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At least 271 records · Page 15

Friction- and mountain-torque estimates from global atmospheric data

Seasonal, zonal surface torques between the atmosphere and the earth are estimated and compared, using data from a number of independent sources. The mountain torque is computed both from surface pressure data and from isobaric height data. The friction torque is estimated from the oceanic stress data of Hellerman and Rosenstein. Results for the total torque are inferred from atmospheric angular momentum data. Finally, the globally integrated total torque is compared with astronomical observations of the earth's rotation rate. These comparisons help us to assess the quality of the different results. Zonal torques are also computed using results from a GFDL general circulation model of the atmosphere. A comparison with the corresponding results inferred from real data is presented and interpreted in terms of model accuracy.

Wahr, J. M.↗

Venus, Earth and Mars: Present bounds on similarities and differences in bulk composition

The bulk compositions of the terrestrial planets are constrained in part by rigorous bounds derivable from geophysical data and from chemical data obtained in situ or by remote sensing. In large part, however, the bulk compositions are constrained only by the inferred plausibility of assumptions made about the processes responsible for producing planets. Present data are consistent with Venus, Earth and Mars all having solar ratios of the major, non-volatile elements. The mantle of Mars has a higher FeO content than the Earth's present upper mantle. The FeO content of the Venus mantle is poorly constrained. Abundances of minor elements are virtually unconstrained by geophysical data and only weakly constrained by existing chemical data. Inferences drawn from SNC meteorites suggest that Mars may be enriched in most volatiles relative to the Earth. Simple models in which volatiles are added in a single component probably do not accurately predict bulk volatile inventories of the planets.

Goettel, K. A.↗

Stratospheric aerosol layer detection.

The earth's daytime horizon was scanned on several occasions between 1963 and 1968. The limb was observed at six wavelengths in the ultraviolet and visible spectrum with a narrow field of view instrument on the X-15 aircraft. The inversion of such horizon observations to yield atmospheric density and the concentrations of ozone and aerosol extinctions is discussed. The most significant features of the X-15 data are effects attributed to stratospheric aerosols. Observations of both the 20-km aerosol layer and a layer at approximately 50 km are inferred from the data. Both layers apparently possess considerable variability. It is pointed out that the existence of substantial aerosol concentrations above 30 km is an important limitation of the nadir technique of determining ozone concentrations in which the earth's radiance is observed at ultraviolet wavelengths from a satellite.

Cunnold, D. M.↗

Prediction of oxidation performance of reinforced carbon-carbon material for Space Shuttle leading edges

A method was developed for predicting oxidation performance, in an earth atmospheric entry environment, of reinforced carbon-carbon material, coated for oxidation resistance. A model was developed which describes oxidation control mechanisms, and the equations defining these mechanisms were derived. These relations were used to correlate oxidation test data, and to infer pertinent rate constants. Predictions were made of material oxidation performance in a representative entry environment, and the predictions were compared with ground test data. Results indicate that the method can be successfully used for predicting material oxidation performance.

Medford, J. E.↗

The Evolution of Sulfide Tolerance in the Cyanobacteria

Understanding how the function of extant microorganisms has recorded both their evolutionary histories and their past interactions with the environment is a stated goal of astrobiology. We are taking a multidisciplinary approach to investigate the diversification of sulfide tolerance mechanisms in the cyanobacteria, which vary both in their degree of exposure to sulfide and in their capacity to tolerate this inhibitor of photosynthetic electron transport. Since conditions were very reducing during the first part of Earth's history and detrital sulfides have been found in Archean sediments, mechanisms conferring sulfide tolerance may have been important for the evolutionary success of the ancestors of extant cyanobacteria. Two tolerance mechanisms have been identified in this group: (1) resistance of photosystem II, the principal target of sulfide toxicity; and (2) maintenance of the ability to fix carbon despite photosystem II inhibition by utilizing sulfide as an electron donor in photosystem I - dependent, anoxygenic photosynthesis. We are presently collecting comparative data on aspects of sulfide physiology for laboratory clones isolated from a variety of habitats. These data will be analyzed within a phylogenetic framework inferred from molecular sequence data collected for these clones to test how frequently different mechanisms of tolerance have evolved and which tolerance mechanism evolved first. In addition, by analyzing these physiological data together with environmental sulfide data collected from our research sites using microelectrodes, we can also test whether the breadth of an organism's sulfide tolerance can be predicted from the magnitude of variation in environmental sulfide concentration it has experienced in its recent evolutionary past and whether greater average sulfide concentration and/or temporal variability in sulfide favors the evolution of a particular mechanism of sulfide tolerance.

Miller, Scott R.↗

(abstract) Measurement of Aerodynamic Roughness Using Radar Backscatter over Vegetated Surfaces

Gathering of local information from remote platforms is often a more cost-effective way of obtaining the required data type than are local measurements. A good example is the collection of wind regime data in order to infer the amount and type of aeolian transport at a given site. This paper describes a potential mechanism for remotely inferring the wind regime from synthetic aperture radar data and describes a project to estimate the practicality of using such a mechanism. Both radar backscatter and wind flow are functions of the roughness of the site under study. It is therefore reasonable to suspect that a fairly well-behaved relationship might exist between normalized radar backscatter coefficient and aerodynamic roughness length. Aeolian transport of small particles depends in turn on wind flow and is an important quantity to measure for several economic-related reasons, but the direct measurement of wind flow regime generally involves construction of wind towers and many days of data collection, making such data extremely expensive and prohibitive in areas that cannot be easily accessed. For both desert and vegetated sites where extensive wind profile data already exist, a NASA airborne multifrequency, multipolarization radar was used to acquire radar data at several incidence angles. At the vegetated sites, vegetation height varied from tens of centimeters to several meters, and surface roughness was a few centimeters.

radar↗

Heliomagnetic latitude dependence of the heliospheric magnetic field

Previous studies have revealed systematic variations of the interplanetary magnetic field with heliographic latitude. Luhmann et al. (1987) modeled Pioneer Venus (PVO) and ISEE-3 observations by assuming an asymmetric dependence on heliolatitude with stronger fields in the northern hemisphere. In a subsequent study, using data from ISEE-3/ICE and IMP-8, Burton et al. (1990) found evidence for a similar asymmetry. However, neither model has been completely successful. The model derived from PVO/ICE observations agrees quite well near solar maximum but shows significant discrepancies during the descending phase of the solar cycle. The model derived from the ICE/IMP-8 comparison suffers from significant phase delays between the difference in field magnitude at the two spacecraft and their latitude difference. In an attempt to account for these phase shifts, the IMP-8 and ICE data have been reexamined in heliomagnetic coordinates which are defined by the orientation of the solar magnetic dipole. The latitude and longitude of the dipole inferred from the data have then been compared with those implicit in source surface calculations. The IMP/ICE correlations have been extended into the recent solar maximum and descending phase. Comparisons have also been carried out between IMP-8 and Ulysses as it traveled to -30 deg south heliographic latitude.

Burton, M. E.↗

Restoration of HST images with missing data

Missing data are a fairly common problem when restoring Hubble Space Telescope observations of extended sources. On Wide Field and Planetary Camera images cosmic ray hits and CCD hot spots are the prevalent causes of data losses, whereas on Faint Object Camera images data are lossed due to reseaux marks, blemishes, areas of saturation and the omnipresent frame edges. This contribution discusses a technique for 'filling in' missing data by statistical inference using information from the surrounding pixels. The major gain consists in minimizing adverse spill-over effects to the restoration in areas neighboring those where data are missing. When the mask delineating the support of 'missing data' is made dynamic, cosmic ray hits, etc. can be detected on the fly during restoration.

Adorf, Hans-Martin↗

Compositional Analysis of Martian Soil: Synergism of APEX and MECA Experiments on MPS 2001

The APEX (ATHENA Precursor Experiment) payload for the Mars 2001 mission will analyze soil and dust with a multispectral panoramic imager and an emission spectrometer on a mast on the lander, a Moessbauer spectrometer on the lander robotic arm (RA), and APXS measurements on the Marie Curie rover. These analytical methods will provide data on elemental abundances and mineralogy. The MECA payload on the lander will apply microscopy, AFM, wet chemistry, adhesive substrates, and electrometry to determine the shape and size of particles in the soil and dust, the presence of toxic substances, and electrostatic, magnetic, and hardness qualities of particles. The two experiments will complement one another through several interactions: (1) The panoramic imager provides the geological setting in which both APEX and MECA samples are acquired, (2) The RA provides samples to MECA from the surface and subsurface and will permit APEX analytical tools access to materials below the inunediate surface, (3) Comparisons can be made between elemental analyses of the Moessbauer, IR, APXS on APEX and the wet chemistry of MECA which will define trace elements (ionic species in solution) and soil redox potential and conductivity. (4) APEX bulk compositional measurements will place MECA trace measurements in context, and similarly, MECA microscopy will provide particle size data that may correlate with compositional differences determined by the APEX instruments. Additionally, lithic fragments viewed by the NMCA microscope station should correlate with mineral/rock species inferred by APEX data, (5) If APEX instruments detect quartz for example, the scratch plates of the N4ECA microscope stage will define if a mineral of this hardness is registered during abrasion tests. This is by no means an exhaustive list of potential interactions, but it is clear that both the sheer number of analytical techniques and their complementarity should provide an analytically powerful capability for both planetary and BEDS communities.

Arvidson, R.↗

Compositional Analysis of Martian Soil: Synergism of APEX and MECA Experiments on MPS 2001

The APEX (ATHENA Precursor Experiment) payload for the Mars 2001 mission will analyze soil and dust with a multispectral panoramic imager and an emission spectrometer on a mast on the lander, a Moessbauer spectrometer on the lander robotic arm (RA), and APXS measurements on the Marie Curie rover. These analytical methods will provide data on elemental abundances and mineralogy. The MECA payload on the lander will apply microscopy, AFM, wet chemistry, adhesive substrates, and electrometry to determine the shape and size of particles in the soil and dust, the presence of toxic substances, and electrostatic, magnetic, and hardness qualities of particles. The two experiments will complement one another through several interactions: (1) The panoramic imager provides the geological setting in which both APEX and MECA samples are acquired, (2) The RA provides samples to MECA from the surface and subsurface and will permit APEX analytical tools access to materials below the immediate surface, (3) Comparisons can be made between elemental analyses of the Moessbauer, IR, APXS on APEX and the wet chemistry of MECA which will define trace elements (ionic species in solution) and soil redox potential and conductivity. (4) APEX bulk compositional measurements will place MECA trace measurements in context, and similarly, MECA microscopy will provide particle size data that may correlate with compositional differences determined by the APEX instruments. Additionally, lithic fragments viewed by the MECA microscope station should correlate with mineral/rock species inferred by APEX data, (5) If APEX instruments detect quartz for example, the scratch plates of the MECA microscope stage will define if a mineral of this hardness is registered during abrasion tests. This is by no means an exhaustive list of potential interactions, but it is clear that both the sheer number of analytical techniques and their complementarity should provide an analytically powerful capability for both planetary and HEDS communities.

Arvidson, R.↗

Hybrid Star Models in the Light of New Multimessenger Data

Abstract Recent astrophysical mass inferences of compact stars HESS J1731-347 and PSR J0952-0607, with extremely small and large masses respectively, as well as the measurement of the neutron skin of Ca in the CREX experiment challenge and constrain the models of dense matter. We examine the concept of hybrid stars—objects containing quark cores surrounded by nucleonic envelopes—as models that account for these new data along with other inferences. We employ a family of 81 nucleonic equations of state (EOSs) with variable skewness and slope of symmetry energy at saturation density and a constant speed-of-sound EOS for quark matter. For each nucleonic EOS, a family of hybrid EOSs is generated by varying the transition density, the energy jump, and the speed of sound. These models are tested against the data from GW170817 and J1731-347, which favor low-density soft EOS and J0592-0607 and J0740+6620, which require high-density stiff EOS. The addition of J0592-0607's mass measurement to the constraints has no significant impact on the parameter space of the admissible EOS, but allows us to explore the potential effect of pulsars more massive than J0740+6620, if such exists. We then examine the occurrence of twin configurations and quantify the ranges of masses and radii that they can possess. It is shown that including J1731-347 data favors EOSs that predict low-mass twins with M ≲ 1.3 M ⊙ that can be realized if the deconfinement transition density is low. If combined with large speed of sound in quark matter such models allow for maximum masses of hybrid stars in 2.0–2.6 M ⊙ .

Astronomy & Astrophysics↗

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗

Synergistic use of optical and microwave data in agrometeorological applications

Remotely sensed optical and microwave data can be synergistically used to infer land surface properties. Optical data can be used to estimate surface albedo, radiation absorption by vegetation canopies and their photosynthetic efficiencies. Vegetation canopy reflectance at red and near-infrared wavelengths can be used to correct for vegetation effect on microwave emissivities at low frequencies for estimating soil moisture. Optical data can also provide information about surface and air temperatures, precipitable water vapor, cloud top temperature and its water content. This information can be utilized to correct microwave data for atmospheric effects. These points are illustrated with theoretical analyses and by application to satellite data. The basic physical mechanisms operative at the various wavelengths are also discussed.

Myneni, R. B.↗

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

Test of Shi et al. Method to Infer the Magnetic Reconnection Geometry from Spacecraft Data: MHD Simulation with Guide Field and Antiparallel Kinetic Simulation

When analyzing data from an array of spacecraft (such as Cluster or MMS) crossing a site of magnetic reconnection, it is desirable to be able to accurately determine the orientation of the reconnection site. If the reconnection is quasi-two dimensional, there are three key directions, the direction of maximum inhomogeneity (the direction across the reconnection site), the direction of the reconnecting component of the magnetic field, and the direction of rough invariance (the "out of plane" direction). Using simulated spacecraft observations of magnetic reconnection in the geomagnetic tail, we extend our previous tests of the direction-finding method developed by Shi et al. (2005) and the method to determine the structure velocity relative to the spacecraft Vstr. These methods require data from four proximate spacecraft. We add artificial noise and calibration errors to the simulation fields, and then use the perturbed gradient of the magnetic field B and perturbed time derivative dB/dt, as described by Denton et al. (2010). Three new simulations are examined: a weakly three-dimensional, i.e., quasi-two-dimensional, MHD simulation without a guide field, a quasi-two-dimensional MHD simulation with a guide field, and a two-dimensional full dynamics kinetic simulation with inherent noise so that the apparent minimum gradient was not exactly zero, even without added artificial errors. We also examined variations of the spacecraft trajectory for the kinetic simulation. The accuracy of the directions found varied depending on the simulation and spacecraft trajectory, but all the directions could be found within about 10 for all cases. Various aspects of the method were examined, including how to choose averaging intervals and the best intervals for determining the directions and velocity. For the kinetic simulation, we also investigated in detail how the errors in the inferred gradient directions from the unmodified Shi et al. method (using the unperturbed gradient) depended on the amplitude of the calibration errors. For an accuracy of 3 for the maximum gradient direction, the calibration errors could be as large as 3% of reconnection magnetic field, while for the same accuracy for the minimum gradient direction, the calibration errors could only be as large as 0.03% of the reconnection magnetic field. These results suggest that the maximum gradient direction can normally be determined by the unmodified Shi et al. method, while the modified method or some other method must be used to accurately determine the minimum gradient direction. The structure velocity was found with magnitude accurate to 2% and direction accurate to within 5%.

Denton, R.↗

Program for Automated Real-Time Monitoring

Process-control decisions made by applying rules to process data streams. Expert System Executive computer program demonstrates feasibility of automated real-time monitoring. Using Executives knowledge of system formally coded as set of rules specifying actions taken under various conditions. Program makes inferences about observed data based on rules. Written in C language.

Goodrum, Glenn R.↗

Estimates of radiative flux divergence in the atmosphere from satellite data

Several options for the inference of the atmospheric radiative flux divergence (ARD) on the basis of satellite data are discussed. Attention is given to the clear-sky case and the cloudy-sky case. LW ARD profiles for different climatological regimes are presented and the effect of cloud base height on LW ARD divergence at various heights is illustrated.

Smith, G. L.↗