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NASA NTRS1994

Modulating terrestrial impacts from Oort cloud comets by the adiabatically changing galactic tides

Time modulation of the flux of new Jupiter-dominated Oort cloud comets is the subject of interest here. The major perturbation of these comets during the present epoch is due to the tidal field of the relatively smooth distribution of matter in the galactic disk. A secondary source of the near-parabolic comet flux are stars penetrating the inner Oort cloud and providing impulses that create brief comet showers. Substantial stellar-induced showers occur approximately every 100 m.y. Less frequent (but stronger) impulses due to giant molecular clouds can also perturb comets from the inner cloud. These occur on timescales of approximately equal to 500 m.y. In contrast to these infrequent stochastic shower phenomena is the continuously varying tidal-induced flux due to the galaxy. As the Sun orbits the galactic center it undergoes quasiharmonic motion about the galactic midplane, which is superimposed on the small eccentricity, near-Keplerian motion in the plane having epicycle period approximately equal to 150 m.y. In the process the galactic tidal field on the Sun/cloud system will vary causing a modulation of the observable Oort cloud flux. We have created a model of the galactic matter distribution as it affects the solar motion over a time interval ranging from 300 m.y. in the past to 100 m.y. into the future. As constraints on the disk's compact dark matter component we require consistency with the following: (1) the observed galactic rotation curve, (2) today's flux distribution of new comets, (3) the studies of K-giant distributions, and (4) the periodicity found in the terrestrial cratering record. The adiabatically varying galactic tidal torque is then determined and used to predict the time dependence of the flux. We find that a model in which approximately half the disk matter is compact is consistent with these constraints. Under such circumstances the peak-to-trough flux variation will be approx. equal to 5:1 with a full width of 9 m.y. This variability will manifest in the terrestrial cratering record and is consistent with the observed cratering periodicity, if over half of the impacts on Earth are caused by comets or asteroids that originate in the outer Oort cloud.

Matese, J. J.↗

NASA NTRS2009

Continuous Lidar Monitoring of Polar Stratospheric Clouds at the South Pole

Polar stratospheric clouds (PSC) play a primary role in the formation of annual ozone holes over Antarctica during the austral sunrise. Meridional temperature gradients in the lower stratosphere and upper troposphere, caused by strong radiative cooling, induce a broad dynamic vortex centered near the South Pole that decouples and insulates the winter polar airmass. PSC nucleate and grow as vortex temperatures gradually fall below equilibrium saturation and frost points for ambient sulfate, nitrate, and water vapor concentrations (generally below 197 K). Cloud surfaces promote heterogeneous reactions that convert stable chlorine and bromine-based molecules into photochemically active ones. As spring nears, and the sun reappears and rises, photolysis decomposes these partitioned compounds into individual halogen atoms that react with and catalytically destroy thousands of ozone molecules before they are stochastically neutralized. Despite a generic understanding of the ozone hole paradigm, many key components of the system, such as cloud occurrence, phase, and composition; particle growth mechanisms; and denitrification of the lower stratosphere have yet to be fully resolved. Satellite-based observations have dramatically improved the ability to detect PSC and quantify seasonal polar chemical partitioning. However, coverage directly over the Antarctic plateau is limited by polar-orbiting tracks that rarely exceed 80 degrees S. In December 1999, a NASA Micropulse Lidar Network instrument (MPLNET) was first deployed to the NOAA Earth Systems Research Laboratory (ESRL) Atmospheric Research Observatory at the Amundsen-Scott South Pole Station for continuous cloud and aerosol profiling. MPLNET instruments are eye-safe, capable of full-time autonomous operation, and suitably rugged and compact to withstand long-term remote deployment. With only brief interruptions during the winters of 2001 and 2002, a nearly continuous data archive exists to the present.

OZONE DESTRUCTION↗

NASA NTRS1989

Cloud field classification based on textural features

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes of features. Preliminary results based on the GLDV textural features alone look promising.

Sengupta, Sailes Kumar↗

NASA NTRS1993

Gas-rich dwarf galaxies in dense and sparse environments

Dwarf irregular galaxies (generically labelled Im for the present purposes) pose an enigma to students of galaxy evolution. In nearby groups and the Virgo cluster, Im galaxies are at least as abundant as spiral galaxies, and their low surface brightnesses and high gas-to-stars ratios suggest that (at least in the stochastic self-propagating star formation scenario) there should be significant numbers of HI clouds with masses approaching 10(exp 8) solar mass which have undergone very little or no star formation. To date, however, no clouds with so little star formation that they would not be recognized as Im galaxies on high-quality photographic plates have been identified. There have been suggestions that such dwarfs may be tidally disrupted in regions of high galactic density, but may be prevalent in low density regions. We offer data from three parallel programs relevant to this issue. (1) A large number of Im galaxies throughout the Local Supercluster have been mapped in the HI spectral line using the Arecibo Radiotelescope, and we can establish the frequency with which HI disks much more extended than their optically visible portions are found. (2) Our extensive mapping of spiral and dwarf galaxies in the Virgo cluster allows us to set stringent limits on the density of star-free Hi clouds in that cluster. (3) We have conducted a sampling of the void in the distribution of galaxies toward the super galactic pole, optimized for finding low-mass HI clouds at redshifts out to approximately 2000 km/s.

Hoffman, G. Lyle↗

NASA NTRS1989

Stochastic evolution of refractory interstellar dust during the chemical evolution of a two-phase interstellar medium

The evolution course of refractoary interstellar dust during the chemical evolution of a two-phase interstellar medium (ISM) is studied using a simple model of the chemical evolution of ISM. It is assumed that, in this medium, the stars are born in molecular clouds, but new nucleosynthesis products and stellar return are entered into a complementary diffuse medium; the well-mixed matter of each interstellar phase is repeatedly cycled stochastically through the complementary phase and back. The dust is studied on a particle-by-particle bases as it is sputtered by shock waves in the diffuse medium, accretes an amorphous mantle of gaseous refractory atoms while its local medium joins the molecular cloud medium, and encounters the possibility of astration within molecular clouds. Results are presented relevant to the size spectrum of accreted mantles, its age spectrum and the distinction among its several lifetimes, depletion factors of refractory atoms in the diffuse gas, and isotopic anomalies.

Liffman, Kurt↗

NASA NTRS1984

Stochastic does not equal ad hoc

Some classes of influential events in solar system history are class-predictable but not event-predictable. Theories of lunar origin should not ignore class-predictable stochastic events. Impacts and close encounters with large objects during planet formation are class-predictable. These stochastic events, such as large impacts that triggered ejection of Earth-mantle material into a circum-Earth cloud, should not be rejected as ad hoc. A way to deal with such events scientifically is to investigate their consequences; if it can be shown that they might produce the Moon, they become viable concepts in theories of lunar origin.

Hartmann, W. K.↗

NASA NTRS1987

UV, optical and infrared properties of star forming galaxies

The UVOIR properties of galaxies with extreme star formation rates are examined. These objects seem to fall into three distinct classes which can be called (1) extragalactic H II regions, (2) clumpy irregulars, and (3) starburst galaxies. Extragalactic H II regions are dominated by recently formed stars and may be considered 'young' galaxies if the definition of young is having the majority of total integrated star formation occurring in the last billion years. Clumpy irregulars are bursts of star formation superposed on an old population and are probably good examples of stochastic star formation. It is possible that star formation in these galaxies is triggered by the infall of gas clouds or dwarf companions. Starburst galaxies are much more luminous, dustier and more metal rich than the other classes. These objects show evidence for shock induced star formation where shocks may be caused by interaction with massive companions or are the result of an extremely strong density wave.

Huchra, John P.↗

NASA NTRS1989

IRAS observations of dust heating and energy balance in the Rho Ophiuchi dark cloud

The equilibrium process dust emission in the Rho Ophiuchi dark cloud is studied. The luminosity of the cloud is found to closely match the luminosity of the clouds's known embedded and external radiation sources. There is no evidence for a large population of undetected low-luminosity sources within the cloud and unknown external heating is also only a minor source of energy. Most of the cloud's luminosity is emitted in the mid-to-far-IR. Dust temperature maps indicate that the dust is not hot enough to heat the gas to observed temperatures. A simple cloud model with a radiation field composed of flux HD 147889, S1, and Sco OB2 associations predicts the observed IRAS 60 to 100 micron in-band flux ratios for a mean cloud density n(H2) = 1400. Flattened 12 and 25 micron observations show much extended emission in these bands, suggesting stochastic heating of very small grains or large molecules.

Greene, Thomas P.↗

NASA NTRS1989

Computer simulation of dust grain evolution

The latest results are reported from a Monte Carlo code that is being developed at NASA Ames. The goal of this program, is to derive from the observed and presumed properties of the interstellar medium (ISM) the following information: (1) the size spectrum of interstellar dust; (2) the chemical structure of interstellar dust; (3) interstellar abundances; and (4) the lifetime of a dust grain in the ISM. Presently this study is restricted to refractory interstellar material, i.e., the formation and destruction of ices are not included in the program. The program is embedded in an analytic solution for the bulk chemical evolution of a two-phase interstellar medium in which stars are born in molecular clouds, but new nucleosynthesis products and stellar return are entered into a complementary intercloud medium. The well-mixed matter of each interstellar phase is repeatedly cycled stochastically through the complementary phase and back. Refractory dust is created by thermal condensation as stellar matter flows away from sites of nucleosynthesis such as novae and supernovae and/or from the matter returned from evolved intermediate stars. The history of each particle is traced by standard Monte Carlo techniques as it is sputtered and fragmented by supernova shock waves in the intercloud medium. It also accretes an amorphous mantle of gaseous refractory atoms when its local medium joins with the molecular cloud medium. Finally it encounters the possibility of astration (destruction by star formation) within the molecular clouds.

Liffman, K.↗

NASA NTRS2011

Allowing for Horizontally Heterogeneous Clouds and Generalized Overlap in an Atmospheric GCM

While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown.

Lee, D.↗

NASA NTRS1997

Stochastic-Dynamical Modeling of Space Time Rainfall

The focus of this research work is the elucidation of the physical origins of the observed extreme-rainfall variability over tropical oceans. The quantitative results of this work may be used to establish links between deterministic models of the mesoscale and synoptic scale with statistical descriptions of the temporal variability of local tropical oceanic rainfall. In addition, they may be used to quantify the influence of measurement error in large-scale forcing and cloud scale observations on the accuracy of local rainfall variability inferences, important for hydrologic studies. A simple statistical-dynamical model, suitable for use in repetitive Monte Carlo experiments, is formulated as a diagnostic tool for this purpose. Stochastic processes with temporal structure and parameters estimated from observed large-scale data represent large-scale forcing.

Georgankakos, Konstantine P.↗

NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

NASA NTRSDate not supplied

A Model for Ice Accretion Roughness Evolution and Spatial Variations

Over the past decade, multiple investigations of ice accretion roughness and spatial variations have been performed in the Icing Research Tunnel (IRT) at the NASA Glenn Research Center. The early investigations used models of NACA 0012 airfoils with different chord sizes and focused on temporal scaling and primary cloud scaling parameters such as stagnation point collection efficiency. Subsequent investigations included the effects of model sweep, airfoil shape, airfoil lifting condition, and freestream static temperature. To develop a predictive model for roughness evolution in generalized icing situations, the maximum roughness values for the airfoils and conditions used in the angle of attack and freestream temperature investigations were scaled to eliminate the temporal variations. LEWICE simulations were employed to identify the local collection efficiency at the locations of maximum roughness, and a two-dimensional panel-method code was used to identify the local static pressure at the location of the maximum roughness. Because of the stochastic nature of ice accretion roughness, a physics-directed approach was employed to develop a multi-dimensional correlation based on the local pressure coefficient, the local total temperature, the cloud properties, and the cloud exposure time. The resulting correlation predictions are compared to ice shapes measured in the IRT for both a 21-in. NACA 0012 airfoil model and a 60-in. HAARP-II model. The resulting predictions indicate that the local freezing fraction must be included in the roughness predictive model. Implications regarding icing heat transfer predictions using the resulting roughness model are also discussed.

Icing↗

NASA NTRS1984

Spiral structure and star formation. I - Formation mechanisms and mean free paths

The wide variety of optical appearances observed in spiral galaxies has encouraged the growth of two theoretical approaches to explain the spiral patterns exhibited by such young objects as OB associations, giant H II regions, and dark dust lanes. These approaches are related to the density wave theory of spiral structure and 'stochastic, self-propagating star formation'. Levinson and Roberts (1981) tried to reconcile these two theoretical approaches, and considered a disk filled with discrete gas clouds. The present investigation is concerned with refinements and extensions of the model of Levinson and Roberts. Attention is given to gravitational forces and dynamical propagation, cloud-cloud collisions, supernova interactions, computational models, a theory concerning the interactions of the gas cloud and stellar association systems, the time evolution of the gas cloud-stellar association systems, and aspects of collisionally triggered star formation.

Roberts, W. W., Jr.↗

NASA NTRS1988

The influence of supernovae and passing stars on comets in the Oort cloud

It is demonstrated here that the passage of luminous stars through the Oort Cloud over the age of the solar system will subject all comets to heating episodes up to at least 16 K, and a sizeable fraction to 30 K. Stochastic supernovae have even more striking effects during monthlong events; conservative estimates of the supernovae are in the Galactic disk suggest that most comets have been heated to 45 K, and a fraction to about 60 K. These results imply that comets are not fully pristine relics of solar system formation.

Stern, S. Alan↗

NASA NTRS1991

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory

The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.

Manning, Robert M.↗

NASA NTRS2019

Ongoing Breakthroughs in Convective Parameterization

While the increase of computer power mobilizes a part of the community towards models with explicit convection or based on machine learning, we review the part of the literature dedicated to convective parameterization development for large-scale forecast and climate models. Recent findings: Many developments are underway to overcome endemic limitations of traditional convective parameterizations, either in unified or multi-object frameworks: scale-aware and stochastic approaches, new prognostic equations or representations of new components such as cold pools. Understanding their impact on the emergent properties of a model remains challenging, due to subsequent tuning of parameters and the limited understanding given by traditional metrics. Summary: Further effort still needs to be dedicated to the representation of the life cycle of convective systems, in particular their mesoscale organization and associated cloud cover. The development of more process-oriented metrics based on new observations is also needed to help quantify model improvement and better understand the mechanisms of climate change.

parameterizations for large-scale models↗

NASA NTRS1987

Stochastic nature of Landsat MSS data

A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.

Labovitz, M. L.↗