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At least 37 records · Page 2

Sampling of Space-Based Observations of XCO2 Associated With Biomass Burning Events

- The OCO-2 Level 3 assimilation product fills in gaps where OCO-2 does not have observations. - Although the Level 3 clearly shows the increased CO2 over the Amazon associated with the September 2017 biomass burning event, the total amount of CO2 may be underestimated because of a sampling bias. - The TCCON observations match fairly well with the OCO-2 observations and can be used to estimate the accuracy of the OCO observations and the temporal sampling bias. However, since it is a remotely sensed product, it may suffer the same sampling biases associated with biomass burning events as OCO-2. - Although aircraft data show that there is a significant variation in xCO2 with altitude, they suggest the OCO-2 fused products created by kriging may be better than the assimilated product at detecting large deviations from the average state on daily and regional scales.

Thomas J. Hearty, III↗

Biases in Total Precipitable Water Vapor Climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer

We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.

Atmospheric Infrared Sounder (AIRS)↗

Unsupervised atomic data mining via multi-kernel graph autoencoders for machine learning force fields

Constructing a chemically diverse dataset while avoiding sampling bias is critical to training efficient and generalizable force fields. However, in computational chemistry and materials science, many common dataset generation techniques are prone to oversampling regions of the potential energy surface. Furthermore, these regions can be difficult to identify and isolate from each other or may not align well with human intuition, making it challenging to systematically remove bias in the dataset. While traditional clustering and pruning (down-sampling) approaches can be useful for this, they can often lead to information loss or a failure to properly identify distinct regions of the potential energy surface due to difficulties associated with the high dimensionality of atomic descriptors. In this work, we introduce the Multi-kernel Edge Attention-based Graph Autoencoder (MEAGraph) model, an unsupervised approach for analyzing atomic datasets. MEAGraph combines multiple linear kernel transformations with attention-based message passing to capture geometric sensitivity and enable effective dataset pruning without relying on labels or extensive training. Demonstrated applications on niobium, tantalum, and iron datasets show that MEAGraph efficiently groups similar atomic environments, allowing for the use of basic pruning techniques for removing sampling bias. This approach provides an effective method for representation learning and clustering that can be used for data analysis, outlier detection, and dataset optimization.

Materials science↗

NASA GRC and MSFC Space-Plasma Arc Testing Procedures

Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space flight Center (MSFC) for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing testing standardization. To be discussed are: 1. Neutral pressures, neutral gases, and vacuum chamber sizes. 2. Electron and ion densities, plasma uniformity, sample sizes, and Debye lengths. 3. Biasing samples versus self-generated voltages. Floating samples versus grounded. 4. Power supplies and current limits. Isolation of samples from power supplies during arcs. Arc circuits. Capacitance during biased arc-threshold tests. Capacitance during sustained arcing and damage tests. Arc detection. Preventing sustained discharges during testing. 5. Real array or structure samples versus idealized samples. 6. Validity of LEO tests for GEO samples. 7. Extracting arc threshold information from arc rate versus voltage tests. 8 . Snapover and current collection at positive sample bias. Glows at positive bias. Kapton pyrolization. 9. Trigger arc thresholds. Sustained arc thresholds. Paschen discharge during sustained arcing. 10. Testing for Paschen discharge thresholds. Testing for dielectric breakdown thresholds. Testing for tether arcing. 11. Testing in very dense plasmas (ie thruster plumes). 12. Arc mitigation strategies. Charging mitigation strategies. Models. 13. Analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.

Ferguson, Dale C.a↗

NASA GRC and MSFC Space-Plasma Arc Testing Procedures

Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space Flight Center (MSFC) in Huntsville, Alabama, for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing-testing standardization. To be discussed are: 1.Neutral pressures, neutral gases, and vacuum chamber sizes. 2. Electron and ion densities, plasma uniformity, sample sizes, and Debuy lengths. 3. Biasing samples versus self-generated voltages. Floating samples versus grounded. 4. Power supplies and current limits. Isolation of samples from power supplies during arcs. 5. Arc circuits. Capacitance during biased arc-threshold tests. Capacitance during sustained arcing and damage tests. Arc detection. Prevention sustained discharges during testing. 6. Real array or structure samples versus idealized samples. 7. Validity of LEO tests for GEO samples. 8. Extracting arc threshold information from arc rate versus voltage tests. 9. Snapover and current collection at positive sample bias. Glows at positive bias. Kapon (R) pyrolisis. 10. Trigger arc thresholds. Sustained arc thresholds. Paschen discharge during sustained arcing. 11. Testing for Paschen discharge threshold. Testing for dielectric breakdown thresholds. Testing for tether arcing. 12. Testing in very dense plasmas (ie thruster plumes). 13. Arc mitigation strategies. Charging mitigation strategies. Models. 14. Analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.

Ferguson, Dale C.↗

Methods and devices configured to operated scanning tunneling microscopes using out-of-bandwidth frequency components added to bias voltage and related software

In the system and method disclosed, an ultrahigh vacuum (UHV) scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from the Si(100)-2X1:H surface by injecting electrons at a negative sample bias voltage. A new lithography method is disclosed that allows the STM to operate under imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative sample bias voltage to deliver the required energy for hydrogen removal. The resulted current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM's feedback loop. This approach offers a significant potential for controlled and precise removal of hydrogen atoms from a hydrogen-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

Moheimani, Seyed Omid Reza↗

Methods and devices configured to operated scanning tunneling microscopes using out-of-bandwidth frequency components added to bias voltage and related software

In the system and method disclosed, an ultrahigh vacuum (UHV) scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from the Si(100)-2X1:H surface by injecting electrons at a negative sample bias voltage. A new lithography method is disclosed that allows the STM to operate under imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative sample bias voltage to deliver the required energy for hydrogen removal. The resulted current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM's feedback loop. This approach offers a significant potential for controlled and precise removal of hydrogen atoms from a hydrogen-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

Moheimani, Seyed Omid Reza↗

A Novel Optical Instrument for On-Line Measurement of Particle Size Distribution—Application to Clean Coal Technologies

A flow cell is a critical measurement interface for many optical instruments. However, the flows are often sampled under harsh conditions, such as under high pressure and/or high temperature, in the presence of particles, moisture, vapors with high dew points or corrosive gases. Therefore, obtaining a high-optical-quality flow cell that does not perturb the measurement is a significant challenge. To address this challenge, we proposed a new flow cell that employs a unique laminar coaxial flow field (for the purge and sample flows). A test system was built to conduct particle size distribution (PSD) measurements with no sampling bias using a state-of-the-art analyzer (Malvern Panalytical Insitec). The results revealed that the measurement zone is well defined solely by the sample flow, and the optical windows are well protected by the purge flow, with minimal risk of any depositions from the sample flow. Using this flow cell, the Insitec can successfully measure PSD under high pressure and temperature under moist, corrosive conditions without generating any sampling bias. Importantly, we successfully applied this flow cell for on-line PSD measurement for the flue gas of a 100 kWth pressurized oxy-coal combustor operating at 15 bara.

Cheng, Mao (ORCID:0000000213273900)↗

Near-Cloud Aerosol Properties from the 1 Km Resolution MODIS Ocean Product

This study examines aerosol properties in the vicinity of clouds by analyzing high-resolution atmospheric correction parameters provided in the MODIS (Moderate Resolution Imaging Spectroradiometer) ocean color product. The study analyzes data from a 2 week long period of September in 10 years, covering a large area in the northeast Atlantic Ocean. The results indicate that on the one hand, the Quality Assessment (QA) flags of the ocean color product successfully eliminate cloud-related uncertainties in ocean parameters such as chlorophyll content, but on the other hand, using the flags introduces a sampling bias in atmospheric products such as aerosol optical thickness (AOT) and Angstrom exponent. Therefore, researchers need to select QA flags by balancing the risks of increased retrieval uncertainties and sampling biases. Using an optimal set of QA flags, the results reveal substantial increases in optical thickness near clouds-on average the increase is 50% for the roughly half of pixels within 5 km from clouds and is accompanied by a roughly matching increase in particle size. Theoretical simulations show that the 50% increase in 550nm AOT changes instantaneous direct aerosol radiative forcing by up to 8W/m2 and that the radiative impact is significantly larger if observed near-cloud changes are attributed to aerosol particles as opposed to undetected cloud particles. These results underline that accounting for near-cloud areas and understanding the causes of near-cloud particle changes are critical for accurate calculations of direct aerosol radiative forcing.

near-cloud aerosols↗

CO2 Flux Estimation Errors Associated with Moist Atmospheric Processes

Vertical transport by moist sub-grid scale processes such as deep convection is a well-known source of uncertainty in CO2 source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO2, and source/sink inversion has not yet been established. By using the same offline transport model with meteorological fields from slightly different data assimilation systems, we examine sensitivity of frontal CO2 transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO2 gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO2 variations contained in moist poleward moving air masses are systematically different from variations in dry equatorward moving air. Moist poleward transport is hidden from orbital sensors on satellites, causing a sampling bias, which leads directly to small but systematic flux retrieval errors in northern mid-latitudes. Second, differences in the representation of moist sub-grid vertical transport in GEOS-4 and GEOS-5 meteorological fields cause differences in vertical gradients of CO2, which leads to systematic differences in moist poleward and dry equatorward CO2 transport and therefore the fraction of CO2 variations hidden in moist air from satellites. As a result, sampling biases are amplified and regional scale flux errors enhanced, most notably in Europe (0.43+/-0.35 PgC /yr). These results, cast from the perspective of moist frontal transport processes, support previous arguments that the vertical gradient of CO2 is a major source of uncertainty in source/sink inversion.

moist atmospheric processes↗

J-PLUS: Uncovering a large population of extreme [OIII] emitters in the local Universe

Over the past decades, several studies have discovered a population of galaxies that undergo very strong star formation events. They are called extreme emission line galaxies (EELGs). We exploit the capabilities of the Javalambre Photometric Local Universe Survey (J-PLUS), a wide-field multifilter survey, with which 2000 square degrees of the northern sky are already observed. We use it to identify EELGs at low redshift by their [OIII]5007 emission line. We intend to provide a more complete, deep, and less biased sample of local EELGs. We selected objects with an excess of flux in the J-PLUS medium-band J0515 filter, which covers the [OIII] line at z < 0.06. We removed contaminants (stars and higher-redshift systems) using J-PLUS and WISE infrared photometry, with SDSS spectra as a benchmark. We performed spectral energy distribution fitting to estimate the physical properties of the galaxies: line fluxes, equivalent widths (EWs), masses, stellar population ages, and so on. We identify 466 EELGs at z < 0.06 with [OIII] EW over 300 Å and an r-band magnitude below 20, of which 411 were previously unknown. Most show compact morphologies, low stellar masses (log(M • /M ⊙ ) ~ 8.13 –0.58 +0.61 ), low dust extinction (E( B–V ) ~ 0.1 –0.1 +0.2 ), and very young bursts of star formation (3.0 –2.0 +2.7 Myr). Our method is up to ~20 times more efficient in detecting EELGs per Mpc 3 than broadband surveys, and it is as complete as magnitude-limited spectroscopic surveys (but reaches fainter objects). The sample is not directly biased against strong Hα emitters, in contrast with works using broadband surveys. We demonstrate that J-PLUS can identify a large sample of previously unknown EELGs showing unique properties following a clear selection process. A fraction of the EELGs are probably similar to the first galaxies in the Universe, but they are at a much lower redshift, which makes them ideal targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Climate and Lightning: An updated TRMM-LIS Analysis

The TRMM Lightning Imaging Sensor (LIS) has sampled global tropical and sub-tropical lightning flash densities for approximately 11 years. These data were originally processed and results presented by the authors in the 3rd AMS MALD Conference held in 2007 using both pre and post TRMM-boost lightning data. These data were normalized for the orbit boost by scaling the pre-boost data by a fixed constant based on the different swath areas for the pre and post-boost years (post-boost after 2001). Inevitably, one must question this simple approach to accounting for the orbit boost when sampling such a noisy quantity. Hence we are in the process of reprocessing the entire 11-year TRMM LIS dataset to reduce the orbit swath of the post-boost era to that of the pre-boost in order to eliminate sampling bias in the dataset. Study of the diurnal/seasonal/annual sampling suggests that those biases are already minimal and should not contribute to error in examination of annual trends. We will present new analysis of the 11-year annual trends in total lightning flash density for all latitudinal belts and select regions/regimes of the tropics as related to conventional climate signals and precipitation contents in the same period. The results should enable us to address, in some fashion, the sensitivity of the lightning flash density to subtle changes in climate.

Petersen, Walter A.↗

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗

Revisiting the role of bars in AGN fuelling with propensity score sample matching

The high luminosity displayed by an active galactic nucleus (AGN) requires that gas be transported to the centre of the galaxy by some mechanism. Bar-driven processes are often pointed out in this context and a number of studies have addressed the bar–AGN connection, but with conflicting results. Some of the inconsistencies can be explained by the different spatial- and timescales involved in bar-driven gas inflows, accretion by the central black hole, and AGN emission. However, the discrepant results could also be due to sample biases, because both the AGN activity determination and the bar detection are influenced by the method employed. We revisit the bar–AGN connection in a sample of galaxies from SDSS, looking for evidence of the influence of bars on AGN activity. We determine AGN activity by emission line diagnostics and the properties of the bar were previously estimated with BUDDA, which performs 2D bulge–bar–disk decomposition. Before comparing active and inactive galaxies, we made a careful selection of the sample to minimise selection biases. We created control samples by matching them with the AGN sample using propensity score matching. This technique offers an analytical approach for creating control samples given some object parameters. We find that AGN are preferentially found in barred galaxies and that the accretion rate is higher in barred galaxies, but only when different M–σ relations are used to estimate the black hole mass M• in barred and unbarred galaxies (from the central velocity dispersion σ). On the other hand, we find no correlation between activity level and bar strength. Altogether, our results strengthen theoretical predictions that the bar is an important mechanism in disc galaxies, creating a gas reservoir to feed AGN, but they also indicate that other mechanisms can play a major role, particularly at scales ≲100 pc.

79 ASTRONOMY AND ASTROPHYSICS↗

On the reality of a boundary in the H-R diagram between late-type stars with and without high temperature outer atmospheres

The Linsky-Haisch hypothesis (1979) that a boundary exists in the H-R diagram separating yellow giants from red giants and supergiants is tested. IUE 1150-2000 A low-resolution spectra of 10 stars chosen to constitute a reverse bias sample are presented and discussed. Despite the bias, weak C IV emission indicative of high-temperature plasma was observed in four of the six stars chosen to be probable red stars, while no C IV emission was detected in the four stars chosen to be yellows. In a second test using the entire sample of 39 stars, nearly all of the yellow giants and supergiants were found to have an emission feature at 1549 A, which is attributed to C IV. The large magnitude dispersion could be attributed to temporal or spatial variability, differing magnetic field strengths and geometries, or age-related effects during post-main-sequence evolution. It is concluded that the Linsky-Haisch transition region boundary is a real phenomenon.

Simon, T.↗

Quashing a suspected selection bias in galaxy samples having dynamically measured supermassive black holes

Local early-type galaxies (ETGs) with directly measured black hole masses, M bh , have been reported to represent a biased sample relative to the ETG population at large. Such galaxies with Spitzer Space Telescope imaging have been purported to possess velocity dispersions, σ, at least ∼0.1 dex larger for a given galaxy stellar mass, M * , gal , than is typically observed among thousands of ETGs imaged by the Sloan Digital Sky Survey (SDSS). This apparent offset led Shankar et al. to reduce the normalisation of the observed M bh ∝ σ 5 relation by at least ∼0.5 dex to give their ‘intrinsic relations’, including σ-based modifications to the observed M bh –M * , gal relation. These modifications were based on the untested assumption that the stellar masses had been derived consistently between the two samples. Here, we provide the necessary check using galaxies common to the Spitzer Survey of Stellar Structure in Galaxies (S 4 G) and the SDSS. We find that the stellar masses of galaxies with and without directly measured black hole masses had appeared offset from each other due to the use of inconsistent stellar mass-to-light ratios, Υ * , for the optical and infrared data. We briefly discuss the ‘intrinsic relations’ and why some of these will at times appear to have had partial success when applied to data based on similarly inconsistent values ofΥ * . Finally, we reiterate the importance of the υ (lower-case Υ) term, which we previously introduced into the M bh –M * relations to help avoid Υ * -related mismatches.

79 ASTRONOMY AND ASTROPHYSICS↗

The density distribution of refractory elements away from the Galactic plane

The density distributions of the three refractory elements Ti II, Ca II, and Fe II away from the Galactic plane are compared with the distribution of hydrogen and dust by examining plots of N s in b versus z. It is found that Ti II and Ca II are considerably more extended in z than the H I and dust and that Fe II has an intermediate extension. Although the results are strongly influenced by sample bias, the indicated exponential scale heights for the data sample are h(Ti II) not less than 2 kpc, h(Ca II) = 1 kpc, h(Fe II) = 0.5 kpc, H(H I) = 0.3 kpc, and h(E/B-V) = 0.1 kpc. Furthermore, it is demonstrated that Ti II and Ca II are much more smoothly distributed in space than the hydrogen or dust. The large scale heights for Ti II and Ca II and their smooth distributions are most easily understood as the effect of a mixture along the line of sight of two H I phases namely, a diffuse cloud phase, in which nearly all of the Ti and Ca are tied up in dust, and an intercloud medium, where refractory elements are less depleted. It is found that Ti II and Ca II mostly trace the smoothly distributed intercloud medium. The smoothness of the distributions of Ti II and Ca II makes them candidates for use as distance indicators.

Edgar, Richard J.↗