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At least 163 records · Page 9

A deep imaging survey of the Pleiades with ROSAT

We have obtained deep ROSAT images of three regions within the Pleiades open cluster. We have detected 317 X-ray sources in these ROSAT Position Sensitive Proportional Counter (PSPC) images, 171 of which we associate with certain or probable members of the Pleiades cluster. We detect nearly all Pleiades members with spectral types later than G0 and within 25 arcminutes of our three field centers where our sensitivity is highest. This has allowed us to derive for the first time the luminosity function for the G, K, amd M dwarfs of an open cluster without the need to use statistical techniques to account for the presence of upper limits in the data sample. Because of our high X-ray detection frequency down to the faint limit of the optical catalog, we suspect that some of our unidentified X-ray sources are previously unknown, very low-mass members of Pleiades. A large fraction of the Pleiades members detected with ROSAT have published rotational velocities. Plots of L(sub X)/L(sub Bol) versus spectroscopic rotational velocity show tightly correlated `saturation' type relations for stars with ((B - V)(sub 0)) greater than or equal to 0.60. For each of several color ranges, X-ray luminosities rise rapidly with increasing rotation rate until c sin i approximately equal to 15 km/sec, and then remains essentially flat for rotation rates up to at least v sin i approximately equal to 100 km/sec. The dispersion in rotation among low-mass stars in the Pleiades is by far the dominant contributor to the dispersion in L(sub X) at a given mass. Only about 35% of the B, A, and early F stars in the Pleiades are detected as X-ray sources in our survey. There is no correlation between X-ray flux and rotation for these stars. The X-ray luminosity function for the early-type Pleiades stars appears to be bimodal -- with only a few exceptions, we either detect these stars at fluxes in the range found for low-mass stars or we derive X-ray limits below the level found for most Pleiades dwarfs. The X-ray spectra for the early-type Pleiades stars detected by ROSAT are indistinguishable from the spectra of the low-mass Pleiades members. We believe that the simplest explanation for this behavior is that the early-type Pleiades stars are not themselves intrinsic X-ray sources and that the X-ray emission actually arises from low-mass companions to these stars.

Stauffer, J. R.↗

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

NASA's Launch Services Program, Ground Systems Development and Operations, Space Launch System and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). Examples include determining if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 km Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the high-resolution WRF Environmental Modeling System (EMS) model configured by the AMU (Watson 2013) in real time. Implementing a real-time version of the ER WRF-EMS would generate a larger database of model output than in the previous AMU task for determining model performance, and allows the AMU more control over and access to the model output archive. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The AMU also calculated verification statistics to determine model performance compared to observational data. Finally, the AMU made the model output available on the AMU Advanced Weather Interactive Processing System II (AWIPS II) servers, which allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations (RWO) AWIPS II client computers and conduct real-time subjective analyses.

Meteorology↗

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Lee, J.↗

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Weger, R. C.↗

Abundance gradients in cooling flow clusters: Ginga Large Area Counters and Einstein Solid State Spectrometer spectra of A496, A1795, A2142, and A2199

We analyze the Ginga Large Area Counters (LAC) and Einstein Solid State Spectrometer (SSS) spectra of four cooling flow clusters, A496, A1795, A2142, and A2199, each of which shows firm evidence of a relatively cool component. The inclusion of such cool spectral components in joint fits of SSS and LAC data leads to somewhat higher global temperatures than are derived from the high-energy LAC data alone. We find little evidence of cool emission outside the SSS field of view. Metal abundances appear to be centrally enhanced in all four clusters, with varying degrees of model dependence and statistical significance: the evidence is statistically strongest for A496 and A2142, somewhat weaker for A2199 and weakest for A1795. We also explore the model dependence in the amount of cold, X-ray-absorbing matter discovered in these clusters by White et al.

White, Raymond E., III↗

Methods of editing cloud and atmospheric layer affected pixels from satellite data

Practical methods of computer screening cloud-contaminated pixels from data of various satellite systems are proposed. Examples are given of the location of clouds and representative landscape features in HCMM spectral space of reflectance (VIS) vs emission (IR). Methods of screening out cloud affected HCMM are discussed. The character of subvisible absorbing-emitting atmospheric layers (subvisible cirrus or SCi) in HCMM data is considered and radiosonde soundings are examined in relation to the presence of SCi. The statistical characteristics of multispectral meteorological satellite data in clear and SCi affected areas are discussed. Examples in TIROS-N and NOAA-7 data from several states and Mexico are presented. The VIS-IR cluster screening method for removing clouds is applied to a 262, 144 pixel HCMM scene from south Texas and northeast Mexico. The SCi that remain after cluster screening are sited out by applying a statistically determined IR limit.

Nixon, P. R.↗

X-ray spectra of 12 distant clusters of galaxies

An X-ray spectral analysis of 12 distant clusters of galaxies observed on-axis with the Einstein Observatory imaging proportional counter is presented. Statistically, X-ray spectral data of the highest red shift clusters in the sample are inconsistent with an optically thin plasma emission model plus absorptions only in the Milky Way. Inclusions of excess absorptions in the clusters significantly improve the spectral fits to the data, indicating the possible presence of large amounts of X-ray absorbing cool gas in some of the distant clusters. By using X-ray luminosities determined from observed fluxes only in the 0.8-3.5 keV band and the temperature-to-luminosity correlation for nearby clusters, the estimated temperatures of the hot intracluster medium in these distant clusters constrain the absorption columns in the clusters. The data also show possible positive temperature evolution of the hot ICM with time which, if present, would further increase the absorptions required in fitting the spectra.

Wang, Qingde↗

Radio observations of Abell clusters and a comparison with certain Einstein observations

Areas around 70 clusters have been observed at the Arecibo Observatory primarily for coordination with about 60 Einstein X-ray sources. Arecibo source coordinates and flux density are tabulated, and some identifications are made with cataloged radio sources. Statistical estimates are made of the percentage of cluster sources among all sources in certain areas and to limits on the flux density of 430 MHz. Arecibo and other radio data are compared with the available Einstein data of seven clusters. Not every Einstein source has a radio counterpart, and the counterparts may variously be bilobed, tailed, or single. A parameter which is proportional to source continuum power at 430 MHz ranges over fewer orders of magnitude than the associated source X-ray luminosity, with no certain correlation between these parameters. NRAO Green Bank interferometer observations of A401 and A2142 are reported.

Johnson, H. M.↗

Continental land cover assessment using Landsat MSS data

A statistical procedure to assess level-II continental resources using Landsat MSS digital data is presented. The statistical procedure involves a two-stage cluster sample within a stratified random sample. The utility of this procedure is assessed by using it to estimate the areal extent of the conifer and hardwood resources of the continental U.S. National estimates of conifer and hardwood derived using this sampling procedure were within 3 percent of U.S. Forest Service (USFS) figures. According to the Landsat-based study, 11 percent of the country is conifer forest and 12 percent is hardwood. The corresponding USFS figures are 13 and 15 percent, respectively. Comparison of the MSS classification products and airphotos showed that the conifer cover class was correctly identified 74 percent of the time and hardwood 80 percent of the time. The average classification accuracy countrywide for the four cover types considered (conifer, hardwood, water, and 'other') is 74 percent, and the overall accuracy is 85 percent. The statistical procedure provides a method of incorporating Landsat MSS digital data as a second state for level-II continental resource assessment. Alternate data sources, e.g., satellite and aircraft photographic imagery, may also be used in conjunction with this statistical model.

Nelson, Ross↗

CIZA: The First Systematic X-Ray Search for Clusters of Galaxies Behind the Milky Way

The aim of the CIZA project (Clusters In the Zone of Avoidance) was to take the first step toward a complete X-ray census of clusters of galaxies behind the plane of the Galaxy (the absolute value of b less than or equal to 20 degrees), the historical Zone of Avoidance of optical extragalactic surveys. Finding these heavily obscured clusters in ROSAT All-Sky Survey data would allow us to: 1. Construct the first truly all-sky, statistically complete, X-ray flux limited sample of galaxy clusters; 2. Use this sample to obtain an improved measurement of the cluster dipole (both amplitude and direction); 3. Chart large-scale structure across the plane of the Milky Way as traced by galaxy clusters; 4. Identify potential massive galaxy clusters contributing to the observed large-scale flow pattern in the local universe, specifically in the region around the Great Attractor; and 5. Use least-action modelling to deduce the gravitational fields created by galaxy clusters and compare this reconstruction with the one obtained from local galaxy surveys. Our project was highly successful in demonstrating the feasibility of this undertaking and allowed substantial progress toward achieving the stated science goals.

Ebeling, Harald↗

Nasa Space Flight Instruments: Cost Time Trends

Are NASA’s space flight instruments becoming cheaper or more expensive as time marches forward? After analyzing the costs of hundreds of instruments launched over the last 30 years, the short answer to this question is no… and yes. This paper gives a visual analysis of the cost time trends for various NASA space flight instrument types, such as optical, particles detectors, fields detectors and microwave instruments. In addition to the statistical approaches utilized, such as significance tests, cluster analysis and principle components analysis (PCA), we will also discuss the intangibles which are likely at play, including technological progress, NASA policy and the luck of the draw associated with mission manifests. This analysis was performed as the main driver for the NASA Instrument Cost Model (NICM) recent cost estimating model redesign. Started in 2004, the first version of NICM was based off of instruments launched from 1985-2005, or 20 years’ worth of data. As NICM hit its 10-year anniversary, we wanted to know: should NICM continue to only use the most recent 20 years’ worth of data (1995-2015)? Are instruments becoming cheaper or more expensive as time marches forward? There is evidence in favor of a drop in the median dollar-per-kg value across some instrument types, but little in others. Whereas further research is needed to substantiate, Particles and Optical-Planetary instrument types show moderate to strong evidence of a downward trend in dollar-per-kg. Further research is required to study the nature of this trend (shift, taper, cyclic, etc.). Little evidence for a similar downward trend was detected for Fields or Microwave instruments, or Optical instruments on Earth Orbiting spacecraft. We presented evidence in favor of a drop in the median dollar-per-kg value for Particles and Optical-Planetary instrument types. While similar evidence was weak at best for Fields and Microwave instruments. We can speculate as to the causes for this effect, but we are also equipped to begin to rule out, or at least prioritize, some of the suspected drivers. We observed, for Particles and Optical-Planetary instruments, that perhaps a launch manifest effect was playing part of the role in the observed decrease in dollar-per-kg over the years, noting that the more flagship class missions, which have more money to spend on their instruments, were seen in the earlier years in our data, versus the later years which were dominated by less expensive class missions. However, if this were a dominating driver, would we not have seen the downward trend in the Fields and Microwave instruments as well, which were drawn from that same launch manifest? The fact that we did not observe this helps us rule out the launch manifest effect, and other drivers, such as advances in technology, that seem to be more likely suspects. In that case, however, why would technology advances be helping the Particles and Optical-Planetary instruments only? Why would it not be impacting Optical-Earth Orbiting instruments? Further suspects were looked at as well and ruled out, such as the “Faster, Better, Cheaper”era of NASA development which did not seem to actually impact trends by instrument type on a dollar-perkg scale. VI. Future Work A. Time Series Detailed Statistical Assessment The analysis discussed above sets the foundation for a more rigorous time series analysis of the data. Time series analysis will further explore evidence to-date of time trends for the instrument types which showed the strongest indicators for a decrease in dollar-per-kg: Optical (Planetary) and Particles instruments. More than providing evidence and top-level significance tests, time series analysis would help elucidate what kind of trend that exists in the data, their significance and allow statistically based forecasting (see Figure 10)

Mrozinksi, Joseph↗

Red supergiants and neutrino emission. II.

Investigation of the variation with stellar mass of the ratio of the numbers of blue and red supergiants. Statistical data for supergiants in young open clusters and subgroups of associations are collected to supplement a more restricted list presented earlier. Improved methods are used to identify hydrogen-burning supergiants, as well as faint supergiant remnants of binary mass exchange, and to arrange the bright evolved supergiants in order of their masses. Neither of these two operations requires knowledge of stellar distances or luminosities. Relevant published work on stellar evolution, rotation, mass loss, and duplicity is used to predict upper and lower limits on the blue-to-red ratio. It is concluded that the observed paucity of very massive red supergiants (and of carbon stars) confirms and extends the trend previously observed, and thereby supports the idea of neutrino-induced acceleration of the carbon burning and later phases of evolution; the h and chi Persei association shows the same dependence of the blue-to-red-ratio on stellar mass as do other clusters and associations; and a moderate decrease of the blue-to-red ratio is observed with increasing galactocentric distance in the Galaxy (as in M33) and seems to be due to a relative scarcity of extremely young stars in distant galactic regions.

Stothers, R.↗

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95%), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗

Manual interpretation of LANDSAT data

The task of the analyst throughout LACIE phases 1 and 2 consisted of outlining representative areas (fields) for all spectral classes within a segment on the basis of their appearance on the LANDSAT image products, and then labeling the crop type (wheat/nonwheat) within the selected training areas. For LACIE phase 3, a procedure was developed and implemented which incorporated clustering for spectral class definition and training statistics generation. The only analyst's task was crop type identification. The logical processes involved in interpretation are described, rather than a step-by-step description of analyst procedures.

Hay, C. M.↗

LACIE/ERIPS software system summary

The Earth resources interactive processing system (ERIPS) supports LACIE by classifying LANDSAT sensed data on the basis of the statistical similarity to those portions which were identified by analysts. The development and capabilities of the ERIPS software system are described with emphasis on (1) system requirements; (2) LACIE/ERIPS hardware; (3) system functions; (4) pattern recognition concept; and (5) LACIE/ERIPS data bases. Algorithms used in LACIE/ERIPS for statistics, divergence, feature selection, classification, registration, adaptive clustering, iterative clustering, clustering report functions, Sun angle correction, mean level adjustment, and bias correction are appended.

Johnson, C. L.↗

Remote Sensing techniques used to characterize soil erosion in southwestern Sao Paulo state

Within randomly sampled squares of a 1 km x 1 km grid, rill/gullies frequency, land cover/land use type and shape of the slopes were extracted from aerial photographs of the Ribeirao Anhumas drainage basin. Mean slope gradient, stream frequency and slope length were calculated on topographic maps. Ground truth data on fine sand/coarse sand ratio and vegetation cover densities were obtained. The MSS-LANDSAT-2 data (CCTs) were analyzed using single-cell, cluster synthesis and slicer algorithms. Graphical and statistical analyses of the data indicate that different slope gradients and land cover/land use types are the most significant factors related to the soil erosion process. The digital analysis of MSS data allowed the association among gray level classes and vegetation cover classes, which defined seven classes. These gray level classes and slope gradient classes were used to rank erosion risk.

Parada, N. D. J.↗

Possible Martian brines - Radar observations and models

The 1971 and 1973 Goldstone 12.6-cm radar observations of Mars are separate data sets which include reflectivity as a function of latitude, longitude, and season. It has been argued that secular reflectivity variations of Mars' surface are indicated by the data and that shallow subsurface melting is the causal mechanism most compatible with the observations; however, the melting hypothesis conflicts with accepted notions of the state and distribution of water on Mars. The data are examined to identify temporal and spatial domains within which statistically significant changes in measured reflectivity are clustered. Brines which might satisfy the best supported reflectivity variations are out of equilibrium with the chemical megaenvironment. It is unclear whether such a brine, if emplaced in the Martian regolith at a depth shallow enough to affect the radar reflectivity, could survive even a single freeze-thaw cycle. Some combination of unique scattering properties or some as yet unidentified process other than melting is responsible for any genuine reflectivity variations.

Zent, Aaron P.↗