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At least 667 records · Page 37

Secure Mass Measurements From Transit Timing: 10 Kepler Exoplanets Between 3 and 8M⊕ with Diverse Densities and Incident Fluxes

We infer dynamical masses in eight multiplanet systems using transit times measured from Keplerʼs complete dataset, including short-cadence data where available. Of the 18 dynamical masses that we infer, 10 pass multiple tests for robustness. These are in systems Kepler-26 (KOI-250), Kepler-29 (KOI-738), Kepler-60 (KOI-2086), Kepler-105 (KOI-115), and Kepler-307 (KOI-1576). Kepler -105 c has a radius of 1.3R⊕ and a density consistent with an Earth-like composition. Strong transit timing variation (TTV) signals were detected from additional planets, but their inferred masses were sensitive to outliers or consistent solutions could not be found with independently measured transit times, including planets orbiting Kepler-49 (KOI-248), Kepler-57 (KOI-1270), Kepler-105 (KOI-115), and Kepler-177 (KOI-523). Nonetheless, strong upper limits on the mass of Kepler-177 cimply an extremely low density of 0.1 g cm−3. In most cases, individual orbital eccentricities were poorly constrained owing to degeneracies in TTV inversion. For five planet pairs in our sample, strong secular interactions imply a moderate to high likelihood of apsidal alignment over a wide range of possible eccentricities. We also find solutions for the three planets known to orbit Kepler-60 in a Laplace-like resonance chain. However, nonlibrating solutions also match the transit timing data. For six systems, we calculate more precise stellar parameters than previously known, enabling useful constraints on planetary densities where we have secure mass measurements. Placing these exoplanets on the mass–radius diagram, we find that a wide range of densities is observed among sub-Neptune-mass planets and that the range in observed densities is anticorrelated with incident flux.

Stars individual↗

Space-Time Data fusion for Remote Sensing Applications

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

carbon dioxide↗

The size of the lunar core

A 0.2 arc second phase shift in the 18.6 year forced precession of the lunar figure was inferred from analysis of lunar laser ranging data. The source of the phase shift is either viscous friction at a lunar core mantle boundary or solid friction caused by tidal flexing of the Moon by the Earth. Core mantle viscous coupling will explain the signature if the core radius R sub c approximately equals 330 km. On the other hand, solid friction can account for the signature only if the lunar solid friction 0 approximately equals 30 is abnormally small compared with that observed for, say, Mars (approximately equals 100 - 200). Although the inferred core radius is certainly within the limits imposed by the Apollo seismic experiment, it is significantly smaller than estimates of order 400-500 km from electromagnetic sounding. How accurate is the estimate of the R sub c derived from the phase shift? The effect of uncertainties in the frictional coupling mechanism, core density and ellipticity on the inferred core radius are discussed. The excitation of lunar free librations by core turbulence vis-a-vis other mechanisms (e.g., cometary or asteroidal impacts) and the influence of changes in lunar precession in the past on lunar dynamo generation are also examined.

Yoder, C. F.↗

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗

Altimeter observations of the Peru-Chile countercurrent

Data from Geosat and TOPEX altimeters are used to infer the structure of the Peru-Chile Countercurrent, a jet that flows from at least as far north as 10 deg S (historical data suggest 7 deg S) to 35 deg - 40 deg S, maintaining its position between approximately 100-300 km offshore. Although the annual mean current cannot be determined from altimeter observations, the nearly antisymmetric patterns in spring and fall, combined with historical observations, suggest that the countercurrent is poleward at most times and is maximum in spring and minimum in fall. Previous studies have linked the offshore countercurrent at 7 deg S to the Equatorial Undercurrent west of the Galapagos Islands, suggesting that the countercurrent is part of a continuous flow that extends from the western equatorial Pacific to the region off Chile between 35 deg - 40 deg S.

Strub, P. Ted↗

Solar-Geophysical Data Number 496, February 1986. Part 1: (Prompt reports). Data for January 1986,December 1985 and late data

Solar-Geophysical Data Number 498, February 1986, Part 1 (Prompt Reports), Data for January 1986, December 1985 and Late Data contains the following:detailed index for 1985-86; data for January 1986--(IUWDS alert periods (advanced and worldwide), Solar activity indices, Solar flares, Solar radio emission, Vostok inferred interplanetary magnetic field polarity, Stanford mean solar magnetic field); data for December 1985--(Solar active regions, Sudden ionospheric disturbances, Solar radio spectral observations, Cosmic ray measurements by neutron monitor, Geomagnetic indices, Radio propagation indices); late data--(Solar radio emission Nancay interferometric chart December 1985, Solar radio spectral observations Culgoora May 1985, Geomagnetic indices sudden commencements November 1985, Calcium plage data).

Coffey, H. E.↗

Solar-geophysical data number 499, March 1986. Part 1: (Prompt reports). Data for February 1986, January 1986 and late data

Solar-Geophysical Data Number 499, March 1986, Part 1 (Prompt Reports); Data for February 1986, January 1986 and Late Data, contains the following: Detailed index for 1985 to 1986; Data for February 1986--(IUWDS alert periods (Advance and worldwide), Solar activity indices, Solar flares, Solar radio emission, Vostok inferred interplanetary magnetic field polarity, Stanford mean solar magnetic field); data for January 1986--(Solar active regions, Sudden ionospheric disturbances, Solar radio spectral observations, Cosmic ray measurements by neutron monitor, Geomagnetic indices, Radio propagation indices); Late data-(Solar active regions, Solar radio spectral observations Culgoora, Cosmic ray measurements by neutron monitor, Calcium plage data).

Coffey, H. E.↗

Magnetic canopies and models of the solar chromosphere

Magnetic canopies are the topologies formed by magnetic field lines as they spread from compact, nearly vertical concentrations of flux in the low photosphere into the large-scale organization of the corona and heliosphere. Analytical techniques for inferring the base-heights of canopies from magnetographic data are reviewed together with observational evidence that much of the sun is covered by canopies which lie two or more pressure scale heights below the level which is traditionally inferred from thin flux tube models. Implications of these results for modeling the structure and energetics of the chromosphere are discussed, and it is argued that future models should be based upon both spectroscopic and polarimetric data. Recent improvements in magnetostatic model atmospheres are reviewed, and new observational data, including C IV Doppler-grams from the Ultraviolet Spectrometer and Polarimeter on the Solar Maximum Mission, are considered. Directions for future research in MHD modeling of canopies, in simulating spectrographic and polarimetric data from such models, and in observational programs are discussed.

Jones, H. P.↗

TMS for Instantiating a Knowledge Base With Incomplete Data

A computer program that belongs to the class known among software experts as output truth-maintenance-systems (output TMSs) has been devised as one of a number of software tools for reducing the size of the knowledge base that must be searched during execution of artificial- intelligence software of the rule-based inference-engine type in a case in which data are missing. This program determines whether the consequences of activation of two or more rules can be combined without causing a logical inconsistency. For example, in a case involving hypothetical scenarios that could lead to turning a given device on or off, the program determines whether a scenario involving a given combination of rules could lead to turning the device both on and off at the same time, in which case that combination of rules would not be included in the scenario.

James, Mark↗

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Bell, Thomas L.↗

Comparison of Profile Total Ozone from SBUV (v8.6) with GOME-Type and Ground-Based Total Ozone for a 16-Year Period (1996 to 2011)

This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile total ozone, (ii) GTO (GOME-type total ozone), and (iii) ground-based total ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0-30degS, 0-30degN, 50-30degS, and 30-60degN. It has been found that, on average, the differences in monthly zonal mean total ozone vary between −0.3 and 0.8% and are well within 1 %. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.6-0.7% and 2.8-3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4-0.6% and 2.2-3.5 %. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4-2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1%/yr (−0.1 and 0.3DU/yr). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multiyear total ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30-60degN from −5% in 1996 to −2% in 2010. In contrast, at 50-30degS and 30degS- 30degN there has been a leveling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1 %, but a slight increase has been found in the differences during the period 1996-2010.

trends↗

Multi-system report integration using blackboards

Blackboards are an Al problem solving methodology. A blackboard system consists of a structured data base (the blackboard) holding input and derived inferences and a collection of procedures for deriving inferences (knowledge sources). Each knowledge source is specialized to operate on some portion of the blackboard. The knowledge sources are invoked opportunistically as the information on the blackboard increases. The methodology is well suited to integrating multiple streams of fully reduced and qualitatively different data such as active radar track reports, passive electronic intelligence reports, and human intelligence reports about enemy intentions. This paper sketches the nature of the blackboard problem solving methodology with an emphasis on those features suiting it to such applications. The sketch is illustrated with examples from a relatively simple multi-system report integration problem. Relevant applications currently under development at Stanford's Knowledge Systems Laboratory are also described.

Delaney, J. R.↗

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗

Using the VAHIRR Radar Algorithm to Investigate Lightning Cessation

Accurately determining the threat posed by lightning is a major area for improved operational forecasts. Most efforts have focused on the initiation of lightning within a storm, with far less effort spent investigating lightning cessation. Understanding both components, initiation and cessation, are vital to improving lightning safety. Few organizations actively forecast lightning onset or cessation. One such organization is the 45th Weather Squadron (45WS) for the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45WS has identified that charged anvil clouds remain a major threat of continued lightning and can greatly extend the window of a potential lightning strike. Furthermore, no discernable trend of total lightning activity has been observed consistently for all storms. This highlights the need for more research to find a robust method of knowing when a storm will cease producing lightning. Previous lightning cessation work has primarily focused on forecasting the cessation of cloud-to -ground lightning only. A more recent, statistical study involved total lightning (both cloud-to-ground and intracloud). Each of these previous works has helped the 45WS take steps forward in creating improved and ultimately safer lightning cessation forecasts. Each study has either relied on radar data or recommended increased use of radar data to improve cessation forecasts. The reasoning is that radar data is able to either directly or by proxy infer more about dynamical environment leading to cloud electrification and eventually lightning cessation. The authors of this project are focusing on a two ]step approach to better incorporate radar data and total lightning to improve cessation forecasts. This project will utilize the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) algorithm originally developed during the Airborne Field Mill II (ABFM II) research project. During the project, the VAHIRR product showed a trend of increasing values with increases in the electric field magnitude above 3 kV/m. An extreme value analysis showed that VAHIRR values less than or equal to 10 dBZ-km showed that the probability of having an electric field magnitude larger than 3 kV/m was less than one in ten thousand. VAHIRR also was found to be sensitive at indicating anvil clouds that posed a threat of initiating a lightning flash. This project seeks to use VAHIRR to analyze its utility as a lightning cessation tool, particularly dealing with the threat posed by detached anvils. The results from this project will serve as a baseline effectiveness of radar ]based lightning cessation algorithms. This baseline will be used in the second, and concurrent work by the co ]author fs who are developing a lightning cessation algorithm based on dual ]polarimetric radar data. Ultimately, an accurate method for identifying lightning cessation can save money on lost manpower time as well as greatly improve lightning safety.

Stano, Geoffrey T.↗

Dynamics of planetary atmospheres

The overall goal is to illuminate the mechanisms that control weather and climate on the Earth and other planets. Each planet presents its own puzzling behavior - the stability of jets and vortices in Jupiter's otherwise turbulent atmosphere, the superrotation of the Venus atmosphere, the interplay of dust, polar volatiles, and climate change in Mars, the supersonic meteorology of Io, and the counterintuitive equator-to-pole temperature gradients on the outer planets. The data sets are generally those obtained from spacecraft - cloud-tracked winds, radiometrically inferred temperatures, and the results of in situ observations where appropriate. The approach includes both data analysis and modeling, ranging from analytic modeling to time-dependent numerical modeling of atmospheric dynamics. The latter approach involves the use of supercomputers such as the San Diego Cray. Progress is generally made when a model with a small number of free parameters either fits a data set that has a large number of independent observations or applies to several planets at once.

Ingersoll, Andrew P.↗

A NICER view of PSR J0030+0451: Implications for the Dense Matter Equation of State

Both the mass and radius of the millisecond pulsar PSRJ0030+0451 have been inferred via pulse-profile modeling of X-ray data obtained by NASA’s Neutron Star Interior Composition Explorer (NICER) mission. In this Letter we study the implications of the mass–radius inference reported for this source by Riley et al. for the dense matter equation of state (EoS), in the context of prior information from nuclear physics at low densities. Using a Bayesian framework we infer central densities and EoS properties for two choices of high-density extensions: a piecewise-polytropic model and a model based on assumptions of the speed of sound in dense matter. Around nuclear saturation density these extensions are matched to an EoS uncertainty band obtained from calculations based on chiral effective field theory interactions, which provide a realistic description of atomic nuclei as well as empirical nuclear matter properties within uncertainties. We further constrain EoS expectations with input from the current highest measured pulsar mass; together, these constraints offer a narrow Bayesian prior informed by theory as well as laboratory and astrophysical measurements. The NICER mass–radius likelihood function derived by Riley et al. using pulse-profile modeling is consistent with the highest-density region of this prior. The present relatively large uncertainties on mass and radius for PSR J0030+0451 offer, however, only a weak posterior information gain over the prior. We explore the sensitivity to the inferred geometry of the heated regions that give rise to the pulsed emission, and find a small increase in posterior gain for an alternative (but less preferred) model. Lastly, we investigate the hypothetical scenario of increasing the NICER exposure time for PSRJ0030+0451.

G Raaijmakers↗