospheric magnetic field

Several parameters measured by Ulysses as it traveled southward to heliographic latitudes of -50 deg are presented and analyzed. The radial component of the magnetic field, averaged over 5 deg latitude increments and extrapolated back to 1 AU, is found to agree with baseline measurements provided by IMP-8. There is little, if any, evidence of a latitude gradient, a result consistent with the dominance of the magnetic field associated with the heliospheric current sheet and with recent models which include the effect of the current sheet as well as of source surface fields. Thus far, the spiral angle agrees with the Parker spiral assuming a rate of rotation of the field lines at the Sun equal to the equatorial value. No evidence is seen of either a change in rotation rate with latitude or an unwinding of the spiral as suggested by a recent analysis. Hourly variances in the field magnitude and in the sum of the variances in the components, normalized to the square of the observed field strenght, show the former to be independent of latitude while the latter shows a strong increase with latitude. These two observations are shown to be associated with Alfven waves that are continuously present at high latitudes. The waves have large amplitudes, extend to long periods, and have important implications for galactic cosmic rays and the solar wind.

Smith, E. J.↗
DOE OSTI2020

Hemispherical variance anomaly and reionization optical depth

ABSTRACT Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic, with the Northern hemisphere displaying an anomalously low variance, while the Southern hemisphere appears consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM). The low signal-to-noise ratio in current polarization data prevents a similar comparison. Polarization realizations constrained by temperature data show that in ΛCDM the lack of variance is not expected to be present in polarization data. Therefore, a natural way of testing whether the temperature result is a fluke is to measure the variance of CMB polarization components. In anticipation of future CMB experiments that will allow for high-precision large-scale polarization measurements, we study how the variance of polarization depends on ΛCDM-parameter uncertainties by forecasting polarization maps with Planck’s Markov chain Monte Carlo chains. We show that polarization variance is sensitive to present uncertainties in cosmological parameters, mainly due to current poor constraints on the reionization optical depth τ, which drives variance at low multipoles. We demonstrate how the improvement in the τ measurement seen between Planck’s two latest data releases results in a tighter constraint on polarization variance expectations. Finally, we consider even smaller uncertainties on τ and how more precise measurements of τ can drive the expectation for polarization variance in a hemisphere close to that of the cosmic-variance-limited distribution.

79 ASTRONOMY AND ASTROPHYSICS↗