Reflection of solar radiation by a cylindrical cloud
NASA Technical Reports Server (NTRS)
Smith, G. L.
1989-01-01
Potential applications of an analytic method for computing the solar radiation reflected by a cylindrical cloud are discussed, including studies of radiative transfer within finite clouds and evaluations of these effects on other clouds and on remote sensing problems involving finite clouds. The pattern of reflected sunlight from a cylindrical cloud as seen at a large distance has been considered and described by the bidirectional function method for finite cloud analysis, as previously studied theoretically for plane-parallel atmospheres by McKee and Cox (1974); Schmetz and Raschke (1981); and Stuhlmann et al. (1985). However, the lack of three-dimensional radiative transfer solutions for anisotropic scattering media have hampered theoretical investigations of bidirectional functions for finite clouds. The present approach permits expression of the directional variation of the radiation field as a spherical harmonic series to any desired degree and order.
2D modeling of direct laser metal deposition process using a finite particle method
NASA Astrophysics Data System (ADS)
Anedaf, T.; Abbès, B.; Abbès, F.; Li, Y. M.
2018-05-01
Direct laser metal deposition is one of the material additive manufacturing processes used to produce complex metallic parts. A thorough understanding of the underlying physical phenomena is required to obtain a high-quality parts. In this work, a mathematical model is presented to simulate the coaxial laser direct deposition process tacking into account of mass addition, heat transfer, and fluid flow with free surface and melting. The fluid flow in the melt pool together with mass and energy balances are solved using the Computational Fluid Dynamics (CFD) software NOGRID-points, based on the meshless Finite Pointset Method (FPM). The basis of the computations is a point cloud, which represents the continuum fluid domain. Each finite point carries all fluid information (density, velocity, pressure and temperature). The dynamic shape of the molten zone is explicitly described by the point cloud. The proposed model is used to simulate a single layer cladding.
AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation
Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; ...
2016-04-19
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less
AP-Cloud: Adaptive Particle-in-Cloud method for optimal solutions to Vlasov–Poisson equation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Xingyu; Samulyak, Roman, E-mail: roman.samulyak@stonybrook.edu; Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less
AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less
A variational multiscale method for particle-cloud tracking in turbomachinery flows
NASA Astrophysics Data System (ADS)
Corsini, A.; Rispoli, F.; Sheard, A. G.; Takizawa, K.; Tezduyar, T. E.; Venturini, P.
2014-11-01
We present a computational method for simulation of particle-laden flows in turbomachinery. The method is based on a stabilized finite element fluid mechanics formulation and a finite element particle-cloud tracking method. We focus on induced-draft fans used in process industries to extract exhaust gases in the form of a two-phase fluid with a dispersed solid phase. The particle-laden flow causes material wear on the fan blades, degrading their aerodynamic performance, and therefore accurate simulation of the flow would be essential in reliable computational turbomachinery analysis and design. The turbulent-flow nature of the problem is dealt with a Reynolds-Averaged Navier-Stokes model and Streamline-Upwind/Petrov-Galerkin/Pressure-Stabilizing/Petrov-Galerkin stabilization, the particle-cloud trajectories are calculated based on the flow field and closure models for the turbulence-particle interaction, and one-way dependence is assumed between the flow field and particle dynamics. We propose a closure model utilizing the scale separation feature of the variational multiscale method, and compare that to the closure utilizing the eddy viscosity model. We present computations for axial- and centrifugal-fan configurations, and compare the computed data to those obtained from experiments, analytical approaches, and other computational methods.
The effect of finite geometry on the three-dimensional transfer of solar irradiance in clouds
NASA Technical Reports Server (NTRS)
Davies, R.
1978-01-01
Results are presented for a Monte Carlo model applied to a wide range of cloud widths and heights, and for an analytical model restricted in its application to cuboidally shaped clouds whose length, breadth, and depth may be varied independently; the clouds must be internally homogeneous with respect to their intrinsic radiative properties. Comparative results from the Monte Carlo method and the derived analytical model are presented for a wide range of cloud sizes, with special emphasis on the effects of varying the single scatter albedo, the solar zenith angle, and the scattering phase angle.
The diffusion approximation. An application to radiative transfer in clouds
NASA Technical Reports Server (NTRS)
Arduini, R. F.; Barkstrom, B. R.
1976-01-01
It is shown how the radiative transfer equation reduces to the diffusion equation. To keep the mathematics as simple as possible, the approximation is applied to a cylindrical cloud of radius R and height h. The diffusion equation separates in cylindrical coordinates and, in a sample calculation, the solution is evaluated for a range of cloud radii with cloud heights of 0.5 km and 1.0 km. The simplicity of the method and the speed with which solutions are obtained give it potential as a tool with which to study the effects of finite-sized clouds on the albedo of the earth-atmosphere system.
Interface-Resolving Simulation of Collision Efficiency of Cloud Droplets
NASA Astrophysics Data System (ADS)
Wang, Lian-Ping; Peng, Cheng; Rosa, Bodgan; Onishi, Ryo
2017-11-01
Small-scale air turbulence could enhance the geometric collision rate of cloud droplets while large-scale air turbulence could augment the diffusional growth of cloud droplets. Air turbulence could also enhance the collision efficiency of cloud droplets. Accurate simulation of collision efficiency, however, requires capture of the multi-scale droplet-turbulence and droplet-droplet interactions, which has only been partially achieved in the recent past using the hybrid direct numerical simulation (HDNS) approach. % where Stokes disturbance flow is assumed. The HDNS approach has two major drawbacks: (1) the short-range droplet-droplet interaction is not treated rigorously; (2) the finite-Reynolds number correction to the collision efficiency is not included. In this talk, using two independent numerical methods, we will develop an interface-resolved simulation approach in which the disturbance flows are directly resolved numerically, combined with a rigorous lubrication correction model for near-field droplet-droplet interaction. This multi-scale approach is first used to study the effect of finite flow Reynolds numbers on the droplet collision efficiency in still air. Our simulation results show a significant finite-Re effect on collision efficiency when the droplets are of similar sizes. Preliminary results on integrating this approach in a turbulent flow laden with droplets will also be presented. This work is partially supported by the National Science Foundation.
NASA Technical Reports Server (NTRS)
da Silva, Arlindo M.; Norris, Peter M.
2013-01-01
Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.
Making Cloud Computing Available For Researchers and Innovators (Invited)
NASA Astrophysics Data System (ADS)
Winsor, R.
2010-12-01
High Performance Computing (HPC) facilities exist in most academic institutions but are almost invariably over-subscribed. Access is allocated based on academic merit, the only practical method of assigning valuable finite compute resources. Cloud computing on the other hand, and particularly commercial clouds, draw flexibly on an almost limitless resource as long as the user has sufficient funds to pay the bill. How can the commercial cloud model be applied to scientific computing? Is there a case to be made for a publicly available research cloud and how would it be structured? This talk will explore these themes and describe how Cybera, a not-for-profit non-governmental organization in Alberta Canada, aims to leverage its high speed research and education network to provide cloud computing facilities for a much wider user base.
Superposition and alignment of labeled point clouds.
Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke
2011-01-01
Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point clouds. A labeled point cloud is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This type of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom type or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points clouds in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point clouds. To this end, we proceed from an optimal superposition of the corresponding point clouds and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.
A vortex wake capturing method for potential flow calculations
NASA Technical Reports Server (NTRS)
Murman, E. M.; Stremel, P. M.
1982-01-01
A method is presented for modifying finite difference solutions of the potential equation to include the calculation of non-planar vortex wake features. The approach is an adaptation of Baker's 'cloud in cell' algorithm developed for the stream function-vorticity equations. The vortex wake is tracked in a Lagrangian frame of reference as a group of discrete vortex filaments. These are distributed to the Eulerian mesh system on which the velocity is calculated by a finite difference solution of the potential equation. An artificial viscosity introduced by the finite difference equations removes the singular nature of the vortex filaments. Computed examples are given for the two-dimensional time dependent roll-up of vortex wakes generated by wings with different spanwise loading distributions.
Castellazzi, Giovanni; D'Altri, Antonio Maria; Bitelli, Gabriele; Selvaggi, Ilenia; Lambertini, Alessandro
2015-07-28
In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation.
Castellazzi, Giovanni; D’Altri, Antonio Maria; Bitelli, Gabriele; Selvaggi, Ilenia; Lambertini, Alessandro
2015-01-01
In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation. PMID:26225978
Fast RBF OGr for solving PDEs on arbitrary surfaces
NASA Astrophysics Data System (ADS)
Piret, Cécile; Dunn, Jarrett
2016-10-01
The Radial Basis Functions Orthogonal Gradients method (RBF-OGr) was introduced in [1] to discretize differential operators defined on arbitrary manifolds defined only by a point cloud. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent complex geometries in any spatial dimension. A large limitation of the RBF-OGr method was its large computational complexity, which greatly restricted the size of the point cloud. In this paper, we apply the RBF-Finite Difference (RBF-FD) technique to the RBF-OGr method for building sparse differentiation matrices discretizing continuous differential operators such as the Laplace-Beltrami operator. This method can be applied to solving PDEs on arbitrary surfaces embedded in ℛ3. We illustrate the accuracy of our new method by solving the heat equation on the unit sphere.
Ramsey scheme for coherent population resonance detection in the optically dense medium
NASA Astrophysics Data System (ADS)
Barantsev, Konstantin; Litvinov, Andrey; Popov, Evgeniy
2018-04-01
This work is devoted to a theoretical investigation of the Ramsey method of detection of the coherent population trapping resonance in cold atomic clouds taking into account collective effects caused by finite optical depth of the considered clouds. The interaction of atoms with pulsed laser radiation is described in the formalism of density matrix by means of Maxwell-Bloch set of equations. The Ramsey signal of coherent population trapping resonance was calculated for the radiation passed through the medium and analyzed for different length of the atomic cloud. Also the population of excited level was calculated in dependence on the two-photon detuning and coordinate along the main optical axis. The light shift of sidebands and appearance of additional harmonics were discovered.
Large eddy simulation of hydrodynamic cavitation
NASA Astrophysics Data System (ADS)
Bhatt, Mrugank; Mahesh, Krishnan
2017-11-01
Large eddy simulation is used to study sheet to cloud cavitation over a wedge. The mixture of water and water vapor is represented using a homogeneous mixture model. Compressible Navier-Stokes equations for mixture quantities along with transport equation for vapor mass fraction employing finite rate mass transfer between the two phases, are solved using the numerical method of Gnanaskandan and Mahesh. The method is implemented on unstructured grid with parallel MPI capabilities. Flow over a wedge is simulated at Re = 200 , 000 and the performance of the homogeneous mixture model is analyzed in predicting different regimes of sheet to cloud cavitation; namely, incipient, transitory and periodic, as observed in the experimental investigation of Harish et al.. This work is supported by the Office of Naval Research.
Particle Size Distributions in Atmospheric Clouds
NASA Technical Reports Server (NTRS)
Paoli, Roberto; Shariff, Karim
2003-01-01
In this note, we derive a transport equation for a spatially integrated distribution function of particles size that is suitable for sparse particle systems, such as in atmospheric clouds. This is done by integrating a Boltzmann equation for a (local) distribution function over an arbitrary but finite volume. A methodology for evolving the moments of the integrated distribution is presented. These moments can be either tracked for a finite number of discrete populations ('clusters') or treated as continuum variables.
NASA Technical Reports Server (NTRS)
1976-01-01
The program called CTRANS is described which was designed to perform radiative transfer computations in an atmosphere with horizontal inhomogeneities (clouds). Since the atmosphere-ground system was to be richly detailed, the Monte Carlo method was employed. This means that results are obtained through direct modeling of the physical process of radiative transport. The effects of atmopheric or ground albedo pattern detail are essentially built up from their impact upon the transport of individual photons. The CTRANS program actually tracks the photons backwards through the atmosphere, initiating them at a receiver and following them backwards along their path to the Sun. The pattern of incident photons generated through backwards tracking automatically reflects the importance to the receiver of each region of the sky. Further, through backwards tracking, the impact of the finite field of view of the receiver and variations in its response over the field of view can be directly simulated.
A laboratory investigation of the reflective properties of simulated, optically thick clouds
NASA Technical Reports Server (NTRS)
Mckee, T. B.; Cox, S. K.
1982-01-01
The Cloud Field Optical Simulator project includes work in the following areas: (1) improvement in the shape of the desired (visible) spectral response of the measurement, (2) selection of two usable materials for cloud simulation, (3) a means of assigning a visible optical depth to the simulated clouds, and (4) confirmation that the apparatus is capable of detecting basic finite cloud characteristics. A brief description of the accomplishments in each of these areas is presented.
Particle-in-cell simulations of the critical ionization velocity effect in finite size clouds
NASA Technical Reports Server (NTRS)
Moghaddam-Taaheri, E.; Lu, G.; Goertz, C. K.; Nishikawa, K. - I.
1994-01-01
The critical ionization velocity (CIV) mechanism in a finite size cloud is studied with a series of electrostatic particle-in-cell simulations. It is observed that an initial seed ionization, produced by non-CIV mechanisms, generates a cross-field ion beam which excites a modified beam-plasma instability (MBPI) with frequency in the range of the lower hybrid frequency. The excited waves accelerate electrons along the magnetic field up to the ion drift energy that exceeds the ionization energy of the neutral atoms. The heated electrons in turn enhance the ion beam by electron-neutral impact ionization, which establishes a positive feedback loop in maintaining the CIV process. It is also found that the efficiency of the CIV mechanism depends on the finite size of the gas cloud in the following ways: (1) Along the ambient magnetic field the finite size of the cloud, L (sub parallel), restricts the growth of the fastest growing mode, with a wavelength lambda (sub m parallel), of the MBPI. The parallel electron heating at wave saturation scales approximately as (L (sub parallel)/lambda (sub m parallel)) (exp 1/2); (2) Momentum coupling between the cloud and the ambient plasma via the Alfven waves occurs as a result of the finite size of the cloud in the direction perpendicular to both the ambient magnetic field and the neutral drift. This reduces exponentially with time the relative drift between the ambient plasma and the neutrals. The timescale is inversely proportional to the Alfven velocity. (3) The transvers e charge separation field across the cloud was found to result in the modulation of the beam velocity which reduces the parallel heating of electrons and increases the transverse acceleration of electrons. (4) Some energetic electrons are lost from the cloud along the magnetic field at a rate characterized by the acoustic velocity, instead of the electron thermal velocity. The loss of energetic electrons from the cloud seems to be larger in the direction of plasma drift relative to the neutrals, where the loss rate is characterized by the neutral drift velocity. It is also shown that a factor of 4 increase in the ambient plasma density, increases the CIV ionization yield by almost 2 orders of magnitude at the end of a typical run. It is concluded that a larger ambient plasma density can result in a larger CIV yield because of (1) larger seed ion production by non-CIV mechanisms, (2) smaller Alfven velocity and hence weak momentum coupling, and (3) smaller ratio of the ion beam density to the ambient ion density, and therefore a weaker modulation of the beam velocity. The simulation results are used to interpret various chemical release experiments in space.
Naff, R.L.; Haley, D.F.; Sudicky, E.A.
1998-01-01
In this, the second of two papers concerned with the use of numerical simulation to examine flow and transport parameters in heterogeneous porous media via Monte Carlo methods, results from the transport aspect of these simulations are reported on. Transport simulations contained herein assume a finite pulse input of conservative tracer, and the numerical technique endeavors to realistically simulate tracer spreading as the cloud moves through a heterogeneous medium. Medium heterogeneity is limited to the hydraulic conductivity field, and generation of this field assumes that the hydraulic-conductivity process is second-order stationary. Methods of estimating cloud moments, and the interpretation of these moments, are discussed. Techniques for estimation of large-time macrodispersivities from cloud second-moment data, and for the approximation of the standard errors associated with these macrodispersivities, are also presented. These moment and macrodispersivity estimation techniques were applied to tracer clouds resulting from transport scenarios generated by specific Monte Carlo simulations. Where feasible, moments and macrodispersivities resulting from the Monte Carlo simulations are compared with first- and second-order perturbation analyses. Some limited results concerning the possible ergodic nature of these simulations, and the presence of non-Gaussian behavior of the mean cloud, are reported on as well.
Theoretical quasar emission-line ratios. VII - Energy-balance models for finite hydrogen slabs
NASA Technical Reports Server (NTRS)
Hubbard, E. N.; Puetter, R. C.
1985-01-01
The present energy balance calculations for finite, isobaric, hydrogen-slab quasar emission line clouds incorporate probabilistic radiative transfer (RT) in all lines and bound-free continua of a five-level continuum model hydrogen atom. Attention is given to the line ratios, line formation regions, level populations and model applicability results obtained. H lines and a variety of other considerations suggest the possibility of emission line cloud densities in excess of 10 to the 10th/cu cm. Lyman-beta/Lyman-alpha line ratios that are in agreement with observed values are obtained by the models. The observed Lyman/Balmer ratios can be achieved with clouds whose column depths are about 10 to the 22nd/sq cm.
THE FREE-FALL TIME OF FINITE SHEETS AND FILAMENTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Toala, Jesus A.; Vazquez-Semadeni, Enrique; Gomez, Gilberto C.
2012-01-10
Molecular clouds often exhibit filamentary or sheet-like shapes. We compute the free-fall time ({tau}{sub ff}) for finite, uniform, self-gravitating circular sheets and filamentary clouds of small but finite thickness, so that their volume density {rho} can still be defined. We find that, for thin sheets, the free-fall time is larger than that of a uniform sphere with the same volume density by a factor proportional to {radical}A, where the aspect ratio A is given by A = R/h, R being the sheet's radius and h is its thickness. For filamentary clouds, the aspect ratio is defined as A=L/R, where Lmore » is the filament's half-length and R is its (small) radius, and the modification factor is more complicated, although in the limit of large A it again reduces to nearly {radical}A. We propose that our result for filamentary shapes naturally explains the ubiquitous configuration of clumps fed by filaments observed in the densest structures of molecular clouds. Also, the longer free-fall times for non-spherical geometries in general may contribute toward partially alleviating the 'star formation conundrum', namely, the star formation rate in the Galaxy appears to be proceeding in a timescale much larger than the total molecular mass in the Galaxy divided by its typical free-fall time. If molecular clouds are in general formed by thin sheets and long filaments, then their relevant free-fall time may have been systematically underestimated, possibly by factors of up to one order of magnitude.« less
Characteristics of finite amplitude stationary gravity waves in the atmosphere of Venus
NASA Technical Reports Server (NTRS)
Young, Richard E.; Walterscheid, Richard L.; Schubert, Gerald; Pfister, Leonhard; Houben, Howard; Bindschadler, Duane L.
1994-01-01
This paper extends the study of stationary gravity waves generated near the surface of Venus reported previously by Young et al. to include finite amplitude effects associated with large amplitude waves. Waves are forced near the surface of Venus by periodic forcing. The height-dependent profiles of static stability and mean wind in the Venus atmosphere play a very important role in the evolution of the nonlinear behavior of the waves, just as they do in the linear wave solutions. Certain wave properties are qualitatively consistent with linear wave theory, such as wave trapping, resonance, and wave evanescence for short horizontal wavelenghts. However, the finite amplitude solutions also exhibit many other interesting features. In particular, for forcing amplitudes representative of those that could be expected in mountainous regions such as Aphrodite Terra, waves generated near the surface can reach large amplitudes at and above cloud levels, with clear signatures in the circulation pattern. At still higher levels, the waves can reach large enough amplitude to break, unless damping rates above the clouds are sufficient to limit wave amplitude growth. Well below cloud levels the waves develop complex flow patterns as the result of finite amplitude wave-wave interactions, and waves are generated having considerably shorter horizontal wavelenghts than that associated with the forcing near the surface. Nonlinear interactions can excite waves that are resonant with the background wind and static stability fields even when the primary surface forcing does not, and these waves can dominate the wave spectrum near cloud levels. A global map of Venus topographic slopes derived from Magellan altimetry data shows that slopes of magnitude comparable to or exceeding that used to force the model are ubiquitous over the surface.
Expansion of a Rarefied Gas Cloud in a Vacuum: Asymptotic Treatment
NASA Astrophysics Data System (ADS)
Zhuk, V. I.
2018-02-01
The unsteady expansion of a rarefied gas of finite mass in an unlimited space is studied. The long-time asymptotic behavior of the solution is examined at Knudsen numbers tending to zero. An asymptotic analysis shows that, in the limit of small Knudsen numbers, the behavior of the macroscopic parameters of the expanding gas cloud at long times (i.e., for small density values) has nothing to do with the free-molecular or continuum flow regimes. This conclusion is unexpected and not obvious, but follows from a uniformly suitable solution constructed by applying the method of outer and inner asymptotic expansions. In particular, the unusual temperature behavior is of interest as applied to remote sensing of rocket exhaust plumes.
Effects of cloud size and cloud particles on satellite-observed reflected brightness
NASA Technical Reports Server (NTRS)
Reynolds, D. W.; Mckee, T. B.; Danielson, K. S.
1978-01-01
Satellite observations allowed obtaining data on the visible brightness of cumulus clouds over South Park, Colorado, while aircraft observations were made in cloud to obtain the drop size distributions and liquid water content of the cloud. Attention is focused on evaluating the relationship between cloud brightness, horizontal dimension, and internal microphysical structure. A Monte Carlo cloud model for finite clouds was run using different distributions of drop sizes and numbers, while varying the cloud depth and width to determine how theory would predict what the satellite would view from its given location in space. Comparison of these results to the satellite observed reflectances is presented. Theoretical results are found to be in good agreement with observations. For clouds of optical thickness between 20 and 60, monitoring cloud brightness changes in clouds of uniform depth and variable width gives adequate information about a cloud's liquid water content. A cloud having a 10:1 width to depth ratio is almost reaching its maximum brightness for a specified optical thickness.
Temporal and spatiotemporal correlation functions for trapped Bose gases
NASA Astrophysics Data System (ADS)
Kohnen, M.; Nyman, R. A.
2015-03-01
Density correlations unambiguously reveal the quantum nature of matter. Here, we study correlations between measurements of density in cold-atom clouds at different times at one position, and also at two separated positions. We take into account the effects of finite-size and -duration measurements made by light beams passing through the atom cloud. We specialize to the case of Bose gases in harmonic traps above critical temperature, for weakly perturbative measurements. For overlapping measurement regions, shot-noise correlations revive after a trap oscillation period. For nonoverlapping regions, bosonic correlations dominate at long times, and propagate at finite speeds. Finally, we give a realistic measurement protocol for performing such experiments.
Transport of infrared radiation in cuboidal clouds
NASA Technical Reports Server (NTRS)
HARSHVARDHAN; Weinman, J. A.; Davies, R.
1981-01-01
The transport of infrared radiation in a single cuboidal cloud using a vertical two steam approximation was modeled. The emittance of the top face of the model cloud is always less than that for a plane parallel cloud of the same optical depth. The hemisphere flux escaping from the cloud top has a gradient from the center to the edges which brighten when the cloud is over warmer ground. Cooling rate calculations in the 8 to 13.6 micrometer region show that there is cooling from the sides of the cloud at all levels even when there is heating of the core from the ground below. The radiances exiting from model cuboidal clouds were computed by path integration over the source function obtained with the two stream approximation. It is suggested that the brightness temperature measured from finite clouds will overestimate the cloud top temperature.
Lagrangian Particle Tracking Simulation for Warm-Rain Processes in Quasi-One-Dimensional Domain
NASA Astrophysics Data System (ADS)
Kunishima, Y.; Onishi, R.
2017-12-01
Conventional cloud simulations are based on the Euler method and compute each microphysics process in a stochastic way assuming infinite numbers of particles within each numerical grid. They therefore cannot provide the Lagrangian statistics of individual particles in cloud microphysics (i.e., aerosol particles, cloud particles, and rain drops) nor discuss the statistical fluctuations due to finite number of particles. We here simulate the entire precipitation process of warm-rain, with tracking individual particles. We use the Lagrangian Cloud Simulator (LCS), which is based on the Euler-Lagrangian framework. In that framework, flow motion and scalar transportation are computed with the Euler method, and particle motion with the Lagrangian one. The LCS tracks particle motions and collision events individually with considering the hydrodynamic interaction between approaching particles with a superposition method, that is, it can directly represent the collisional growth of cloud particles. It is essential for trustworthy collision detection to take account of the hydrodynamic interaction. In this study, we newly developed a stochastic model based on the Twomey cloud condensation nuclei (CCN) activation for the Lagrangian tracking simulation and integrated it into the LCS. Coupling with the Euler computation for water vapour and temperature fields, the initiation and condensational growth of water droplets were computed in the Lagrangian way. We applied the integrated LCS for a kinematic simulation of warm-rain processes in a vertically-elongated domain of, at largest, 0.03×0.03×3000 (m3) with horizontal periodicity. Aerosol particles with a realistic number density, 5×107 (m3), were evenly distributed over the domain at the initial state. Prescribed updraft at the early stage initiated development of a precipitating cloud. We have confirmed that the obtained bulk statistics fairly agree with those from a conventional spectral-bin scheme for a vertical column domain. The centre of the discussion will be the Lagrangian statistics which is collected from the individual behaviour of the tracked particles.
Simulating incompressible flow on moving meshfree grids using General Finite Differences (GFD)
NASA Astrophysics Data System (ADS)
Vasyliv, Yaroslav; Alexeev, Alexander
2016-11-01
We simulate incompressible flow around an oscillating cylinder at different Reynolds numbers using General Finite Differences (GFD) on a meshfree grid. We evolve the meshfree grid by treating each grid node as a particle. To compute velocities and accelerations, we consider the particles at a particular instance as Eulerian observation points. The incompressible Navier-Stokes equations are directly discretized using GFD with boundary conditions enforced using a sharp interface treatment. Cloud sizes are set such that the local approximations use only 16 neighbors. To enforce incompressibility, we apply a semi-implicit approximate projection method. To prevent overlapping particles and formation of voids in the grid, we propose a particle regularization scheme based on a local minimization principle. We validate the GFD results for an oscillating cylinder against the lattice Boltzmann method and find good agreement. Financial support provided by National Science Foundation (NSF) Graduate Research Fellowship, Grant No. DGE-1148903.
Rayleigh convective instability in a cloud medium
NASA Astrophysics Data System (ADS)
Shmerlin, B. Ya.; Shmerlin, M. B.
2017-09-01
The problem of convective instability of an atmospheric layer containing a horizontally finite region filled with a cloud medium is considered. Solutions exponentially growing with time, i.e., solitary cloud rolls or spatially localized systems of cloud rolls, have been constructed. In the case of axial symmetry, their analogs are convective vortices with both ascending and descending motions on the axis and cloud clusters with ring-shaped convective structures. Depending on the anisotropy of turbulent exchange, the scale of vortices changes from the tornado scale to the scale of tropical cyclones. The solutions with descending motions on the axis can correspond to the formation of a tornado funnel or a hurricane eye in tropical cyclones.
Mingus Discontinuous Multiphysics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pat Notz, Dan Turner
Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model
Applications and Improvement of a Coupled, Global and Cloud-Resolving Modeling System
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Chern, J.; Atlas, R.
2005-01-01
Recently Grabowski (2001) and Khairoutdinov and Randall (2001) have proposed the use of 2D CFWs as a "super parameterization" [or multi-scale modeling framework (MMF)] to represent cloud processes within atmospheric general circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization used in conventional GCMs. A prototype Goddard MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) is now being developed. The prototype includes the fvGCM run at 2.50 x 20 horizontal resolution with 32 vertical layers from the surface to 1 mb and the 2D (x-z) GCE using 64 horizontal and 32 vertical grid points with 4 km horizontal resolution and a cyclic lateral boundary. The time step for the 2D GCE would be 15 seconds, and the fvGCM-GCE coupling frequency would be 30 minutes (i.e. the fvGCM physical time step). We have successfully developed an fvGCM-GCE coupler for this prototype. Because the vertical coordinate of the fvGCM (a terrain-following floating Lagrangian coordinate) is different from that of the GCE (a z coordinate), vertical interpolations between the two coordinates are needed in the coupler. In interpolating fields from the GCE to fvGCM, we use an existing fvGCM finite- volume piecewise parabolic mapping (PPM) algorithm, which conserves the mass, momentum, and total energy. A new finite-volume PPM algorithm, which conserves the mass, momentum and moist static energy in the z coordinate, is being developed for interpolating fields from the fvGCM to the GCE. In the meeting, we will discuss the major differences between the two MMFs (i.e., the CSU MMF and the Goddard MMF). We will also present performance and critical issues related to the MMFs. In addition, we will present multi-dimensional cloud datasets (i.e., a cloud data library) generated by the Goddard MMF that will be provided to the global modeling community to help improve the representation and performance of moist processes in climate models and to improve our understanding of cloud processes globally (the software tools needed to produce cloud statistics and to identify various types of clouds and cloud systems from both high-resolution satellite and model data will be also presented).
Cognitive Radio Cloud Networks: Assured Access In The Future Electromagnetic Operating Environment
2017-04-04
AIR COMMAND AND STAFF COLLEGE AIR UNIVERSITY COGNITIVE RADIO CLOUD NETWORKS: ASSURED ACCESS IN THE FUTURE ELECTROMAGNETIC OPERATING...3 Abstract The electromagnetic spectrum is a finite resource that is critical to the United States military’s...ability to gain superiority in the other five warfighting domains. The Department of Defense’s electromagnetic strategy is spectrum access when and
Light Scattering by Gaussian Particles: A Solution with Finite-Difference Time Domain Technique
NASA Technical Reports Server (NTRS)
Sun, W.; Nousiainen, T.; Fu, Q.; Loeb, N. G.; Videen, G.; Muinonen, K.
2003-01-01
The understanding of single-scattering properties of complex ice crystals has significance in atmospheric radiative transfer and remote-sensing applications. In this work, light scattering by irregularly shaped Gaussian ice crystals is studied with the finite-difference time-domain (FDTD) technique. For given sample particle shapes and size parameters in the resonance region, the scattering phase matrices and asymmetry factors are calculated. It is found that the deformation of the particle surface can significantly smooth the scattering phase functions and slightly reduce the asymmetry factors. The polarization properties of irregular ice crystals are also significantly different from those of spherical cloud particles. These FDTD results could provide a reference for approximate light-scattering models developed for irregular particle shapes and can have potential applications in developing a much simpler practical light scattering model for ice clouds angular-distribution models and for remote sensing of ice clouds and aerosols using polarized light. (copyright) 2003 Elsevier Science Ltd. All rights reserved.
BMS supertranslation symmetry implies Faddeev-Kulish amplitudes
NASA Astrophysics Data System (ADS)
Choi, Sangmin; Akhoury, Ratindranath
2018-02-01
We show explicitly that, among the scattering amplitudes constructed from eigenstates of the BMS supertranslation charge, the ones that conserve this charge, are equal to those constructed from Faddeev-Kulish states. Thus, Faddeev-Kulish states naturally arise as a consequence of the asymptotic symmetries of perturbative gravity and all charge conserving amplitudes are infrared finite. In the process we show an important feature of the Faddeev-Kulish clouds dressing the external hard particles: these clouds can be moved from the incoming states to the outgoing ones, and vice-versa, without changing the infrared finiteness properties of S matrix elements. We also apply our discussion to the problem of the decoherence of momentum configurations of hard particles due to soft boson effects.
Nonlinear Bubble Dynamics And The Effects On Propagation Through Near-Surface Bubble Layers
NASA Astrophysics Data System (ADS)
Leighton, Timothy G.
2004-11-01
Nonlinear bubble dynamics are often viewed as the unfortunate consequence of having to use high acoustic pressure amplitudes when the void fraction in the near-surface oceanic bubble layer is great enough to cause severe attenuation (e.g. >50 dB/m). This is seen as unfortunate since existing models for acoustic propagation in bubbly liquids are based on linear bubble dynamics. However, the development of nonlinear models does more than just allow quantification of the errors associated with the use of linear models. It also offers the possibility of propagation modeling and acoustic inversions which appropriately incorporate the bubble nonlinearity. Furthermore, it allows exploration and quantification of possible nonlinear effects which may be exploited. As a result, high acoustic pressure amplitudes may be desirable even in low void fractions, because they offer opportunities to gain information about the bubble cloud from the nonlinearities, and options to exploit the nonlinearities to enhance communication and sonar in bubbly waters. This paper presents a method for calculating the nonlinear acoustic cross-sections, scatter, attenuations and sound speeds from bubble clouds which may be inhomogeneous. The method allows prediction of the time dependency of these quantities, both because the cloud may vary and because the incident acoustic pulse may have finite and arbitrary time history. The method can be readily adapted for bubbles in other environments (e.g. clouds of interacting bubbles, sediments, structures, in vivo, reverberant conditions etc.). The possible exploitation of bubble acoustics by marine mammals, and for sonar enhancement, is explored.
Li, Ping; Wang, Weiwei; Song, Zhijian; An, Yong; Zhang, Chenxi
2014-07-01
Brain retraction causes great distortion that limits the accuracy of an image-guided neurosurgery system that uses preoperative images. Therefore, brain retraction correction is an important intraoperative clinical application. We used a linear elastic biomechanical model, which deforms based on the eXtended Finite Element Method (XFEM) within a framework for brain retraction correction. In particular, a laser range scanner was introduced to obtain a surface point cloud of the exposed surgical field including retractors inserted into the brain. A brain retraction surface tracking algorithm converted these point clouds into boundary conditions applied to XFEM modeling that drive brain deformation. To test the framework, we performed a brain phantom experiment involving the retraction of tissue. Pairs of the modified Hausdorff distance between Canny edges extracted from model-updated images, pre-retraction, and post-retraction CT images were compared to evaluate the morphological alignment of our framework. Furthermore, the measured displacements of beads embedded in the brain phantom and the predicted ones were compared to evaluate numerical performance. The modified Hausdorff distance of 19 pairs of images decreased from 1.10 to 0.76 mm. The forecast error of 23 stainless steel beads in the phantom was between 0 and 1.73 mm (mean 1.19 mm). The correction accuracy varied between 52.8 and 100 % (mean 81.4 %). The results demonstrate that the brain retraction compensation can be incorporated intraoperatively into the model-updating process in image-guided neurosurgery systems.
Fragmentation of interstellar clouds and star formation
NASA Technical Reports Server (NTRS)
Silk, J.
1982-01-01
The principal issues are addressed: the fragmentation of molecular clouds into units of stellar mass and the impact of star formation on molecular clouds. The observational evidence for fragmentation is summarized, and the gravitational instability described of a uniform spherical cloud collapsing from rest. The implications are considered of a finite pressure for the minimum fragment mass that is attainable in opacity-limited fragmentation. The role of magnetic fields is discussed in resolving the angular momentum problem and in making the collapse anisotropic, with notable consequences for fragmentation theory. Interactions between fragments are described, with emphasis on the effect of protostellar winds on the ambient cloud matter and on inhibiting further star formation. Such interactions are likely to have profound consequences for regulating the rate of star formation and on the energetics and dynamics of molecular clouds.
Stereoscopic, thermal, and true deep cumulus cloud top heights
NASA Astrophysics Data System (ADS)
Llewellyn-Jones, D. T.; Corlett, G. K.; Lawrence, S. P.; Remedios, J. J.; Sherwood, S. C.; Chae, J.; Minnis, P.; McGill, M.
2004-05-01
We compare cloud-top height estimates from several sensors: thermal tops from GOES-8 and MODIS, stereoscopic tops from MISR, and directly measured heights from the Goddard Cloud Physics Lidar on board the ER-2, all collected during the CRYSTAL-FACE field campaign. Comparisons reveal a persistent 1-2 km underestimation of cloud-top heights by thermal imagery, even when the finite optical extinctions near cloud top and in thin overlying cirrus are taken into account. The most severe underestimates occur for the tallest clouds. The MISR "best-sinds" and lidar estimates disagree in very similar ways with thermally estimated tops, which we take as evidence of excellent performance by MISR. Encouraged by this, we use MISR to examine variations in cloud penetration and thermal top height errors in several locations of tropical deep convection over multiple seasons. The goals of this are, first, to learn how cloud penetration depends on the near-tropopause environment; and second, to gain further insight into the mysterious underestimation of tops by thermal imagery.
NASA Technical Reports Server (NTRS)
Thuemmel, Helmar T.; Huo, Winifred M.; Langhoff, Stephen R. (Technical Monitor)
1995-01-01
For the calculation of electron molecule collision cross sections R-matrix methods automatically take advantage of the division of configuration space into an inner region (I) bounded by radius tau b, where the scattered electron is within the molecular charge cloud and the system is described by an correlated Configuration Interaction (CI) treatment in close analogy to bound state calculations, and an outer region (II) where the scattered electron moves in the long-range multipole potential of the target and efficient analytic methods can be used for solving the asymptotic Schroedinger equation plus boundary conditions.
NASA Technical Reports Server (NTRS)
Winchester, L. W., Jr.
1980-01-01
Using the finite difference method with overrelaxation, numerical solutions of the steady-state vorticity transport equation were obtained for a continuous flow diffusion chamber of the Hudson-Squires type. The calculation neglected the effects due to temperature, gravity, and saturation. The size and shape of the manifold used to inject the aerosol laden flow were varied to obtain a design which would improve the performance of the chamber from strictly low Reynolds number (less than 20) fluid dynamical considerations.
Self-confinement of finite dust clusters in isotropic plasmas.
Miloshevsky, G V; Hassanein, A
2012-05-01
Finite two-dimensional dust clusters are systems of a small number of charged grains. The self-confinement of dust clusters in isotropic plasmas is studied using the particle-in-cell method. The energetically favorable configurations of grains in plasma are found that are due to the kinetic effects of plasma ions and electrons. The self-confinement phenomenon is attributed to the change in the plasma composition within a dust cluster resulting in grain attraction mediated by plasma ions. This is a self-consistent state of a dust cluster in which grain's repulsion is compensated by the reduced charge and floating potential on grains, overlapped ion clouds, and depleted electrons within a cluster. The common potential well is formed trapping dust clusters in the confined state. These results provide both valuable insights and a different perspective to the classical view on the formation of boundary-free dust clusters in isotropic plasmas.
Finite slice analysis (FINA) of sliced and velocity mapped images on a Cartesian grid
NASA Astrophysics Data System (ADS)
Thompson, J. O. F.; Amarasinghe, C.; Foley, C. D.; Rombes, N.; Gao, Z.; Vogels, S. N.; van de Meerakker, S. Y. T.; Suits, A. G.
2017-08-01
Although time-sliced imaging yields improved signal-to-noise and resolution compared with unsliced velocity mapped ion images, for finite slice widths as encountered in real experiments there is a loss of resolution and recovered intensities for the slow fragments. Recently, we reported a new approach that permits correction of these effects for an arbitrarily sliced distribution of a 3D charged particle cloud. This finite slice analysis (FinA) method utilizes basis functions that model the out-of-plane contribution of a given velocity component to the image for sequential subtraction in a spherical polar coordinate system. However, the original approach suffers from a slow processing time due to the weighting procedure needed to accurately model the out-of-plane projection of an anisotropic angular distribution. To overcome this issue we present a variant of the method in which the FinA approach is performed in a cylindrical coordinate system (Cartesian in the image plane) rather than a spherical polar coordinate system. Dubbed C-FinA, we show how this method is applied in much the same manner. We compare this variant to the polar FinA method and find that the processing time (of a 510 × 510 pixel image) in its most extreme case improves by a factor of 100. We also show that although the resulting velocity resolution is not quite as high as the polar version, this new approach shows superior resolution for fine structure in the differential cross sections. We demonstrate the method on a range of experimental and synthetic data at different effective slice widths.
NASA Astrophysics Data System (ADS)
McKague, Darren Shawn
2001-12-01
The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)
Cloud Model-Based Artificial Immune Network for Complex Optimization Problem
Wang, Mingan; Li, Jianming; Guo, Dongliang
2017-01-01
This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators—cloning, mutation, and suppression—are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications—finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning—are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm. PMID:28630620
Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.
Wang, Mingan; Feng, Shuo; Li, Jianming; Li, Zhonghua; Xue, Yu; Guo, Dongliang
2017-01-01
This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications-finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning-are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm.
Computation of shear-induced collective-diffusivity in emulsions
NASA Astrophysics Data System (ADS)
Malipeddi, Abhilash Reddy; Sarkar, Kausik
2017-11-01
The shear-induced collective-diffusivity of drops in an emulsion is calculated through simulation. A front-tracking finite difference method is used to integrate the Navier-Stokes equations. When a cloud of drops is subjected to shear flow, after a certain time, the width of the cloud increases with the 1/3 power of time. This scaling of drop-cloud-width with time is characteristic of (sub-)diffusion that arises from irreversible two-drop interactions. The collective diffusivity is calculated from this relationship. A feature of the procedure adopted here is the modest computational requirement, wherein, a few drops ( 70) in shear for short time ( 70 strain) is found to be sufficient to get a good estimate. As far as we know, collective-diffusivity has not been calculated for drops through simulation till now. The computed values match with experimental measurements reported in the literature. The diffusivity in emulsions is calculated for a range of Capillary (Ca) and Reynolds (Re) numbers. It is found to be a unimodal function of Ca , similar to self-diffusivity. A sub-linear increase of the diffusivity with Re is seen for Re < 5 . This work has been limited to a viscosity matched case.
Sensitivity of liquid clouds to homogenous freezing parameterizations.
Herbert, Ross J; Murray, Benjamin J; Dobbie, Steven J; Koop, Thomas
2015-03-16
Water droplets in some clouds can supercool to temperatures where homogeneous ice nucleation becomes the dominant freezing mechanism. In many cloud resolving and mesoscale models, it is assumed that homogeneous ice nucleation in water droplets only occurs below some threshold temperature typically set at -40°C. However, laboratory measurements show that there is a finite rate of nucleation at warmer temperatures. In this study we use a parcel model with detailed microphysics to show that cloud properties can be sensitive to homogeneous ice nucleation as warm as -30°C. Thus, homogeneous ice nucleation may be more important for cloud development, precipitation rates, and key cloud radiative parameters than is often assumed. Furthermore, we show that cloud development is particularly sensitive to the temperature dependence of the nucleation rate. In order to better constrain the parameterization of homogeneous ice nucleation laboratory measurements are needed at both high (>-35°C) and low (<-38°C) temperatures. Homogeneous freezing may be significant as warm as -30°CHomogeneous freezing should not be represented by a threshold approximationThere is a need for an improved parameterization of homogeneous ice nucleation.
Electrostatic forces in planetary rings
NASA Technical Reports Server (NTRS)
Goertz, C. K.; Shan, Linhua; Havnes, O.
1988-01-01
The average charge on a particle in a particle-plasma cloud, the plasma potential inside the cloud, and the Coulomb force acting on the particle are calculated. The net repulsive electrostatic force on a particle depends on the plasma density, temperature, density of particles, particle size, and the gradient of the particle density. In a uniformly dense ring the electrostatic repulsion is zero. It is also shown that the electrostatic force acts like a pressure force, that even a collisionless ring can be stable against gravitational collapse, and that a finite ring thickness does not necessarily imply a finite velocity dispersion. A simple criterion for the importance of electrostatic forces in planetary rings is derived which involves the calculation of the vertical ring thickness which would result if only electrostatic repulsion were responsible for the finite ring thickness. Electrostatic forces are entirely negligible in the main rings of Saturn and the E and G rings. They may also be negligible in the F ring. However, the Uranian rings and Jupiter's ring seem to be very much influenced by electrostatic repulsion. In fact, electrostatic forces could support a Jovian ring which is an order of magnitude more dense than observed.
Fixtureless nonrigid part inspection using depth cameras
NASA Astrophysics Data System (ADS)
Xiong, Hanwei; Xu, Jun; Xu, Chenxi; Pan, Ming
2016-10-01
In automobile industry, flexible thin shell parts are used to cover car body. Such parts could have a different shape in a free state than the design model due to dimensional variation, gravity loads and residual strains. Special inspection fixtures are generally indispensable for geometric inspection. Recently, some researchers have proposed fixtureless nonridged inspect methods using intrinsic geometry or virtual spring-mass system, based on some assumptions about deformation between Free State shape and nominal CAD shape. In this paper, we propose a new fixtureless method to inspect flexible parts with a depth camera, which is efficient and low computational complexity. Unlike traditional method, we gather two point cloud set of the manufactured part in two different states, and make correspondences between them and one of them to the CAD model. The manufacturing defects can be derived from the correspondences. Finite element method (FEM) disappears in our method. Experimental evaluation of the proposed method is presented.
NASA Astrophysics Data System (ADS)
Chen, W. A.; Woods, C. P.; Li, J. F.; Waliser, D. E.; Chern, J.; Tao, W.; Jiang, J. H.; Tompkins, A. M.
2010-12-01
CloudSat provides important estimates of vertically resolved ice water content (IWC) on a global scale based on radar reflectivity. These estimates of IWC have proven beneficial in evaluating the representations of ice clouds in global models. An issue when performing model-data comparisons of IWC particularly germane to this investigation, is the question of which component(s) of the frozen water mass are represented by retrieval estimates and how they relate to what is represented in models. The present study developed and applied a new technique to partition CloudSat total IWC into small and large ice hydrometeors, based on the CloudSat-retrieved ice particle size distribution (PSD) parameters. The new method allows one to make relevant model-data comparisons and provides new insights into the model’s representation of atmospheric IWC. The partitioned CloudSat IWC suggests that the small ice particles contribute to 20-30% of the total IWC in the upper troposphere when a threshold size of 100 μm is used. Sensitivity measures with respect to the threshold size, the PSD parameters, and the retrieval algorithms are presented. The new dataset is compared to model estimates, pointing to areas for model improvement. Cloud ice analyses from the European Centre for Medium-Range Weather Forecasts model agree well with the small IWC from CloudSat. The finite-volume multi-scale modeling framework model underestimates total IWC at 147 and 215 hPa, while overestimating the fractional contribution from the small ice species. These results are discussed in terms of their applications to, and implications for, the evaluation of global atmospheric models, providing constraints on the representations of cloud feedback and precipitation in global models, which in turn can help reduce uncertainties associated with climate change projections. Figure 1. A sample lognormal ice number distribution (red curve), and the corresponding mass distribution (black curve). The dotted line represents the cutoff size for IWC partitioning (Dc = 100 µm as an example). The partial integrals of the mass distribution for particles smaller and larger than Dc correspond to IWC<100 (green area) and IWC>100 (blue area), respectively.
Influence of carbon dioxide clouds on early martian climate.
Mischna, M A; Kasting, J F; Pavlov, A; Freedman, R
2000-06-01
Recent studies have shown that clouds made of carbon dioxide ice may have warmed the surface of early Mars by reflecting not only incoming solar radiation but upwelling IR radiation as well. However, these studies have not treated scattering self-consistently in the thermal IR. Our own calculations, which treat IR scattering properly, confirm these earlier calculations but show that CO2 clouds can also cool the surface, especially if they are low and optically thick. Estimating the actual effect of CO2 clouds on early martian climate will require three-dimensional models in which cloud location, height, and optical depth, as well as surface temperature and pressure, are determined self-consistently. Our calculations further confirm that CO2 clouds should extend the outer boundary of the habitable zone around a star but that there is still a finite limit beyond which above-freezing surface temperatures cannot be maintained by a CO2-H2O atmosphere. For our own Solar System, the absolute outer edge of the habitable zone is at approximately 2.4 AU.
Application-oriented offloading in heterogeneous networks for mobile cloud computing
NASA Astrophysics Data System (ADS)
Tseng, Fan-Hsun; Cho, Hsin-Hung; Chang, Kai-Di; Li, Jheng-Cong; Shih, Timothy K.
2018-04-01
Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.
NASA Astrophysics Data System (ADS)
Marshall, R. A.; Inan, U. S.; Glukhov, V. S.
2010-04-01
A 3-D finite difference time domain model is used to simulate the lightning electromagnetic pulse (EMP) and its interaction with the lower ionosphere. Results agree with the frequently observed, doughnut-shaped optical signature of elves but show that the structure exhibits asymmetry due to the presence of Earth's ambient magnetic field. Furthermore, in-cloud (horizontal) lightning channels produce observable optical emissions without the doughnut shape and, in fact, produce a much stronger optical output for the same channel current. Electron density perturbations associated with elves are also calculated, with contributions from attachment and ionization. Results presented as a function of parameters such as magnetic field direction, dipole current orientation, altitude and amplitude, and ambient ionospheric density profile demonstrate the highly nonlinear nature of the EMP-ionosphere interaction. Ionospheric effects of a sequence of in-cloud discharges are calculated, simulating a burst of in-cloud lightning activity and resulting in large density changes in the overlying ionosphere.
Ross, David S; Thurston, George M; Lutzer, Carl V
2008-08-14
In this paper we present a method for determining the free energies of ternary mixtures from light scattering data. We use an approximation that is appropriate for liquid mixtures, which we formulate as a second-order nonlinear partial differential equation. This partial differential equation (PDE) relates the Hessian of the intensive free energy to the efficiency of light scattering in the forward direction. This basic equation applies in regions of the phase diagram in which the mixtures are thermodynamically stable. In regions in which the mixtures are unstable or metastable, the appropriate PDE is the nonlinear equation for the convex hull. We formulate this equation along with continuity conditions for the transition between the two equations at cloud point loci. We show how to discretize this problem to obtain a finite-difference approximation to it, and we present an iterative method for solving the discretized problem. We present the results of calculations that were done with a computer program that implements our method. These calculations show that our method is capable of reconstructing test free energy functions from simulated light scattering data. If the cloud point loci are known, the method also finds the tie lines and tie triangles that describe thermodynamic equilibrium between two or among three liquid phases. A robust method for solving this PDE problem, such as the one presented here, can be a basis for optical, noninvasive means of characterizing the thermodynamics of multicomponent mixtures.
1994-06-01
charge clouds. These finitely-remote fields are then used to compute asymptotic radiation fields in the limit of the field point going to infinity in a 0...like to thank Doug Beason for providing an environment conducive to performing the research reported on here and Michelle Tafoya for her excellent...radiation quantities, however, are obtained only in the limit of the field point going to infinity ; we thus demonstrate the existence of this limit and
Element fracture technique for hypervelocity impact simulation
NASA Astrophysics Data System (ADS)
Zhang, Xiao-tian; Li, Xiao-gang; Liu, Tao; Jia, Guang-hui
2015-05-01
Hypervelocity impact dynamics is the theoretical support of spacecraft shielding against space debris. The numerical simulation has become an important approach for obtaining the ballistic limits of the spacecraft shields. Currently, the most widely used algorithm for hypervelocity impact is the smoothed particle hydrodynamics (SPH). Although the finite element method (FEM) is widely used in fracture mechanics and low-velocity impacts, the standard FEM can hardly simulate the debris cloud generated by hypervelocity impact. This paper presents a successful application of the node-separation technique for hypervelocity impact debris cloud simulation. The node-separation technique assigns individual/coincident nodes for the adjacent elements, and it applies constraints to the coincident node sets in the modeling step. In the explicit iteration, the cracks are generated by releasing the constrained node sets that meet the fracture criterion. Additionally, the distorted elements are identified from two aspects - self-piercing and phase change - and are deleted so that the constitutive computation can continue. FEM with the node-separation technique is used for thin-wall hypervelocity impact simulations. The internal structures of the debris cloud in the simulation output are compared with that in the test X-ray graphs under different material fracture criteria. It shows that the pressure criterion is more appropriate for hypervelocity impact. The internal structures of the debris cloud are also simulated and compared under different thickness-to-diameter ratios (t/D). The simulation outputs show the same spall pattern with the tests. Finally, the triple-plate impact case is simulated with node-separation FEM.
NASA Technical Reports Server (NTRS)
Putman, William P.
2012-01-01
Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.
Cavitation clouds created by shock scattering from bubbles during histotripsy
Maxwell, Adam D.; Wang, Tzu-Yin; Cain, Charles A.; Fowlkes, J. Brian; Sapozhnikov, Oleg A.; Bailey, Michael R.; Xu, Zhen
2011-01-01
Histotripsy is a therapy that focuses short-duration, high-amplitude pulses of ultrasound to incite a localized cavitation cloud that mechanically breaks down tissue. To investigate the mechanism of cloud formation, high-speed photography was used to observe clouds generated during single histotripsy pulses. Pulses of 5−20 cycles duration were applied to a transparent tissue phantom by a 1-MHz spherically focused transducer. Clouds initiated from single cavitation bubbles that formed during the initial cycles of the pulse, and grew along the acoustic axis opposite the propagation direction. Based on these observations, we hypothesized that clouds form as a result of large negative pressure generated by the backscattering of shockwaves from a single bubble. The positive-pressure phase of the wave inverts upon scattering and superimposes on the incident negative-pressure phase to create this negative pressure and cavitation. The process repeats with each cycle of the incident wave, and the bubble cloud elongates toward the transducer. Finite-amplitude propagation distorts the incident wave such that the peak-positive pressure is much greater than the peak-negative pressure, which exaggerates the effect. The hypothesis was tested with two modified incident waves that maintained negative pressure but reduced the positive pressure amplitude. These waves suppressed cloud formation which supported the hypothesis. PMID:21973343
Cooperative scattering and radiation pressure force in dense atomic clouds
NASA Astrophysics Data System (ADS)
Bachelard, R.; Piovella, N.; Courteille, Ph. W.
2011-07-01
Atomic clouds prepared in “timed Dicke” states, i.e. states where the phase of the oscillating atomic dipole moments linearly varies along one direction of space, are efficient sources of superradiant light emission [Scully , Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.96.010501 96, 010501 (2006)]. Here, we show that, in contrast to previous assertions, timed Dicke states are not the states automatically generated by incident laser light. In reality, the atoms act back on the driving field because of the finite refraction of the cloud. This leads to nonuniform phase shifts, which, at higher optical densities, dramatically alter the cooperative scattering properties, as we show by explicit calculation of macroscopic observables, such as the radiation pressure force.
Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data
NASA Technical Reports Server (NTRS)
2000-01-01
Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.
NASA Technical Reports Server (NTRS)
Myhill, Elizabeth A.; Boss, Alan P.
1993-01-01
In Boss & Myhill (1992) we described the derivation and testing of a spherical coordinate-based scheme for solving the hydrodynamic equations governing the gravitational collapse of nonisothermal, nonmagnetic, inviscid, radiative, three-dimensional protostellar clouds. Here we discuss a Cartesian coordinate-based scheme based on the same set of hydrodynamic equations. As with the spherical coorrdinate-based code, the Cartesian coordinate-based scheme employs explicit Eulerian methods which are both spatially and temporally second-order accurate. We begin by describing the hydrodynamic equations in Cartesian coordinates and the numerical methods used in this particular code. Following Finn & Hawley (1989), we pay special attention to the proper implementations of high-order accuracy, finite difference methods. We evaluate the ability of the Cartesian scheme to handle shock propagation problems, and through convergence testing, we show that the code is indeed second-order accurate. To compare the Cartesian scheme discussed here with the spherical coordinate-based scheme discussed in Boss & Myhill (1992), the two codes are used to calculate the standard isothermal collapse test case described by Bodenheimer & Boss (1981). We find that with the improved codes, the intermediate bar-configuration found previously disappears, and the cloud fragments directly into a binary protostellar system. Finally, we present the results from both codes of a new test for nonisothermal protostellar collapse.
A tractable prescription for large-scale free flight expansion of wavefunctions
NASA Astrophysics Data System (ADS)
Deuar, P.
2016-11-01
A numerical recipe is given for obtaining the density image of an initially compact quantum mechanical wavefunction that has expanded by a large but finite factor under free flight. The recipe given avoids the memory storage problems that plague this type of calculation by reducing the problem to the sum of a number of fast Fourier transforms carried out on the relatively small initial lattice. The final expanded state is given exactly on a coarser magnified grid with the same number of points as the initial state. An important application of this technique is the simulation of measured time-of-flight images in ultracold atom experiments, especially when the initial clouds contain superfluid defects. It is shown that such a finite-time expansion, rather than a far-field approximation is essential to correctly predict images of defect-laden clouds, even for long flight times. Examples shown are: an expanding quasicondensate with soliton defects and a matter-wave interferometer in 3D.
New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework
NASA Technical Reports Server (NTRS)
Sud, Y. C.; Walker, G. K.; Lau, William (Technical Monitor)
2002-01-01
Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).
A new 3D maser code applied to flaring events
NASA Astrophysics Data System (ADS)
Gray, M. D.; Mason, L.; Etoka, S.
2018-06-01
We set out the theory and discretization scheme for a new finite-element computer code, written specifically for the simulation of maser sources. The code was used to compute fractional inversions at each node of a 3D domain for a range of optical thicknesses. Saturation behaviour of the nodes with regard to location and optical depth was broadly as expected. We have demonstrated via formal solutions of the radiative transfer equation that the apparent size of the model maser cloud decreases as expected with optical depth as viewed by a distant observer. Simulations of rotation of the cloud allowed the construction of light curves for a number of observable quantities. Rotation of the model cloud may be a reasonable model for quasi-periodic variability, but cannot explain periodic flaring.
Resolving Rapid Variation in Energy for Particle Transport
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haut, Terry Scot; Ahrens, Cory Douglas; Jonko, Alexandra
2016-08-23
Resolving the rapid variation in energy in neutron and thermal radiation transport is needed for the predictive simulation capability in high-energy density physics applications. Energy variation is difficult to resolve due to rapid variations in cross sections and opacities caused by quantized energy levels in the nuclei and electron clouds. In recent work, we have developed a new technique to simultaneously capture slow and rapid variations in the opacities and the solution using homogenization theory, which is similar to multiband (MB) and to the finite-element with discontiguous support (FEDS) method, but does not require closure information. We demonstrated the accuracymore » and efficiency of the method for a variety of problems. We are researching how to extend the method to problems with multiple materials and the same material but with different temperatures and densities. In this highlight, we briefly describe homogenization theory and some results.« less
Nyx: Adaptive mesh, massively-parallel, cosmological simulation code
NASA Astrophysics Data System (ADS)
Almgren, Ann; Beckner, Vince; Friesen, Brian; Lukic, Zarija; Zhang, Weiqun
2017-12-01
Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx use a finite volume methodology on an adaptive set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics for accurately modeling the intergalactic medium; in optically thin limits and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field.
Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2005-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.
NASA Technical Reports Server (NTRS)
Weckmann, Stephanie
1997-01-01
The Clouds and the Earth's Radiant Energy System (CERES) is a program sponsored by the National Aeronautics and Space Administration (NASA) aimed at evaluating the global energy balance. Current scanning radiometers used for CERES consist of thin-film thermistor bolometers viewing the Earth through a Cassegrain telescope. The Thermal Radiation Group, a laboratory in the Department of Mechanical Engineering at Virginia Polytechnic Institute and State University, is currently studying a new sensor concept to replace the current bolometer: a thermopile thermal radiation detector. This next-generation detector would consist of a thermal sensor array made of thermocouple junction pairs, or thermopiles. The objective of the current research is to perform a thermal analysis of the thermopile. Numerical thermal models are particularly suited to solve problems for which temperature is the dominant mechanism of the operation of the device (through the thermoelectric effect), as well as for complex geometries composed of numerous different materials. Feasibility and design specifications are studied by developing a dynamic electrothermal model of the thermopile using the finite element method. A commercial finite element-modeling package, ALGOR, is used.
Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2004-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to imiprove the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.
Coupled fvGCM-GCE Modeling System: TRMM Latent Heating and Cloud Library
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2005-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. In this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the GCE model on developing a global cloud simulator.
Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2005-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.
The Relation of Finite Element and Finite Difference Methods
NASA Technical Reports Server (NTRS)
Vinokur, M.
1976-01-01
Finite element and finite difference methods are examined in order to bring out their relationship. It is shown that both methods use two types of discrete representations of continuous functions. They differ in that finite difference methods emphasize the discretization of independent variable, while finite element methods emphasize the discretization of dependent variable (referred to as functional approximations). An important point is that finite element methods use global piecewise functional approximations, while finite difference methods normally use local functional approximations. A general conclusion is that finite element methods are best designed to handle complex boundaries, while finite difference methods are superior for complex equations. It is also shown that finite volume difference methods possess many of the advantages attributed to finite element methods.
NASA Astrophysics Data System (ADS)
Hansell, Richard Allen, Jr.
The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud coverage for the Persian Gulf case compare reasonably well to those from the "Deep Blue" algorithm developed at NASA-GSFC. The nighttime dust/cloud detection for the cases surrounding Cape Verde and Niger, West Africa has been validated by comparing to coincident and collocated ground-based micro-pulse lidar measurements.
An efficient framework for modeling clouds from Landsat8 images
NASA Astrophysics Data System (ADS)
Yuan, Chunqiang; Guo, Jing
2015-03-01
Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.
Gravitational fragmentation caught in the act: the filamentary Musca molecular cloud
NASA Astrophysics Data System (ADS)
Kainulainen, J.; Hacar, A.; Alves, J.; Beuther, H.; Bouy, H.; Tafalla, M.
2016-02-01
Context. Filamentary structures are common in molecular clouds. Explaining how they fragment to dense cores is a missing step in understanding their role in star formation. Aims: We perform a case study of whether low-mass filaments are close to hydrostatic prior to their fragmentation, and whether their fragmentation agrees with gravitational fragmentation models. To accomplish this, we study the ~6.5 pc long Musca molecular cloud, which is an ideal candidate for a filament at an early stage of fragmentation. Methods: We employ dust extinction mapping, in conjunction with near-infrared JHKS-band data from the CTIO/NEWFIRM instrument, and 870 μm dust continuum emission data from the APEX/LABOCA instrument to estimate column densities in Musca. We use the data to identify fragments from the cloud and to determine the radial density distribution of its filamentary part. We compare the cloud's morphology with 13CO and C18O line emission observed with the APEX/SHeFI instrument. Results: The Musca cloud is pronouncedly fragmented at its ends, but harbors a remarkably well-defined, ~1.6 pc long filament in its center region. The line mass of the filament is 21-31 M⊙ pc-1 and the full width at half maximum (FWHM) 0.07 pc. The radial profile of the filament can be fitted with a Plummer profile, which has the power-index of 2.6 ± 11% and is flatter than that of an infinite hydrostatic filament. The profile can also be fitted with a hydrostatic cylinder truncated by external pressure. These models imply a central density of ~5-10 × 104 cm-3. The fragments in the cloud have a mean separation of ~0.4 pc, in agreement with gravitational fragmentation. These properties, together with the subsonic and velocity-coherent nature of the cloud, suggest a scenario in which an initially hydrostatic cloud is currently gravitationally fragmenting. The fragmentation started a few tenths of a Myr ago from the ends of the cloud, leaving its center still relatively nonfragmented, possibly because of gravitational focusing in a finite geometry. This publication is based on data acquired with the Atacama Pathfinder Experiment (APEX), which is a collaboration between the Max-Planck-Institut für Radioastronomie, the European Southern Observatory, and the Onsala Space Observatory (Max-Planck programme ID M-085.F-0027).The maps as FITS files are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/586/A27
NASA Astrophysics Data System (ADS)
Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo
2016-10-01
Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.
A new time domain random walk method for solute transport in 1-D heterogeneous media
DOE Office of Scientific and Technical Information (OSTI.GOV)
Banton, O.; Delay, F.; Porel, G.
A new method to simulate solute transport in 1-D heterogeneous media is presented. This time domain random walk method (TDRW), similar in concept to the classical random walk method, calculates the arrival time of a particle cloud at a given location (directly providing the solute breakthrough curve). The main advantage of the method is that the restrictions on the space increments and the time steps which exist with the finite differences and random walk methods are avoided. In a homogeneous zone, the breakthrough curve (BTC) can be calculated directly at a given distance using a few hundred particles or directlymore » at the boundary of the zone. Comparisons with analytical solutions and with the classical random walk method show the reliability of this method. The velocity and dispersivity calculated from the simulated results agree within two percent with the values used as input in the model. For contrasted heterogeneous media, the random walk can generate high numerical dispersion, while the time domain approach does not.« less
Thin Cloud Detection Method by Linear Combination Model of Cloud Image
NASA Astrophysics Data System (ADS)
Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.
2018-04-01
The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.
Cloud-Induced Uncertainty for Visual Navigation
2014-12-26
images at the pixel level. The result is a method that can overlay clouds with various structures on top of any desired image to produce realistic...cloud-shaped structures . The primary contribution of this research, however, is to investigate and quantify the errors in features due to clouds. The...of clouds types, this method does not emulate the true structure of clouds. An alternative popular modern method of creating synthetic clouds is known
NASA Astrophysics Data System (ADS)
Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying
2018-04-01
Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct accuracy exceeding 80%, approximately 5% of the areas were wrongly identified, and approximately 10% of the cloud shadow areas were missing. The accuracy of this method is obviously higher than the recognition accuracy of Fmask, which has correct accuracy lower than 60%, and the missing recognition is approximately 40%.
Effect of atmospheric scattering and surface reflection on upwelling solar radiation
NASA Technical Reports Server (NTRS)
Suttles, J. T.; Barkstrom, B. R.; Tiwari, S. N.
1981-01-01
A study is presented of the solar radiation transfer in the complete earth-atmosphere system, and numerical results are compared with satellite data obtained during the Earth Radiation Budget Experiment on Nimbus 6, in August, 1975. Emphasis is placed on the upwelling radiance distribution at the top of the atmosphere, assumed to be at 50 km. The numerical technique is based on the finite difference method, which includes azimuth and spectral variations for the entire solar wavelength range. Detailed solar properties, atmospheric physical properties, and optical properties are used. However, since the property descriptions are based on a trade-off between accuracy and computational realities, aerosol and cloud optical properties are treated with simple approximations. The radiative transfer model is in good agreement with the satellite radiance observations. The method provides a valuable tool in analyzing satellite- and ground-based radiation budget measurements and in designing instrumentation.
Methods for estimating 2D cloud size distributions from 1D observations
Romps, David M.; Vogelmann, Andrew M.
2017-08-04
The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also performmore » well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. Finally, as a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the RACORO campaign, which then allow for an estimate of the true area-weighted mean cloud size.« less
Methods for estimating 2D cloud size distributions from 1D observations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Romps, David M.; Vogelmann, Andrew M.
The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also performmore » well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. Finally, as a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the RACORO campaign, which then allow for an estimate of the true area-weighted mean cloud size.« less
NASA Astrophysics Data System (ADS)
Li, DaLei; Lou, Yu-Qing; Esimbek, Jarken
2018-01-01
We study self-similar hydrodynamics of spherical symmetry using a general polytropic (GP) equation of state and derive the GP dynamic Lane-Emden equation (LEE) with a radial inertial force. In reference to Lou & Cao, we solve the GP dynamic LEE for both polytropic index γ = 1 + 1/n and the isothermal case n → +∞; our formalism is more general than the conventional polytropic model with n = 3 or γ = 4/3 of Goldreich & Weber. For proper boundary conditions, we obtain an exact constant solution for arbitrary n and analytic variable solutions for n = 0 and n = 1, respectively. Series expansion solutions are derived near the origin with the explicit recursion formulae for the series coefficients for both the GP and isothermal cases. By extensive numerical explorations, we find that there is no zero density at a finite radius for n ≥ 5. For 0 ≤ n < 5, we adjust the inertial force parameter c and find the range of c > 0 for monotonically decreasing density from the origin and vanishing at a finite radius for c being less than a critical value Ccr. As astrophysical applications, we invoke our solutions of the GP dynamic LEE with central finite boundary conditions to fit the molecular cloud core Barnard 68 in contrast to the static isothermal Bonnor-Ebert sphere by Alves et al. Our GP dynamic model fits appear to be sensibly consistent with several more observations and diagnostics for density, temperature and gas pressure profiles.
Study on Diagnosing Three Dimensional Cloud Region
NASA Astrophysics Data System (ADS)
Cai, M., Jr.; Zhou, Y., Sr.
2017-12-01
Cloud mask and relative humidity (RH) provided by Cloudsat products from 2007 to 2008 are statistical analyzed to get RH Threshold between cloud and clear sky and its variation with height. A diagnosis method is proposed based on reanalysis data and applied to three-dimensional cloud field diagnosis of a real case. Diagnostic cloud field was compared to satellite, radar and other cloud precipitation observation. Main results are as follows. 1.Cloud region where cloud mask is bigger than 20 has a good space and time corresponding to the high value relative humidity region, which is provide by ECWMF AUX product. Statistical analysis of the RH frequency distribution within and outside cloud indicated that, distribution of RH in cloud at different height range shows single peak type, and the peak is near a RH value of 100%. Local atmospheric environment affects the RH distribution outside cloud, which leads to TH distribution vary in different region or different height. 2. RH threshold and its vertical distribution used for cloud diagnostic was analyzed from Threat Score method. The method is applied to a three dimension cloud diagnosis case study based on NCEP reanalysis data and th diagnostic cloud field is compared to satellite, radar and cloud precipitation observation on ground. It is found that, RH gradient is very big around cloud region and diagnosed cloud area by RH threshold method is relatively stable. Diagnostic cloud area has a good corresponding to updraft region. The cloud and clear sky distribution corresponds to satellite the TBB observations overall. Diagnostic cloud depth, or sum cloud layers distribution consists with optical thickness and precipitation on ground better. The cloud vertical profile reveals the relation between cloud vertical structure and weather system clearly. Diagnostic cloud distribution correspond to cloud observations on ground very well. 3. The method is improved by changing the vertical interval from altitude to temperature. The result shows that, the five factors , including TS score for clear sky, empty forecast, missed forecast, and especially TS score for cloud region and the accurate rate increased obviously. So, the RH threshold and its vertical distribution with temperature is better than with altitude. More tests and comparision should be done to assess the diagnosis method.
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2006-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).
NASA Astrophysics Data System (ADS)
Professor Khachay, Yurie
2015-04-01
Two characteristic times are significant for evolution the interior of the homogeneous proto-planetary cloud: the time of bodies free fall towards the clouds mass center and the time of sound distribution through the cloud. With the beginning of proto-planetary disk fragmentation and accumulation of the proto-planets from the bodies and particles there are formed matter content heterogeneities of the finite dimension, heterogeneities of temperature, density and values of kinetic coefficients. The system became more and more complicated with interior interconnections. By the growing of the bodies the difference between the values of the characteristic times and dimensions become larger. The dynamical evolution of the system we could observe with use the numerical modeling of the Earth and Moon formation into the 3-D model [1,2]. The fact, that the linear dimensions of the objects during the accumulation process change from the centimeter and meter dimensions to some thousands of kilometers significantly prevent the mathematical description of these processes. The corresponding values of the no dimensional similarity criterions, which are included into the systems of differential equations, which describe the proto-planetary growing, the conditions for entropy and mass on the growing surface, the equations of the impulse balance, energy and mass into the interior parts of the planet change on an orders of values. Therefore we used very detailed space and time grids for solution the problem using the method of finite differences. The additional complications occur according to necessity to take into account the nonlinear dependence of matter viscosity from the temperature, pressure and chemical matter content. At last we took into account the principal random distribution of heterogeneities, stipulated by bodies and particles falling. Only progression towards that direction and constructing corresponding systems of observation and interpretation allow to hope receiving more and more realistic models of self organizing structures and to understand the laws of their reconstruction during the complicated process of planetary accumulation. The work is fulfilled by partly support of RFBR (grant N13-05-00138). References. 1. Y. Khachay , V. Anfilogov , and A. Antipin (2014) Numerical Results of 3-D Modeling of Moon Accumulation // Geophysical Research Abstracts, Vol. 16, EGU2014-1011 2. Y.Khachay, A.Antipin and V.Anfilogov (2014)Numerical modeling of temperature distribution on the stage of Earth's accumulation in a frame of 3-D model and peculiarities of its initial minerageny. Ural geophysical bulletin 1: 81-85.
NASA Astrophysics Data System (ADS)
Weatherill, Daniel P.; Stefanov, Konstantin D.; Greig, Thomas A.; Holland, Andrew D.
2014-07-01
Pixellated monolithic silicon detectors operated in a photon-counting regime are useful in spectroscopic imaging applications. Since a high energy incident photon may produce many excess free carriers upon absorption, both energy and spatial information can be recovered by resolving each interaction event. The performance of these devices in terms of both the energy and spatial resolution is in large part determined by the amount of diffusion which occurs during the collection of the charge cloud by the pixels. Past efforts to predict the X-ray performance of imaging sensors have used either analytical solutions to the diffusion equation or simplified monte carlo electron transport models. These methods are computationally attractive and highly useful but may be complemented using more physically detailed models based on TCAD simulations of the devices. Here we present initial results from a model which employs a full transient numerical solution of the classical semiconductor equations to model charge collection in device pixels under stimulation from initially Gaussian photogenerated charge clouds, using commercial TCAD software. Realistic device geometries and doping are included. By mapping the pixel response to different initial interaction positions and charge cloud sizes, the charge splitting behaviour of the model sensor under various illuminations and operating conditions is investigated. Experimental validation of the model is presented from an e2v CCD30-11 device under varying substrate bias, illuminated using an Fe-55 source.
Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes.
Zhou, Du; Yuan, Xi; Gao, Haoxiang; Wang, Ailing; Liu, Jun; El Fakir, Omer; Politis, Denis J; Wang, Liliang; Lin, Jianguo
2016-12-13
The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.
Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
Zhou, Du; Yuan, Xi; Gao, Haoxiang; Wang, Ailing; Liu, Jun; El Fakir, Omer; Politis, Denis J.; Wang, Liliang; Lin, Jianguo
2016-01-01
The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions. PMID:28060298
A class of renormalised meshless Laplacians for boundary value problems
NASA Astrophysics Data System (ADS)
Basic, Josip; Degiuli, Nastia; Ban, Dario
2018-02-01
A meshless approach to approximating spatial derivatives on scattered point arrangements is presented in this paper. Three various derivations of approximate discrete Laplace operator formulations are produced using the Taylor series expansion and renormalised least-squares correction of the first spatial derivatives. Numerical analyses are performed for the introduced Laplacian formulations, and their convergence rate and computational efficiency are examined. The tests are conducted on regular and highly irregular scattered point arrangements. The results are compared to those obtained by the smoothed particle hydrodynamics method and the finite differences method on a regular grid. Finally, the strong form of various Poisson and diffusion equations with Dirichlet or Robin boundary conditions are solved in two and three dimensions by making use of the introduced operators in order to examine their stability and accuracy for boundary value problems. The introduced Laplacian operators perform well for highly irregular point distribution and offer adequate accuracy for mesh and mesh-free numerical methods that require frequent movement of the grid or point cloud.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roehm, Dominic; Pavel, Robert S.; Barros, Kipton
We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less
Distributed database kriging for adaptive sampling (D²KAS)
Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; ...
2015-03-18
We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zardecki, A.
The effect of multiple scattering on the validity of the Beer-Lambert law is discussed for a wide range of particle-size parameters and optical depths. To predict the amount of received radiant power, appropriate correction terms are introduced. For particles larger than or comparable to the wavelength of radiation, the small-angle approximation is adequate; whereas for small densely packed particles, the diffusion theory is advantageously employed. These two approaches are used in the context of the problem of laser-beam propagation in a dense aerosol medium. In addition, preliminary results obtained by using a two-dimensional finite-element discrete-ordinates transport code are described. Multiple-scatteringmore » effects for laser propagation in fog, cloud, rain, and aerosol cloud are modeled.« less
Shapes of star-gas waves in spiral galaxies
NASA Technical Reports Server (NTRS)
Lubow, Stephen H.
1988-01-01
Density-wave profile shapes are influenced by several effects. By solving viscous fluid equations, the nonlinear effects of the gas and its gravitational interaction with the stars can be analyzed. The stars are treated through a linear theory developed by Lin and coworkers. Short wavelength gravitational forces are important in determining the gas density profile shape. With the inclusion of disk finite thickness effects, the gas gravitational field remains important, but is significantly reduced at short wavelengths. Softening of the gas equation of state results in an enhanced response and a smoothing of the gas density profile. A Newtonian stress relation is marginally acceptable for HI gas clouds, but not acceptable for giant molecular clouds.
NASA Astrophysics Data System (ADS)
Biagi, C. J.; Cummins, K. L.
2015-12-01
The growing possibility of inexpensive airborne observations of electric fields using one or more small UAVs increases the importance of understanding what can be determined about cloud electrification and associated electric fields outside cloud boundaries. If important information can be inferred from carefully selected flight paths outside of a cloud, then the aircraft and its instrumentation will be much cheaper to develop and much safer to operate. These facts have led us to revisit this long-standing topic using quasi-static, finite-element modeling inside and outside arbitrarily shaped clouds with a variety of internal charge distributions. In particular, we examine the effect of screening layers on electric fields outside of electrified clouds by comparing modeling results for charged clouds having electrical conductivities that are both equal to and lower than the surrounding clear air. The comparisons indicate that the spatial structure of the electric field is approximately the same regardless of the difference in the conductivities between the cloud and clear air and the formation of a screening layer, even for altitude-dependent electrical conductivities. This result is consistent with the numerical modeling results reported by Driscoll et al [1992]. The similarity of the spatial structure of the electric field outside of clouds with and without a screening layer suggests that "bulk" properties related to cloud electrification might be determined using measurements of the electric field at multiple locations in space outside the cloud, particularly at altitude. Finally, for this somewhat simplified model, the reduction in electric field magnitude outside the cloud due to the presence of a screening layer exhibits a simple dependence on the difference in conductivity between the cloud and clear air. These results are particularly relevant for studying clouds that are not producing lightning, such as developing thunderstorms and decaying anvils associated with mature storm systems.Driscoll K.T., R.J. Blakeslee, M.E. Baginski, 1992, A modeling study of the time-averaged electric currents in the vicinity of isolated thunderstorms, J. Geophys. Res., 97, D11, pp 11535-11551.
A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2005-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.
Extinction efficiencies from DDA calculations solved for finite circular cylinders and disks
NASA Technical Reports Server (NTRS)
Withrow, J. R.; Cox, S. K.
1993-01-01
One of the most commonly noted uncertainties with respect to the modeling of cirrus clouds and their effect upon the planetary radiation balance is the disputed validity of the use of Mie scattering results as an approximation to the scattering results of the hexagonal plates and columns found in cirrus clouds. This approximation has historically been a kind of default, a result of the lack of an appropriate analytical solution of Maxwell's equations to particles other than infinite cylinders and spheroids. Recently, however, the use of such approximate techniques as the Discrete Dipole Approximation has made scattering solutions on such particles a computationally intensive but feasible possibility. In this study, the Discrete Dipole Approximation (DDA) developed by Flatau (1992) is used to find such solutions for homogeneous, circular cylinders and disks. This can serve to not only assess the validity of the current radiative transfer schemes which are available for the study of cirrus but also to extend the current approximation of equivalent spheres to an approximation of second order, homogeneous finite circular cylinders and disks. The results will be presented in the form of a single variable, the extinction efficiency.
Application of 3D Laser Scanning Technology in Complex Rock Foundation Design
NASA Astrophysics Data System (ADS)
Junjie, Ma; Dan, Lu; Zhilong, Liu
2017-12-01
Taking the complex landform of Tanxi Mountain Landscape Bridge as an example, the application of 3D laser scanning technology in the mapping of complex rock foundations is studied in this paper. A set of 3D laser scanning technologies are formed and several key engineering problems are solved. The first is 3D laser scanning technology of complex landforms. 3D laser scanning technology is used to obtain a complete 3D point cloud data model of the complex landform. The detailed and accurate results of the surveying and mapping decrease the measuring time and supplementary measuring times. The second is 3D collaborative modeling of the complex landform. A 3D model of the complex landform is established based on the 3D point cloud data model. The super-structural foundation model is introduced for 3D collaborative design. The optimal design plan is selected and the construction progress is accelerated. And the last is finite-element analysis technology of the complex landform foundation. A 3D model of the complex landform is introduced into ANSYS for building a finite element model to calculate anti-slide stability of the rock, and provides a basis for the landform foundation design and construction.
Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.
Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi
2016-12-16
Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.
Inference of Ice Cloud Properties from High-spectral Resolution Infrared Observations. Appendix 4
NASA Technical Reports Server (NTRS)
Huang, Hung-Lung; Yang, Ping; Wei, Heli; Baum, Bryan A.; Hu, Yongxiang; Antonelli, Paolo; Ackerman, Steven A.
2005-01-01
The theoretical basis is explored for inferring the microphysical properties of ice crystal from high-spectral resolution infrared observations. A radiative transfer model is employed to simulate spectral radiances to address relevant issues. The extinction and absorption efficiencies of individual ice crystals, assumed as hexagonal columns for large particles and droxtals for small particles, are computed from a combination of the finite- difference time-domain (FDTD) technique and a composite method. The corresponding phase functions are computed from a combination of FDTD and an improved geometric optics method (IGOM). Bulk scattering properties are derived by averaging the single- scattering properties of individual particles for 30 particle size distributions developed from in situ measurements and for additional four analytical Gamma size distributions for small particles. The non-sphericity of ice crystals is shown to have a significant impact on the radiative signatures in the infrared (IR) spectrum; the spherical particle approximation for inferring ice cloud properties may result in an overest&ation of the optical thickness and an inaccurate retrieval of effective particle size. Furthermore, we show that the error associated with the use of the Henyey-Greenstein phase function can be as larger as 1 K in terms of brightness temperature for larger particle effective size at some strong scattering wavenumbers. For small particles, the difference between the two phase functions is much less, with brightness temperatures generally differing by less than 0.4 K. The simulations undertaken in this study show that the slope of the IR brightness temperature spectrum between 790-960/cm is sensitive to the effective particle size. Furthermore, a strong sensitivity of IR brightness temperature to cloud optical thickness is noted within the l050-1250/cm region. Based on this spectral feature, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution infrared data under ice cloudy con&tion. The error analysis shows that the uncertainty of the retrieved optical thickness and effective particle size has a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud'temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding e m r in the uncertainty of optical thickness is within 5-2096, depending on the value of cloud optical thickness. The applicability of the technique is demonstrated using the aircraft-based High- resolution Interferometer Sounder (HIS) data from the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS) in 1996 and the First ISCCP Regional Experiment - Arctic Clouds Experiment (FIRE-ACE) in 1998.
Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation
Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi
2016-01-01
Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261
NASA Astrophysics Data System (ADS)
Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua
Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.
USDA-ARS?s Scientific Manuscript database
Thick cloud contaminations in Landsat images limit their regular usage for land applications. A few methods have been developed to remove thick clouds using additional cloud-free images. Unfortunately, the cloud-free composition image produced by existing methods commonly lacks from the desired spat...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goswami, Rituparno; Joshi, Pankaj S.; Vaz, Cenalo
We construct a class of spherically symmetric collapse models in which a naked singularity may develop as the end state of collapse. The matter distribution considered has negative radial and tangential pressures, but the weak energy condition is obeyed throughout. The singularity forms at the center of the collapsing cloud and continues to be visible for a finite time. The duration of visibility depends on the nature of energy distribution. Hence the causal structure of the resulting singularity depends on the nature of the mass function chosen for the cloud. We present a general model in which the naked singularitymore » formed is timelike, neither pointlike nor null. Our work represents a step toward clarifying the necessary conditions for the validity of the Cosmic Censorship Conjecture.« less
A New Cloud and Aerosol Layer Detection Method Based on Micropulse Lidar Measurements
NASA Astrophysics Data System (ADS)
Wang, Q.; Zhao, C.; Wang, Y.; Li, Z.; Wang, Z.; Liu, D.
2014-12-01
A new algorithm is developed to detect aerosols and clouds based on micropulse lidar (MPL) measurements. In this method, a semi-discretization processing (SDP) technique is first used to inhibit the impact of increasing noise with distance, then a value distribution equalization (VDE) method is introduced to reduce the magnitude of signal variations with distance. Combined with empirical threshold values, clouds and aerosols are detected and separated. This method can detect clouds and aerosols with high accuracy, although classification of aerosols and clouds is sensitive to the thresholds selected. Compared with the existing Atmospheric Radiation Measurement (ARM) program lidar-based cloud product, the new method detects more high clouds. The algorithm was applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu site. At SGP, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring, and shows bi-modal vertical distributions with maximum frequency at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. By contrast, the cloud frequency at Taihu shows no clear seasonal variation and the maximum frequency is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at SGP.
Theory of peak coalescence in Fourier transform ion cyclotron resonance mass spectrometry.
Boldin, Ivan A; Nikolaev, Eugene N
2009-10-01
Peak coalescence, i.e. the merging of two close peaks in a Fourier transform ion cyclotron resonance (FTICR) mass spectrum at a high number of ions, plays an important role in various FTICR experiments. In order to describe the coalescence phenomenon we would like to propose a new theory of motion for ion clouds with close mass-to-charge ratios, driven by a uniform magnetic field and Coulomb interactions between the clouds. We describe the motion of the ion clouds in terms of their averaged drift motion in crossed magnetic and electric fields. The ion clouds are considered to be of constant size and their motion is studied in two dimensions. The theory deals with the first-order approximation of the equations of motion in relation to dm/m, where dm is the mass difference and m is the mass of a single ion. The analysis was done for an arbitrary inter-cloud interaction potential, which makes it possible to analyze finite-size ion clouds of any shape. The final analytical expression for the condition of the onset of coalescence is found for the case of uniformly charged spheres. An algorithm for finding this condition for an arbitrary interaction potential is proposed. The critical number of ions for the peak coalescence to take place is shown to depend quadratically on the magnetic field strength and to be proportional to the cyclotron radius and inversely proportional to the ion masses. Copyright (c) 2009 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.
2005-01-01
This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.
Finite elements and finite differences for transonic flow calculations
NASA Technical Reports Server (NTRS)
Hafez, M. M.; Murman, E. M.; Wellford, L. C.
1978-01-01
The paper reviews the chief finite difference and finite element techniques used for numerical solution of nonlinear mixed elliptic-hyperbolic equations governing transonic flow. The forms of the governing equations for unsteady two-dimensional transonic flow considered are the Euler equation, the full potential equation in both conservative and nonconservative form, the transonic small-disturbance equation in both conservative and nonconservative form, and the hodograph equations for the small-disturbance case and the full-potential case. Finite difference methods considered include time-dependent methods, relaxation methods, semidirect methods, and hybrid methods. Finite element methods include finite element Lax-Wendroff schemes, implicit Galerkin method, mixed variational principles, dual iterative procedures, optimal control methods and least squares.
NASA Technical Reports Server (NTRS)
Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.
2001-01-01
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds
NASA Technical Reports Server (NTRS)
Kawamoto, K.; Minnis, P.; Smith, W. L., Jr.
2001-01-01
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.
Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications
2016-10-17
finite volume schemes, discontinuous Galerkin finite element method, and related methods, for solving computational fluid dynamics (CFD) problems and...approximation for finite element methods. (3) The development of methods of simulation and analysis for the study of large scale stochastic systems of...laws, finite element method, Bernstein-Bezier finite elements , weakly interacting particle systems, accelerated Monte Carlo, stochastic networks 16
An efficient cloud detection method for high resolution remote sensing panchromatic imagery
NASA Astrophysics Data System (ADS)
Li, Chaowei; Lin, Zaiping; Deng, Xinpu
2018-04-01
In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.
Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...
2015-02-16
Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less
NASA Astrophysics Data System (ADS)
Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.
2011-04-01
The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.
a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery
NASA Astrophysics Data System (ADS)
Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.
2018-04-01
Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.
NASA Astrophysics Data System (ADS)
Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.
2016-05-01
Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.
Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jian-Ping; Nguyen, Louis; Khaiyer, Mandana M.
2005-01-01
Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.
Detection and retrieval of multi-layered cloud properties using satellite data
NASA Astrophysics Data System (ADS)
Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.
2005-10-01
Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.
NASA Astrophysics Data System (ADS)
Ellis, T. D.
2015-12-01
The NASA CloudSat mission has been revealing the inner secrets of clouds since 2006 using its one-of-a-kind spaceborne cloud radar. During its mission, the CloudSat Education Network, consisting of schools in Asia, Europe, and North America, have been collecting data on Clouds when CloudSat passes overhead. The education team has spent many hours researching and presenting different methods for making clouds for demonstrations in formal and informal settings. In this presentation, we will present several variations on methods for doing the cloud in a bottle demonstration, including strengths and weaknesses for each, and a brief overview of the science involved in the various demonstrations.
NASA Astrophysics Data System (ADS)
Mendonça, João M.; Malik, Matej; Demory, Brice-Olivier; Heng, Kevin
2018-04-01
Recently acquired Hubble and Spitzer phase curves of the short-period hot Jupiter WASP-43b make it an ideal target for confronting theory with data. On the observational front, we re-analyze the 3.6 and 4.5 μm Spitzer phase curves and demonstrate that our improved analysis better removes residual red noise due to intra-pixel sensitivity, which leads to greater fluxes emanating from the nightside of WASP-43b, thus reducing the tension between theory and data. On the theoretical front, we construct cloud-free and cloudy atmospheres of WASP-43b using our Global Circulation Model (GCM), THOR, which solves the non-hydrostatic Euler equations (compared to GCMs that typically solve the hydrostatic primitive equations). The cloud-free atmosphere produces a reasonable fit to the dayside emission spectrum. The multi-phase emission spectra constrain the cloud deck to be confined to the nightside and have a finite cloud-top pressure. The multi-wavelength phase curves are naturally consistent with our cloudy atmospheres, except for the 4.5 μm phase curve, which requires the presence of enhanced carbon dioxide in the atmosphere of WASP-43b. Multi-phase emission spectra at higher spectral resolution, as may be obtained using the James Webb Space Telescope, and a reflected-light phase curve at visible wavelengths would further constrain the properties of clouds in WASP-43b.
Simulating glories and cloudbows in color.
Gedzelman, Stanley D
2003-01-20
Glories and cloudbows are simulated in color by use of the Mie scattering theory of light upwelling from small-droplet clouds of finite optical thickness embedded in a Rayleigh scattering atmosphere. Glories are generally more distinct for clouds of droplets of as much as approximately 10 microm in radius. As droplet radius increases, the glory shrinks and becomes less prominent, whereas the cloudbow becomes more distinct and eventually colorful. Cloudbows typically consist of a broad, almost white band with a slightly orange outer edge and a dark inner band. Multiple light and dark bands that are related to supernumerary rainbows first appear inside the cloudbow as droplet radius increases above approximately 10 microm and gradually become more prominent when all droplets are the same size. Bright glories with multiple rings and high color purity are simulated when all droplets are the same size and every light beam is scattered just once. Color purity decreases and outer rings fade as the range of droplet sizes widens and when skylight, reflected light from the ground or background, and multiply scattered light from the cloud are included. Consequently, the brightest and most colorful glories and bows are seen when the observer is near a cloud or a rain swath with optical thickness of approximately 0.25 that consists of uniform-sized drops and when a dark or shaded background lies a short distance behind the cloud.
Precipitating Condensation Clouds in Substellar Atmospheres
NASA Technical Reports Server (NTRS)
Ackerman, Andrew S.; Marley, Mark S.; Gore, Warren J. (Technical Monitor)
2000-01-01
We present a method to calculate vertical profiles of particle size distributions in condensation clouds of giant planets and brown dwarfs. The method assumes a balance between turbulent diffusion and precipitation in horizontally uniform cloud decks. Calculations for the Jovian ammonia cloud are compared with previous methods. An adjustable parameter describing the efficiency of precipitation allows the new model to span the range of predictions from previous models. Calculations for the Jovian ammonia cloud are found to be consistent with observational constraints. Example calculations are provided for water, silicate, and iron clouds on brown dwarfs and on a cool extrasolar giant planet.
Zhao, Yue; Zhu, Dianwen; Baikejiang, Reheman; Li, Changqing
2015-11-10
This work introduces a fast, low-cost, robust method based on fringe pattern and phase shifting to obtain three-dimensional (3D) mouse surface geometry for fluorescence molecular tomography (FMT) imaging. We used two pico projector/webcam pairs to project and capture fringe patterns from different views. We first calibrated the pico projectors and the webcams to obtain their system parameters. Each pico projector/webcam pair had its own coordinate system. We used a cylindrical calibration bar to calculate the transformation matrix between these two coordinate systems. After that, the pico projectors projected nine fringe patterns with a phase-shifting step of 2π/9 onto the surface of a mouse-shaped phantom. The deformed fringe patterns were captured by the corresponding webcam respectively, and then were used to construct two phase maps, which were further converted to two 3D surfaces composed of scattered points. The two 3D point clouds were further merged into one with the transformation matrix. The surface extraction process took less than 30 seconds. Finally, we applied the Digiwarp method to warp a standard Digimouse into the measured surface. The proposed method can reconstruct the surface of a mouse-sized object with an accuracy of 0.5 mm, which we believe is sufficient to obtain a finite element mesh for FMT imaging. We performed an FMT experiment using a mouse-shaped phantom with one embedded fluorescence capillary target. With the warped finite element mesh, we successfully reconstructed the target, which validated our surface extraction approach.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Badosa, Jordi; Calbo, J.; McKenzie, R. L.
2014-07-01
In the present study, we assess the cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover estimations and sunny conditions (from sky imaging products) as well as of solar zenith angle (SZA). These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (< 60%) and large SZA (> 60º). Similarly, clouds enhance TR more than UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Twomore » methods to estimate UVI are developed: 1) from sky imaging cloud cover and sunny conditions, and 2) from TR measurements. Both methods may be used in practical operational applications, although Method 2 shows overall the best performance, since TR allows accounting for cloud optical properties. The mean absolute differences of Method 2 estimations with respect to measured values are 0.17 UVI units (for 1-minute data) and 0.79 Standard Erythemal Dose (SED) units (for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units and 1.6 SED.« less
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2007-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2006-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).
NASA Astrophysics Data System (ADS)
Boss, Alan P.
2002-04-01
Recent observations of star-forming regions suggest that binary and multiple young stars are the rule rather than the exception and implicate fragmentation as the likely mechanism for their formation. Most numerical hydrodynamic calculations of fragmentation have neglected the possibly deleterious effects of magnetic fields, despite ample evidence for the importance of magnetic support of precollapse clouds. We present here the first numerical hydrodynamic survey of the collapse and fragmentation of initially magnetically supported clouds that takes into account several magnetic field effects in an approximate manner. The models are calculated with a three-dimensional, finite differences code that solves the equations of hydrodynamics, gravitation, and radiative transfer in the Eddington and diffusion approximations. Magnetic field effects are included through two simple approximations: magnetic pressure is added to the gas pressure, and magnetic tension is approximated by gravity dilution once collapse is well underway. Ambipolar diffusion of the magnetic field leading to cloud collapse is treated approximately as well. Models are calculated for a variety of initial cloud density profiles, shapes, and rotation rates. We find that in spite of the inclusion of magnetic field effects, dense cloud cores are capable of fragmenting into binary and multiple protostar systems. Initially prolate clouds tend to fragment into binary protostars, while initially oblate clouds tend to fragment into multiple protostar systems containing a small number (of the order of 4) of fragments. The latter are likely to be subject to rapid orbital evolution, with close encounters possibly leading to the ejection of fragments. Contrary to expectation, magnetic tension effects appear to enhance fragmentation, allowing lower mass fragments to form than would otherwise be possible, because magnetic tension helps to prevent a central density singularity from forming and producing a dominant single object. Magnetically supported dense cloud cores thus seem to be capable of collapsing and fragmenting into sufficient numbers of binary and multiple protostar systems to be compatible with observations of the relative rarity of single protostars.
A new cloud and aerosol layer detection method based on micropulse lidar measurements
NASA Astrophysics Data System (ADS)
Zhao, Chuanfeng; Wang, Yuzhao; Wang, Qianqian; Li, Zhanqing; Wang, Zhien; Liu, Dong
2014-06-01
This paper introduces a new algorithm to detect aerosols and clouds based on micropulse lidar measurements. A semidiscretization processing technique is first used to inhibit the impact of increasing noise with distance. The value distribution equalization method which reduces the magnitude of signal variations with distance is then introduced. Combined with empirical threshold values, we determine if the signal waves indicate clouds or aerosols. This method can separate clouds and aerosols with high accuracy, although differentiation between aerosols and clouds are subject to more uncertainties depending on the thresholds selected. Compared with the existing Atmospheric Radiation Measurement program lidar-based cloud product, the new method appears more reliable and detects more clouds with high bases. The algorithm is applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu sites. At the SGP site, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring and shows bimodal vertical distributions with maximum occurrences at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. The dominant clouds are stratiform in winter and convective in summer. By contrast, the cloud frequency at the Taihu site shows no clear seasonal variation and the maximum occurrence is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at the SGP site. A seasonal analysis of cloud base occurrence frequency suggests that stratiform clouds dominate at the Taihu site.
NASA Astrophysics Data System (ADS)
Letu, Husi; Ishimoto, Hiroshi; Riedi, Jerome; Nakajima, Takashi Y.; -Labonnote, Laurent C.; Baran, Anthony J.; Nagao, Takashi M.; Sekiguchi, Miho
2016-09-01
In this study, various ice particle habits are investigated in conjunction with inferring the optical properties of ice clouds for use in the Global Change Observation Mission-Climate (GCOM-C) satellite programme. We develop a database of the single-scattering properties of five ice habit models: plates, columns, droxtals, bullet rosettes, and Voronoi. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor on board the GCOM-C satellite, which is scheduled to be launched in 2017 by the Japan Aerospace Exploration Agency. A combination of the finite-difference time-domain method, the geometric optics integral equation technique, and the geometric optics method is applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible to the infrared spectral regions. This covers the SGLI channels for the size parameter, which is defined as a single-particle radius of an equivalent volume sphere, ranging between 6 and 9000 µm. The database includes the extinction efficiency, absorption efficiency, average geometrical cross section, single-scattering albedo, asymmetry factor, size parameter of a volume-equivalent sphere, maximum distance from the centre of mass, particle volume, and six nonzero elements of the scattering phase matrix. The characteristics of calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, size-integrated bulk scattering properties for the five ice particle habit models are calculated from the single-scattering database and microphysical data. Using the five ice particle habit models, the optical thickness and spherical albedo of ice clouds are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements, recorded on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The optimal ice particle habit for retrieving the SGLI ice cloud properties is investigated by adopting the spherical albedo difference (SAD) method. It is found that the SAD is distributed stably due to the scattering angle increases for bullet rosettes with an effective diameter (Deff) of 10 µm and Voronoi particles with Deff values of 10, 60, and 100 µm. It is confirmed that the SAD of small bullet-rosette particles and all sizes of Voronoi particles has a low angular dependence, indicating that a combination of the bullet-rosette and Voronoi models is sufficient for retrieval of the ice cloud's spherical albedo and optical thickness as effective habit models for the SGLI sensor. Finally, SAD analysis based on the Voronoi habit model with moderate particle size (Deff = 60 µm) is compared with the conventional general habit mixture model, inhomogeneous hexagonal monocrystal model, five-plate aggregate model, and ensemble ice particle model. The Voronoi habit model is found to have an effect similar to that found in some conventional models for the retrieval of ice cloud properties from space-borne radiometric observations.
A shape-based segmentation method for mobile laser scanning point clouds
NASA Astrophysics Data System (ADS)
Yang, Bisheng; Dong, Zhen
2013-07-01
Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.
NASA Astrophysics Data System (ADS)
Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.
2014-08-01
The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.
NASA Astrophysics Data System (ADS)
Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.
2014-04-01
The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds on climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 193 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e. when the whole CVS is correctly estimated) for the methods ranges between 26-64%; the methods show additional approximate agreement (i.e. when at least one cloud layer is correctly assessed) from 15-41%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, like those from the outputs of reanalysis methods or from the WMO's Global Telecommunication System. The perfect agreement, even when using low resolution profiles, can be improved up to 67% (plus 25% of approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.
Cloud-top height retrieval from polarizing remote sensor POLDER
NASA Astrophysics Data System (ADS)
He, Xianqiang; Pan, Delu; Yan, Bai; Mao, Zhihua
2006-10-01
A new cloud-top height retrieval method is proposed by using polarizing remote sensing. In cloudy conditions, it shows that, in purple and blue bands, linear polarizing radiance at the top-of-atmosphere (TOA) is mainly contributed by Rayleigh scattering of the atmosphere's molecules above cloud, and the contribution by cloud reflection and aerosol scattering can be neglected. With such characteristics, the basis principle and method of cloud-top height retrieval using polarizing remote sensing are presented in detail, and tested by the polarizing remote sensing data of POLDER. The satellite-derived cloud-top height product can not only show the distribution of global cloud-top height, but also obtain the cloud-top height distribution of moderate-scale meteorological phenomena like hurricanes and typhoons. This new method is promising to become the operational algorithm for cloud-top height retrieval for POLDER and the future polarizing remote sensing satellites.
NASA Astrophysics Data System (ADS)
Wong, Michael H.; Atreya, Sushil K.; Kuhn, William R.; Romani, Paul N.; Mihalka, Kristen M.
2015-01-01
Models of cloud condensation under thermodynamic equilibrium in planetary atmospheres are useful for several reasons. These equilibrium cloud condensation models (ECCMs) calculate the wet adiabatic lapse rate, determine saturation-limited mixing ratios of condensing species, calculate the stabilizing effect of latent heat release and molecular weight stratification, and locate cloud base levels. Many ECCMs trace their heritage to Lewis (Lewis, J.S. [1969]. Icarus 10, 365-378) and Weidenschilling and Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465-476). Calculation of atmospheric structure and gas mixing ratios are correct in these models. We resolve errors affecting the cloud density calculation in these models by first calculating a cloud density rate: the change in cloud density with updraft length scale. The updraft length scale parameterizes the strength of the cloud-forming updraft, and converts the cloud density rate from the ECCM into cloud density. The method is validated by comparison with terrestrial cloud data. Our parameterized updraft method gives a first-order prediction of cloud densities in a “fresh” cloud, where condensation is the dominant microphysical process. Older evolved clouds may be better approximated by another 1-D method, the diffusive-precipitative Ackerman and Marley (Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872-884) model, which represents a steady-state equilibrium between precipitation and condensation of vapor delivered by turbulent diffusion. We re-evaluate observed cloud densities in the Galileo Probe entry site (Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891-22910), and show that the upper and lower observed clouds at ∼0.5 and ∼3 bars are consistent with weak (cirrus-like) updrafts under conditions of saturated ammonia and water vapor, respectively. The densest observed cloud, near 1.3 bar, requires unexpectedly strong updraft conditions, or higher cloud density rates. The cloud density rate in this layer may be augmented by a composition with non-NH4SH components (possibly including adsorbed NH3).
Fingerprinting Reverse Proxies Using Timing Analysis of TCP Flows
2013-09-01
bayes classifier,” in Cloud Computing Security , ser. CCSW ’09. New York City, NY: ACM, 2009, pp. 31–42. [30] J. Zhang, R. Perdisci, W. Lee, U. Sarfraz...FSM Finite State Machine HTML Hypertext Markup Language HTTP Hypertext Transfer Protocol HTTPS Hypertext Transfer Protocol Secure ICMP Internet Control...This hidden traffic concept supports network access control, security protection through obfuscation, and performance boosts at the Internet facing
The Role of CO2 Clouds on the Stability of the Early Mars Atmosphere Against Collapse
NASA Astrophysics Data System (ADS)
Kahre, Melinda A.; Haberle, Robert; Steakley, Kathryn; Murphy, Jim; Kling, Alexandre
2017-10-01
The early Mars atmosphere was likely significantly more massive than it is today, given the growing body of evidence that liquid water flowed on the surface early in the planet’s history. Although the CO2 inventory was likely larger in the past, there is much we still do not understand about the state of that CO2. As surface pressure increases, the temperature at which CO2 condenses also increases, making it more likely that CO2 ice would form and persist on the surface when the atmospheric mass increases. An atmosphere that is stable against collapse must contain enough energy, distributed globally, to prohibit the formation of permanents CO2 ice reservoirs that lead to collapse. The presence of the “faint young sun” compounds this issue. Previous global climate model (GCM) investigations show that atmospheres within specific ranges of obliquities and atmospheric masses are stable against collapse. We use the NASA Ames Mars GCM to expand on these works by focusing specifically on the role of CO2 clouds in atmospheric stability. Two end member simulations are executed, one that includes CO2 cloud formation and one that does not. The simulation that explicitly includes CO2 clouds is stable, while the simulation without CO2 clouds collapses into permanent surface CO2 reservoirs. In both cases, significant atmospheric condensation is occurring in the atmosphere throughout the year. In the case without CO2 clouds, all atmospheric condensation (even if it occurs at altitude) leads directly to the accumulation of surface ice, whereas in the case with CO2 clouds, there is a finite settling timescale for the cloud particles. Depending on this timescale and the local conditions, the cloud particles could stay aloft or sublimate as they fall toward the surface. Thus, the striking difference between these two cases illustrates the important role of CO2 clouds. We plan to conduct and present further simulations to better understand how atmospheric stability depends on the details of CO2 cloud microphysical processes and assumptions.
From LIDAR Scanning to 3d FEM Analysis for Complex Surface and Underground Excavations
NASA Astrophysics Data System (ADS)
Chun, K.; Kemeny, J.
2017-12-01
Light detection and ranging (LIDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease to use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of three-dimensional numerical model that can be used in FEM analysis. To date, however, straightforward techniques in reconstructing numerical model from the scanned data of underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating from LIDAR scanning to finite element numerical analysis, specifically converting LIDAR 3D point clouds of object containing complex surface geometry into finite element model. This methodology has been applied to the Kartchner Caverns in Arizona for the stability analysis. Numerical simulations were performed using the finite element code ABAQUS. The results indicate that the highlights of our technologies obtained from LIDAR is effective and provide reference for other similar engineering project in practice.
The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)
NASA Astrophysics Data System (ADS)
Kuçak, R. A.; Özdemir, E.; Erol, S.
2017-05-01
Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.
NASA Astrophysics Data System (ADS)
Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.
2013-06-01
The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44-88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.
Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics
NASA Astrophysics Data System (ADS)
Kohira, K.; Masuda, H.
2017-09-01
A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.
NASA Astrophysics Data System (ADS)
Norris, P. M.; da Silva, A. M., Jr.
2016-12-01
Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.
DOUAR: A new three-dimensional creeping flow numerical model for the solution of geological problems
NASA Astrophysics Data System (ADS)
Braun, Jean; Thieulot, Cédric; Fullsack, Philippe; DeKool, Marthijn; Beaumont, Christopher; Huismans, Ritske
2008-12-01
We present a new finite element code for the solution of the Stokes and energy (or heat transport) equations that has been purposely designed to address crustal-scale to mantle-scale flow problems in three dimensions. Although it is based on an Eulerian description of deformation and flow, the code, which we named DOUAR ('Earth' in Breton language), has the ability to track interfaces and, in particular, the free surface, by using a dual representation based on a set of particles placed on the interface and the computation of a level set function on the nodes of the finite element grid, thus ensuring accuracy and efficiency. The code also makes use of a new method to compute the dynamic Delaunay triangulation connecting the particles based on non-Euclidian, curvilinear measure of distance, ensuring that the density of particles remains uniform and/or dynamically adapted to the curvature of the interface. The finite element discretization is based on a non-uniform, yet regular octree division of space within a unit cube that allows efficient adaptation of the finite element discretization, i.e. in regions of strong velocity gradient or high interface curvature. The finite elements are cubes (the leaves of the octree) in which a q1- p0 interpolation scheme is used. Nodal incompatibilities across faces separating elements of differing size are dealt with by introducing linear constraints among nodal degrees of freedom. Discontinuities in material properties across the interfaces are accommodated by the use of a novel method (which we called divFEM) to integrate the finite element equations in which the elemental volume is divided by a local octree to an appropriate depth (resolution). A variety of rheologies have been implemented including linear, non-linear and thermally activated creep and brittle (or plastic) frictional deformation. A simple smoothing operator has been defined to avoid checkerboard oscillations in pressure that tend to develop when using a highly irregular octree discretization and the tri-linear (or q1- p0) finite element. A three-dimensional cloud of particles is used to track material properties that depend on the integrated history of deformation (the integrated strain, for example); its density is variable and dynamically adapted to the computed flow. The large system of algebraic equations that results from the finite element discretization and linearization of the basic partial differential equations is solved using a multi-frontal massively parallel direct solver that can efficiently factorize poorly conditioned systems resulting from the highly non-linear rheology and the presence of the free surface. The code is almost entirely parallelized. We present example results including the onset of a Rayleigh-Taylor instability, the indentation of a rigid-plastic material and the formation of a fold beneath a free eroding surface, that demonstrate the accuracy, efficiency and appropriateness of the new code to solve complex geodynamical problems in three dimensions.
Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...
2015-07-02
Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less
Towards a true aerosol-and-cloud retrieval scheme
NASA Astrophysics Data System (ADS)
Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don
2014-05-01
The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.
NASA Technical Reports Server (NTRS)
Hodges, D. B.
1976-01-01
An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.
The application of time series models to cloud field morphology analysis
NASA Technical Reports Server (NTRS)
Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.
1987-01-01
A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.
NASA Technical Reports Server (NTRS)
Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne
2012-01-01
Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.
From Faddeev-Kulish to LSZ. Towards a non-perturbative description of colliding electrons
NASA Astrophysics Data System (ADS)
Dybalski, Wojciech
2017-12-01
In a low energy approximation of the massless Yukawa theory (Nelson model) we derive a Faddeev-Kulish type formula for the scattering matrix of N electrons and reformulate it in LSZ terms. To this end, we perform a decomposition of the infrared finite Dollard modifier into clouds of real and virtual photons, whose infrared divergencies mutually cancel. We point out that in the original work of Faddeev and Kulish the clouds of real photons are omitted, and consequently their wave-operators are ill-defined on the Fock space of free electrons. To support our observations, we compare our final LSZ expression for N = 1 with a rigorous non-perturbative construction due to Pizzo. While our discussion contains some heuristic steps, they can be formulated as clear-cut mathematical conjectures.
Is isotropic turbulent diffusion symmetry restoring?
NASA Astrophysics Data System (ADS)
Effinger, H.; Grossmann, S.
1984-07-01
The broadening of a cloud of marked particle pairs in longitudinal and transverse directions relative to the initial separation in fully developed isotropic turbulent flow is evaluated on the basis of the unified theory of turbulent relative diffusion of Grossmann and Procaccia (1984). The closure assumption of the theory is refined; its validity is confirmed by comparing experimental data; approximate analytical expressions for the traces of variance and asymmetry in the inertial subrange are obtained; and intermittency is treated using a log-normal model. The difference between the longitudinal and transverse components of the variance tensor is shown to tend to a finite nonzero limit dependent on the radial distribution of the cloud. The need for further measurements and the implications for studies of particle waste in air or water are indicated.
NASA Astrophysics Data System (ADS)
Gaburro, Elena; Castro, Manuel J.; Dumbser, Michael
2018-06-01
In this work, we present a novel second-order accurate well-balanced arbitrary Lagrangian-Eulerian (ALE) finite volume scheme on moving nonconforming meshes for the Euler equations of compressible gas dynamics with gravity in cylindrical coordinates. The main feature of the proposed algorithm is the capability of preserving many of the physical properties of the system exactly also on the discrete level: besides being conservative for mass, momentum and total energy, also any known steady equilibrium between pressure gradient, centrifugal force, and gravity force can be exactly maintained up to machine precision. Perturbations around such equilibrium solutions are resolved with high accuracy and with minimal dissipation on moving contact discontinuities even for very long computational times. This is achieved by the novel combination of well-balanced path-conservative finite volume schemes, which are expressly designed to deal with source terms written via non-conservative products, with ALE schemes on moving grids, which exhibit only very little numerical dissipation on moving contact waves. In particular, we have formulated a new HLL-type and a novel Osher-type flux that are both able to guarantee the well balancing in a gas cloud rotating around a central object. Moreover, to maintain a high level of quality of the moving mesh, we have adopted a nonconforming treatment of the sliding interfaces that appear due to the differential rotation. A large set of numerical tests has been carried out in order to check the accuracy of the method close and far away from the equilibrium, both, in one- and two-space dimensions.
Norris, Peter M.; da Silva, Arlindo M.
2018-01-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848
NASA Technical Reports Server (NTRS)
Norris, Peter M.; da Silva, Arlindo M.
2016-01-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.
Norris, Peter M; da Silva, Arlindo M
2016-07-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.
a Fast Method for Measuring the Similarity Between 3d Model and 3d Point Cloud
NASA Astrophysics Data System (ADS)
Zhang, Zongliang; Li, Jonathan; Li, Xin; Lin, Yangbin; Zhang, Shanxin; Wang, Cheng
2016-06-01
This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.
Identifying clouds over the Pierre Auger Observatory using infrared satellite data
NASA Astrophysics Data System (ADS)
Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Mariş, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Mićanović, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Rodriguez Fernandez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F. G.; Schulz, J.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.
2013-12-01
We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ˜2.4 km by ˜5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.
Identifying clouds over the Pierre Auger Observatory using infrared satellite data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abreu, Pedro; et al.,
2013-12-01
We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.
NASA Astrophysics Data System (ADS)
Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho
2016-12-01
Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.
Cloud Property Retrieval Products for Graciosa Island, Azores
Dong, Xiquan
2014-05-05
The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.
NASA Astrophysics Data System (ADS)
Hsu, Kuo-Hsien
2012-11-01
Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.
NASA Astrophysics Data System (ADS)
Huang, Wei; Chen, Xiu; Wang, Yueyun
2018-03-01
Landsat data are widely used in various earth observations, but the clouds interfere with the applications of the images. This paper proposes a weighted variational gradient-based fusion method (WVGBF) for high-fidelity thin cloud removal of Landsat images, which is an improvement of the variational gradient-based fusion (VGBF) method. The VGBF method integrates the gradient information from the reference band into visible bands of cloudy image to enable spatial details and remove thin clouds. The VGBF method utilizes the same gradient constraints to the entire image, which causes the color distortion in cloudless areas. In our method, a weight coefficient is introduced into the gradient approximation term to ensure the fidelity of image. The distribution of weight coefficient is related to the cloud thickness map. The map is built on Independence Component Analysis (ICA) by using multi-temporal Landsat images. Quantitatively, we use R value to evaluate the fidelity in the cloudless regions and metric Q to evaluate the clarity in the cloud areas. The experimental results indicate that the proposed method has the better ability to remove thin cloud and achieve high fidelity.
Ground-based cloud classification by learning stable local binary patterns
NASA Astrophysics Data System (ADS)
Wang, Yu; Shi, Cunzhao; Wang, Chunheng; Xiao, Baihua
2018-07-01
Feature selection and extraction is the first step in implementing pattern classification. The same is true for ground-based cloud classification. Histogram features based on local binary patterns (LBPs) are widely used to classify texture images. However, the conventional uniform LBP approach cannot capture all the dominant patterns in cloud texture images, thereby resulting in low classification performance. In this study, a robust feature extraction method by learning stable LBPs is proposed based on the averaged ranks of the occurrence frequencies of all rotation invariant patterns defined in the LBPs of cloud images. The proposed method is validated with a ground-based cloud classification database comprising five cloud types. Experimental results demonstrate that the proposed method achieves significantly higher classification accuracy than the uniform LBP, local texture patterns (LTP), dominant LBP (DLBP), completed LBP (CLTP) and salient LBP (SaLBP) methods in this cloud image database and under different noise conditions. And the performance of the proposed method is comparable with that of the popular deep convolutional neural network (DCNN) method, but with less computation complexity. Furthermore, the proposed method also achieves superior performance on an independent test data set.
The Blended Finite Element Method for Multi-fluid Plasma Modeling
2016-07-01
Briefing Charts 3. DATES COVERED (From - To) 07 June 2016 - 01 July 2016 4. TITLE AND SUBTITLE The Blended Finite Element Method for Multi-fluid Plasma...BLENDED FINITE ELEMENT METHOD FOR MULTI-FLUID PLASMA MODELING Éder M. Sousa1, Uri Shumlak2 1ERC INC., IN-SPACE PROPULSION BRANCH (RQRS) AIR FORCE RESEARCH...MULTI-FLUID PLASMA MODEL 2 BLENDED FINITE ELEMENT METHOD Blended Finite Element Method Nodal Continuous Galerkin Modal Discontinuous Galerkin Model
NASA Astrophysics Data System (ADS)
Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.
2014-12-01
We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.
GOES Cloud Detection at the Global Hydrology and Climate Center
NASA Technical Reports Server (NTRS)
Laws, Kevin; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)
2002-01-01
The bi-spectral threshold (BTH) for cloud detection and height assignment is now operational at NASA's Global Hydrology and Climate Center (GHCC). This new approach is similar in principle to the bi-spectral spatial coherence (BSC) method with improvements made to produce a more robust cloud-filtering algorithm for nighttime cloud detection and subsequent 24-hour operational cloud top pressure assignment. The method capitalizes on cloud and surface emissivity differences from the GOES 3.9 and 10.7-micrometer channels to distinguish cloudy from clear pixels. Separate threshold values are determined for day and nighttime detection, and applied to a 20-day minimum composite difference image to better filter background effects and enhance differences in cloud properties. A cloud top pressure is assigned to each cloudy pixel by referencing the 10.7-micrometer channel temperature to a thermodynamic profile from a locally -run regional forecast model. This paper and supplemental poster will present an objective validation of nighttime cloud detection by the BTH approach in comparison with previous methods. The cloud top pressure will be evaluated by comparing to the NESDIS operational CO2 slicing approach.
Development of a Global Multilayered Cloud Retrieval System
NASA Technical Reports Server (NTRS)
Huang, J.; Minnis, P.; Lin, B.; Yi, Y.; Ayers, J. K.; Khaiyer, M. M.; Arduini, R.; Fan, T.-F
2004-01-01
A more rigorous multilayered cloud retrieval system has been developed to improve the determination of high cloud properties in multilayered clouds. The MCRS attempts a more realistic interpretation of the radiance field than earlier methods because it explicitly resolves the radiative transfer that would produce the observed radiances. A two-layer cloud model was used to simulate multilayered cloud radiative characteristics. Despite the use of a simplified two-layer cloud reflectance parameterization, the MCRS clearly produced a more accurate retrieval of ice water path than simple differencing techniques used in the past. More satellite data and ground observation have to be used to test the MCRS. The MCRS methods are quite appropriate for interpreting the radiances when the high cloud has a relatively large optical depth (tau(sub I) greater than 2). For thinner ice clouds, a more accurate retrieval might be possible using infrared methods. Selection of an ice cloud retrieval and a variety of other issues must be explored before a complete global application of this technique can be implemented. Nevertheless, the initial results look promising.
The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach
NASA Astrophysics Data System (ADS)
McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.
2018-06-01
The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.
1980-12-01
size data has been obtained with diffusion batteries, electrostatic precipitators , and cascade im- pactors. There is a strong (5 to 1) seasonal variation...dimensional Eddington approximation to derive microwave radiances emerging from finite clouds of precipitation , it was noted that the Eddington...condensation nuclei. They can then accrete water and grow by condensation, and fall as rain, collecting water droplets after they have grown to precipitation
Aerosol Microphysical Effects on Cloud Fraction over the Nighttime Arctic Ocean
NASA Astrophysics Data System (ADS)
Zamora, L. M.; Kahn, R. A.; Stohl, A.; Eckhardt, S.
2017-12-01
Cloud fraction is a key component affecting the surface energy balance in the Arctic. Aerosol microphysical processes can affect cloud fraction, for example through cloud lifetime effects. However, the importance of aerosol impacts on cloud fraction is not well constrained on a regional scale at high latitudes. Here we discuss a new method for identifying and comparing clean and aerosol-influenced cloud characteristics using a combination of multi-year remote sensing data (CALIPSO, CloudSat) and the FLEXPART aerosol model. We use this method to investigate a variety of aerosol microphysical impacts on nighttime Arctic Ocean clouds on regional and local scales. We observe differences in factors that can impact cloud lifetime, including cloud thickness and phase, within a subset of clean vs. polluted clouds. We will also discuss cumulative cloud fraction differences in clean and non-clean environments, as well as their likely impact on longwave cloud radiative effects at the Arctic Ocean surface during polar night.
NASA Astrophysics Data System (ADS)
Zhao, Yu; Shi, Chen-Xiao; Kwon, Ki-Chul; Piao, Yan-Ling; Piao, Mei-Lan; Kim, Nam
2018-03-01
We propose a fast calculation method for a computer-generated hologram (CGH) of real objects that uses a point cloud gridding method. The depth information of the scene is acquired using a depth camera and the point cloud model is reconstructed virtually. Because each point of the point cloud is distributed precisely to the exact coordinates of each layer, each point of the point cloud can be classified into grids according to its depth. A diffraction calculation is performed on the grids using a fast Fourier transform (FFT) to obtain a CGH. The computational complexity is reduced dramatically in comparison with conventional methods. The feasibility of the proposed method was confirmed by numerical and optical experiments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Wenyang; Cheung, Yam; Sawant, Amit
2016-05-15
Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparsemore » regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.« less
Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan
2016-01-01
Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications. PMID:27147347
Some physical and thermodynamic properties of rocket exhaust clouds measured with infrared scanners
NASA Technical Reports Server (NTRS)
Gomberg, R. I.; Kantsios, A. G.; Rosensteel, F. J.
1977-01-01
Measurements using infrared scanners were made of the radiation from exhaust clouds from liquid- and solid-propellant rocket boosters. Field measurements from four launches were discussed. These measurements were intended to explore the physical and thermodynamic properties of these exhaust clouds during their formation and subsequent dispersion. Information was obtained concerning the initial cloud's buoyancy, the stabilized cloud's shape and trajectory, the cloud volume as a function of time, and it's initial and stabilized temperatures. Differences in radiation intensities at various wavelengths from ambient and stabilized exhaust clouds were investigated as a method of distinguishing between the two types of clouds. The infrared remote sensing method used can be used at night when visible range cameras are inadequate. Infrared scanning techniques developed in this project can be applied directly to natural clouds, clouds containing certain radionuclides, or clouds of industrial pollution.
A Catalog of Molecular Clouds in the Milky Way Galaxy
NASA Astrophysics Data System (ADS)
Wahl, Matthew; Koda, J.
2010-01-01
We have created a complete catalog of molecular clouds in the Milky Way Galaxy. This is an extension of our previous study (Koda et al. 2006) which used a preliminary data set from The Boston University Five College Radio Astronomy Observatory Galactic Ring Survey (BUFCRAO GRS). This work is of the complete data set from this GRS. The data covers the inner part of the northern Galactic disk between galactic longitudes 15 to 56 degrees, galactic latitudes -1.1 to 1.1 degrees, and the entire Galactic velocities. We used the standard cloud identification method. This method searches the data cube for a peak in temperature above a specified value, and then searches around that peak in all directions until the extents of the cloud are found. This method is iterated until all clouds are found. We prefer this method over other methods, because of its simplicity. The properties of our molecular clouds are very similar to those based on a more evolved method (Rathborne et al. 2009).
Magnetic Fields and Multiple Protostar Formation
NASA Astrophysics Data System (ADS)
Boss, A. P.
2001-12-01
Recent observations of star-forming regions suggest that binary and multiple young stars are the rule rather than the exception, and implicate fragmentation as the likely mechanism for their formation. Most numerical hydrodynamical calculations of fragmentation have neglected the possibly deleterious effects of magnetic fields, in spite of ample evidence for the importance of magnetic support of pre-collapse clouds. We present here the first numerical hydrodynamical survey of the full effects of magnetic fields on the collapse and fragmentation of dense cloud cores. The models are calculated with a three dimensional, finite differences code which solves the equations of hydrodynamics, gravitation, and radiative transfer in the Eddington and diffusion approximations. Magnetic field effects are included through two simple approximations: magnetic pressure is added to the gas pressure, and magnetic tension is approximated by gravity dilution once collapse is well underway. Ambipolar diffusion of the magnetic field leading to cloud collapse is treated approximately as well. Models are calculated for a variety of initial cloud density profiles, shapes, and rotation rates. We find that in spite of the inclusion of magnetic field effects, dense cloud cores are capable of fragmenting into binary and multiple protostar systems. Initially prolate clouds tend to fragment into binary protostars, while initially oblate clouds tend to fragment into multiple protostar systems containing a small number (of order four) of fragments. The latter are likely to be subject to rapid orbital evolution, with close encounters possibly leading to the ejection of fragments. Contrary to expectation, magnetic tension effects appear to enhance fragmentation, allowing lower mass fragments to form than would otherwise be possible, because magnetic tension helps to prevent a central density singularity from forming and producing a dominant single object. Magnetically-supported dense cloud cores thus seem to be capable of collapsing and fragmenting into sufficient numbers of binary and multiple protostar systems to be compatible with observations of the relative rarity of single protostars. This work was partially supported by NSF grants AST-9983530 and MRI-9976645.
Influence of Ice-phase of Hydrometeors on Moist-Convection
NASA Technical Reports Server (NTRS)
Sud, Y. C.; Walker, G. K.
2003-01-01
Climate models often ignore the influence of ice-phase physics (IPP) of hydrometeors as a second order effect. This has also been true for McRAS (Microphysics of clouds with Relaxed Arakawa Schubert Scheme) developed by the authors. Recognizing that the temperature sounding is critical for moist-convection, and, that IPP would modify it, we investigated the influence of introducing IPP into McRAS coupled to FvGCM (finite volume General Circulation Model with NCAR physics). We analyzed three 3-yr long simulations; the first called Control Case, CC and had no IPP; the other two called Experiments El and E2 had IPP introduced with two different in-cloud freezing assumptions. Simulation El assumed that all hydrometeors remain liquid in the updraft and freeze upon detrainment. Simulation E2 invoked the in-cloud freezing of new condensate generated at subfreezing temperatures in the updraft while old cloud water continued to ascend as liquid. Upon detrainment, this cloud water also froze like in E1. With these assumptions, about 50% of hydrometeors froze in the tower and the rest froze in the anvil. However, in both El and E2, the frozen hydrometeors melted during fall at the first encounter of above freezing ambient temperature. Comparative analysis revealed that El simulated far more mid-level and far less deep clouds while E2 had modified deep and more mid-level clouds as compared to CC along with some major changes around the melt-level. We infer that IPP produced a more realistic response in E2. At the basic level, the results show that ice-phase processes influence convective detrainment at mid- and deep levels in accord with TOGAGOARE observations. The results suggest that IPP can help to mitigate less-than-observed mid-level and over-abundance of deep convective clouds in McRAS.
NASA Astrophysics Data System (ADS)
Meinke, I.
2003-04-01
A new method is presented to validate cloud parametrization schemes in numerical atmospheric models with satellite data of scanning radiometers. This method is applied to the regional atmospheric model HRM (High Resolution Regional Model) using satellite data from ISCCP (International Satellite Cloud Climatology Project). Due to the limited reliability of former validations there has been a need for developing a new validation method: Up to now differences between simulated and measured cloud properties are mostly declared as deficiencies of the cloud parametrization scheme without further investigation. Other uncertainties connected with the model or with the measurements have not been taken into account. Therefore changes in the cloud parametrization scheme based on such kind of validations might not be realistic. The new method estimates uncertainties of the model and the measurements. Criteria for comparisons of simulated and measured data are derived to localize deficiencies in the model. For a better specification of these deficiencies simulated clouds are classified regarding their parametrization. With this classification the localized model deficiencies are allocated to a certain parametrization scheme. Applying this method to the regional model HRM the quality of forecasting cloud properties is estimated in detail. The overestimation of simulated clouds in low emissivity heights especially during the night is localized as model deficiency. This is caused by subscale cloudiness. As the simulation of subscale clouds in the regional model HRM is described by a relative humidity parametrization these deficiencies are connected with this parameterization.
Yan, Fang; Xu, Kaili
2017-01-01
Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific.
NASA Astrophysics Data System (ADS)
Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia
2014-01-01
The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.
Yan, Fang; Xu, Kaili
2017-01-01
Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific. PMID:28076440
Investigation of methods to produce a uniform cloud of fuel particles in a flame tube
NASA Technical Reports Server (NTRS)
Siegert, Clifford E.; Pla, Frederic G.; Rubinstein, Robert; Niezgoda, Thomas F.; Burns, Robert J.; Johnson, Jerome A.
1990-01-01
The combustion of a uniform, quiescent cloud of 30-micron fuel particles in a flame tube was proposed as a space-based, low-gravity experiment. The subject is the normal- and low-gravity testing of several methods to produce such a cloud, including telescoping propeller fans, air pumps, axial and quadrature acoustical speakers, and combinations of these devices. When operated in steady state, none of the methods produced an acceptably uniform cloud (+ or - 5 percent of the mean concentration), and voids in the cloud were clearly visible. In some cases, severe particle agglomeration was observed; however, these clusters could be broken apart by a short acoustic burst from an axially in-line speaker. Analyses and experiments reported elsewhere suggest that transient, acoustic mixing methods can enhance cloud uniformity while minimizing particle agglomeration.
Cloud Detection of Optical Satellite Images Using Support Vector Machine
NASA Astrophysics Data System (ADS)
Lee, Kuan-Yi; Lin, Chao-Hung
2016-06-01
Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.
Shallow cumuli ensemble statistics for development of a stochastic parameterization
NASA Astrophysics Data System (ADS)
Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs
2014-05-01
According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.
A Novel Deployment Method for Communication-Intensive Applications in Service Clouds
Liu, Chuanchang; Yang, Jingqi
2014-01-01
The service platforms are migrating to clouds for reasonably solving long construction periods, low resource utilizations, and isolated constructions of service platforms. However, when the migration is conducted in service clouds, there is a little focus of deploying communication-intensive applications in previous deployment methods. To address this problem, this paper proposed the combination of the online deployment and the offline deployment for deploying communication-intensive applications in service clouds. Firstly, the system architecture was designed for implementing the communication-aware deployment method for communication-intensive applications in service clouds. Secondly, in the online-deployment algorithm and the offline-deployment algorithm, service instances were deployed in an optimal cloud node based on the communication overhead which is determined by the communication traffic between services, as well as the communication performance between cloud nodes. Finally, the experimental results demonstrated that the proposed methods deployed communication-intensive applications effectively with lower latency and lower load compared with existing algorithms. PMID:25140331
A novel deployment method for communication-intensive applications in service clouds.
Liu, Chuanchang; Yang, Jingqi
2014-01-01
The service platforms are migrating to clouds for reasonably solving long construction periods, low resource utilizations, and isolated constructions of service platforms. However, when the migration is conducted in service clouds, there is a little focus of deploying communication-intensive applications in previous deployment methods. To address this problem, this paper proposed the combination of the online deployment and the offline deployment for deploying communication-intensive applications in service clouds. Firstly, the system architecture was designed for implementing the communication-aware deployment method for communication-intensive applications in service clouds. Secondly, in the online-deployment algorithm and the offline-deployment algorithm, service instances were deployed in an optimal cloud node based on the communication overhead which is determined by the communication traffic between services, as well as the communication performance between cloud nodes. Finally, the experimental results demonstrated that the proposed methods deployed communication-intensive applications effectively with lower latency and lower load compared with existing algorithms.
A Novel College Network Resource Management Method using Cloud Computing
NASA Astrophysics Data System (ADS)
Lin, Chen
At present information construction of college mainly has construction of college networks and management information system; there are many problems during the process of information. Cloud computing is development of distributed processing, parallel processing and grid computing, which make data stored on the cloud, make software and services placed in the cloud and build on top of various standards and protocols, you can get it through all kinds of equipments. This article introduces cloud computing and function of cloud computing, then analyzes the exiting problems of college network resource management, the cloud computing technology and methods are applied in the construction of college information sharing platform.
Motion Estimation System Utilizing Point Cloud Registration
NASA Technical Reports Server (NTRS)
Chen, Qi (Inventor)
2016-01-01
A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.
Comparison of Histograms for Use in Cloud Observation and Modeling
NASA Technical Reports Server (NTRS)
Green, Lisa; Xu, Kuan-Man
2005-01-01
Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.
LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings
NASA Astrophysics Data System (ADS)
Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan
2018-01-01
This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.
Research on cloud background infrared radiation simulation based on fractal and statistical data
NASA Astrophysics Data System (ADS)
Liu, Xingrun; Xu, Qingshan; Li, Xia; Wu, Kaifeng; Dong, Yanbing
2018-02-01
Cloud is an important natural phenomenon, and its radiation causes serious interference to infrared detector. Based on fractal and statistical data, a method is proposed to realize cloud background simulation, and cloud infrared radiation data field is assigned using satellite radiation data of cloud. A cloud infrared radiation simulation model is established using matlab, and it can generate cloud background infrared images for different cloud types (low cloud, middle cloud, and high cloud) in different months, bands and sensor zenith angles.
Cloud characterization and clear-sky correction from Landsat-7
Cahalan, Robert F.; Oreopoulos, L.; Wen, G.; Marshak, S.; Tsay, S. -C.; DeFelice, Tom
2001-01-01
Landsat, with its wide swath and high resolution, fills an important mesoscale gap between atmospheric variations seen on a few kilometer scale by local surface instrumentation and the global view of coarser resolution satellites such as MODIS. In this important scale range, Landsat reveals radiative effects on the few hundred-meter scale of common photon mean-free-paths, typical of scattering in clouds at conservative (visible) wavelengths, and even shorter mean-free-paths of absorptive (near-infrared) wavelengths. Landsat also reveals shadowing effects caused by both cloud and vegetation that impact both cloudy and clear-sky radiances. As a result, Landsat has been useful in development of new cloud retrieval methods and new aerosol and surface retrievals that account for photon diffusion and shadowing effects. This paper discusses two new cloud retrieval methods: the nonlocal independent pixel approximation (NIPA) and the normalized difference nadir radiance method (NDNR). We illustrate the improvements in cloud property retrieval enabled by the new low gain settings of Landsat-7 and difficulties found at high gains. Then, we review the recently developed “path radiance” method of aerosol retrieval and clear-sky correction using data from the Department of Energy Atmospheric Radiation Measurement (ARM) site in Oklahoma. Nearby clouds change the solar radiation incident on the surface and atmosphere due to indirect illumination from cloud sides. As a result, if clouds are nearby, this extra side-illumination causes clear pixels to appear brighter, which can be mistaken for extra aerosol or higher surface albedo. Thus, cloud properties must be known in order to derive accurate aerosol and surface properties. A three-dimensional (3D) Monte Carlo (MC) radiative transfer simulation illustrates this point and suggests a method to subtract the cloud effect from aerosol and surface retrievals. The main conclusion is that cloud, aerosol, and surface retrievals are linked and must be treated as a combined system. Landsat provides the range of scales necessary to observe the 3D cloud radiative effects that influence joint surface-atmospheric retrievals.
A study of the 3D radiative transfer effect in cloudy atmospheres
NASA Astrophysics Data System (ADS)
Okata, M.; Teruyuki, N.; Suzuki, K.
2015-12-01
Evaluation of the effect of clouds in the atmosphere is a significant problem in the Earth's radiation budget study with their large uncertainties of microphysics and the optical properties. In this situation, we still need more investigations of 3D cloud radiative transer problems using not only models but also satellite observational data.For this purpose, we have developed a 3D-Monte-Carlo radiative transfer code that is implemented with various functions compatible with the OpenCLASTR R-Star radiation code for radiance and flux computation, i.e. forward and backward tracing routines, non-linear k-distribution parameterization (Sekiguchi and Nakajima, 2008) for broad band solar flux calculation, and DM-method for flux and TMS-method for upward radiance (Nakajima and Tnaka 1998). We also developed a Minimum cloud Information Deviation Profiling Method (MIDPM) as a method for a construction of 3D cloud field with MODIS/AQUA and CPR/CloudSat data. We then selected a best-matched radar reflectivity factor profile from the library for each of off-nadir pixels of MODIS where CPR profile is not available, by minimizing the deviation between library MODIS parameters and those at the pixel. In this study, we have used three cloud microphysical parameters as key parameters for the MIDPM, i.e. effective particle radius, cloud optical thickness and top of cloud temperature, and estimated 3D cloud radiation budget. We examined the discrepancies between satellite observed and mode-simulated radiances and three cloud microphysical parameter's pattern for studying the effects of cloud optical and microphysical properties on the radiation budget of the cloud-laden atmospheres.
Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan
2016-05-01
To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.
NASA Astrophysics Data System (ADS)
Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.
2015-12-01
Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.
NASA Astrophysics Data System (ADS)
Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Cribb, Maureen
2013-01-01
Cloud vertical structure is a key quantity in meteorological and climate studies, but it is also among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP), Tropical Western Pacific (TWP), and North Slope of Alaska (NSA) sites and a shorter-term product for the ARM Mobile Facility (AMF) deployed in Shouxian, Anhui Province, China (AMF-China). The AMF-China site was in operation from 14 May to 28 December 2008; the ARM sites have been collecting data for over 15 years. The Active Remote Sensing of Cloud (ARSCL) value-added product (VAP), which combines data from the 95-GHz W-band ARM Cloud Radar (WACR) and/or the 35-GHz Millimeter Microwave Cloud Radar (MMCR), is used in this study to validate the radiosonde-based cloud layer retrieval method. The performance of the radiosonde-based cloud layer retrieval method applied to data from different climate regimes is evaluated. Overall, cloud layers derived from the ARSCL VAP and radiosonde data agree very well at the SGP and AMF-China sites. At the TWP and NSA sites, the radiosonde tends to detect more cloud layers in the upper troposphere.
Stress-intensity factors for small surface and corner cracks in plates
NASA Technical Reports Server (NTRS)
Raju, I. S.; Atluri, S. N.; Newman, J. C., Jr.
1988-01-01
Three-dimensional finite-element and finite-alternating methods were used to obtain the stress-intensity factors for small surface and corner cracked plates subjected to remote tension and bending loads. The crack-depth-to-crack-length ratios (a/c) ranged from 0.2 to 1 and the crack-depth-to-plate-thickness ratios (a/t) ranged from 0.05 to 0.2. The performance of the finite-element alternating method was studied on these crack configurations. A study of the computational effort involved in the finite-element alternating method showed that several crack configurations could be analyzed with a single rectangular mesh idealization, whereas the conventional finite-element method requires a different mesh for each configuration. The stress-intensity factors obtained with the finite-element-alternating method agreed well (within 5 percent) with those calculated from the finite-element method with singularity elements.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, W; Sawant, A; Ruan, D
2016-06-15
Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity inmore » local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less
NASA Technical Reports Server (NTRS)
Putman, William M.
2010-01-01
The Goddard Earth Observing System Model (GEOS-S), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-S from irs standard 72-level 27-km resolution (approx.5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (approx. 3.6 billion cells).
Evaluation of finite difference and FFT-based solutions of the transport of intensity equation.
Zhang, Hongbo; Zhou, Wen-Jing; Liu, Ying; Leber, Donald; Banerjee, Partha; Basunia, Mahmudunnabi; Poon, Ting-Chung
2018-01-01
A finite difference method is proposed for solving the transport of intensity equation. Simulation results show that although slower than fast Fourier transform (FFT)-based methods, finite difference methods are able to reconstruct the phase with better accuracy due to relaxed assumptions for solving the transport of intensity equation relative to FFT methods. Finite difference methods are also more flexible than FFT methods in dealing with different boundary conditions.
Cloud Detection by Fusing Multi-Scale Convolutional Features
NASA Astrophysics Data System (ADS)
Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang
2018-04-01
Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
3D dust clouds (Yukawa Balls) in strongly coupled dusty plasmas
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melzer, A.; Passvogel, M.; Miksch, T.
2010-06-16
Three-dimensional finite systems of charged dust particles confined to concentric spherical shells in a dusty plasma, so-called 'Yukawa balls', have been studied with respect to their static and dynamic properties. Here, we review the charging of particles in a dusty plasma discharge by computer simulations and the respective particle arrangements. The normal mode spectrum of Yukawa balls is measured from the 3D thermal Brownian motion of the dust particles around their equilibrium positions.
NASA Astrophysics Data System (ADS)
Xu, Miaomiao; Bu, Xiongzhu; Yu, Jing; He, Zilu
2018-01-01
Based on the study of earth infrared radiation and further requirement of anticloud interference ability for a spinning projectile's infrared attitude measurement, a compensation method of cloud infrared radiation interference is proposed. First, the theoretical model of infrared radiation interference is established by analyzing the generation mechanism and interference characteristics of cloud infrared radiation. Then, the influence of cloud infrared radiation on attitude angle is calculated in the following two situations. The first situation is the projectile in cloud, and the maximum of roll angle error can reach ± 20 deg. The second situation is the projectile outside of cloud, and it results in the inability to measure the projectile's attitude angle. Finally, a multisensor weighted fusion algorithm is proposed based on trust function method to reduce the influence of cloud infrared radiation. The results of semiphysical experiments show that the error of roll angle with a weighted fusion algorithm can be kept within ± 0.5 deg in the presence of cloud infrared radiation interference. This proposed method improves the accuracy of roll angle by nearly four times in attitude measurement and also solves the problem of low accuracy of infrared radiation attitude measurement in navigation and guidance field.
Introducing two Random Forest based methods for cloud detection in remote sensing images
NASA Astrophysics Data System (ADS)
Ghasemian, Nafiseh; Akhoondzadeh, Mehdi
2018-07-01
Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The quantitative values on Landsat 8 images show similar trend. Consequently, while SVM and K-nearest neighbor show overestimation in predicting cloud and snow/ice pixels, our Random Forest (RF) based models can achieve higher cloud, snow/ice kappa values on MODIS and thin cloud, thick cloud and snow/ice kappa values on Landsat 8 images. Our algorithms predict both thin and thick cloud on Landsat 8 images while the existing cloud detection algorithm, Fmask cannot discriminate them. Compared to the state-of-the-art methods, our algorithms have acquired higher average cloud and snow/ice kappa values for different spatial resolutions.
NASA Astrophysics Data System (ADS)
Letu, H.; Ishimoto, H.; Riedi, J.; Nakajima, T. Y.; -Labonnote, L. C.; Baran, A. J.; Nagao, T. M.; Skiguchi, M.
2015-11-01
Various ice particle habits are investigated in conjunction with inferring the optical properties of ice cloud for the Global Change Observation Mission-Climate (GCOM-C) satellite program. A database of the single-scattering properties of five ice particle habits, namely, plates, columns, droxtals, bullet-rosettes, and Voronoi, is developed. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor onboard the GCOM-C satellite, which is scheduled to be launched in 2017 by Japan Aerospace Exploration Agency (JAXA). A combination of the finite-difference time-domain (FDTD) method, Geometric Optics Integral Equation (GOIE) technique, and geometric optics method (GOM) are applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible-to-infrared spectral region, covering the SGLI channels for the size parameter, which is defined with respect to the equivalent-volume radius sphere, which ranges between 6 and 9000. The database includes the extinction efficiency, absorption efficiency, average geometrical cross-section, single-scattering albedo, asymmetry factor, size parameter of an equivalent volume sphere, maximum distance from the center of mass, particle volume, and six non-zero elements of the scattering phase matrix. The characteristics of the calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, the optical thickness and spherical albedo of ice clouds using the five ice particle habit models are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL). The optimal ice particle habit for retrieving the SGLI ice cloud properties was investigated by adopting the spherical albedo difference (SAD) method. It is found that the SAD, for bullet-rosette particle, with radii of equivalent volume spheres (r~) ranging between 6 to 10 μm, and the Voronoi particle, with r~ ranging between 28 to 38 μm, and 70 to 100 μm, is distributed stably as the scattering angle increases. It is confirmed that the SAD of small bullet rosette and all sizes of voronoi particles has a low angular dependence, indicating that the combination of the bullet-rosette and Voronoi models are sufficient for retrieval of the ice cloud spherical albedo and optical thickness as an effective habit models of the SGLI sensor. Finally, SAD analysis based on the Voronoi habit model with moderate particles (r~ = 30 μm) is compared to the conventional General Habit Mixture (GHM), Inhomogeneous Hexagonal Monocrystal (IHM), 5-plate aggregate and ensemble ice particle model. It is confirmed that the Voronoi habit model has an effect similar to the counterparts of some conventional models on the retrieval of ice cloud properties from space-borne radiometric observations.
The aggregated unfitted finite element method for elliptic problems
NASA Astrophysics Data System (ADS)
Badia, Santiago; Verdugo, Francesc; Martín, Alberto F.
2018-07-01
Unfitted finite element techniques are valuable tools in different applications where the generation of body-fitted meshes is difficult. However, these techniques are prone to severe ill conditioning problems that obstruct the efficient use of iterative Krylov methods and, in consequence, hinders the practical usage of unfitted methods for realistic large scale applications. In this work, we present a technique that addresses such conditioning problems by constructing enhanced finite element spaces based on a cell aggregation technique. The presented method, called aggregated unfitted finite element method, is easy to implement, and can be used, in contrast to previous works, in Galerkin approximations of coercive problems with conforming Lagrangian finite element spaces. The mathematical analysis of the new method states that the condition number of the resulting linear system matrix scales as in standard finite elements for body-fitted meshes, without being affected by small cut cells, and that the method leads to the optimal finite element convergence order. These theoretical results are confirmed with 2D and 3D numerical experiments.
Improved methods of vibration analysis of pretwisted, airfoil blades
NASA Technical Reports Server (NTRS)
Subrahmanyam, K. B.; Kaza, K. R. V.
1984-01-01
Vibration analysis of pretwisted blades of asymmetric airfoil cross section is performed by using two mixed variational approaches. Numerical results obtained from these two methods are compared to those obtained from an improved finite difference method and also to those given by the ordinary finite difference method. The relative merits, convergence properties and accuracies of all four methods are studied and discussed. The effects of asymmetry and pretwist on natural frequencies and mode shapes are investigated. The improved finite difference method is shown to be far superior to the conventional finite difference method in several respects. Close lower bound solutions are provided by the improved finite difference method for untwisted blades with a relatively coarse mesh while the mixed methods have not indicated any specific bound.
NASA Astrophysics Data System (ADS)
Martin, William G. K.; Hasekamp, Otto P.
2018-01-01
In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.
Kicking atoms with finite duration pulses
NASA Astrophysics Data System (ADS)
Fekete, Julia; Chai, Shijie; Daszuta, Boris; Andersen, Mikkel F.
2016-05-01
The atom optics delta-kicked particle is a paradigmatic system for experimental studies of quantum chaos and classical-quantum correspondence. It consists of a cloud of laser cooled atoms exposed to a periodically pulsed standing wave of far off-resonant laser light. A purely quantum phenomena in such systems are quantum resonances which transfers the atoms into a coherent superposition of largely separated momentum states. Using such large momentum transfer ``beamsplitters'' in atom interferometers may have applications in high precision metrology. The growth in momentum separation cannot be maintained indefinitely due to finite laser power. The largest momentum transfer is achieved by violating the usual delta-kick assumption. Therefore we explore the behavior of the atom optics kicked particle with finite pulse duration. We have developed a semi-classical model which shows good agreement with the full quantum description as well as our experiments. Furthermore we have found a simple scaling law that helps to identify optimal parameters for an atom interferometer. We verify this by measurements of the ``Talbot time'' (a measurement of h/m) which together with other well-known constants constitute a measurement of the fine structure constant.
NASA Technical Reports Server (NTRS)
Pounder, Nicola L.; Hogan, Robin J.; Varnai, Tamas; Battaglia, Alessandro; Cahalan, Robert F.
2011-01-01
While liquid clouds playa very important role in the global radiation budget, it's been very difficult to remotely determine their internal cloud structure. Ordinary lidar instruments (similar to radars but using visible light pulses) receive strong signals from such clouds, but the information is limited to a thin layer near the cloud boundary. Multiple field-of-view (FOV) lidars offer some new hope as they are able to isolate photons that were scattered many times by cloud droplets and penetrated deep into a cloud before returning to the instrument. Their data contains new information on cloud structure, although the lack of fast simulation methods made it challenging to interpret the observations. This paper describes a fast new technique that can simulate multiple-FOV lidar signals and can even estimate the way the signals would change in response to changes in cloud properties-an ability that allows quick refinements in our initial guesses of cloud structure. Results for a hypothetical airborne three-FOV lidar suggest that this approach can help determine cloud structure for a deeper layer in clouds, and can reliably determine the optical thickness of even fairly thick liquid clouds. The algorithm is also applied to stratocumulus observations by the 8-FOV airborne "THOR" lidar. These tests demonstrate that the new method can determine the depth to which a lidar provides useful information on vertical cloud structure. This work opens the way to exploit data from spaceborne lidar and radar more rigorously than has been possible up to now.
High-Order Entropy Stable Finite Difference Schemes for Nonlinear Conservation Laws: Finite Domains
NASA Technical Reports Server (NTRS)
Fisher, Travis C.; Carpenter, Mark H.
2013-01-01
Developing stable and robust high-order finite difference schemes requires mathematical formalism and appropriate methods of analysis. In this work, nonlinear entropy stability is used to derive provably stable high-order finite difference methods with formal boundary closures for conservation laws. Particular emphasis is placed on the entropy stability of the compressible Navier-Stokes equations. A newly derived entropy stable weighted essentially non-oscillatory finite difference method is used to simulate problems with shocks and a conservative, entropy stable, narrow-stencil finite difference approach is used to approximate viscous terms.
NASA Astrophysics Data System (ADS)
Khatri, Pradeep; Hayasaka, Tadahiro; Iwabuchi, Hironobu; Takamura, Tamio; Irie, Hitoshi; Nakajima, Takashi Y.; Letu, Husi; Kai, Qin
2017-04-01
Clouds are known to have profound impacts on atmospheric radiation and water budget, climate change, atmosphere-surface interaction, and so on. Cloud optical thickness (COT) and effective radius (Re) are two fundamental cloud parameters required to study clouds from climatological and hydrological point of view. Large spatial-temporal coverages of those cloud parameters from space observation have proved to be very useful for cloud research; however, validation of space-based products is still a challenging task due to lack of reliable data. Ground-based remote sensing instruments, such as sky radiometers distributed around the world through international observation networks of SKYNET (http://atmos2.cr.chiba-u.jp/skynet/) and AERONET (https://aeronet.gsfc.nasa.gov/) have a great potential to produce ground-truth cloud parameters at different parts of the globe to validate satellite products. Focusing to the sky radiometers of SKYNET and AERONET, a few cloud retrieval methods exists, but those methods have some difficulties to address the problem when cloud is optically thin. It is because the observed transmittances at two wavelengths can be originated from more than one set of COD and Re, and the choice of the most plausible set is difficult. At the same time, calibration issue, especially for the wavelength of near infrared (NIR) region, which is important to retrieve Re, is also a difficult task at present. As a result, instruments need to be calibrated at a high mountain or calibration terms need to be transferred from a standard instrument. Taking those points on account, we developed a new retrieval method emphasizing to overcome above-mentioned difficulties. We used observed transmittances of multiple wavelengths to overcome the first problem. We further proposed a method to obtain calibration constant of NIR wavelength channel using observation data. Our cloud retrieval method is found to produce relatively accurate COD and Re when validated them using data of a narrow field of view radiometer of collocated observation in one SKYNET site. Though the method is developed for the sky radiometer of SKYNET, it can be still used for the sky radiometer of AERONET and other instruments observing spectral zenith transmittances. The proposed retrieval method is then applied to retrieve cloud parameters at key sites of SKYNET within Japan, which are then used to validate cloud products obtained from space observations by MODIS sensors onboard TERRA/AQUA satellites and Himawari 8, a Japanese geostationary satellite. Our analyses suggest the underestimation (overestimation) of COD (Re) from space observations.
Cloud radiative properties and aerosol - cloud interaction
NASA Astrophysics Data System (ADS)
Viviana Vladutescu, Daniela; Gross, Barry; Li, Clement; Han, Zaw
2015-04-01
The presented research discusses different techniques for improvement of cloud properties measurements and analysis. The need for these measurements and analysis arises from the high errors noticed in existing methods that are currently used in retrieving cloud properties and implicitly cloud radiative forcing. The properties investigated are cloud fraction (cf) and cloud optical thickness (COT) measured with a suite of collocated remote sensing instruments. The novel approach makes use of a ground based "poor man's camera" to detect cloud and sky radiation in red, green, and blue with a high spatial resolution of 30 mm at 1km. The surface-based high resolution photography provides a new and interesting view of clouds. As the cloud fraction cannot be uniquely defined or measured, it depends on threshold and resolution. However as resolution decreases, cloud fraction tends to increase if the threshold is below the mean, and vice versa. Additionally cloud fractal dimension also depends on threshold. Therefore these findings raise concerns over the ability to characterize clouds by cloud fraction or fractal dimension. Our analysis indicate that Principal Component analysis may lead to a robust means of quantifying cloud contribution to radiance. The cloud images are analyzed in conjunction with a collocated CIMEL sky radiometer, Microwave Radiometer and LIDAR to determine homogeneity and heterogeneity. Additionally, MFRSR measurements are used to determine the cloud radiative properties as a validation tool to the results obtained from the other instruments and methods. The cloud properties to be further studied are aerosol- cloud interaction, cloud particle radii, and vertical homogeneity.
Multilayered Clouds Identification and Retrieval for CERES Using MODIS
NASA Technical Reports Server (NTRS)
Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung
2006-01-01
Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.
A Study of Global Cirrus Cloud Morphology with AIRS Cloud-clear Radiances (CCRs)
NASA Technical Reports Server (NTRS)
Wu, Dong L.; Gong, Jie
2012-01-01
Version 6 (V6) AIRS cloud-clear radiances (CCR) are used to derive cloud-induced radiance (Tcir=Tb-CCR) at the infrared frequencies of weighting functions peaked in the middle troposphere. The significantly improved V 6 CCR product allows a more accurate estimation of the expected clear-sky radiance as if clouds are absent. In the case where strong cloud scattering is present, the CCR becomes unreliable, which is reflected by its estimated uncertainty, and interpolation is employed to replace this CCR value. We find that Tcir derived from this CCR method are much better than other methods and detect more clouds in the upper and lower troposphere as well as in the polar regions where cloud detection is particularly challenging. The cloud morphology derived from the V6 test month, as well as some artifacts, will be shown.
Automatic cloud coverage assessment of Formosat-2 image
NASA Astrophysics Data System (ADS)
Hsu, Kuo-Hsien
2011-11-01
Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.
Using cloud models of heartbeats as the entity identifier to secure mobile devices.
Fu, Donglai; Liu, Yanhua
2017-01-01
Mobile devices are extensively used to store more private and often sensitive information. Therefore, it is important to protect them against unauthorised access. Authentication ensures that authorised users can use mobile devices. However, traditional authentication methods, such as numerical or graphic passwords, are vulnerable to passive attacks. For example, an adversary can steal the password by snooping from a shorter distance. To avoid these problems, this study presents a biometric approach that uses cloud models of heartbeats as the entity identifier to secure mobile devices. Here, it is identified that these concepts including cloud model or cloud have nothing to do with cloud computing. The cloud model appearing in the study is the cognitive model. In the proposed method, heartbeats are collected by two ECG electrodes that are connected to one mobile device. The backward normal cloud generator is used to generate ECG standard cloud models characterising the heartbeat template. When a user tries to have access to their mobile device, cloud models regenerated by fresh heartbeats will be compared with ECG standard cloud models to determine if the current user can use this mobile device. This authentication method was evaluated from three aspects including accuracy, authentication time and energy consumption. The proposed method gives 86.04% of true acceptance rate with 2.73% of false acceptance rate. One authentication can be done in 6s, and this processing consumes about 2000 mW of power.
Morphable Word Clouds for Time-Varying Text Data Visualization.
Chi, Ming-Te; Lin, Shih-Syun; Chen, Shiang-Yi; Lin, Chao-Hung; Lee, Tong-Yee
2015-12-01
A word cloud is a visual representation of a collection of text documents that uses various font sizes, colors, and spaces to arrange and depict significant words. The majority of previous studies on time-varying word clouds focuses on layout optimization and temporal trend visualization. However, they do not fully consider the spatial shapes and temporal motions of word clouds, which are important factors for attracting people's attention and are also important cues for human visual systems in capturing information from time-varying text data. This paper presents a novel method that uses rigid body dynamics to arrange multi-temporal word-tags in a specific shape sequence under various constraints. Each word-tag is regarded as a rigid body in dynamics. With the aid of geometric, aesthetic, and temporal coherence constraints, the proposed method can generate a temporally morphable word cloud that not only arranges word-tags in their corresponding shapes but also smoothly transforms the shapes of word clouds over time, thus yielding a pleasing time-varying visualization. Using the proposed frame-by-frame and morphable word clouds, people can observe the overall story of a time-varying text data from the shape transition, and people can also observe the details from the word clouds in frames. Experimental results on various data demonstrate the feasibility and flexibility of the proposed method in morphable word cloud generation. In addition, an application that uses the proposed word clouds in a simulated exhibition demonstrates the usefulness of the proposed method.
NASA Technical Reports Server (NTRS)
Reichardt, J.; Reichardt, S.; Yang, P.; McGee, T. J.; Bhartia, P. K. (Technical Monitor)
2001-01-01
A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salloum, Maher; Fabian, Nathan D.; Hensinger, David M.
Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate itsmore » usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Finally, our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.« less
NASA Technical Reports Server (NTRS)
Ackerman, Thomas P.; Lin, Ruei-Fong
1993-01-01
The radiation field over a broken stratocumulus cloud deck is simulated by the Monte Carlo method. We conducted four experiments to investigate the main factor for the observed shortwave reflectively over the FIRE flight 2 leg 5, in which reflectivity decreases almost linearly from the cloud center to cloud edge while the cloud top height and the brightness temperature remain almost constant through out the clouds. From our results, the geometry effect, however, did not contribute significantly to what has been observed. We found that the variation of the volume extinction coefficient as a function of its relative position in the cloud affects the reflectivity efficiently. Additional check of the brightness temperature of each experiment also confirms this conclusion. The cloud microphysical data showed some interesting features. We found that the cloud droplet spectrum is nearly log-normal distributed when the clouds were solid. However, whether the shift of cloud droplet spectrum toward the larger end is not certain. The decrease of number density from cloud center to cloud edges seems to have more significant effects on the optical properties.
Creating cloud-free Landsat ETM+ data sets in tropical landscapes: cloud and cloud-shadow removal
Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez
2007-01-01
Clouds and cloud shadows are common features of visible and infrared remotelysensed images collected from many parts of the world, particularly in humid and tropical regions. We have developed a simple and semiautomated method to mask clouds and shadows in Landsat ETM+ imagery, and have developed a recent cloud-free composite of multitemporal images for Puerto Rico and...
A comparison of food crispness based on the cloud model.
Wang, Minghui; Sun, Yonghai; Hou, Jumin; Wang, Xia; Bai, Xue; Wu, Chunhui; Yu, Libo; Yang, Jie
2018-02-01
The cloud model is a typical model which transforms the qualitative concept into the quantitative description. The cloud model has been used less extensively in texture studies before. The purpose of this study was to apply the cloud model in food crispness comparison. The acoustic signals of carrots, white radishes, potatoes, Fuji apples, and crystal pears were recorded during compression. And three time-domain signal characteristics were extracted, including sound intensity, maximum short-time frame energy, and waveform index. The three signal characteristics and the cloud model were used to compare the crispness of the samples mentioned above. The crispness based on the Ex value of the cloud model, in a descending order, was carrot > potato > white radish > Fuji apple > crystal pear. To verify the results of the acoustic signals, mechanical measurement and sensory evaluation were conducted. The results of the two verification experiments confirmed the feasibility of the cloud model. The microstructures of the five samples were also analyzed. The microstructure parameters were negatively related with crispness (p < .01). The cloud model method can be used for crispness comparison of different kinds of foods. The method is more accurate than the traditional methods such as mechanical measurement and sensory evaluation. The cloud model method can also be applied to other texture studies extensively. © 2017 Wiley Periodicals, Inc.
Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System
NASA Technical Reports Server (NTRS)
Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.
1996-01-01
An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.
NASA Technical Reports Server (NTRS)
Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.
2013-01-01
This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.
NASA Technical Reports Server (NTRS)
Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.
2014-01-01
This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.
Zhang, Zhenjun; Li, Yang; Liao, Zhenhua; Liu, Weiqiang
2016-12-01
Based on the application of finite element analysis in spine biomechanics,the research progress of finite element method applied in lumbar spine mechanics is reviewed and the prospect is forecasted.The related works,including lumbar ontology modeling,clinical application research,and occupational injury and protection,are summarized.The main research areas of finite element method are as follows:new accurate modeling process,the optimized simulation method,diversified clinical effect evaluation,and the clinical application of artificial lumbar disc.According to the recent research progress,the application prospects of finite element method,such as automation and individuation of modeling process,evaluation and analysis of new operation methods and simulation of mechanical damage and dynamic response,are discussed.The purpose of this paper is to provide the theoretical reference and practical guidance for the clinical lumbar problems by reviewing the application of finite element method in the field of the lumbar spine biomechanics.
Liu, Yu; Xia, Jun; Shi, Chun-Xiang; Hong, Yang
2009-01-01
The crowning objective of this research was to identify a better cloud classification method to upgrade the current window-based clustering algorithm used operationally for China’s first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA) and a Support Vector Machine (SVM), using 2864 cloud samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3–11.3 μm; IR2, 11.5–12.5 μm and WV 6.3–7.6 μm) imagery. The result shows that: (1) ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2) among the six ANN networks, higher cloud classification accuracy was obtained with the Self-Organizing Map (SOM) and Probabilistic Neural Network (PNN). Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network identified from this study, as an automated cloud classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in cloud patch-level classification by more accurately identifying cloud types such as cumulonimbus, cirrus and clouds in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated Cloud Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products. PMID:22346714
Liu, Yu; Xia, Jun; Shi, Chun-Xiang; Hong, Yang
2009-01-01
The crowning objective of this research was to identify a better cloud classification method to upgrade the current window-based clustering algorithm used operationally for China's first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA) and a Support Vector Machine (SVM), using 2864 cloud samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3-11.3 μm; IR2, 11.5-12.5 μm and WV 6.3-7.6 μm) imagery. The result shows that: (1) ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2) among the six ANN networks, higher cloud classification accuracy was obtained with the Self-Organizing Map (SOM) and Probabilistic Neural Network (PNN). Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network identified from this study, as an automated cloud classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in cloud patch-level classification by more accurately identifying cloud types such as cumulonimbus, cirrus and clouds in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated Cloud Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products.
NASA Technical Reports Server (NTRS)
Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.;
2007-01-01
This study compares cirrus particle effective radius retrieved by a CALIPSO-like method with two similar methods using MODIS, MODI Airborne Simulator (MAS), and GOES imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-micrometer, 11.15-micrometer and 12.05-micrometer bands to infer the microphysical properties of cirrus clouds. The two other methods, sing passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the CERES team at LaRC (Langley Research Center) in support of CERES algorithms; the two algorithms will be referred to as MOD06- and LaRC-method, respectively. The three techniques are compared at two different latitudes: (i) the mid-latitude ice clouds study uses 18 days of observations at the Palaiseau ground-based site in France (SIRTA: Site Instrumental de Recherche par Teledetection Atmospherique) including a ground-based 532 nm lidar and the Moderate Resolution Imaging Spectrometer (MODIS) overpasses on the Terra Platform, (ii) the tropical ice clouds study uses 14 different flight legs of observations collected in Florida, during the intensive field experiment CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers-Florida Area Cirrus Experiment), including the airborne Cloud Physics Lidar (CPL) and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness, but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote-sensing method (CALIPSO-like) for the study of sub-visible ice clouds, in both mid-latitudes and tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds.
A New Way to Measure Cirrus Ice Water Content by Using Ice Raman Scatter with Raman Lidar
NASA Technical Reports Server (NTRS)
Wang, Zhien; Whiteman, David N.; Demoz, Belay; Veselovskii, Igor
2004-01-01
High and cold cirrus clouds mainly contain irregular ice crystals, such as, columns, hexagonal plates, bullet rosettes, and dendrites, and have different impacts on the climate system than low-level clouds, such as stratus, stratocumulus, and cumulus. The radiative effects of cirrus clouds on the current and future climate depend strongly on cirrus cloud microphysical properties including ice water content (IWC) and ice crystal sizes, which are mostly an unknown aspect of cinus clouds. Because of the natural complexity of cirrus clouds and their high locations, it is a challenging task to get them accurately by both remote sensing and in situ sampling. This study presents a new method to remotely sense cirrus microphysical properties by using ice Raman scatter with a Raman lidar. The intensity of Raman scattering is fundamentally proportional to the number of molecules involved. Therefore, ice Raman scattering signal provides a more direct way to measure IWC than other remote sensing methods. Case studies show that this method has the potential to provide essential information of cirrus microphysical properties to study cloud physical processes in cirrus clouds.
Overview of MPLNET Version 3 Cloud Detection
NASA Technical Reports Server (NTRS)
Lewis, Jasper R.; Campbell, James; Welton, Ellsworth J.; Stewart, Sebastian A.; Haftings, Phillip
2016-01-01
The National Aeronautics and Space Administration Micro Pulse Lidar Network, version 3, cloud detection algorithm is described and differences relative to the previous version are highlighted. Clouds are identified from normalized level 1 signal profiles using two complementary methods. The first method considers vertical signal derivatives for detecting low-level clouds. The second method, which detects high-level clouds like cirrus, is based on signal uncertainties necessitated by the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multitemporal averaging scheme is used to improve cloud detection under conditions of a weak signal-to-noise ratio. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, Maryland) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5 km, above MSL), which increase in occurrence by over 5%. There is also an increase in the detection of multilayered cloud profiles from 9% to 19%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which the cirrus cloud optical depth could be reliably estimated occurs between 0.5 and 0.8. A comparison using collocated CALIPSO measurements at the Goddard Space Flight Center and Singapore Micro Pulse Lidar Network (MPLNET) sites indicates improvements in cloud occurrence frequencies and layer heights.
Investigating the Accuracy of Point Clouds Generated for Rock Surfaces
NASA Astrophysics Data System (ADS)
Seker, D. Z.; Incekara, A. H.
2016-12-01
Point clouds which are produced by means of different techniques are widely used to model the rocks and obtain the properties of rock surfaces like roughness, volume and area. These point clouds can be generated by applying laser scanning and close range photogrammetry techniques. Laser scanning is the most common method to produce point cloud. In this method, laser scanner device produces 3D point cloud at regular intervals. In close range photogrammetry, point cloud can be produced with the help of photographs taken in appropriate conditions depending on developing hardware and software technology. Many photogrammetric software which is open source or not currently provide the generation of point cloud support. Both methods are close to each other in terms of accuracy. Sufficient accuracy in the mm and cm range can be obtained with the help of a qualified digital camera and laser scanner. In both methods, field work is completed in less time than conventional techniques. In close range photogrammetry, any part of rock surfaces can be completely represented owing to overlapping oblique photographs. In contrast to the proximity of the data, these two methods are quite different in terms of cost. In this study, whether or not point cloud produced by photographs can be used instead of point cloud produced by laser scanner device is investigated. In accordance with this purpose, rock surfaces which have complex and irregular shape located in İstanbul Technical University Ayazaga Campus were selected as study object. Selected object is mixture of different rock types and consists of both partly weathered and fresh parts. Study was performed on a part of 30m x 10m rock surface. 2D and 3D analysis were performed for several regions selected from the point clouds of the surface models. 2D analysis is area-based and 3D analysis is volume-based. Analysis conclusions showed that point clouds in both are similar and can be used as alternative to each other. This proved that point cloud produced using photographs which are both economical and enables to produce data in less time can be used in several studies instead of point cloud produced by laser scanner.
Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks
NASA Astrophysics Data System (ADS)
Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.
2017-12-01
Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.
Villeneuve-Faure, C; Boudou, L; Makasheva, K; Teyssedre, G
2017-12-15
To understand the physical phenomena occurring at metal/dielectric interfaces, determination of the charge density profile at nanoscale is crucial. To deal with this issue, charges were injected applying a DC voltage on lateral Al-electrodes embedded in a SiN x thin dielectric layer. The surface potential induced by the injected charges was probed by Kelvin probe force microscopy (KPFM). It was found that the KPFM frequency mode is a better adapted method to probe accurately the charge profile. To extract the charge density profile from the surface potential two numerical approaches based on the solution to Poisson's equation for electrostatics were investigated: the second derivative model method, already reported in the literature, and a new 2D method based on the finite element method (FEM). Results highlight that the FEM is more robust to noise or artifacts in the case of a non-flat initial surface potential. Moreover, according to theoretical study the FEM appears to be a good candidate for determining charge density in dielectric films with thicknesses in the range from 10 nm to 10 μm. By applying this method, the charge density profile was determined at nanoscale, highlighting that the charge cloud remains close to the interface.
NASA Astrophysics Data System (ADS)
Villeneuve-Faure, C.; Boudou, L.; Makasheva, K.; Teyssedre, G.
2017-12-01
To understand the physical phenomena occurring at metal/dielectric interfaces, determination of the charge density profile at nanoscale is crucial. To deal with this issue, charges were injected applying a DC voltage on lateral Al-electrodes embedded in a SiN x thin dielectric layer. The surface potential induced by the injected charges was probed by Kelvin probe force microscopy (KPFM). It was found that the KPFM frequency mode is a better adapted method to probe accurately the charge profile. To extract the charge density profile from the surface potential two numerical approaches based on the solution to Poisson’s equation for electrostatics were investigated: the second derivative model method, already reported in the literature, and a new 2D method based on the finite element method (FEM). Results highlight that the FEM is more robust to noise or artifacts in the case of a non-flat initial surface potential. Moreover, according to theoretical study the FEM appears to be a good candidate for determining charge density in dielectric films with thicknesses in the range from 10 nm to 10 μm. By applying this method, the charge density profile was determined at nanoscale, highlighting that the charge cloud remains close to the interface.
NASA Technical Reports Server (NTRS)
Chung, T. J. (Editor); Karr, Gerald R. (Editor)
1989-01-01
Recent advances in computational fluid dynamics are examined in reviews and reports, with an emphasis on finite-element methods. Sections are devoted to adaptive meshes, atmospheric dynamics, combustion, compressible flows, control-volume finite elements, crystal growth, domain decomposition, EM-field problems, FDM/FEM, and fluid-structure interactions. Consideration is given to free-boundary problems with heat transfer, free surface flow, geophysical flow problems, heat and mass transfer, high-speed flow, incompressible flow, inverse design methods, MHD problems, the mathematics of finite elements, and mesh generation. Also discussed are mixed finite elements, multigrid methods, non-Newtonian fluids, numerical dissipation, parallel vector processing, reservoir simulation, seepage, shallow-water problems, spectral methods, supercomputer architectures, three-dimensional problems, and turbulent flows.
A portable low-cost 3D point cloud acquiring method based on structure light
NASA Astrophysics Data System (ADS)
Gui, Li; Zheng, Shunyi; Huang, Xia; Zhao, Like; Ma, Hao; Ge, Chao; Tang, Qiuxia
2018-03-01
A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.
Optimal least-squares finite element method for elliptic problems
NASA Technical Reports Server (NTRS)
Jiang, Bo-Nan; Povinelli, Louis A.
1991-01-01
An optimal least squares finite element method is proposed for two dimensional and three dimensional elliptic problems and its advantages are discussed over the mixed Galerkin method and the usual least squares finite element method. In the usual least squares finite element method, the second order equation (-Delta x (Delta u) + u = f) is recast as a first order system (-Delta x p + u = f, Delta u - p = 0). The error analysis and numerical experiment show that, in this usual least squares finite element method, the rate of convergence for flux p is one order lower than optimal. In order to get an optimal least squares method, the irrotationality Delta x p = 0 should be included in the first order system.
Automated cloud screening of AVHRR imagery using split-and-merge clustering
NASA Technical Reports Server (NTRS)
Gallaudet, Timothy C.; Simpson, James J.
1991-01-01
Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.
NASA Technical Reports Server (NTRS)
Fix, G. J.; Rose, M. E.
1983-01-01
A least squares formulation of the system divu = rho, curlu = zeta is surveyed from the viewpoint of both finite element and finite difference methods. Closely related arguments are shown to establish convergence estimates.
A Multi-scale Modeling System: Developments, Applications and Critical Issues
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa;
2006-01-01
A multi-scale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The GCM allows global coverage and the CRM allows explicit simulation of cloud processes and their interactions with radiation and surface processes. A new MMF has been developed that is based the Goddard finite volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved .surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger, propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using conventional cloud parameterizations. Both MMFs also produce a precipitation bias in the western Pacific during Northern Hemisphere summer. However, there are also notable differences between two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF overestimates global rainfall because of its oceanic component. Some critical issues associated with the Goddard MMF are presented in this paper.
Formation of Bidisperse Particle Clouds
NASA Astrophysics Data System (ADS)
Er, Jenn Wei; Zhao, Bing; Law, Adrian W. K.; Adams, E. Eric
2014-11-01
When a group of dense particles is released instantaneously into water, their motion has been conceptualized as a circulating particle thermal (Ruggerber 2000). However, Wen and Nacamuli (1996) observed the formation of particle clumps characterized by a narrow, fast moving core shedding particles into wakes. They observed the clump formation even for particles in the non-cohesive range as long as the source Rayleigh number was large (Ra > 1E3) or equivalently the source cloud number (Nc) was small (Nc < 3.2E2). This physical phenomenon has been investigated by Zhao et al. (2014) through physical experiments. They proposed the theoretical support for Nc dependence and categorized the formation processes into cloud formation, transitional regime and clump formation. Previous works focused mainly on the behavior of monodisperse particles. The present study further extends the experimental investigation to the formation process of bidisperse particles. Experiments are conducted in a glass tank with a water depth of 90 cm. Finite amounts of sediments with various weight proportions between coarser and finer particles are released from a cylindrical tube. The Nc being tested ranges from 6E-3 to 9.9E-2, which covers all the three formation regimes. The experimental results showed that the introduction of coarse particles promotes cloud formation and reduce the losses of finer particles into the wake. More quantitative descriptions of the effects of source conditions on the formation processes will be presented during the conference.
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Harrison, Edwin F.; Gibson, Gary G.
1987-01-01
A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.
NASA Technical Reports Server (NTRS)
Welch, Ronald M.
1993-01-01
A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.
Using polarimetry to retrieve the cloud coverage of Earth-like exoplanets
NASA Astrophysics Data System (ADS)
Rossi, L.; Stam, D. M.
2017-11-01
Context. Clouds have already been detected in exoplanetary atmospheres. They play crucial roles in a planet's atmosphere and climate and can also create ambiguities in the determination of atmospheric parameters such as trace gas mixing ratios. Knowledge of cloud properties is required when assessing the habitability of a planet. Aims: We aim to show that various types of cloud cover such as polar cusps, subsolar clouds, and patchy clouds on Earth-like exoplanets can be distinguished from each other using the polarization and flux of light that is reflected by the planet. Methods: We have computed the flux and polarization of reflected starlight for different types of (liquid water) cloud covers on Earth-like model planets using the adding-doubling method, that fully includes multiple scattering and polarization. Variations in cloud-top altitudes and planet-wide cloud cover percentages were taken into account. Results: We find that the different types of cloud cover (polar cusps, subsolar clouds, and patchy clouds) can be distinguished from each other and that the percentage of cloud cover can be estimated within 10%. Conclusions: Using our proposed observational strategy, one should be able to determine basic orbital parameters of a planet such as orbital inclination and estimate cloud coverage with reduced ambiguities from the planet's polarization signals along its orbit.
Norris, Peter M; da Silva, Arlindo M
2016-07-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.
NASA Technical Reports Server (NTRS)
Norris, Peter M.; Da Silva, Arlindo M.
2016-01-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.
Norris, Peter M.; da Silva, Arlindo M.
2018-01-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC. PMID:29618847
Cloud masking and removal in remote sensing image time series
NASA Astrophysics Data System (ADS)
Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau
2017-01-01
Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.
Ice Cloud Optical Thickness and Extinction Estimates from Radar Measurements.
NASA Astrophysics Data System (ADS)
Matrosov, Sergey Y.; Shupe, Matthew D.; Heymsfield, Andrew J.; Zuidema, Paquita
2003-11-01
A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness.
NASA Technical Reports Server (NTRS)
Gartling, D. K.; Roache, P. J.
1978-01-01
The efficiency characteristics of finite element and finite difference approximations for the steady-state solution of the Navier-Stokes equations are examined. The finite element method discussed is a standard Galerkin formulation of the incompressible, steady-state Navier-Stokes equations. The finite difference formulation uses simple centered differences that are O(delta x-squared). Operation counts indicate that a rapidly converging Newton-Raphson-Kantorovitch iteration scheme is generally preferable over a Picard method. A split NOS Picard iterative algorithm for the finite difference method was most efficient.
A comparison of the finite difference and finite element methods for heat transfer calculations
NASA Technical Reports Server (NTRS)
Emery, A. F.; Mortazavi, H. R.
1982-01-01
The finite difference method and finite element method for heat transfer calculations are compared by describing their bases and their application to some common heat transfer problems. In general it is noted that neither method is clearly superior, and in many instances, the choice is quite arbitrary and depends more upon the codes available and upon the personal preference of the analyst than upon any well defined advantages of one method. Classes of problems for which one method or the other is better suited are defined.
NASA Technical Reports Server (NTRS)
Cohen, Charles
1998-01-01
A method is developed which uses numerical tracers to make accurate diagnoses of entraimnent and detrainment rates and of the properties of the entrained and detrained air in numerically simulated clouds. The numerical advection scheme is modified to make it nondispersive, as required by the use of the tracers. Tests of the new method are made, and an appropriate definition of clouds is selected. Distributions of mixing fractions in the model consistently show maximums at the end points, for nearly undilute environmental air or nearly undilute cloud air, with a uniform distribution between. The cumulonimbus clouds simulated here entrain air that had been substantially changed by the clouds, and detrained air that is not necessarily representative of the cloud air at the same level.
Characterization of Cloud Water-Content Distribution
NASA Technical Reports Server (NTRS)
Lee, Seungwon
2010-01-01
The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.
NASA Astrophysics Data System (ADS)
Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.
2006-12-01
During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.
NASA Astrophysics Data System (ADS)
Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.
2005-05-01
During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.
NASA Astrophysics Data System (ADS)
Dong, Yumin; Xiao, Shufen; Ma, Hongyang; Chen, Libo
2016-12-01
Cloud computing and big data have become the developing engine of current information technology (IT) as a result of the rapid development of IT. However, security protection has become increasingly important for cloud computing and big data, and has become a problem that must be solved to develop cloud computing. The theft of identity authentication information remains a serious threat to the security of cloud computing. In this process, attackers intrude into cloud computing services through identity authentication information, thereby threatening the security of data from multiple perspectives. Therefore, this study proposes a model for cloud computing protection and management based on quantum authentication, introduces the principle of quantum authentication, and deduces the quantum authentication process. In theory, quantum authentication technology can be applied in cloud computing for security protection. This technology cannot be cloned; thus, it is more secure and reliable than classical methods.
NASA Astrophysics Data System (ADS)
Lai, Wencong; Khan, Abdul A.
2018-04-01
A computationally efficient hybrid finite-volume/finite-difference method is proposed for the numerical solution of Saint-Venant equations in one-dimensional open channel flows. The method adopts a mass-conservative finite volume discretization for the continuity equation and a semi-implicit finite difference discretization for the dynamic-wave momentum equation. The spatial discretization of the convective flux term in the momentum equation employs an upwind scheme and the water-surface gradient term is discretized using three different schemes. The performance of the numerical method is investigated in terms of efficiency and accuracy using various examples, including steady flow over a bump, dam-break flow over wet and dry downstream channels, wetting and drying in a parabolic bowl, and dam-break floods in laboratory physical models. Numerical solutions from the hybrid method are compared with solutions from a finite volume method along with analytic solutions or experimental measurements. Comparisons demonstrates that the hybrid method is efficient, accurate, and robust in modeling various flow scenarios, including subcritical, supercritical, and transcritical flows. In this method, the QUICK scheme for the surface slope discretization is more accurate and less diffusive than the center difference and the weighted average schemes.
Collisional Evolution of the Enceladus Neutral Cloud
NASA Technical Reports Server (NTRS)
Cassidy, T. A.; Johnson, R. E.; Hendrix, A. R.
2011-01-01
Water vapor ejected from Saturn's small moon Enceladus easily escapes its meager gravity to form a Saturn-encircling cloud with a low collision rate. Observations show that the cloud is quite broad in the radial direction, and we show here that collisions, though quite rare, may be largely responsible for this radial spreading. We modeled this cloud using the Direct Simulation Monte Carlo method, as fluid methods would be inappropriate for such a tenuous gas.
An Approach of Web-based Point Cloud Visualization without Plug-in
NASA Astrophysics Data System (ADS)
Ye, Mengxuan; Wei, Shuangfeng; Zhang, Dongmei
2016-11-01
With the advances in three-dimensional laser scanning technology, the demand for visualization of massive point cloud is increasingly urgent, but a few years ago point cloud visualization was limited to desktop-based solutions until the introduction of WebGL, several web renderers are available. This paper addressed the current issues in web-based point cloud visualization, and proposed a method of web-based point cloud visualization without plug-in. The method combines ASP.NET and WebGL technologies, using the spatial database PostgreSQL to store data and the open web technologies HTML5 and CSS3 to implement the user interface, a visualization system online for 3D point cloud is developed by Javascript with the web interactions. Finally, the method is applied to the real case. Experiment proves that the new model is of great practical value which avoids the shortcoming of the existing WebGIS solutions.
NASA Technical Reports Server (NTRS)
Robertson, Franklin R.; Roads, John; Oglesby, Robert; Marshall, Susan
2004-01-01
One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2.
Satellite-based estimation of cloud-base updrafts for convective clouds and stratocumulus
NASA Astrophysics Data System (ADS)
Zheng, Y.; Rosenfeld, D.; Li, Z.
2017-12-01
Updraft speeds of thermals have always been notoriously difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information. In this study, we introduce three methods of retrieving updraft speeds at cloud base () for convective clouds and marine stratocumulus with VIIRS onboard Suomi-NPP satellite. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The third method is for marine stratocumulus. A statistically significant relationship between Wb and cloud-top radiative cooling rate (CTRC) is found from measurements over northeastern Pacific and Atlantic. Based on this relation, satellite- and reanalysis-derived CTRC is utilized to infer the Wb of stratocumulus clouds. Evaluations against ground-based Doppler lidar measurements show estimation errors of 24%, 21% and 22% for the three methods, respectively.
Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products
NASA Technical Reports Server (NTRS)
Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny
2015-01-01
To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.
Methods for analysis of cracks in three-dimensional solids
NASA Technical Reports Server (NTRS)
Raju, I. S.; Newman, J. C., Jr.
1984-01-01
Various analytical and numerical methods used to evaluate the stress intensity factors for cracks in three-dimensional (3-D) solids are reviewed. Classical exact solutions and many of the approximate methods used in 3-D analyses of cracks are reviewed. The exact solutions for embedded elliptic cracks in infinite solids are discussed. The approximate methods reviewed are the finite element methods, the boundary integral equation (BIE) method, the mixed methods (superposition of analytical and finite element method, stress difference method, discretization-error method, alternating method, finite element-alternating method), and the line-spring model. The finite element method with singularity elements is the most widely used method. The BIE method only needs modeling of the surfaces of the solid and so is gaining popularity. The line-spring model appears to be the quickest way to obtain good estimates of the stress intensity factors. The finite element-alternating method appears to yield the most accurate solution at the minimum cost.
Consistency of aerosols above clouds characterization from A-Train active and passive measurements
NASA Astrophysics Data System (ADS)
Deaconu, Lucia T.; Waquet, Fabien; Josset, Damien; Ferlay, Nicolas; Peers, Fanny; Thieuleux, François; Ducos, Fabrice; Pascal, Nicolas; Tanré, Didier; Pelon, Jacques; Goloub, Philippe
2017-09-01
This study presents a comparison between the retrieval of optical properties of aerosol above clouds (AAC) from different techniques developed for the A-Train sensors CALIOP/CALIPSO and POLDER/PARASOL. The main objective is to analyse the consistency between the results derived from the active and the passive measurements. We compare the aerosol optical thickness (AOT) above optically thick clouds (cloud optical thickness (COT) larger than 3) and their Ångström exponent (AE). These parameters are retrieved with the CALIOP operational method, the POLDER operational polarization method and the CALIOP-based depolarization ratio method (DRM) - for which we also propose a calibrated version (denominated DRMSODA, where SODA is the Synergized Optical Depth of Aerosols). We analyse 6 months of data over three distinctive regions characterized by different types of aerosols and clouds. Additionally, for these regions, we select three case studies: a biomass-burning event over the South Atlantic Ocean, a Saharan dust case over the North Atlantic Ocean and a Siberian biomass-burning event over the North Pacific Ocean. Four and a half years of data are studied over the entire globe for distinct situations where aerosol and cloud layers are in contact or vertically separated. Overall, the regional analysis shows a good correlation between the POLDER and the DRMSODA AOTs when the microphysics of aerosols is dominated by fine-mode particles of biomass-burning aerosols from southern Africa (correlation coefficient (R2) of 0.83) or coarse-mode aerosols of Saharan dust (R2 of 0.82). A good correlation between these methods (R2 of 0.68) is also observed in the global treatment, when the aerosol and cloud layers are separated well. The analysis of detached layers also shows a mean difference in AOT of 0.07 at 532 nm between POLDER and DRMSODA at a global scale. The correlation between the retrievals decreases when a complex mixture of aerosols is expected (R2 of 0.37) - as in the East Asia region - and when the aerosol-cloud layers are in contact (R2 of 0.36). The correlation coefficient between the CALIOP operational method and POLDER is found to be low, as the CALIOP method largely underestimates the aerosol loading above clouds by a factor that ranges from 2 to 4. Potential biases on the retrieved AOT as a function of cloud properties are also investigated. For different types of scenes, the retrieval of above-cloud AOT from POLDER and from DRM are compared for different underlying cloud properties (droplet effective radius (reff) and COT retrieved with MODIS). The results reveal that DRM AOT vary with reff. When accounting for reff in the DRM algorithm, the consistency between the methods increases. The sensitivity study shows that an additional polarized signal coming from aerosols located within the cloud could affect the polarization method, which leads to an overestimation of the AOT retrieved with POLDER algorithm. In addition, the aerosols attached to or within the cloud can potentially impact the DRM retrievals through the modification of the cloud droplet chemical composition and its ability to backscatter light. The next step of this work is to combine POLDER and CALIOP to investigate the impacts of aerosols on clouds and climate when these particles are transported above or within clouds.
Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery
NASA Technical Reports Server (NTRS)
Inomata, Yasushi; Feind, R. E.; Welch, R. M.
1996-01-01
A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.
NASA Astrophysics Data System (ADS)
Boyd, O. S.; Dreger, D. S.; Gritto, R.
2015-12-01
Enhanced Geothermal Systems (EGS) resource development requires knowledge of subsurface physical parameters to quantify the evolution of fracture networks. We investigate seismicity in the vicinity of the EGS development at The Geysers Prati-32 injection well to determine moment magnitude, focal mechanism, and kinematic finite-source models with the goal of developing a rupture area scaling relationship for the Geysers and specifically for the Prati-32 EGS injection experiment. Thus far we have analyzed moment tensors of M ≥ 2 events, and are developing the capability to analyze the large numbers of events occurring as a result of the fluid injection and to push the analysis to smaller magnitude earthquakes. We have also determined finite-source models for five events ranging in magnitude from M 3.7 to 4.5. The scaling relationship between rupture area and moment magnitude of these events resembles that of a published empirical relationship derived for events from M 4.5 to 8.3. We plan to develop a scaling relationship in which moment magnitude and corner frequency are predictor variables for source rupture area constrained by the finite-source modeling. Inclusion of corner frequency in the empirical scaling relationship is proposed to account for possible variations in stress drop. If successful, we will use this relationship to extrapolate to the large numbers of events in the EGS seismicity cloud to estimate the coseismic fracture density. We will present the moment tensor and corner frequency results for the micro earthquakes, and for select events, finite-source models. Stress drop inferred from corner frequencies and from finite-source modeling will be compared.
Transient analysis of 1D inhomogeneous media by dynamic inhomogeneous finite element method
NASA Astrophysics Data System (ADS)
Yang, Zailin; Wang, Yao; Hei, Baoping
2013-12-01
The dynamic inhomogeneous finite element method is studied for use in the transient analysis of onedimensional inhomogeneous media. The general formula of the inhomogeneous consistent mass matrix is established based on the shape function. In order to research the advantages of this method, it is compared with the general finite element method. A linear bar element is chosen for the discretization tests of material parameters with two fictitious distributions. And, a numerical example is solved to observe the differences in the results between these two methods. Some characteristics of the dynamic inhomogeneous finite element method that demonstrate its advantages are obtained through comparison with the general finite element method. It is found that the method can be used to solve elastic wave motion problems with a large element scale and a large number of iteration steps.
NASA Astrophysics Data System (ADS)
Satyanarayana, M.; Radhakrishnan, S.-R.; Krishnakumar, V.; Mahadevan Pillai, V. P.; Raghunath, K.
2008-12-01
Cirrus clouds have been identified as one of the most uncertain component in the atmospheric research. It is known that cirrus clouds modulate the earth's climate through direct and indirect modification of radiation. The role of cirrus clouds depends mainly on their microphysical properties. To understand cirrus clouds better, we must observe and characterize their properties. In-situ observation of such clouds is a challenging experiment, as the clouds are located at high altitudes. Active remote sensing method based on lidar can detect high and thin cirrus clouds with good spatial and temporal resolution. We present the result obtained on the microphysical properties of the cirrus clouds at two Tropical stations namely Gadhanki, Tirupati (13.50 N, 79.20 E), India and Trivandrum (13.50 N, 770 E) Kerala, India from the ground based pulsed Nd: YAG lidar systems installed at the stations. A variant of the widely used Klett's lidar inversion method with range dependent scattering ratio is used for the present study for the retrieval of aerosol extinction and microphysical parameters of cirrus cloud.
NASA Astrophysics Data System (ADS)
Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa
2018-01-01
Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.
Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band
NASA Technical Reports Server (NTRS)
Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.
2009-01-01
Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases
NASA Astrophysics Data System (ADS)
Buldyrev, S.; Davis, A.; Marshak, A.; Stanley, H. E.
2001-12-01
Two-stream radiation transport models, as used in all current GCM parameterization schemes, are mathematically equivalent to ``standard'' diffusion theory where the physical picture is a slow propagation of the diffuse radiation by Gaussian random walks. The space/time spread (technically, the Green function) of this diffusion process is described exactly by a Gaussian distribution; from the statistical physics viewpoint, this follows from the convergence of the sum of many (rescaled) steps between scattering events with a finite variance. This Gaussian picture follows directly from first principles (the radiative transfer equation) under the assumptions of horizontal uniformity and large optical depth, i.e., there is a homogeneous plane-parallel cloud somewhere in the column. The first-order effect of 3D variability of cloudiness, the main source of scattering, is to perturb the distribution of single steps between scatterings which, modulo the ``1-g'' rescaling, can be assumed effectively isotropic. The most natural generalization of the Gaussian distribution is the 1-parameter family of symmetric Lévy-stable distributions because the sum of many zero-mean random variables with infinite variance, but finite moments of order q < α (0 < α < 2), converge to them. It has been shown on heuristic grounds that for these Lévy-based random walks the typical number of scatterings is now (1-g)τ α for transmitted light. The appearance of a non-rational exponent is why this is referred to as ``anomalous'' diffusion. Note that standard/Gaussian diffusion is retrieved in the limit α = 2-. Lévy transport theory has been successfully used in the statistical physics literature to investigate a wide variety of systems with strongly nonlinear dynamics; these applications range from random advection in turbulent fluids to the erratic behavior of financial time-series and, most recently, self-regulating ecological systems. We will briefly survey the state-of-the-art observations that offer compelling empirical support for the Lévy/anomalous diffusion model in atmospheric radiation: (1) high-resolution spectroscopy of differential absorption in the O2 A-band from ground; (2) temporal transient records of lightning strokes transmitted through clouds to a sensitive detector in space; and (3) the Gamma-distributions of optical depths derived from Landsat cloud scenes at 30-m resolution. We will then introduce a rigorous analytical formulation of Lévy/anomalous transport through finite media based on fractional derivatives and Sonin calculus. A remarkable result from this new theoretical development is an extremal property of the α = 1+ case (divergent mean-free-path), as is observed in the cloudy atmosphere. Finally, we will discuss the implications of anomalous transport theory for bulk 3D effects on the current enhanced absorption problem as well as its role as the basis of a next-generation GCM radiation parameterization.
NASA Technical Reports Server (NTRS)
Ransom, Jonathan B.
2002-01-01
A multifunctional interface method with capabilities for variable-fidelity modeling and multiple method analysis is presented. The methodology provides an effective capability by which domains with diverse idealizations can be modeled independently to exploit the advantages of one approach over another. The multifunctional method is used to couple independently discretized subdomains, and it is used to couple the finite element and the finite difference methods. The method is based on a weighted residual variational method and is presented for two-dimensional scalar-field problems. A verification test problem and a benchmark application are presented, and the computational implications are discussed.
Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations
NASA Technical Reports Server (NTRS)
Lynnes, Chris; Little, Mike; Huang, Thomas; Jacob, Joseph; Yang, Phil; Kuo, Kwo-Sen
2016-01-01
Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.
Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations
NASA Astrophysics Data System (ADS)
Lynnes, C.; Little, M. M.; Huang, T.; Jacob, J. C.; Yang, C. P.; Kuo, K. S.
2016-12-01
Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based filesystems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.
ICASE Semiannual Report, October 1, 1992 through March 31, 1993
1993-06-01
NUMERICAL MATHEMATICS Saul Abarbanel Further results have been obtained regarding long time integration of high order compact finite difference schemes...overall accuracy. These problems are common to all numerical methods: finite differences , finite elements and spectral methods. It should be noted that...fourth order finite difference scheme. * In the same case, the D6 wavelets provide a sixth order finite difference , noncompact formula. * The wavelets
A Method to Analyze How Various Parts of Clouds Influence Each Other's Brightness
NASA Technical Reports Server (NTRS)
Varnai, Tamas; Marshak, Alexander; Lau, William (Technical Monitor)
2001-01-01
This paper proposes a method for obtaining new information on 3D radiative effects that arise from horizontal radiative interactions in heterogeneous clouds. Unlike current radiative transfer models, it can not only calculate how 3D effects change radiative quantities at any given point, but can also determine which areas contribute to these 3D effects, to what degree, and through what mechanisms. After describing the proposed method, the paper illustrates its new capabilities both for detailed case studies and for the statistical processing of large datasets. Because the proposed method makes it possible, for the first time, to link a particular change in cloud properties to the resulting 3D effect, in future studies it can be used to develop new radiative transfer parameterizations that would consider 3D effects in practical applications currently limited to 1D theory-such as remote sensing of cloud properties and dynamical cloud modeling.
Methods of editing cloud and atmospheric layer affected pixels from satellite data
NASA Technical Reports Server (NTRS)
Nixon, P. R. (Principal Investigator); Wiegand, C. L.; Richardson, A. J.; Johnson, M. P.
1982-01-01
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.
Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds
NASA Astrophysics Data System (ADS)
Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.
2012-11-01
A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.
A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography
Bassiouni, Maoya; Scholl, Martha A.; Torres-Sanchez, Angel J.; Murphy, Sheila F.
2017-01-01
Quantifying the frequency, duration, and elevation range of fog or cloud immersion is essential to estimate cloud water deposition in water budgets and to understand the ecohydrology of cloud forests. The goal of this study was to develop a low-cost and high spatial-coverage method to detect occurrence of cloud immersion within a mountain cloud forest by using time-lapse photography. Trail cameras and temperature/relative humidity sensors were deployed at five sites covering the elevation range from the assumed lifting condensation level to the mountain peaks in the Luquillo Mountains of Puerto Rico. Cloud-sensitive image characteristics (contrast, the coefficient of variation and the entropy of pixel luminance, and image colorfulness) were used with a k-means clustering approach to accurately detect cloud-immersed conditions in a time series of images from March 2014 to May 2016. Images provided hydrologically meaningful cloud-immersion information while temperature-relative humidity data were used to refine the image analysis using dew point information and provided temperature gradients along the elevation transect. Validation of the image processing method with human-judgment based classification generally indicated greater than 90% accuracy. Cloud-immersion frequency averaged 80% at sites above 900 m during nighttime hours and 49% during daytime hours, and was consistent with diurnal patterns of cloud immersion measured in a previous study. Results for the 617 m site demonstrated that cloud immersion in the Luquillo Mountains rarely occurs at the previously-reported cloud base elevation of about 600 m (11% during nighttime hours and 5% during daytime hours). The framework presented in this paper will be used to monitor at a low cost and high spatial resolution the long-term variability of cloud-immersion patterns in the Luquillo Mountains, and can be applied to ecohydrology research at other cloud-forest sites or in coastal ecosystems with advective sea fog.
NASA Astrophysics Data System (ADS)
Rusli, Stephanie P.; Donovan, David P.; Russchenberg, Herman W. J.
2017-12-01
Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parameterization are used in an optimal-estimation-type framework in order to retrieve the best estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud-drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived using the three independent methods.
NASA Astrophysics Data System (ADS)
Davis, A. B.; von Allmen, P. A.; Marshak, A.; Bal, G.
2010-12-01
The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity-type model is used where the cloud surface "emits" either reflected (sunny-side) or transmitted (shady-side) light at different levels. As it turns out, the reflected/transmitted light ratio yields an approximate cloud optical thickness. Another approach is to invoke tomography techniques to define the volume occupied by the cloud using, as it were, cloud masks for each direction of observation. In the shape and opacity refinement phase, initial guesses along with solar and viewing geometry information are used to predict radiance in each pixel using a fast diffusion model for the 3D RT in MISR's non-absorbing red channel (275 m resolution). Refinement is constrained and stopped when optimal resolution is reached. Finally, multi-pixel/mono-angle MODIS data for the same cloud (at comparable 250 m resolution) reveals the desired droplet size information, hence the volume-averaged LWC. This is an ambitious remote sensing science project drawing on cross-disciplinary expertise gained in medical imaging using both X-ray and near-IR sources and detectors. It is high risk but with potentially high returns not only for the cloud modeling community but also aerosol and surface characterization in the presence of broken 3D clouds.
Ablative Thermal Response Analysis Using the Finite Element Method
NASA Technical Reports Server (NTRS)
Dec John A.; Braun, Robert D.
2009-01-01
A review of the classic techniques used to solve ablative thermal response problems is presented. The advantages and disadvantages of both the finite element and finite difference methods are described. As a first step in developing a three dimensional finite element based ablative thermal response capability, a one dimensional computer tool has been developed. The finite element method is used to discretize the governing differential equations and Galerkin's method of weighted residuals is used to derive the element equations. A code to code comparison between the current 1-D tool and the 1-D Fully Implicit Ablation and Thermal Response Program (FIAT) has been performed.
Development and Application of the p-version of the Finite Element Method.
1985-11-21
this property hierarchic families of finite elements. The h-version of the finite element method has been the subject of inten- sive study since the...early 1950’s and perhaps even earlier. Study of the p-version of the finite element method, on the other hand, began at Washington University in St...Louis in the early 1970’s and led to a more recent study of * .the h-p version. Research in the p-version (formerly called The Constraint Method) has
A method for estimating vertical distibution of the SAGE II opaque cloud frequency
NASA Technical Reports Server (NTRS)
Wang, Pi-Huan; Mccormick, M. Patrick; Minnis, Patrick; Kent, Geoffrey S.; Yue, Glenn K.; Skeens, Kristi M.
1995-01-01
A method is developed to infer the vertical distribution of the occurrence frequency of clouds that are opaque to the Stratospheric Aerosol and Gas Experiment (SAGE) II instrument. An application of the method to the 1986 SAGE II observations is included in this paper. The 1986 SAGE II results are compared with the 1952-1981 cloud climatology of Warren et al. (1986, 1988)
Application of the Finite Element Method to Rotary Wing Aeroelasticity
NASA Technical Reports Server (NTRS)
Straub, F. K.; Friedmann, P. P.
1982-01-01
A finite element method for the spatial discretization of the dynamic equations of equilibrium governing rotary-wing aeroelastic problems is presented. Formulation of the finite element equations is based on weighted Galerkin residuals. This Galerkin finite element method reduces algebraic manipulative labor significantly, when compared to the application of the global Galerkin method in similar problems. The coupled flap-lag aeroelastic stability boundaries of hingeless helicopter rotor blades in hover are calculated. The linearized dynamic equations are reduced to the standard eigenvalue problem from which the aeroelastic stability boundaries are obtained. The convergence properties of the Galerkin finite element method are studied numerically by refining the discretization process. Results indicate that four or five elements suffice to capture the dynamics of the blade with the same accuracy as the global Galerkin method.
NASA Astrophysics Data System (ADS)
Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.
2007-06-01
This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.
Improved finite-element methods for rotorcraft structures
NASA Technical Reports Server (NTRS)
Hinnant, Howard E.
1991-01-01
An overview of the research directed at improving finite-element methods for rotorcraft airframes is presented. The development of a modification to the finite element method which eliminates interelement discontinuities is covered. The following subject areas are discussed: geometric entities, interelement continuity, dependent rotational degrees of freedom, and adaptive numerical integration. This new methodology is being implemented as an anisotropic, curvilinear, p-version, beam, shell, and brick finite element program.
Using Finite Element Method to Estimate the Material Properties of a Bearing Cage
2018-02-01
UNCLASSIFIED UNCLASSIFIED AD-E403 988 Technical Report ARMET-TR-17035 USING FINITE ELEMENT METHOD TO ESTIMATE THE MATERIAL...TITLE AND SUBTITLE USING FINITE ELEMENT METHOD TO ESTIMATE THE MATERIAL PROPERTIES OF A BEARING CAGE 5a. CONTRACT NUMBER 5b. GRANT...specifications of non-metallic bearing cages are typically not supplied by the manufacturer. In order to setup a finite element analysis of a
Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands
NASA Technical Reports Server (NTRS)
Kuze, Akihiko; Chance, Kelly V.
1994-01-01
Cloud height and cloud coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect cloud top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between cloud top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or cloud top height to high accuracy using FASCODE 3. Cloud top height and a cloud coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of cloud top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between cloud top height and fractional coverage. Using the above-mentioned method, an operational cloud detection algorithm which uses minimal computation time can be implemented.
Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results
NASA Astrophysics Data System (ADS)
Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.
2016-03-01
Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not observed in limb geometry. Co-located cloud top height measurements of the limb-viewing Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT are compared for the period from January 2008 to March 2012. The global CTH agreement of about 1 km is observed, which is smaller than the vertical field of view of both instruments. Lower stratospheric aerosols from volcanic eruptions occasionally interfere with the cloud retrieval and inhibit the detection of tropospheric clouds. The aerosol impact on cloud retrievals was studied for the volcanoes Kasatochi (August 2008), Sarychev Peak (June 2009), and Nabro (June 2011). Long-lasting aerosol scattering is detected after these events in the Northern Hemisphere for heights above 12.5 km in tropical and polar latitudes. Aerosol top heights up to about 22 km are found in 2009 and the enhanced lower stratospheric aerosol layer persisted for about 7 months. In August 2009 about 82 % of the lower stratosphere between 30 and 70° N was filled with scattering particles and nearly 50 % in October 2008.
Finite difference and Runge-Kutta methods for solving vibration problems
NASA Astrophysics Data System (ADS)
Lintang Renganis Radityani, Scolastika; Mungkasi, Sudi
2017-11-01
The vibration of a storey building can be modelled into a system of second order ordinary differential equations. If the number of floors of a building is large, then the result is a large scale system of second order ordinary differential equations. The large scale system is difficult to solve, and if it can be solved, the solution may not be accurate. Therefore, in this paper, we seek for accurate methods for solving vibration problems. We compare the performance of numerical finite difference and Runge-Kutta methods for solving large scale systems of second order ordinary differential equations. The finite difference methods include the forward and central differences. The Runge-Kutta methods include the Euler and Heun methods. Our research results show that the central finite difference and the Heun methods produce more accurate solutions than the forward finite difference and the Euler methods do.
NASA Astrophysics Data System (ADS)
Herman, J. R.; Boccara, M.; Albers, S. C.
2017-12-01
The Earth Polychromatic Imaging Camera (EPIC) onboard the DSCOVR satellite continuously views the sun-illuminated portion of the Earth with spectral coverage in the visible band, among others. Ideally, such a system would be able to provide a video with continuous coverage up to real time. However due to limits in onboard storage, bandwidth, and antenna coverage on the ground, we can receive at most 20 images a day, separated by at least one hour. Also, the processing time to generate the visible image out of the separate RGB channels delays public images delivery by a day or two. Finally, occasional remote tuning of instruments can cause several day periods where the imagery is completely missing. We are proposing a model-based method to fill these gaps and restore images lost in real-time processing. We are combining two sets of algorithms. The first, called Blueturn, interpolates successive images while projecting them on a 3-D model of the Earth, all this being done in real-time using the GPU. The second, called Simulated Weather Imagery (SWIM), makes EPIC-like images utilizing a ray-tracing model of scattering and absorption of sunlight by clouds, atmospheric gases, aerosols, and land surface. Clouds are obtained from 3-D gridded analyses and forecasts using weather modeling systems such as the Local Analysis and Prediction System (LAPS), and the Flow-following finite-volume Finite Icosahedral Model (FIM). SWIM uses EPIC images to validate its models. Typical model grid spacing is about 20km and is roughly commensurate with the EPIC imagery. Calculating one image per hour is enough for Blueturn to generate a smooth video. The synthetic images are designed to be visually realistic and aspire to be indistinguishable from the real ones. Resulting interframe transitions become seamless, and real-time delay is reduced to 1 hour. With Blueturn already available as a free online app, streaming EPIC images directly from NASA's public website, and with another SWIM server to ensure constant interval between key images, this work brings transcendance to EPIC's tribute. Enriched by two years of actual service in space, the most real holistic view of the Earth will be continued at a high degree of fidelity, regardless of EPIC limitations or interruptions.
NASA Technical Reports Server (NTRS)
Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.;
2011-01-01
Different methods for retrieving atmospheric profiles in the presence of clouds from hyperspectral satellite remote sensing data will be described. We will present results from the JPSS cloud-clearing algorithm and NASA Langley cloud retrieval algorithm.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Fei; Zhen, Zhao; Liu, Chun
Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method throughmore » the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.« less
Wang, Fei; Zhen, Zhao; Liu, Chun; ...
2017-12-18
Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method throughmore » the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.« less
Establishing the 3-D finite element solid model of femurs in partial by volume rendering.
Zhang, Yinwang; Zhong, Wuxue; Zhu, Haibo; Chen, Yun; Xu, Lingjun; Zhu, Jianmin
2013-01-01
It remains rare to report three-dimensional (3-D) finite element solid model of femurs in partial by volume rendering method, though several methods of femoral 3-D finite element modeling are already available. We aim to analyze the advantages of the modeling method by establishing the 3-D finite element solid model of femurs in partial by volume rendering. A 3-D finite element model of the normal human femurs, made up of three anatomic structures: cortical bone, cancellous bone and pulp cavity, was constructed followed by pretreatment of the CT original image. Moreover, the finite-element analysis was carried on different material properties, three types of materials given for cortical bone, six assigned for cancellous bone, and single for pulp cavity. The established 3-D finite element of femurs contains three anatomical structures: cortical bone, cancellous bone, and pulp cavity. The compressive stress primarily concentrated in the medial surfaces of femur, especially in the calcar femorale. Compared with whole modeling by volume rendering method, the 3-D finite element solid model created in partial is more real and fit for finite element analysis. Copyright © 2013 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kollias, Pavlos
2016-09-06
This the final report for the DE-SC0007096 - Advancing Clouds Lifecycle Representation in Numerical Models Using Innovative Analysis Methods that Bridge ARM Observations and Models Over a Breadth of Scales - PI: Pavlos Kollias. The final report outline the main findings of the research conducted using the aforementioned award in the area of cloud research from the cloud scale (10-100 m) to the mesoscale (20-50 km).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Jinqiang; Li, Jun; Xia, Xiangao
In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less
Zhang, Jinqiang; Li, Jun; Xia, Xiangao; ...
2016-11-28
In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less
NASA Astrophysics Data System (ADS)
Marín, M. J.; Serrano, D.; Utrillas, M. P.; Núñez, M.; Martínez-Lozano, J. A.
2017-10-01
Partly cloudy skies with liquid water clouds have been analysed, founding that it is essential to distinguish data if the Sun is obstructed or not by clouds. Both cases can be separated considering simultaneously the Cloud Modification Factor (CMF) and the clearness index (kt). For partly cloudy skies and the Sun obstructed the effective cloud optical depth (τ) has been obtained by the minimization method for overcast skies. This method was previously developed by the authors but, in this case, taking into account partial cloud cover. This study has been conducted for the years 2011-2015 with the multiple scattering model SBDART and irradiance measurements for the UV Erythemal Radiation (UVER) and the broadband ranges. Afterwards a statistical analysis of τ has shown that the maximum value is much lower than for overcast skies and there is more discrepancy between the two spectral ranges regarding the results for overcast skies. In order to validate these results the effective cloud optical depth has been correlated with several transmission factors, giving similar fit parameters to those obtained for overcast skies except for the clearness index in the UVER range. As our method is not applicable for partly cloudy skies with the visible Sun, the enhancement of radiation caused by clouds when the Sun is visible has been studied. Results show that the average enhancement CMF values are the same for both ranges although enhancement is more frequent for low cloud cover in the UVER and medium-high cloud cover in the broadband range and it does not depend on the solar zenith angle.
Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements
NASA Astrophysics Data System (ADS)
Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian
2018-02-01
Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.
A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL
NASA Technical Reports Server (NTRS)
Pfister, Leonhard; Ueyama, Rei; Jensen, Eric; Schoeberl, Mark
2017-01-01
Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.
NASA Technical Reports Server (NTRS)
Chen, Zhangxin; Ewing, Richard E.
1996-01-01
Multigrid algorithms for nonconforming and mixed finite element methods for second order elliptic problems on triangular and rectangular finite elements are considered. The construction of several coarse-to-fine intergrid transfer operators for nonconforming multigrid algorithms is discussed. The equivalence between the nonconforming and mixed finite element methods with and without projection of the coefficient of the differential problems into finite element spaces is described.
Vectorial finite elements for solving the radiative transfer equation
NASA Astrophysics Data System (ADS)
Badri, M. A.; Jolivet, P.; Rousseau, B.; Le Corre, S.; Digonnet, H.; Favennec, Y.
2018-06-01
The discrete ordinate method coupled with the finite element method is often used for the spatio-angular discretization of the radiative transfer equation. In this paper we attempt to improve upon such a discretization technique. Instead of using standard finite elements, we reformulate the radiative transfer equation using vectorial finite elements. In comparison to standard finite elements, this reformulation yields faster timings for the linear system assemblies, as well as for the solution phase when using scattering media. The proposed vectorial finite element discretization for solving the radiative transfer equation is cross-validated against a benchmark problem available in literature. In addition, we have used the method of manufactured solutions to verify the order of accuracy for our discretization technique within different absorbing, scattering, and emitting media. For solving large problems of radiation on parallel computers, the vectorial finite element method is parallelized using domain decomposition. The proposed domain decomposition method scales on large number of processes, and its performance is unaffected by the changes in optical thickness of the medium. Our parallel solver is used to solve a large scale radiative transfer problem of the Kelvin-cell radiation.
NASA Astrophysics Data System (ADS)
Astionenko, I. O.; Litvinenko, O. I.; Osipova, N. V.; Tuluchenko, G. Ya.; Khomchenko, A. N.
2016-10-01
Recently the interpolation bases of the hierarchical type have been used for the problem solving of the approximation of multiple arguments functions (such as in the finite-element method). In this work the cognitive graphical method of constructing of the hierarchical form bases on the serendipity finite elements is suggested, which allowed to get the alternative bases on a biquadratic finite element from the serendipity family without internal knots' inclusion. The cognitive-graphic method allowed to improve the known interpolation procedure of Taylor and to get the modified elements with irregular arrangement of knots. The proposed procedures are universal and are spread in the area of finite-elements.
NASA Astrophysics Data System (ADS)
Okamura, Rintaro; Iwabuchi, Hironobu; Schmidt, K. Sebastian
2017-12-01
Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.
NASA Technical Reports Server (NTRS)
Minnis, P.; Harrison, E. F.
1984-01-01
Cloud cover is one of the most important variables affecting the earth radiation budget (ERB) and, ultimately, the global climate. The present investigation is concerned with several aspects of the effects of extended cloudiness, taking into account hourly visible and infrared data from the Geostationary Operational Environmental Satelite (GOES). A methodology called the hybrid bispectral threshold method is developed to extract regional cloud amounts at three levels in the atmosphere, effective cloud-top temperatures, clear-sky temperature and cloud and clear-sky visible reflectance characteristics from GOES data. The diurnal variations are examined in low, middle, high, and total cloudiness determined with this methodology for November 1978. The bulk, broadband radiative properties of the resultant cloud and clear-sky data are estimated to determine the possible effect of the diurnal variability of regional cloudiness on the interpretation of ERB measurements.
A total variation diminishing finite difference algorithm for sonic boom propagation models
NASA Technical Reports Server (NTRS)
Sparrow, Victor W.
1993-01-01
It is difficult to accurately model the rise phases of sonic boom waveforms with traditional finite difference algorithms because of finite difference phase dispersion. This paper introduces the concept of a total variation diminishing (TVD) finite difference method as a tool for accurately modeling the rise phases of sonic booms. A standard second order finite difference algorithm and its TVD modified counterpart are both applied to the one-way propagation of a square pulse. The TVD method clearly outperforms the non-TVD method, showing great potential as a new computational tool in the analysis of sonic boom propagation.
Pattern recognition of satellite cloud imagery for improved weather prediction
NASA Technical Reports Server (NTRS)
Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.
1986-01-01
The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.
NASA Technical Reports Server (NTRS)
Platnick, S.; Wind, G.
2004-01-01
In order to perform satellite retrievals of cloud properties, it is important to account for the effect of the above-cloud atmosphere on the observations. The solar bands used in the operational MODIS Terra and Aqua cloud optical and microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser extent by well-mixed gases. For water vapor, the above-cloud column amount, or precipitable water, provides adequate information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level of correction required. Cloud-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases, cloud-top pressure is also required for estimates of above-cloud abundances. We present a method for obtaining above-cloud precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an iterative procedure for establishing cloud-top temperature and pressure, and is useful for both single layer water and ice clouds. Knowledge of cloud thermodynamic phase is fundamental in retrieving cloud optical and microphysical properties. However, in cases of optically thin cirrus overlapping lower water clouds, the concept of a single unique phase is ill- defined and depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase cloud detection which uses above-cloud precipitable water retrievals along with several existing MODIS operational cloud products (cloud-top pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative signature in the MODIS solar bands is primarily that of a water cloud with ice cloud contamination, or visa-versa. Examples in polar and mid-latitude regions will be shown.
The least-squares finite element method for low-mach-number compressible viscous flows
NASA Technical Reports Server (NTRS)
Yu, Sheng-Tao
1994-01-01
The present paper reports the development of the Least-Squares Finite Element Method (LSFEM) for simulating compressible viscous flows at low Mach numbers in which the incompressible flows pose as an extreme. Conventional approach requires special treatments for low-speed flows calculations: finite difference and finite volume methods are based on the use of the staggered grid or the preconditioning technique; and, finite element methods rely on the mixed method and the operator-splitting method. In this paper, however, we show that such difficulty does not exist for the LSFEM and no special treatment is needed. The LSFEM always leads to a symmetric, positive-definite matrix through which the compressible flow equations can be effectively solved. Two numerical examples are included to demonstrate the method: first, driven cavity flows at various Reynolds numbers; and, buoyancy-driven flows with significant density variation. Both examples are calculated by using full compressible flow equations.
A class of hybrid finite element methods for electromagnetics: A review
NASA Technical Reports Server (NTRS)
Volakis, J. L.; Chatterjee, A.; Gong, J.
1993-01-01
Integral equation methods have generally been the workhorse for antenna and scattering computations. In the case of antennas, they continue to be the prominent computational approach, but for scattering applications the requirement for large-scale computations has turned researchers' attention to near neighbor methods such as the finite element method, which has low O(N) storage requirements and is readily adaptable in modeling complex geometrical features and material inhomogeneities. In this paper, we review three hybrid finite element methods for simulating composite scatterers, conformal microstrip antennas, and finite periodic arrays. Specifically, we discuss the finite element method and its application to electromagnetic problems when combined with the boundary integral, absorbing boundary conditions, and artificial absorbers for terminating the mesh. Particular attention is given to large-scale simulations, methods, and solvers for achieving low memory requirements and code performance on parallel computing architectures.
Numerical Methods for 2-Dimensional Modeling
1980-12-01
high-order finite element methods, and a multidimensional version of the method of lines, both utilizing an optimized stiff integrator for the time...integration. The finite element methods have proved disappointing, but the method of lines has provided an unexpectedly large gain in speed. Two...diffusion problems with the same number of unknowns (a 21 x 41 grid), solved by second-order finite element methods, took over seven minutes on the Cray-i
Computer-Aided Engineering of Semiconductor Integrated Circuits
1979-07-01
equation using a five point finite difference approximation. Section 4.3.6 describes the numerical techniques and iterative algorithms which are used...neighbor points. This is generally referred to as a five point finite difference scheme on a rectangular grid, as described below. The finite difference ...problems in steady state have been analyzed by the finite difference method [4. 16 ] [4.17 3 or finite element method [4. 18 3, [4. 19 3 as reported last
NASA Astrophysics Data System (ADS)
Peers, F.; Haywood, J. M.; Francis, P. N.; Meyer, K.; Platnick, S. E.
2017-12-01
Over the South East Atlantic Ocean, biomass burning aerosols from Southern Africa are frequently observed above clouds during fire season. However, the quantification of their interactions with both radiations and clouds remains uncertain because of a lack of information on aerosol properties and on their interaction process. In the last decade, methods have been developed to retrieve aerosol optical properties above clouds from satellite measurements, especially over the South East Atlantic Ocean. Most of these methods have been applied to polar orbiting instruments which prevent the analysis of aerosols and clouds at a sub-daily scale. With its wide spatial coverage and its high temporal resolution, the geostationary instrument SEVIRI, on board the MSG platform, offers a unique opportunity to monitor aerosols in this region and to evaluate their impact on clouds and their radiative effects. In this study, we will investigate the possibility of retrieving simultaneously aerosol and cloud properties (i.e. aerosol and cloud optical thicknesses and cloud droplet effective radius) when aerosols are located above clouds. The retrieved properties will then be compared with the ones obtained from MODIS [Meyer et al., 2015] as well as observations from the CLARIFY-2017 field campaign.
Huang, Chih-Hsu; Lin, Chou-Ching K; Ju, Ming-Shaung
2015-02-01
Compared with the Monte Carlo method, the population density method is efficient for modeling collective dynamics of neuronal populations in human brain. In this method, a population density function describes the probabilistic distribution of states of all neurons in the population and it is governed by a hyperbolic partial differential equation. In the past, the problem was mainly solved by using the finite difference method. In a previous study, a continuous Galerkin finite element method was found better than the finite difference method for solving the hyperbolic partial differential equation; however, the population density function often has discontinuity and both methods suffer from a numerical stability problem. The goal of this study is to improve the numerical stability of the solution using discontinuous Galerkin finite element method. To test the performance of the new approach, interaction of a population of cortical pyramidal neurons and a population of thalamic neurons was simulated. The numerical results showed good agreement between results of discontinuous Galerkin finite element and Monte Carlo methods. The convergence and accuracy of the solutions are excellent. The numerical stability problem could be resolved using the discontinuous Galerkin finite element method which has total-variation-diminishing property. The efficient approach will be employed to simulate the electroencephalogram or dynamics of thalamocortical network which involves three populations, namely, thalamic reticular neurons, thalamocortical neurons and cortical pyramidal neurons. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Putman, W. M.; Suarez, M.
2009-12-01
The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.
Big data mining analysis method based on cloud computing
NASA Astrophysics Data System (ADS)
Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao
2017-08-01
Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.
Ground-based remote sensing scheme for monitoring aerosol–cloud interactions
Sarna, Karolina; Russchenberg, Herman W. J.
2016-03-14
A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius ( r e) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m -2 wide. For every LWP bin we present the correlation coefficient between ln r e and ln ATB, as well as ACI r (defined as ACI r = -d ln r e d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACI r are in the range 0.01–0.1. In conclusion, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less
High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.
Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter
2016-12-30
Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.
High-Precision Registration of Point Clouds Based on Sphere Feature Constraints
Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter
2016-01-01
Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. PMID:28042846
Yang, Xiaomei; Zhou, Chenghu; Li, Zhi
2017-01-01
Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features. PMID:28914787
Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi
2017-09-15
Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.
An Error Analysis for the Finite Element Method Applied to Convection Diffusion Problems.
1981-03-01
D TFhG-]NOLOGY k 4b 00 \\" ) ’b Technical Note BN-962 AN ERROR ANALYSIS FOR THE FINITE ELEMENT METHOD APPLIED TO CONVECTION DIFFUSION PROBLEM by I...Babu~ka and W. G. Szym’czak March 1981 V.. UNVI I Of- ’i -S AN ERROR ANALYSIS FOR THE FINITE ELEMENT METHOD P. - 0 w APPLIED TO CONVECTION DIFFUSION ...AOAO98 895 MARYLAND UNIVYCOLLEGE PARK INST FOR PHYSICAL SCIENCE--ETC F/G 12/I AN ERROR ANALYIS FOR THE FINITE ELEMENT METHOD APPLIED TO CONV..ETC (U
Global finite-time attitude consensus tracking control for a group of rigid spacecraft
NASA Astrophysics Data System (ADS)
Li, Penghua
2017-10-01
The problem of finite-time attitude consensus for multiple rigid spacecraft with a leader-follower architecture is investigated in this paper. To achieve the finite-time attitude consensus, at the first step, a distributed finite-time convergent observer is proposed for each follower to estimate the leader's attitude in a finite time. Then based on the terminal sliding mode control method, a new finite-time attitude tracking controller is designed such that the leader's attitude can be tracked in a finite time. Finally, a finite-time observer-based distributed control strategy is proposed. It is shown that the attitude consensus can be achieved in a finite time under the proposed controller. Simulation results are given to show the effectiveness of the proposed method.
Use of system identification techniques for improving airframe finite element models using test data
NASA Technical Reports Server (NTRS)
Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.
1991-01-01
A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.
Radiation Heat Transfer Between Diffuse-Gray Surfaces Using Higher Order Finite Elements
NASA Technical Reports Server (NTRS)
Gould, Dana C.
2000-01-01
This paper presents recent work on developing methods for analyzing radiation heat transfer between diffuse-gray surfaces using p-version finite elements. The work was motivated by a thermal analysis of a High Speed Civil Transport (HSCT) wing structure which showed the importance of radiation heat transfer throughout the structure. The analysis also showed that refining the finite element mesh to accurately capture the temperature distribution on the internal structure led to very large meshes with unacceptably long execution times. Traditional methods for calculating surface-to-surface radiation are based on assumptions that are not appropriate for p-version finite elements. Two methods for determining internal radiation heat transfer are developed for one and two-dimensional p-version finite elements. In the first method, higher-order elements are divided into a number of sub-elements. Traditional methods are used to determine radiation heat flux along each sub-element and then mapped back to the parent element. In the second method, the radiation heat transfer equations are numerically integrated over the higher-order element. Comparisons with analytical solutions show that the integration scheme is generally more accurate than the sub-element method. Comparison to results from traditional finite elements shows that significant reduction in the number of elements in the mesh is possible using higher-order (p-version) finite elements.
Optical properties of aerosol contaminated cloud derived from MODIS instrument
NASA Astrophysics Data System (ADS)
Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.
2016-04-01
The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.
Infinite Possibilities for the Finite Element.
ERIC Educational Resources Information Center
Finlayson, Bruce A.
1981-01-01
Describes the uses of finite element methods in solving problems of heat transfer, fluid flow, etc. Suggests that engineers should know the general concepts and be able to apply the principles of finite element methods. (Author/WB)
Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods
NASA Technical Reports Server (NTRS)
Lin, Bing; Rossow, William B.
1994-01-01
Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.
Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.
Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki
2014-11-01
Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.
Moisture Transport in Composites during Repair Work,
1983-09-01
4 * FINITE DIFFERENCE EQUATIONS. .. . . .. . .. .. .. .. .. 6 INI I A ANBOUNAAYYCONDITIONS................ 7 REASONABLE FIRST...DURING DRYING AND CURING . . . ........ 9 5 CONVERGENCE OF FINITE DIFFERENCE METHOD USING DIFFERENT At . . .. 12 6 CONVERGENCE OF FDA METHOD FOR SAME At...transport we will use a finite difference approach, changing the Fickian equation to a finite number of linear algebraic equations that can be solved by
NASA Technical Reports Server (NTRS)
Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.
2013-01-01
The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.
Semi-automatic sparse preconditioners for high-order finite element methods on non-uniform meshes
NASA Astrophysics Data System (ADS)
Austin, Travis M.; Brezina, Marian; Jamroz, Ben; Jhurani, Chetan; Manteuffel, Thomas A.; Ruge, John
2012-05-01
High-order finite elements often have a higher accuracy per degree of freedom than the classical low-order finite elements. However, in the context of implicit time-stepping methods, high-order finite elements present challenges to the construction of efficient simulations due to the high cost of inverting the denser finite element matrix. There are many cases where simulations are limited by the memory required to store the matrix and/or the algorithmic components of the linear solver. We are particularly interested in preconditioned Krylov methods for linear systems generated by discretization of elliptic partial differential equations with high-order finite elements. Using a preconditioner like Algebraic Multigrid can be costly in terms of memory due to the need to store matrix information at the various levels. We present a novel method for defining a preconditioner for systems generated by high-order finite elements that is based on a much sparser system than the original high-order finite element system. We investigate the performance for non-uniform meshes on a cube and a cubed sphere mesh, showing that the sparser preconditioner is more efficient and uses significantly less memory. Finally, we explore new methods to construct the sparse preconditioner and examine their effectiveness for non-uniform meshes. We compare results to a direct use of Algebraic Multigrid as a preconditioner and to a two-level additive Schwarz method.
Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei
2011-04-01
An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.
Optimal Compressed Sensing and Reconstruction of Unstructured Mesh Datasets
Salloum, Maher; Fabian, Nathan D.; Hensinger, David M.; ...
2017-08-09
Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate itsmore » usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Finally, our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bacvarov, D.C.
1981-01-01
A new method for probabilistic risk assessment of transmission line insulation flashovers caused by lightning strokes is presented. The utilized approach of applying the finite element method for probabilistic risk assessment is demonstrated to be very powerful. The reasons for this are two. First, the finite element method is inherently suitable for analysis of three dimensional spaces where the parameters, such as three variate probability densities of the lightning currents, are non-uniformly distributed. Second, the finite element method permits non-uniform discretization of the three dimensional probability spaces thus yielding high accuracy in critical regions, such as the area of themore » low probability events, while at the same time maintaining coarse discretization in the non-critical areas to keep the number of grid points and the size of the problem to a manageable low level. The finite element probabilistic risk assessment method presented here is based on a new multidimensional search algorithm. It utilizes an efficient iterative technique for finite element interpolation of the transmission line insulation flashover criteria computed with an electro-magnetic transients program. Compared to other available methods the new finite element probabilistic risk assessment method is significantly more accurate and approximately two orders of magnitude computationally more efficient. The method is especially suited for accurate assessment of rare, very low probability events.« less
NASA Technical Reports Server (NTRS)
Lacis, A. A.; Wang, W. C.; Hansen, J. E.
1979-01-01
A radiative transfer method appropriate for use in simple climate models and three dimensional global climate models was developed. It is fully interactive with climate changes, such as in the temperature-pressure profile, cloud distribution, and atmospheric composition, and it is accurate throughout the troposphere and stratosphere. The vertical inhomogeneity of the atmosphere is accounted for by assuming a correlation of gaseous k-distributions of different pressures and temperatures. Line-by-line calculations are made to demonstrate that The method is remarkably accurate. The method is then used in a one-dimensional radiative-convective climate model to study the effect of cirrus clouds on surface temperature. It is shown that an increase in cirrus cloud cover can cause a significant warming of the troposphere and the Earth's surface, by the mechanism of an enhanced green-house effect. The dependence of this phenomenon on cloud optical thickness, altitude, and latitude is investigated.
Laaksonen, Ari; Malila, Jussi; Nenes, Athanasios; Hung, Hui-Ming; Chen, Jen-Ping
2016-05-03
Surface porosity affects the ability of a substance to adsorb gases. The surface fractal dimension D is a measure that indicates the amount that a surface fills a space, and can thereby be used to characterize the surface porosity. Here we propose a new method for determining D, based on measuring both the water vapour adsorption isotherm of a given substance, and its ability to act as a cloud condensation nucleus when introduced to humidified air in aerosol form. We show that our method agrees well with previous methods based on measurement of nitrogen adsorption. Besides proving the usefulness of the new method for general surface characterization of materials, our results show that the surface fractal dimension is an important determinant in cloud drop formation on water insoluble particles. We suggest that a closure can be obtained between experimental critical supersaturation for cloud drop activation and that calculated based on water adsorption data, if the latter is corrected using the surface fractal dimension of the insoluble cloud nucleus.
NASA Astrophysics Data System (ADS)
Laaksonen, Ari; Malila, Jussi; Nenes, Athanasios; Hung, Hui-Ming; Chen, Jen-Ping
2016-05-01
Surface porosity affects the ability of a substance to adsorb gases. The surface fractal dimension D is a measure that indicates the amount that a surface fills a space, and can thereby be used to characterize the surface porosity. Here we propose a new method for determining D, based on measuring both the water vapour adsorption isotherm of a given substance, and its ability to act as a cloud condensation nucleus when introduced to humidified air in aerosol form. We show that our method agrees well with previous methods based on measurement of nitrogen adsorption. Besides proving the usefulness of the new method for general surface characterization of materials, our results show that the surface fractal dimension is an important determinant in cloud drop formation on water insoluble particles. We suggest that a closure can be obtained between experimental critical supersaturation for cloud drop activation and that calculated based on water adsorption data, if the latter is corrected using the surface fractal dimension of the insoluble cloud nucleus.
The use of Galerkin finite-element methods to solve mass-transport equations
Grove, David B.
1977-01-01
The partial differential equation that describes the transport and reaction of chemical solutes in porous media was solved using the Galerkin finite-element technique. These finite elements were superimposed over finite-difference cells used to solve the flow equation. Both convection and flow due to hydraulic dispersion were considered. Linear and Hermite cubic approximations (basis functions) provided satisfactory results: however, the linear functions were computationally more efficient for two-dimensional problems. Successive over relaxation (SOR) and iteration techniques using Tchebyschef polynomials were used to solve the sparce matrices generated using the linear and Hermite cubic functions, respectively. Comparisons of the finite-element methods to the finite-difference methods, and to analytical results, indicated that a high degree of accuracy may be obtained using the method outlined. The technique was applied to a field problem involving an aquifer contaminated with chloride, tritium, and strontium-90. (Woodard-USGS)
The effect of cloud screening on MAX-DOAS aerosol retrievals.
NASA Astrophysics Data System (ADS)
Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim
2014-05-01
In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.
Providing Access and Visualization to Global Cloud Properties from GEO Satellites
NASA Astrophysics Data System (ADS)
Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.; Ayers, J. K.
2015-12-01
Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition. This project builds upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider. Using the Open Geospatial Consortium's Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also "merged" datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.
NASA Technical Reports Server (NTRS)
Chiu, J. C.; Marshak, A.; Huang, C.-H.; Varnai, T.; Hogan, R. J.; Giles, D. M.; Holben, B. N.; Knyazikhin, Y.; O'Connor, E. J.; Wiscombe, W. J.
2012-01-01
The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less
NASA Astrophysics Data System (ADS)
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; Turner, David D.; Eloranta, Edwin W.
2017-06-01
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; ...
2017-06-09
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less
Properties of CIRRUS Overlapping Clouds as Deduced from the GOES-12 Imagery Data
NASA Technical Reports Server (NTRS)
Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny; Khaiyer, Mandana
2006-01-01
Understanding the impact of cirrus clouds on modifying both the solar reflected and terrestrial emitted radiations is crucial for climate studies. Unlike most boundary layer stratus and stratocumulus clouds that have a net cooling effect on the climate, high-level thin cirrus clouds can have a warming effect on our climate. Many research efforts have been devoted to retrieving cirrus cloud properties due to their ubiquitous presence. However, using satellite observations to detect and/or retrieve cirrus cloud properties faces two major challenges. First, they are often semitransparent at visible to infrared wavelengths; and secondly, they often occur over a lower cloud system. The overlapping of high-level cirrus and low-level stratus cloud poses a difficulty in determining the individual cloud top altitudes and optical properties, especially when the signals from cirrus clouds are overwhelmed by the signals of stratus clouds. Moreover, the operational satellite retrieval algorithms, which often assume only single layer cloud in the development of cloud retrieval techniques, cannot resolve the cloud overlapping situation properly. The new geostationary satellites, starting with the Twelfth Geostationary Operational Environmental Satellite (GOES-12), are providing a new suite of imager bands that have replaced the conventional 12-micron channel with a 13.3-micron CO2 absorption channel. The replacement of the 13.3-micron channel allows for the application of a CO2-slicing retrieval technique (Chahine et al. 1974; Smith and Platt 1978), which is one of the important passive satellite methods for remote sensing the altitudes of mid to high-level clouds. Using the CO2- slicing technique is more effective in detecting semitransparent cirrus clouds than using the conventional infrared-window method.
Correlation buildup during recrystallization in three-dimensional dusty plasma clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schella, André; Mulsow, Matthias; Melzer, André
2014-05-15
The recrystallization process of finite three-dimensional dust clouds after laser heating is studied experimentally. The time-dependent Coulomb coupling parameter is presented, showing that the recrystallization starts with an exponential cooling phase where cooling is slower than damping by the neutral gas friction. At later times, the coupling parameter oscillates into equilibrium. It is found that a large fraction of cluster states after recrystallization experiments is in metastable states. The temporal evolution of the correlation buildup shows that correlation occurs on even slower time scale than cooling.
Incompressible flow simulations on regularized moving meshfree grids
NASA Astrophysics Data System (ADS)
Vasyliv, Yaroslav; Alexeev, Alexander
2017-11-01
A moving grid meshfree solver for incompressible flows is presented. To solve for the flow field, a semi-implicit approximate projection method is directly discretized on meshfree grids using General Finite Differences (GFD) with sharp interface stencil modifications. To maintain a regular grid, an explicit shift is used to relax compressed pseudosprings connecting a star node to its cloud of neighbors. The following test cases are used for validation: the Taylor-Green vortex decay, the analytic and modified lid-driven cavities, and an oscillating cylinder enclosed in a container for a range of Reynolds number values. We demonstrate that 1) the grid regularization does not impede the second order spatial convergence rate, 2) the Courant condition can be used for time marching but the projection splitting error reduces the convergence rate to first order, and 3) moving boundaries and arbitrary grid distortions can readily be handled. Financial support provided by the National Science Foundation (NSF) Graduate Research Fellowship, Grant No. DGE-1148903.
NASA Technical Reports Server (NTRS)
Papadakis, M.; Breer, M.; Craig, N.; Liu, X.
1994-01-01
An experimental method has been developed to determine the water droplet impingement characteristics on two- and three-dimensional aircraft surfaces. The experimental water droplet impingement data are used to validate particle trajectory analysis codes that are used in aircraft icing analyses and engine inlet particle separator analyses. The aircraft surface is covered with thin strips of blotter paper in areas of interest. The surface is then exposed to an airstream that contains a dyed-water spray cloud. The water droplet impingement data are extracted from the dyed blotter paper strips by measuring the optical reflectance of each strip with an automated reflectometer. Experimental impingement efficiency data represented for a NLF (1)-0414 airfoil, a swept MS (1)-0317 airfoil, a Boeing 737-300 engine inlet model, two simulated ice shapes and a swept NACA 0012 wingtip. Analytical impingement efficiency data are also presented for the NLF (1)-0414 airfoil and the Boeing 737-300 engine inlet model.
Phonon assisted carrier motion on the Wannier-Stark ladder
NASA Astrophysics Data System (ADS)
Cheung, Alfred; Berciu, Mona
2014-03-01
It is well known that at zero temperature and in the absence of electron-phonon coupling, the presence of an electric field leads to localization of carriers residing in a single band of finite bandwidth. In this talk, we will present an implementation of the self-consistent Born approximation (SCBA) to study the effect of weak electron-phonon coupling on the motion of a carrier in a biased system. At moderate and strong electron-phonon coupling, we supplement the SCBA, describing the string of phonons left behind by the carrier, with the momentum average approximation to describe the phonon cloud that accompanies the resulting polaron. We find that coupling to the lattice delocalizes the carrier, as expected, although long-lived resonances resulting from the Wannier-Stark states of the polaron may appear in certain regions of the parameter space. We end with a discussion of how our method can be improved to model disorder, other types of electron-phonon coupling, and electron-hole pair dissociation in a biased system.
Cloud cover archiving on a global scale - A discussion of principles
NASA Technical Reports Server (NTRS)
Henderson-Sellers, A.; Hughes, N. A.; Wilson, M.
1981-01-01
Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.
Adaptive finite element methods for two-dimensional problems in computational fracture mechanics
NASA Technical Reports Server (NTRS)
Min, J. B.; Bass, J. M.; Spradley, L. W.
1994-01-01
Some recent results obtained using solution-adaptive finite element methods in two-dimensional problems in linear elastic fracture mechanics are presented. The focus is on the basic issue of adaptive finite element methods for validating the new methodology by computing demonstration problems and comparing the stress intensity factors to analytical results.
An enriched finite element method to fractional advection-diffusion equation
NASA Astrophysics Data System (ADS)
Luan, Shengzhi; Lian, Yanping; Ying, Yuping; Tang, Shaoqiang; Wagner, Gregory J.; Liu, Wing Kam
2017-08-01
In this paper, an enriched finite element method with fractional basis [ 1,x^{α }] for spatial fractional partial differential equations is proposed to obtain more stable and accurate numerical solutions. For pure fractional diffusion equation without advection, the enriched Galerkin finite element method formulation is demonstrated to simulate the exact solution successfully without any numerical oscillation, which is advantageous compared to the traditional Galerkin finite element method with integer basis [ 1,x] . For fractional advection-diffusion equation, the oscillatory behavior becomes complex due to the introduction of the advection term which can be characterized by a fractional element Peclet number. For the purpose of addressing the more complex numerical oscillation, an enriched Petrov-Galerkin finite element method is developed by using a dimensionless fractional stabilization parameter, which is formulated through a minimization of the residual of the nodal solution. The effectiveness and accuracy of the enriched finite element method are demonstrated by a series of numerical examples of fractional diffusion equation and fractional advection-diffusion equation, including both one-dimensional and two-dimensional, steady-state and time-dependent cases.
NASA Technical Reports Server (NTRS)
Tsai, C.; Szabo, B. A.
1973-01-01
An approch to the finite element method which utilizes families of conforming finite elements based on complete polynomials is presented. Finite element approximations based on this method converge with respect to progressively reduced element sizes as well as with respect to progressively increasing orders of approximation. Numerical results of static and dynamic applications of plates are presented to demonstrate the efficiency of the method. Comparisons are made with plate elements in NASTRAN and the high-precision plate element developed by Cowper and his co-workers. Some considerations are given to implementation of the constraint method into general purpose computer programs such as NASTRAN.
Wave Scattering in Heterogeneous Media using the Finite Element Method
2016-10-21
AFRL-AFOSR-JP-TR-2016-0086 Wave Scattering in Heterogeneous Media using the Finite Element Method Chiruvai Vendhan INDIAN INSTITUTE OF TECHNOLOGY...Scattering in Heterogeneous Media using the Finite Element Method 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA2386-12-1-4026 5c. PROGRAM ELEMENT NUMBER 61102F 6...14. ABSTRACT The primary aim of this study is to develop a finite element model for elastic scattering by axisymmetric bodies submerged in a
Finite Volume Method for Pricing European Call Option with Regime-switching Volatility
NASA Astrophysics Data System (ADS)
Lista Tauryawati, Mey; Imron, Chairul; Putri, Endah RM
2018-03-01
In this paper, we present a finite volume method for pricing European call option using Black-Scholes equation with regime-switching volatility. In the first step, we formulate the Black-Scholes equations with regime-switching volatility. we use a finite volume method based on fitted finite volume with spatial discretization and an implicit time stepping technique for the case. We show that the regime-switching scheme can revert to the non-switching Black Scholes equation, both in theoretical evidence and numerical simulations.
Use of system identification techniques for improving airframe finite element models using test data
NASA Technical Reports Server (NTRS)
Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.
1993-01-01
A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.
T-Check in System-of-Systems Technologies: Cloud Computing
2010-09-01
T-Check in System-of-Systems Technologies: Cloud Computing Harrison D. Strowd Grace A. Lewis September 2010 TECHNICAL NOTE CMU/SEI-2010... Cloud Computing 1 1.2 Types of Cloud Computing 2 1.3 Drivers and Barriers to Cloud Computing Adoption 5 2 Using the T-Check Method 7 2.1 T-Check...Hypothesis 3 25 3.4.2 Deployment View of the Solution for Testing Hypothesis 3 27 3.5 Selecting Cloud Computing Providers 30 3.6 Implementing the T-Check
Cloud and Traditional Videoconferencing Technology for Telemedicine and Distance Learning
Zhang, Kai; Locatis, Craig; Ackerman, Michael
2015-01-01
Abstract Introduction: Cloud-based videoconferencing versus traditional systems are described for possible use in telemedicine and distance learning. Materials and Methods: Differences between traditional and cloud-based videoconferencing systems are examined, and the methods for identifying and testing systems are explained. Findings are presented characterizing the cloud conferencing genre and its attributes versus traditional H.323 conferencing. Results: Because the technology is rapidly evolving and needs to be evaluated in reference to local needs, it is strongly recommended that this or other reviews not be considered substitutes for personal hands-on experience. Conclusions: This review identifies key attributes of the technology that can be used to appraise the relevance of cloud conferencing technology and to determine whether migration from traditional technology to a cloud environment is warranted. An evaluation template is provided for assessing systems appropriateness. PMID:25785761
NASA Technical Reports Server (NTRS)
Kinne, S.; Wiscombe, Warren; Einaudi, Franco (Technical Monitor)
2001-01-01
Understanding the effect of aerosol on cloud systems is one of the major challenges in atmospheric and climate research. Local studies suggest a multitude of influences on cloud properties. Yet the overall effect on cloud albedo, a critical parameter in climate simulations, remains uncertain. NASA's Triana mission will provide, from its EPIC multi-spectral imager, simultaneous data on aerosol properties and cloud reflectivity. With Triana's unique position in space these data will be available not only globally but also over the entire daytime, well suited to accommodate the often short lifetimes of aerosol and investigations around diurnal cycles. This pilot study explores the ability to detect relationships between aerosol properties and cloud reflectivity with sophisticated statistical methods. Sample results using data from the EOS Terra platform to simulate Triana are presented.
Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm
Yan, Li; Xie, Hong; Chen, Changjun
2017-01-01
Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%. PMID:28850100
Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm.
Yan, Li; Tan, Junxiang; Liu, Hua; Xie, Hong; Chen, Changjun
2017-08-29
Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%.
Ground-based remote sensing of thin clouds in the Arctic
NASA Astrophysics Data System (ADS)
Garrett, T. J.; Zhao, C.
2013-05-01
This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm-1, 935.8 cm-1, and 988.4 cm-1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm-1. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius re, visible optical depth τ, number concentration N, and water path WP are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement programme (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with both ground-based microwave radiometer measurements of liquid water path and a method that uses combined shortwave and microwave measurements to retrieve re, τ and N. Compared to other retrieval methods, advantages of this technique include its ability to characterise thin clouds year round, that water vapour is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies and that it relies on a fairly comprehensive suite of ground based measurements.
FPFH-based graph matching for 3D point cloud registration
NASA Astrophysics Data System (ADS)
Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua
2018-04-01
Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.
Deformation of two-phase aggregates using standard numerical methods
NASA Astrophysics Data System (ADS)
Duretz, Thibault; Yamato, Philippe; Schmalholz, Stefan M.
2013-04-01
Geodynamic problems often involve the large deformation of material encompassing material boundaries. In geophysical fluids, such boundaries often coincide with a discontinuity in the viscosity (or effective viscosity) field and subsequently in the pressure field. Here, we employ popular implementations of the finite difference and finite element methods for solving viscous flow problems. On one hand, we implemented finite difference method coupled with a Lagrangian marker-in-cell technique to represent the deforming fluid. Thanks to it Eulerian nature, this method has a limited geometric flexibility but is characterized by a light and stable discretization. On the other hand, we employ the Lagrangian finite element method which offers full geometric flexibility at the cost of relatively heavier discretization. In order to test the accuracy of the finite difference scheme, we ran large strain simple shear deformation of aggregates containing either weak of strong circular inclusion (1e6 viscosity ratio). The results, obtained for different grid resolutions, are compared to Lagrangian finite element results which are considered as reference solution. The comparison is then used to establish up to which strain can finite difference simulations be run given the nature of the inclusions (dimensions, viscosity) and the resolution of the Eulerian mesh.
[Progression on finite element modeling method in scoliosis].
Fan, Ning; Zang, Lei; Hai, Yong; Du, Peng; Yuan, Shuo
2018-04-25
Scoliosis is a complex spinal three-dimensional malformation with complicated pathogenesis, often associated with complications as thoracic deformity and shoulder imbalance. Because the acquisition of specimen or animal models are difficult, the biomechanical study of scoliosis is limited. In recent years, along with the development of the computer technology, software and image, the technology of establishing a finite element model of human spine is maturing and it has been providing strong support for the research of pathogenesis of scoliosis, the design and application of brace, and the selection of surgical methods. The finite element model method is gradually becoming an important tool in the biomechanical study of scoliosis. Establishing a high quality finite element model is the basis of analysis and future study. However, the finite element modeling process can be complex and modeling methods are greatly varied. Choosing the appropriate modeling method according to research objectives has become researchers' primary task. In this paper, the author reviews the national and international literature in recent years and concludes the finite element modeling methods in scoliosis, including data acquisition, establishment of the geometric model, the material properties, parameters setting, the validity of the finite element model validation and so on. Copyright© 2018 by the China Journal of Orthopaedics and Traumatology Press.
A simple finite element method for linear hyperbolic problems
Mu, Lin; Ye, Xiu
2017-09-14
Here, we introduce a simple finite element method for solving first order hyperbolic equations with easy implementation and analysis. Our new method, with a symmetric, positive definite system, is designed to use discontinuous approximations on finite element partitions consisting of arbitrary shape of polygons/polyhedra. Error estimate is established. Extensive numerical examples are tested that demonstrate the robustness and flexibility of the method.
A simple finite element method for linear hyperbolic problems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mu, Lin; Ye, Xiu
Here, we introduce a simple finite element method for solving first order hyperbolic equations with easy implementation and analysis. Our new method, with a symmetric, positive definite system, is designed to use discontinuous approximations on finite element partitions consisting of arbitrary shape of polygons/polyhedra. Error estimate is established. Extensive numerical examples are tested that demonstrate the robustness and flexibility of the method.
Registration algorithm of point clouds based on multiscale normal features
NASA Astrophysics Data System (ADS)
Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua
2015-01-01
The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.
Ground-based remote sensing of thin clouds in the Arctic
NASA Astrophysics Data System (ADS)
Garrett, T. J.; Zhao, C.
2012-11-01
This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.
NASA Astrophysics Data System (ADS)
Lague, D.
2014-12-01
High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.
Validating Lidar Depolorization Calibration using Solar Radiation Scattered by Ice Clouds
NASA Technical Reports Server (NTRS)
Liu, Zhao-Yang; McGill, Matthew; Hu, Yong-Xiang; Hostetter, Chris; Winker, David; Vaughan, Mark
2004-01-01
This letter proposes the use of solar background radiation scattered by ice clouds for validating space lidar depolarization calibration. The method takes advantage of the fact that the background light scattered by ice clouds is almost entirely unpolarized. The theory is examined with Cloud Physics Lidar (CPL) background light measurements.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chitra Sivaraman, PNNL
Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloudmore » interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).« less
NASA Technical Reports Server (NTRS)
Shu, Chi-Wang
2004-01-01
This project is about the investigation of the development of the discontinuous Galerkin finite element methods, for general geometry and triangulations, for solving convection dominated problems, with applications to aeroacoustics. Other related issues in high order WENO finite difference and finite volume methods have also been investigated. methods are two classes of high order, high resolution methods suitable for convection dominated simulations with possible discontinuous or sharp gradient solutions. In [18], we first review these two classes of methods, pointing out their similarities and differences in algorithm formulation, theoretical properties, implementation issues, applicability, and relative advantages. We then present some quantitative comparisons of the third order finite volume WENO methods and discontinuous Galerkin methods for a series of test problems to assess their relative merits in accuracy and CPU timing. In [3], we review the development of the Runge-Kutta discontinuous Galerkin (RKDG) methods for non-linear convection-dominated problems. These robust and accurate methods have made their way into the main stream of computational fluid dynamics and are quickly finding use in a wide variety of applications. They combine a special class of Runge-Kutta time discretizations, that allows the method to be non-linearly stable regardless of its accuracy, with a finite element space discretization by discontinuous approximations, that incorporates the ideas of numerical fluxes and slope limiters coined during the remarkable development of the high-resolution finite difference and finite volume schemes. The resulting RKDG methods are stable, high-order accurate, and highly parallelizable schemes that can easily handle complicated geometries and boundary conditions. We review the theoretical and algorithmic aspects of these methods and show several applications including nonlinear conservation laws, the compressible and incompressible Navier-Stokes equations, and Hamilton-Jacobi-like equations.
Turbulence in molecular clouds - A new diagnostic tool to probe their origin
NASA Technical Reports Server (NTRS)
Canuto, V. M.; Battaglia, A.
1985-01-01
A method is presented to uncover the instability responsible for the type of turbulence observed in molecular clouds and the value of the physical parameters of the 'placental medium' from which turbulence originated. The method utilizes the observational relation between velocities and sizes of molecular clouds, together with a recent model for large-scale turbulence (constructed by Canuto and Goldman, 1985).
Numerical computation of transonic flows by finite-element and finite-difference methods
NASA Technical Reports Server (NTRS)
Hafez, M. M.; Wellford, L. C.; Merkle, C. L.; Murman, E. M.
1978-01-01
Studies on applications of the finite element approach to transonic flow calculations are reported. Different discretization techniques of the differential equations and boundary conditions are compared. Finite element analogs of Murman's mixed type finite difference operators for small disturbance formulations were constructed and the time dependent approach (using finite differences in time and finite elements in space) was examined.
Modeling Lidar Multiple Scattering
NASA Astrophysics Data System (ADS)
Sato, Kaori; Okamoto, Hajime; Ishimoto, Hiroshi
2016-06-01
A practical model to simulate multiply scattered lidar returns from inhomogeneous cloud layers are developed based on Backward Monte Carlo (BMC) simulations. The estimated time delay of the backscattered intensities returning from different vertical grids by the developed model agreed well with that directly obtained from BMC calculations. The method was applied to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data to improve the synergetic retrieval of cloud microphysics with CloudSat radar data at optically thick cloud grids. Preliminary results for retrieving mass fraction of co-existing cloud particles and drizzle size particles within lowlevel clouds are demonstrated.
Applications: Cloud Height at Night.
ERIC Educational Resources Information Center
Mathematics Teacher, 1980
1980-01-01
The method used at airports in determining the cloud height at night is presented. Several problems, the equation used, and a simple design of an alidade (an instrument that shows cloud heights directly) are also included. (MP)
Ice Cloud Backscatter Study and Comparison with CALIPSO and MODIS Satellite Data
NASA Technical Reports Server (NTRS)
Ding, Jiachen; Yang, Ping; Holz, Robert E.; Platnick, Steven; Meyer, Kerry G.; Vaughan, Mark A.; Hu, Yongxiang; King, Michael D.
2016-01-01
An invariant imbedding T-matrix (II-TM) method is used to calculate the single-scattering properties of 8-column aggregate ice crystals. The II-TM based backscatter values are compared with those calculated by the improved geometric-optics method (IGOM) to refine the backscattering properties of the ice cloud radiative model used in the MODIS Collection 6 cloud optical property product. The integrated attenuated backscatter-to-cloud optical depth (IAB-ICOD) relation is derived from simulations using a CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite) lidar simulator based on a Monte Carlo radiative transfer model. By comparing the simulation results and co-located CALIPSO and MODIS (Moderate Resolution Imaging Spectroradiometer) observations, the non-uniform zonal distribution of ice clouds over ocean is characterized in terms of a mixture of smooth and rough ice particles. The percentage of the smooth particles is approximately 6 percent and 9 percent for tropical and mid-latitude ice clouds, respectively.
NASA Astrophysics Data System (ADS)
Vaillant de Guélis, Thibault; Chepfer, Hélène; Noel, Vincent; Guzman, Rodrigo; Winker, David M.; Plougonven, Riwal
2017-12-01
Measurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).
Solution-adaptive finite element method in computational fracture mechanics
NASA Technical Reports Server (NTRS)
Min, J. B.; Bass, J. M.; Spradley, L. W.
1993-01-01
Some recent results obtained using solution-adaptive finite element method in linear elastic two-dimensional fracture mechanics problems are presented. The focus is on the basic issue of adaptive finite element method for validating the applications of new methodology to fracture mechanics problems by computing demonstration problems and comparing the stress intensity factors to analytical results.
2016-06-01
7 Development of Cohesive Finite Element Method (CFEM) Capability ................................7 3D...Cohesive Finite Element Method (CFEM) framework A new scientific framework and technical capability is developed for the computational analyses of...this section should shift from reporting activities to reporting accomplishments. Development of Cohesive Finite Element Method (CFEM) Capability
NASA Astrophysics Data System (ADS)
Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan
2015-03-01
Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.
A Discontinuous Galerkin Finite Element Method for Hamilton-Jacobi Equations
NASA Technical Reports Server (NTRS)
Hu, Changqing; Shu, Chi-Wang
1998-01-01
In this paper, we present a discontinuous Galerkin finite element method for solving the nonlinear Hamilton-Jacobi equations. This method is based on the Runge-Kutta discontinuous Galerkin finite element method for solving conservation laws. The method has the flexibility of treating complicated geometry by using arbitrary triangulation, can achieve high order accuracy with a local, compact stencil, and are suited for efficient parallel implementation. One and two dimensional numerical examples are given to illustrate the capability of the method.
Cognitive Approaches for Medicine in Cloud Computing.
Ogiela, Urszula; Takizawa, Makoto; Ogiela, Lidia
2018-03-03
This paper will present the application potential of the cognitive approach to data interpretation, with special reference to medical areas. The possibilities of using the meaning approach to data description and analysis will be proposed for data analysis tasks in Cloud Computing. The methods of cognitive data management in Cloud Computing are aimed to support the processes of protecting data against unauthorised takeover and they serve to enhance the data management processes. The accomplishment of the proposed tasks will be the definition of algorithms for the execution of meaning data interpretation processes in safe Cloud Computing. • We proposed a cognitive methods for data description. • Proposed a techniques for secure data in Cloud Computing. • Application of cognitive approaches for medicine was described.
Remote sensing of cirrus cloud vertical size profile using MODIS data
NASA Astrophysics Data System (ADS)
Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.
2009-05-01
This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.
NASA Technical Reports Server (NTRS)
Strong, Stuart L.; Meade, Andrew J., Jr.
1992-01-01
Preliminary results are presented of a finite element/finite difference method (semidiscrete Galerkin method) used to calculate compressible boundary layer flow about airfoils, in which the group finite element scheme is applied to the Dorodnitsyn formulation of the boundary layer equations. The semidiscrete Galerkin (SDG) method promises to be fast, accurate and computationally efficient. The SDG method can also be applied to any smoothly connected airfoil shape without modification and possesses the potential capability of calculating boundary layer solutions beyond flow separation. Results are presented for low speed laminar flow past a circular cylinder and past a NACA 0012 airfoil at zero angle of attack at a Mach number of 0.5. Also shown are results for compressible flow past a flat plate for a Mach number range of 0 to 10 and results for incompressible turbulent flow past a flat plate. All numerical solutions assume an attached boundary layer.
Research on Finite Element Model Generating Method of General Gear Based on Parametric Modelling
NASA Astrophysics Data System (ADS)
Lei, Yulong; Yan, Bo; Fu, Yao; Chen, Wei; Hou, Liguo
2017-06-01
Aiming at the problems of low efficiency and poor quality of gear meshing in the current mainstream finite element software, through the establishment of universal gear three-dimensional model, and explore the rules of unit and node arrangement. In this paper, a finite element model generation method of universal gear based on parameterization is proposed. Visual Basic program is used to realize the finite element meshing, give the material properties, and set the boundary / load conditions and other pre-processing work. The dynamic meshing analysis of the gears is carried out with the method proposed in this pape, and compared with the calculated values to verify the correctness of the method. The method greatly shortens the workload of gear finite element pre-processing, improves the quality of gear mesh, and provides a new idea for the FEM pre-processing.
A Moving Discontinuous Galerkin Finite Element Method for Flows with Interfaces
2017-12-07
Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6040--17-9765 A Moving Discontinuous Galerkin Finite Element Method for Flows with...guidance to revise the method to ensure such properties. Acknowledgements This work was sponsored by the Office of Naval Research through the Naval...18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT A Moving Discontinuous Galerkin Finite Element Method for Flows with Interfaces Andrew Corrigan, Andrew
Atom probe trajectory mapping using experimental tip shape measurements.
Haley, D; Petersen, T; Ringer, S P; Smith, G D W
2011-11-01
Atom probe tomography is an accurate analytical and imaging technique which can reconstruct the complex structure and composition of a specimen in three dimensions. Despite providing locally high spatial resolution, atom probe tomography suffers from global distortions due to a complex projection function between the specimen and detector which is different for each experiment and can change during a single run. To aid characterization of this projection function, this work demonstrates a method for the reverse projection of ions from an arbitrary projection surface in 3D space back to an atom probe tomography specimen surface. Experimental data from transmission electron microscopy tilt tomography are combined with point cloud surface reconstruction algorithms and finite element modelling to generate a mapping back to the original tip surface in a physically and experimentally motivated manner. As a case study, aluminium tips are imaged using transmission electron microscopy before and after atom probe tomography, and the specimen profiles used as input in surface reconstruction methods. This reconstruction method is a general procedure that can be used to generate mappings between a selected surface and a known tip shape using numerical solutions to the electrostatic equation, with quantitative solutions to the projection problem readily achievable in tens of minutes on a contemporary workstation. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.
NASA Astrophysics Data System (ADS)
Abdi, Daniel S.; Giraldo, Francis X.
2016-09-01
A unified approach for the numerical solution of the 3D hyperbolic Euler equations using high order methods, namely continuous Galerkin (CG) and discontinuous Galerkin (DG) methods, is presented. First, we examine how classical CG that uses a global storage scheme can be constructed within the DG framework using constraint imposition techniques commonly used in the finite element literature. Then, we implement and test a simplified version in the Non-hydrostatic Unified Model of the Atmosphere (NUMA) for the case of explicit time integration and a diagonal mass matrix. Constructing CG within the DG framework allows CG to benefit from the desirable properties of DG such as, easier hp-refinement, better stability etc. Moreover, this representation allows for regional mixing of CG and DG depending on the flow regime in an area. The different flavors of CG and DG in the unified implementation are then tested for accuracy and performance using a suite of benchmark problems representative of cloud-resolving scale, meso-scale and global-scale atmospheric dynamics. The value of our unified approach is that we are able to show how to carry both CG and DG methods within the same code and also offer a simple recipe for modifying an existing CG code to DG and vice versa.
The effect of clouds on the earth's radiation budget
NASA Technical Reports Server (NTRS)
Ziskin, Daniel; Strobel, Darrell F.
1991-01-01
The radiative fluxes from the Earth Radiation Budget Experiment (ERBE) and the cloud properties from the International Satellite Cloud Climatology Project (ISCCP) over Indonesia for the months of June and July of 1985 and 1986 were analyzed to determine the cloud sensitivity coefficients. The method involved a linear least squares regression between co-incident flux and cloud coverage measurements. The calculated slope is identified as the cloud sensitivity. It was found that the correlations between the total cloud fraction and radiation parameters were modest. However, correlations between cloud fraction and IR flux were improved by separating clouds by height. Likewise, correlations between the visible flux and cloud fractions were improved by distinguishing clouds based on optical depth. Calculating correlations between the net fluxes and either height or optical depth segregated cloud fractions were somewhat improved. When clouds were classified in terms of their height and optical depth, correlations among all the radiation components were improved. Mean cloud sensitivities based on the regression of radiative fluxes against height and optical depth separated cloud types are presented. Results are compared to a one-dimensional radiation model with a simple cloud parameterization scheme.
Study of the Radiative Properties of Inhomogeneous Stratocumulus Clouds
NASA Technical Reports Server (NTRS)
Batey, Michael
1996-01-01
Clouds play an important role in the radiation budget of the atmosphere. A good understanding of how clouds interact with solar radiation is necessary when considering their effects in both general circulation models and climate models. This study examined the radiative properties of clouds in both an inhomogeneous cloud system, and a simplified cloud system through the use of a Monte Carlo model. The purpose was to become more familiar with the radiative properties of clouds, especially absorption, and to investigate the excess absorption of solar radiation from observations over that calculated from theory. The first cloud system indicated that the absorptance actually decreased as the cloud's inhomogeneity increased, and that cloud forcing does not indicate any changes. The simplified cloud system looked at two different cases of absorption of solar radiation in the cloud. The absorptances calculated from the Monte Carlo is compared to a correction method for calculating absorptances and found that the method can over or underestimate absorptances at cloud edges. Also the cloud edge effects due to solar radiation points to a possibility of overestimating the retrieved optical depth at the edge, and indicates a possible way to correct for it. The effective cloud fraction (Ne) for a long time has been calculated from a cloud's reflectance. From the reflectance it has been observed that the N, for most cloud geometries is greater than the actual cloud fraction (Nc) making a cloud appear wider than it is optically. Recent studies we have performed used a Monte Carlo model to calculate the N, of a cloud using not only the reflectance but also the absorptance. The derived Ne's from the absorptance in some of the Monte Carlo runs did not give the same results as derived from the reflectance. This study also examined the inhomogeneity of clouds to find a relationship between larger and smaller scales, or wavelengths, of the cloud. Both Fourier transforms and wavelet transforms were used to analyze the liquid water content of marine stratocumulus clouds taken during the ASTEX project. From the analysis it was found that the energy in the cloud is not uniformly distributed but is greater at the larger scales than at the smaller scales. This was determined by examining the slope of the power spectrum, and by comparing the variability at two scales from a wavelet analysis.
Radiative Properties of Cirrus Clouds in the Infrared (8-13 microns) Spectral Region
NASA Technical Reports Server (NTRS)
Yang, Ping; Gao, Bo-Cai; Baum, Bryan A.; Hu, Yong X.; Wiscombe, Warren J.; Tsay, Si-Chee; Winker, Dave M.; Einaudi, Franco (Technical Monitor)
2000-01-01
Atmospheric radiation in the infrared (IR) 8-13 microns spectral region contains a wealth of information that is very useful for the retrieval of ice cloud properties from aircraft or space-borne measurements. To provide the scattering and absorption properties of nonspherical ice crystals that are fundamental to the IR retrieval implementation, we use the finite-difference time domain (FDTD) method to solve for the extinction efficiency, single-scattering albedo, and the asymmetry parameter of the phase function for ice crystals smaller than 40 microns. For particles larger than this size, the improved geometric optics method (IGOM) can be employed to calculate the asymmetry parameter with an acceptable accuracy, provided that we properly account for the inhomogeneity of the refracted wave due to strong absorption inside the ice particle. A combination of the results computed from the two methods provides the asymmetry parameter for the entire practical range of particle sizes between 1 micron and 10000 microns over wavelengths ranging from 8 microns to 13 microns. For the extinction and absorption efficiency calculations, several methods including the IGOM, Mie solution for equivalent spheres (MSFES), and the anomalous diffraction theory (ADT) can lead to a substantial discontinuity in comparison with the FDTD solutions for particle sizes on the order of 40 microns. To overcome this difficulty, we have developed a novel approach called the stretched scattering potential method (SSPM). For the IR 8-13 microns spectral region, we show that SSPM is a more accurate approximation than ADT, MSFES, and IGOM. The SSPM solution can be further refined numerically. Through a combination of the FDTD and SSPM, we have computed the extinction and absorption efficiency for hexagonal ice crystals with sizes ranging from 1 to 10000 microns at 12 wavelengths between 8 and 13 microns Calculations of the cirrus bulk scattering and absorption properties are performed for 30 size distributions obtained from various field campaigns for midlatitude and tropical cirrus cloud systems. Parameterization of these bulk scattering properties is carried out by using second-order polynomial functions for the extinction efficiency and the single-scattering albedo and the power law expression for the asymmetry parameter. We note that the volume-normalized extinction coefficient can be separated into two parts: one is inversely proportional to effective size and is independent of wavelength, and the other is the wavelength-dependent effective extinction efficiency. Unlike conventional parameterization efforts, the present parameterization scheme is more accurate because only the latter part of the volume-normalized extinction coefficient is approximated in terms of an analytical expression. After averaging over size distribution, the single-scattering albedo is shown to decrease with an increase in effective size for wavelengths shorter than 10.0 microns whereas the opposite behavior is observed for longer wavelengths. The variation of the asymmetry parameter as a function of effective size is substantial when the effective size is smaller than 50 microns. For effective sizes larger than 100 microns, the asymmetry parameter approaches its asymptotic value. The results derived in this study can be useful to remote sensing applications involving IR window bands under cirrus cloud conditions.
a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree
NASA Astrophysics Data System (ADS)
Kang, Q.; Huang, G.; Yang, S.
2018-04-01
Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.
Building Reflection with Word Clouds for Online RN to BSN Students.
Volkert, Delene R
Reflection allows students to integrate learning with their personal context, developing deeper knowledge and promoting critical thinking. Word clouds help students develop themes/concepts beyond traditional methods, introducing visual aspects to an online learning environment. Students created word clouds and captions, then responded to those created by peers for a weekly discussion assignment. Students indicated overwhelming support for the use of word clouds to develop deeper understanding of the subject matter. This reflection assignment could be utilized in asynchronous, online undergraduate nursing courses for creative methods of building reflection and developing knowledge for the undergraduate RN to BSN student.
Cloud Properties Derived from Surface-Based Near-Infrared Spectral Transmission
NASA Technical Reports Server (NTRS)
Pilewskie, Peter; Twomey, S.; Gore, Warren J. Y. (Technical Monitor)
1996-01-01
Surface based near-infrared cloud spectral transmission measurements from a recent precipitation/cloud physics field study are used to determine cloud physical properties and relate them to other remote sensing and in situ measurements. Asymptotic formulae provide an effective means of closely approximating the qualitative and quantitative behavior of transmission computed by more laborious detailed methods. Relationships derived from asymptotic formulae are applied to measured transmission spectra to test objectively the internal consistency of data sets acquired during the field program and they confirmed the quality of the measurements. These relationships appear to be very useful in themselves, not merely as a quality control measure, but also a potentially valuable remote-sensing technique in its own right. Additional benefits from this analysis have been the separation of condensed water (cloud) transmission and water vapor transmission and the development of a method to derive cloud liquid water content.
A hybrid cloud read aligner based on MinHash and kmer voting that preserves privacy
NASA Astrophysics Data System (ADS)
Popic, Victoria; Batzoglou, Serafim
2017-05-01
Low-cost clouds can alleviate the compute and storage burden of the genome sequencing data explosion. However, moving personal genome data analysis to the cloud can raise serious privacy concerns. Here, we devise a method named Balaur, a privacy preserving read mapper for hybrid clouds based on locality sensitive hashing and kmer voting. Balaur can securely outsource a substantial fraction of the computation to the public cloud, while being highly competitive in accuracy and speed with non-private state-of-the-art read aligners on short read data. We also show that the method is significantly faster than the state of the art in long read mapping. Therefore, Balaur can enable institutions handling massive genomic data sets to shift part of their analysis to the cloud without sacrificing accuracy or exposing sensitive information to an untrusted third party.
A hybrid cloud read aligner based on MinHash and kmer voting that preserves privacy
Popic, Victoria; Batzoglou, Serafim
2017-01-01
Low-cost clouds can alleviate the compute and storage burden of the genome sequencing data explosion. However, moving personal genome data analysis to the cloud can raise serious privacy concerns. Here, we devise a method named Balaur, a privacy preserving read mapper for hybrid clouds based on locality sensitive hashing and kmer voting. Balaur can securely outsource a substantial fraction of the computation to the public cloud, while being highly competitive in accuracy and speed with non-private state-of-the-art read aligners on short read data. We also show that the method is significantly faster than the state of the art in long read mapping. Therefore, Balaur can enable institutions handling massive genomic data sets to shift part of their analysis to the cloud without sacrificing accuracy or exposing sensitive information to an untrusted third party. PMID:28508884
Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra
NASA Technical Reports Server (NTRS)
Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne
2004-01-01
Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.
An Automated Method for Landmark Identification and Finite-Element Modeling of the Lumbar Spine.
Campbell, Julius Quinn; Petrella, Anthony J
2015-11-01
The purpose of this study was to develop a method for the automated creation of finite-element models of the lumbar spine. Custom scripts were written to extract bone landmarks of lumbar vertebrae and assemble L1-L5 finite-element models. End-plate borders, ligament attachment points, and facet surfaces were identified. Landmarks were identified to maintain mesh correspondence between meshes for later use in statistical shape modeling. 90 lumbar vertebrae were processed creating 18 subject-specific finite-element models. Finite-element model surfaces and ligament attachment points were reproduced within 1e-5 mm of the bone surface, including the critical contact surfaces of the facets. Element quality exceeded specifications in 97% of elements for the 18 models created. The current method is capable of producing subject-specific finite-element models of the lumbar spine with good accuracy, quality, and robustness. The automated methods developed represent advancement in the state of the art of subject-specific lumbar spine modeling to a scale not possible with prior manual and semiautomated methods.
Gok, Kadir; Inal, Sermet; Gok, Arif; Gulbandilar, Eyyup
2017-05-01
In this study, biomechanical behaviors of three different screw materials (stainless steel, titanium and cobalt-chromium) have analyzed to fix with triangle fixation under axial loading in femoral neck fracture and which material is best has been investigated. Point cloud obtained after scanning the human femoral model with the three dimensional (3D) scanner and this point cloud has been converted to 3D femoral model by Geomagic Studio software. Femoral neck fracture was modeled by SolidWorks software for only triangle configuration and computer-aided numerical analyses of three different materials have been carried out by AnsysWorkbench finite element analysis (FEA) software. The loading, boundary conditions and material properties have prepared for FEA and Von-Misses stress values on upper and lower proximity of the femur and screws have been calculated. At the end of numerical analyses, the best advantageous screw material has calculated as titanium because it creates minimum stress at the upper and lower proximity of the fracture line.
Mapping of the extinction in giant molecular clouds using optical star counts
NASA Astrophysics Data System (ADS)
Cambrésy, L.
1999-05-01
This paper presents large scale extinction maps of most nearby Giant Molecular Clouds of the Galaxy (Lupus, rho Ophiuchus, Scorpius, Coalsack, Taurus, Chamaeleon, Musca, Corona Australis, Serpens, IC 5146, Vela, Orion, Monoceros R1 and R2, Rosette, Carina) derived from a star count method using an adaptive grid and a wavelet decomposition applied to the optical data provided by the USNO-Precision Measuring Machine. The distribution of the extinction in the clouds leads to estimate their total individual masses M and their maximum of extinction. I show that the relation between the mass contained within an iso-extinction contour and the extinction is similar from cloud to cloud and allows the extrapolation of the maximum of extinction in the range 5.7 to 25.5 magnitudes. I found that about half of the mass is contained in regions where the visual extinction is smaller than 1 magnitude. The star count method used on large scale ( ~ 250 square degrees) is a powerful and relatively straightforward method to estimate the mass of molecular complexes. A systematic study of the all sky would lead to discover new clouds as I did in the Lupus complex for which I found a sixth cloud of about 10(4) M_⊙.
CFD Analysis of the SBXC Glider Airframe
2016-06-01
mathematically on finite element methods. To validate and verify the methodology developed, a mathematical comparison was made with the previous research data...greater than 15 m/s. 14. SUBJECT TERMS finite element method, computational fluid dynamics, Y Plus, mesh element quality, aerodynamic data, fluid...based mathematically on finite element methods. To validate and verify the methodology developed, a mathematical comparison was made with the
NASA Astrophysics Data System (ADS)
Balusu, K.; Huang, H.
2017-04-01
A combined dislocation fan-finite element (DF-FE) method is presented for efficient and accurate simulation of dislocation nodal forces in 3D elastically anisotropic crystals with dislocations intersecting the free surfaces. The finite domain problem is decomposed into half-spaces with singular traction stresses, an infinite domain, and a finite domain with non-singular traction stresses. As such, the singular and non-singular parts of the traction stresses are addressed separately; the dislocation fan (DF) method is introduced to balance the singular traction stresses in the half-spaces while the finite element method (FEM) is employed to enforce the non-singular boundary conditions. The accuracy and efficiency of the DF method is demonstrated using a simple isotropic test case, by comparing it with the analytical solution as well as the FEM solution. The DF-FE method is subsequently used for calculating the dislocation nodal forces in a finite elastically anisotropic crystal, which produces dislocation nodal forces that converge rapidly with increasing mesh resolutions. In comparison, the FEM solution fails to converge, especially for nodes closer to the surfaces.
A multilevel correction adaptive finite element method for Kohn-Sham equation
NASA Astrophysics Data System (ADS)
Hu, Guanghui; Xie, Hehu; Xu, Fei
2018-02-01
In this paper, an adaptive finite element method is proposed for solving Kohn-Sham equation with the multilevel correction technique. In the method, the Kohn-Sham equation is solved on a fixed and appropriately coarse mesh with the finite element method in which the finite element space is kept improving by solving the derived boundary value problems on a series of adaptively and successively refined meshes. A main feature of the method is that solving large scale Kohn-Sham system is avoided effectively, and solving the derived boundary value problems can be handled efficiently by classical methods such as the multigrid method. Hence, the significant acceleration can be obtained on solving Kohn-Sham equation with the proposed multilevel correction technique. The performance of the method is examined by a variety of numerical experiments.
Monte Carlo Calculations of Polarized Microwave Radiation Emerging from Cloud Structures
NASA Technical Reports Server (NTRS)
Kummerow, Christian; Roberti, Laura
1998-01-01
The last decade has seen tremendous growth in cloud dynamical and microphysical models that are able to simulate storms and storm systems with very high spatial resolution, typically of the order of a few kilometers. The fairly realistic distributions of cloud and hydrometeor properties that these models generate has in turn led to a renewed interest in the three-dimensional microwave radiative transfer modeling needed to understand the effect of cloud and rainfall inhomogeneities upon microwave observations. Monte Carlo methods, and particularly backwards Monte Carlo methods have shown themselves to be very desirable due to the quick convergence of the solutions. Unfortunately, backwards Monte Carlo methods are not well suited to treat polarized radiation. This study reviews the existing Monte Carlo methods and presents a new polarized Monte Carlo radiative transfer code. The code is based on a forward scheme but uses aliasing techniques to keep the computational requirements equivalent to the backwards solution. Radiative transfer computations have been performed using a microphysical-dynamical cloud model and the results are presented together with the algorithm description.
NASA Astrophysics Data System (ADS)
Schwantes, Adam Christopher
Stratocumuli are a type of low clouds composed of individual convective elements that together form a continuous layer of clouds. Stratocumuli cover large regions of the Earth's surface, which make them important components in the Earth's radiation budget. Stratocumuli strongly reflect solar shortwave radiation, while weakly affecting outgoing longwave radiation. This leads to a strong radiative cooling effect that affects the Earth's radiation budget. Therefore it is important to investigate the mechanisms that affect the longevity of stratocumuli, so that their impact on the Earth's radiation budget can be fully understood. One mechanism that is currently being studied as influencing the lifetime of such cloud layers is boundary layer/surface coupling. It has been shown than in some regions (i.e. the west coast of South America) stratocumuli tend to break up when the boundary layer is decoupled with the surface, because they are cut off from their moisture source. This study will investigate the macro- and micro-physical properties of stratocumuli when boundary layers are either coupled to or decoupled from the surface. This will help advance understanding of the effects these macro- and micro-physical properties have on the lifetime of stratocumuli under different boundary layer conditions. This study used the Department of Energy Atmospheric Radiation Measurement (DOE ARM) mobile measurements facility (AMF) at the Azores site from June 2009 to December 2010. The measurements that were used include temperature profiles from radiosondes, cloud liquid water path (LWP) retrieved from the Microwave radiometer, and cloud base and top heights derived from W-band ARM Cloud Radar and lidar. Satellite images provided by the NASA Langley Research Center were also used to visually decipher cloud types over the region so that only single-layered stratocumuli cases are used in the study. To differentiate between coupled and decoupled cloud layers, two methods are used. The first method compares cloud base height and lifting condensation level (LCL) for surface air parcels. The second method uses potential temperature profiles to indicate whether a boundary layer is coupled or decoupled from the surface. The results from these two methods were then compared using select cases/samples when both methods classified a sample as coupled or decoupled. In this study, a total of seven coupled or decoupled cases (2-3 days long each) have been selected from the 19 month AMF dataset. Characteristics of the coupled and decoupled cases have been studied to identify similarities and differences. Furthermore, comparison results from this study have shown that there are similarities and differences between drizzling/non-drizzling stratocumulus clouds and decoupled/coupled stratocumulus clouds. Drizzling/decoupled stratocumuli tend to have higher LWP, cloud-droplet effective radius (re), cloud-top height, and cloud thickness values while non-drizzling/coupled stratocumuli have higher cloud-droplet number concentration (Nd) and cloud condensation nuclei concentration (NCCN) values. It was also determined that during daytime hours when stratocumuli are decoupled, they tend to be open cells, while coupled stratocumuli tend to be closed cells. Finally, decoupled nighttime stratocumuli were found to have higher LWPs compared to decoupled daytime stratocumuli, which resulted in the significant amount of heavy drizzle events occurring at night.
NASA Technical Reports Server (NTRS)
Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene
1993-01-01
Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.
NASA Astrophysics Data System (ADS)
Champion, N.
2012-08-01
Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.
The Development of a Finite Volume Method for Modeling Sound in Coastal Ocean Environment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Long, Wen; Yang, Zhaoqing; Copping, Andrea E.
: As the rapid growth of marine renewable energy and off-shore wind energy, there have been concerns that the noises generated from construction and operation of the devices may interfere marine animals’ communication. In this research, a underwater sound model is developed to simulate sound prorogation generated by marine-hydrokinetic energy (MHK) devices or offshore wind (OSW) energy platforms. Finite volume and finite difference methods are developed to solve the 3D Helmholtz equation of sound propagation in the coastal environment. For finite volume method, the grid system consists of triangular grids in horizontal plane and sigma-layers in vertical dimension. A 3Dmore » sparse matrix solver with complex coefficients is formed for solving the resulting acoustic pressure field. The Complex Shifted Laplacian Preconditioner (CSLP) method is applied to efficiently solve the matrix system iteratively with MPI parallelization using a high performance cluster. The sound model is then coupled with the Finite Volume Community Ocean Model (FVCOM) for simulating sound propagation generated by human activities in a range-dependent setting, such as offshore wind energy platform constructions and tidal stream turbines. As a proof of concept, initial validation of the finite difference solver is presented for two coastal wedge problems. Validation of finite volume method will be reported separately.« less
A weak Galerkin least-squares finite element method for div-curl systems
NASA Astrophysics Data System (ADS)
Li, Jichun; Ye, Xiu; Zhang, Shangyou
2018-06-01
In this paper, we introduce a weak Galerkin least-squares method for solving div-curl problem. This finite element method leads to a symmetric positive definite system and has the flexibility to work with general meshes such as hybrid mesh, polytopal mesh and mesh with hanging nodes. Error estimates of the finite element solution are derived. The numerical examples demonstrate the robustness and flexibility of the proposed method.
Applications of discrete element method in modeling of grain postharvest operations
USDA-ARS?s Scientific Manuscript database
Grain kernels are finite and discrete materials. Although flowing grain can behave like a continuum fluid at times, the discontinuous behavior exhibited by grain kernels cannot be simulated solely with conventional continuum-based computer modeling such as finite-element or finite-difference methods...
NASA Astrophysics Data System (ADS)
Christlieb, Andrew J.; Feng, Xiao; Seal, David C.; Tang, Qi
2016-07-01
We propose a high-order finite difference weighted ENO (WENO) method for the ideal magnetohydrodynamics (MHD) equations. The proposed method is single-stage (i.e., it has no internal stages to store), single-step (i.e., it has no time history that needs to be stored), maintains a discrete divergence-free condition on the magnetic field, and has the capacity to preserve the positivity of the density and pressure. To accomplish this, we use a Taylor discretization of the Picard integral formulation (PIF) of the finite difference WENO method proposed in Christlieb et al. (2015) [23], where the focus is on a high-order discretization of the fluxes (as opposed to the conserved variables). We use the version where fluxes are expanded to third-order accuracy in time, and for the fluid variables space is discretized using the classical fifth-order finite difference WENO discretization. We use constrained transport in order to obtain divergence-free magnetic fields, which means that we simultaneously evolve the magnetohydrodynamic (that has an evolution equation for the magnetic field) and magnetic potential equations alongside each other, and set the magnetic field to be the (discrete) curl of the magnetic potential after each time step. In this work, we compute these derivatives to fourth-order accuracy. In order to retain a single-stage, single-step method, we develop a novel Lax-Wendroff discretization for the evolution of the magnetic potential, where we start with technology used for Hamilton-Jacobi equations in order to construct a non-oscillatory magnetic field. The end result is an algorithm that is similar to our previous work Christlieb et al. (2014) [8], but this time the time stepping is replaced through a Taylor method with the addition of a positivity-preserving limiter. Finally, positivity preservation is realized by introducing a parameterized flux limiter that considers a linear combination of high and low-order numerical fluxes. The choice of the free parameter is then given in such a way that the fluxes are limited towards the low-order solver until positivity is attained. Given the lack of additional degrees of freedom in the system, this positivity limiter lacks energy conservation where the limiter turns on. However, this ingredient can be dropped for problems where the pressure does not become negative. We present two and three dimensional numerical results for several standard test problems including a smooth Alfvén wave (to verify formal order of accuracy), shock tube problems (to test the shock-capturing ability of the scheme), Orszag-Tang, and cloud shock interactions. These results assert the robustness and verify the high-order of accuracy of the proposed scheme.
APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels
NASA Astrophysics Data System (ADS)
Klüser, L.; Killius, N.; Gesell, G.
2015-04-01
The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.
Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter
NASA Technical Reports Server (NTRS)
Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej
2015-01-01
Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi-layered clouds as well as cloud phase. When determining multi-layered CTHs, limits on the upper clouds opacity are assessed.
NASA Astrophysics Data System (ADS)
Amiri-Farahani, Anahita; Allen, Robert J.; Neubauer, David; Lohmann, Ulrike
2017-05-01
One component of aerosol-cloud interactions (ACI) involves dust and marine stratocumulus clouds (MSc). Few observational studies have focused on dust-MSc interactions, and thus this effect remains poorly quantified. We use observations from multiple sensors in the NASA A-Train satellite constellation from 2004 to 2012 to obtain estimates of the aerosol-cloud radiative effect, including its uncertainty, of dust aerosol influencing Atlantic MSc off the coast of northern Africa between 45° W and 15° E and between 0 and 35° N. To calculate the aerosol-cloud radiative effect, we use two methods following Quaas et al. (2008) (Method 1) and Chen et al. (2014) (Method 2). These two methods yield similar results of -1.5 ± 1.4 and -1.5 ± 1.6 W m-2, respectively, for the annual mean aerosol-cloud radiative effect. Thus, Saharan dust modifies MSc in a way that acts to cool the planet. There is a strong seasonal variation, with the aerosol-cloud radiative effect switching from significantly negative during the boreal summer to weakly positive during boreal winter. Method 1 (Method 2) yields -3.8 ± 2.5 (-4.3 ± 4.1) during summer and 1 ± 2.9 (0.6 ± 1) W m-2 during winter. In Method 1, the aerosol-cloud radiative effect can be decomposed into two terms, one representing the first aerosol indirect effect and the second representing the combination of the second aerosol indirect effect and the semidirect effect (i.e., changes in liquid water path and cloud fraction in response to changes in absorbing aerosols and local heating). The first aerosol indirect effect is relatively small, varying from -0.7 ± 0.6 in summer to 0.1 ± 0.5 W m-2 in winter. The second term, however, dominates the overall radiative effect, varying from -3.2 ± 2.5 in summer to 0.9 ± 2.9 W m-2 during winter. Studies show that the semidirect effect can result in a negative (i.e., absorbing aerosol lies above low clouds like MSc) or positive (i.e., absorbing aerosol lies within low clouds) aerosol-cloud radiative effect. The semipermanent MSc are low and confined within the boundary layer. CALIPSO shows that 61.8 ± 12.6 % of Saharan dust resides above North Atlantic MSc during summer for our study area. This is consistent with a relatively weak first aerosol indirect effect and also suggests the second aerosol indirect effect plus semidirect effect (the second term in Method 1) is dominated by the semidirect effect. In contrast, the percentage of Saharan dust above North Atlantic MSc in winter is 11.9 ± 10.9 %, which is much lower than in summer. CALIPSO also shows that 88.3 ± 8.5 % of dust resides below 2.2 km the winter average of MSc top height. During summer, however, there are two peaks, with 35.6 ± 13 % below 1.9 km (summer average of MSc top height) and 44.4 ± 9.2 % between 2 and 4 km. Because the aerosol-cloud radiative effect is positive during winter, and is also dominated by the second term, this again supports the importance of the semidirect effect. We conclude that Saharan dust-MSc interactions off the coast of northern Africa are likely dominated by the semidirect effect.
Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data
NASA Technical Reports Server (NTRS)
Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny
2010-01-01
Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.
NASA Technical Reports Server (NTRS)
Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.
2012-01-01
With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.
SOME NEW FINITE DIFFERENCE METHODS FOR HELMHOLTZ EQUATIONS ON IRREGULAR DOMAINS OR WITH INTERFACES
Wan, Xiaohai; Li, Zhilin
2012-01-01
Solving a Helmholtz equation Δu + λu = f efficiently is a challenge for many applications. For example, the core part of many efficient solvers for the incompressible Navier-Stokes equations is to solve one or several Helmholtz equations. In this paper, two new finite difference methods are proposed for solving Helmholtz equations on irregular domains, or with interfaces. For Helmholtz equations on irregular domains, the accuracy of the numerical solution obtained using the existing augmented immersed interface method (AIIM) may deteriorate when the magnitude of λ is large. In our new method, we use a level set function to extend the source term and the PDE to a larger domain before we apply the AIIM. For Helmholtz equations with interfaces, a new maximum principle preserving finite difference method is developed. The new method still uses the standard five-point stencil with modifications of the finite difference scheme at irregular grid points. The resulting coefficient matrix of the linear system of finite difference equations satisfies the sign property of the discrete maximum principle and can be solved efficiently using a multigrid solver. The finite difference method is also extended to handle temporal discretized equations where the solution coefficient λ is inversely proportional to the mesh size. PMID:22701346
SOME NEW FINITE DIFFERENCE METHODS FOR HELMHOLTZ EQUATIONS ON IRREGULAR DOMAINS OR WITH INTERFACES.
Wan, Xiaohai; Li, Zhilin
2012-06-01
Solving a Helmholtz equation Δu + λu = f efficiently is a challenge for many applications. For example, the core part of many efficient solvers for the incompressible Navier-Stokes equations is to solve one or several Helmholtz equations. In this paper, two new finite difference methods are proposed for solving Helmholtz equations on irregular domains, or with interfaces. For Helmholtz equations on irregular domains, the accuracy of the numerical solution obtained using the existing augmented immersed interface method (AIIM) may deteriorate when the magnitude of λ is large. In our new method, we use a level set function to extend the source term and the PDE to a larger domain before we apply the AIIM. For Helmholtz equations with interfaces, a new maximum principle preserving finite difference method is developed. The new method still uses the standard five-point stencil with modifications of the finite difference scheme at irregular grid points. The resulting coefficient matrix of the linear system of finite difference equations satisfies the sign property of the discrete maximum principle and can be solved efficiently using a multigrid solver. The finite difference method is also extended to handle temporal discretized equations where the solution coefficient λ is inversely proportional to the mesh size.
Giant molecular cloud scaling relations: the role of the cloud definition
NASA Astrophysics Data System (ADS)
Khoperskov, S. A.; Vasiliev, E. O.; Ladeyschikov, D. A.; Sobolev, A. M.; Khoperskov, A. V.
2016-01-01
We investigate the physical properties of molecular clouds in disc galaxies with different morphologies: a galaxy without prominent structure, a spiral barred galaxy and a galaxy with flocculent structure. Our N-body/hydrodynamical simulations take into account non-equilibrium H2 and CO chemical kinetics, self-gravity, star formation and feedback processes. For the simulated galaxies, the scaling relations of giant molecular clouds, or so-called Larson's relations, are studied for two types of cloud definition (or extraction method): the first is based on total column density position-position (PP) data sets and the second is indicated by the CO (1-0) line emission used in position-position-velocity (PPV) data. We find that the cloud populations obtained using both cloud extraction methods generally have similar physical parameters, except that for the CO data the mass spectrum of clouds has a tail with low-mass objects M ˜ 103-104 M⊙. Owing toa varying column density threshold, the power-law indices in the scaling relations are significantly changed. In contrast, the relations are invariant to the CO brightness temperature threshold. Finally, we find that the mass spectra of clouds for PPV data are almost insensitive to the galactic morphology, whereas the spectra for PP data demonstrate significant variation.
The Incorporation and Initialization of Cloud Water/ice in AN Operational Forecast Model
NASA Astrophysics Data System (ADS)
Zhao, Qingyun
Quantitative precipitation forecasts have been one of the weakest aspects of numerical weather prediction models. Theoretical studies show that the errors in precipitation calculation can arise from three sources: errors in the large-scale forecasts of primary variables, errors in the crude treatment of condensation/evaporation and precipitation processes, and errors in the model initial conditions. A new precipitation parameterization scheme has been developed to investigate the forecast value of improved precipitation physics via the introduction of cloud water and cloud ice into a numerical prediction model. The main feature of this scheme is the explicit calculation of cloud water and cloud ice in both the convective and stratiform precipitation parameterization. This scheme has been applied to the eta model at the National Meteorological Center. Four extensive tests have been performed. The statistical results showed a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly. Since three-dimensional cloud data is absent from the analysis/assimilation system for most numerical models, a method has been proposed to incorporate observed precipitation and nephanalysis data into the data assimilation system to obtain the initial cloud field for the eta model. In this scheme, the initial moisture and vertical motion fields are also improved at the same time as cloud initialization. The physical initialization is performed in a dynamical initialization framework that uses the Newtonian dynamical relaxation method to nudge the model's wind and mass fields toward analyses during a 12-hour data assimilation period. Results from a case study showed that a realistic cloud field was produced by this method at the end of the data assimilation period. Precipitation forecasts have been significantly improved as a result of the improved initial cloud, moisture and vertical motion fields.
NASA Astrophysics Data System (ADS)
Melnikova, Irina; Gatebe, Charles K.
2018-07-01
Past strategies for retrieving cloud optical properties from remote sensing assumed significant limits for desired parameters such as semi-infinite optical thickness, single scattering albedo equaling unity (non-absorbing scattering), absence of spectral dependence of the optical thickness, etc., and only one optical parameter could be retrieved (either optical thickness or single scattering albedo). Here, we demonstrate a new method based on asymptotic theory for thick atmospheres, and the presence of a diffusion domain within the clouds that does not put restrictions and makes it possible to get two or even three optical parameters (optical thickness, single scattering albedo and phase function asymmetry parameter) for every wavelength independently. We applied this method to measurements of angular distribution of solar radiation above, inside and below clouds, obtained with NASA's Cloud Absorption Radiometer (CAR) over two cases of marine stratocumulus clouds; first case, offshore of Namibia and the second case, offshore of California. The observational and retrieval errors are accounted for by regularization, which allows stable and smooth solutions. Results show good potential for parameterization of the shortwave radiative properties (reflection, transmission, radiative divergence and heating rate) of water clouds.
NASA Technical Reports Server (NTRS)
Strode, Sarah A.; Douglass, Anne R.; Ziemke, Jerald R.; Manyin, Michael; Nielsen, J. Eric; Oman, Luke D.
2017-01-01
Satellite observations of in-cloud ozone concentrations from the Ozone Monitoring Instrument and Microwave Limb Sounder instruments show substantial differences from background ozone concentrations. We develop a method for comparing a free-running chemistry-climate model (CCM) to in-cloud and background ozone observations using a simple criterion based on cloud fraction to separate cloudy and clear-sky days. We demonstrate that the CCM simulates key features of the in-cloud versus background ozone differences and of the geographic distribution of in-cloud ozone. Since the agreement is not dependent on matching the meteorological conditions of a specific day, this is a promising method for diagnosing how accurately CCMs represent the relationships between ozone and clouds, including the lower ozone concentrations shown by in-cloud satellite observations. Since clouds are associated with convection as well as changes in chemistry, we diagnose the tendency of tropical ozone at 400 hPa due to chemistry, convection and turbulence, and large-scale dynamics. While convection acts to reduce ozone concentrations at 400 hPa throughout much of the tropics, it has the opposite effect over highly polluted regions of South and East Asia.
A dynamic access control method based on QoS requirement
NASA Astrophysics Data System (ADS)
Li, Chunquan; Wang, Yanwei; Yang, Baoye; Hu, Chunyang
2013-03-01
A dynamic access control method is put forward to ensure the security of the sharing service in Cloud Manufacturing, according to the application characteristics of cloud manufacturing collaborative task. The role-based access control (RBAC) model is extended according to the characteristics of cloud manufacturing in this method. The constraints are considered, which are from QoS requirement of the task context to access control, based on the traditional static authorization. The fuzzy policy rules are established about the weighted interval value of permissions. The access control authorities of executable service by users are dynamically adjusted through the fuzzy reasoning based on the QoS requirement of task. The main elements of the model are described. The fuzzy reasoning algorithm of weighted interval value based QoS requirement is studied. An effective method is provided to resolve the access control of cloud manufacturing.
Game Theory Based Trust Model for Cloud Environment
Gokulnath, K.; Uthariaraj, Rhymend
2015-01-01
The aim of this work is to propose a method to establish trust at bootload level in cloud computing environment. This work proposes a game theoretic based approach for achieving trust at bootload level of both resources and users perception. Nash equilibrium (NE) enhances the trust evaluation of the first-time users and providers. It also restricts the service providers and the users to violate service level agreement (SLA). Significantly, the problem of cold start and whitewashing issues are addressed by the proposed method. In addition appropriate mapping of cloud user's application to cloud service provider for segregating trust level is achieved as a part of mapping. Thus, time complexity and space complexity are handled efficiently. Experiments were carried out to compare and contrast the performance of the conventional methods and the proposed method. Several metrics like execution time, accuracy, error identification, and undecidability of the resources were considered. PMID:26380365
Finite-time state feedback stabilisation of stochastic high-order nonlinear feedforward systems
NASA Astrophysics Data System (ADS)
Xie, Xue-Jun; Zhang, Xing-Hui; Zhang, Kemei
2016-07-01
This paper studies the finite-time state feedback stabilisation of stochastic high-order nonlinear feedforward systems. Based on the stochastic Lyapunov theorem on finite-time stability, by using the homogeneous domination method, the adding one power integrator and sign function method, constructing a ? Lyapunov function and verifying the existence and uniqueness of solution, a continuous state feedback controller is designed to guarantee the closed-loop system finite-time stable in probability.
An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path
NASA Astrophysics Data System (ADS)
Greenwald, Thomas J.; Bennartz, Ralf; Lebsock, Matthew; Teixeira, João.
2018-04-01
The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9-year record of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E): clear-sky bias, cloud-rain partition (CRP) bias, cloud-fraction-dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR-E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud-Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud-fraction-dependent bias was found to be a combination of the CRP bias, an in-cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in-cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias-corrected AMSR-E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible-infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations.
NASA Technical Reports Server (NTRS)
Mei, Chuh; Shen, Mo-How
1987-01-01
Multiple-mode nonlinear forced vibration of a beam was analyzed by the finite element method. Inplane (longitudinal) displacement and inertia (IDI) are considered in the formulation. By combining the finite element method and nonlinear theory, more realistic models of structural response are obtained more easily and faster.
NASA Astrophysics Data System (ADS)
Shi, H.
2017-12-01
We presented a method to identify and calculate cloud radiative forcing (CRF) and horizontal chore length (L) of shallow convective clouds (SCC) using a network of 9 broadband pyranometers. The analyzing data was collected from the SCC campaign during two years summers (2015 2016) at Baiqi site over Inner Mongolia grassland. The network of pyranometers was operated across a spatial domain covering 42.16-42.30° N and 114.83-114.98° E. The SCC detection method was verified by observer reports and cameras, which showed that the detection method and human observations were in agreement about 75 %. The differences between the SCC detection method and human observations can be responsible for following factors: 1) small or dissipating clouds can be neglected for the value of 1 min of temporal resolution of pyranometer; 2) human observation recorded weather conditions four times every day; 3) SCC was indistinguishable from coexistence of SCC and Cirrus (Ci); 4) the SCC detection method is weighted toward clouds crossing the sun's path, while the human observer can view clouds over the entire sky. The deviation of L can be attributed to two factors: 1) the accuracy of wind speed at height of SCC and the ratio of horizontal and vertical length play a key role in determine values of L; 2) the effect of variance of solar zenith angle can be negligible. The downwelling shortwave CRF of SCC was -134.1 Wm-2. The average value of L of SCC was 1129 m. Besides, the distribution of normalized cloud chore length agreed well with power-law fit.
Evaluation of Methods to Estimate the Surface Downwelling Longwave Flux during Arctic Winter
NASA Technical Reports Server (NTRS)
Chiacchio, Marc; Francis, Jennifer; Stackhouse, Paul, Jr.
2002-01-01
Surface longwave radiation fluxes dominate the energy budget of nighttime polar regions, yet little is known about the relative accuracy of existing satellite-based techniques to estimate this parameter. We compare eight methods to estimate the downwelling longwave radiation flux and to validate their performance with measurements from two field programs in thc Arctic: the Coordinated Eastern Arctic Experiment (CEAREX ) conducted in the Barents Sea during the autumn and winter of 1988, and the Lead Experiment performed in the Beaufort Sea in the spring of 1992. Five of the eight methods were developed for satellite-derived quantities, and three are simple parameterizations based on surface observations. All of the algorithms require information about cloud fraction, which is provided from the NASA-NOAA Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) polar pathfinder dataset (Path-P): some techniques ingest temperature and moisture profiles (also from Path-P): one-half of the methods assume that clouds are opaque and have a constant geometric thickness of 50 hPa, and three include no thickness information whatsoever. With a somewhat limited validation dataset, the following primary conclusions result: (1) all methods exhibit approximately the same correlations with measurements and rms differences, but the biases range from -34 W sq m (16% of the mean) to nearly 0; (2) the error analysis described here indicates that the assumption of a 50-hPa cloud thickness is too thin by a factor of 2 on average in polar nighttime conditions; (3) cloud-overlap techniques. which effectively increase mean cloud thickness, significantly improve the results; (4) simple Arctic-specific parameterizations performed poorly, probably because they were developed with surface-observed cloud fractions; and (5) the single algorithm that includes an estimate of cloud thickness exhibits the smallest differences from observations.
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Young, David F.; Heck, Patrick W.; Liou, Kuo-Nan; Takano, Yoshihide
1992-01-01
The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances.
Stabilized Finite Elements in FUN3D
NASA Technical Reports Server (NTRS)
Anderson, W. Kyle; Newman, James C.; Karman, Steve L.
2017-01-01
A Streamlined Upwind Petrov-Galerkin (SUPG) stabilized finite-element discretization has been implemented as a library into the FUN3D unstructured-grid flow solver. Motivation for the selection of this methodology is given, details of the implementation are provided, and the discretization for the interior scheme is verified for linear and quadratic elements by using the method of manufactured solutions. A methodology is also described for capturing shocks, and simulation results are compared to the finite-volume formulation that is currently the primary method employed for routine engineering applications. The finite-element methodology is demonstrated to be more accurate than the finite-volume technology, particularly on tetrahedral meshes where the solutions obtained using the finite-volume scheme can suffer from adverse effects caused by bias in the grid. Although no effort has been made to date to optimize computational efficiency, the finite-element scheme is competitive with the finite-volume scheme in terms of computer time to reach convergence.
Cascades of Particles Moving at Finite Velocity in Hyperbolic Spaces
NASA Astrophysics Data System (ADS)
Cammarota, V.; Orsingher, E.
2008-12-01
A branching process of particles moving at finite velocity over the geodesic lines of the hyperbolic space (Poincaré half-plane and Poincaré disk) is examined. Each particle can split into two particles only once at Poisson spaced times and deviates orthogonally when splitted. At time t, after N( t) Poisson events, there are N( t)+1 particles moving along different geodesic lines. We are able to obtain the exact expression of the mean hyperbolic distance of the center of mass of the cloud of particles. We derive such mean hyperbolic distance from two different and independent ways and we study the behavior of the relevant expression as t increases and for different values of the parameters c (hyperbolic velocity of motion) and λ (rate of reproduction). The mean hyperbolic distance of each moving particle is also examined and a useful representation, as the distance of a randomly stopped particle moving over the main geodesic line, is presented.
NASA Technical Reports Server (NTRS)
Zhang, Zhibo; Meyer, Kerry G.; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin; Yu, Hongbin
2014-01-01
This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.
Data distribution method of workflow in the cloud environment
NASA Astrophysics Data System (ADS)
Wang, Yong; Wu, Junjuan; Wang, Ying
2017-08-01
Cloud computing for workflow applications provides the required high efficiency calculation and large storage capacity and it also brings challenges to the protection of trade secrets and other privacy data. Because of privacy data will cause the increase of the data transmission time, this paper presents a new data allocation algorithm based on data collaborative damage degree, to improve the existing data allocation strategy? Safety and public cloud computer algorithm depends on the private cloud; the static allocation method in the initial stage only to the non-confidential data division to improve the original data, in the operational phase will continue to generate data to dynamically adjust the data distribution scheme. The experimental results show that the improved method is effective in reducing the data transmission time.
NASA Technical Reports Server (NTRS)
Filyushkin, V. V.; Madronich, S.; Brasseur, G. P.; Petropavlovskikh, I. V.
1994-01-01
Based on a derivation of the two-stream daytime-mean equations of radiative flux transfer, a method for computing the daytime-mean actinic fluxes in the absorbing and scattering vertically inhomogeneous atmosphere is suggested. The method applies direct daytime integration of the particular solutions of the two-stream approximations or the source functions. It is valid for any duration of period of averaging. The merit of the method is that the multiple scattering computation is carried out only once for the whole averaging period. It can be implemented with a number of widely used two-stream approximations. The method agrees with the results obtained with 200-point multiple scattering calculations. The method was also tested in runs with a 1-km cloud layer with optical depth of 10, as well as with aerosol background. Comparison of the results obtained for a cloud subdivided into 20 layers with those obtained for a one-layer cloud with the same optical parameters showed that direct integration of particular solutions possesses an 'analytical' accuracy. In the case of the source function interpolation, the actinic fluxes calculated above the one-layer and 20-layer clouds agreed within 1%-1.5%, while below the cloud they may differ up to 5% (in the worst case). The ways of enhancing the accuracy (in a 'two-stream sense') and computational efficiency of the method are discussed.
NASA Astrophysics Data System (ADS)
Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.
2016-12-01
Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.
NASA Astrophysics Data System (ADS)
Smith, William L., Jr.
The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This thesis develops new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft in a wide range of cloud conditions. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS, the satellite icing detection and intensity accuracies are found to be about 90% and 70%, respectively. Mean differences between the imager IWC retrievals with those from CloudSat and Calipso are less than 30%. This level of closure in the cloud water budget can only be achieved by correcting for errors in the imager retrievals due to the simplifying but poor assumption that deep optically thick clouds are single-phase and vertically homogeneous. When applied to geostationary satellite data, the profiling method provides a real-time characterization of clouds in 4-D. This research should improve the utility of satellite imager data for quantitatively diagnosing and predicting clouds and their effects in weather and climate applications.
Night Sky Weather Monitoring System Using Fish-Eye CCD
NASA Astrophysics Data System (ADS)
Tomida, Takayuki; Saito, Yasunori; Nakamura, Ryo; Yamazaki, Katsuya
Telescope Array (TA) is international joint experiment observing ultra-high energy cosmic rays. TA employs fluorescence detection technique to observe cosmic rays. In this technique, tho existence of cloud significantly affects quality of data. Therefore, cloud monitoring provides important information. We are developing two new methods for evaluating night sky weather with pictures taken by charge-coupled device (CCD) camera. One is evaluating the amount of cloud with pixels brightness. The other is counting the number of stars with contour detection technique. The results of these methods show clear correlation, and we concluded both the analyses are reasonable methods for weather monitoring. We discuss reliability of the star counting method.
Finite-volume and partial quenching effects in the magnetic polarizability of the neutron
NASA Astrophysics Data System (ADS)
Hall, J. M. M.; Leinweber, D. B.; Young, R. D.
2014-03-01
There has been much progress in the experimental measurement of the electric and magnetic polarizabilities of the nucleon. Similarly, lattice QCD simulations have recently produced dynamical QCD results for the magnetic polarizability of the neutron approaching the chiral regime. In order to compare the lattice simulations with experiment, calculation of partial quenching and finite-volume effects is required prior to an extrapolation in quark mass to the physical point. These dependencies are described using chiral effective field theory. Corrections to the partial quenching effects associated with the sea-quark-loop electric charges are estimated by modeling corrections to the pion cloud. These are compared to the uncorrected lattice results. In addition, the behavior of the finite-volume corrections as a function of pion mass is explored. Box sizes of approximately 7 fm are required to achieve a result within 5% of the infinite-volume result at the physical pion mass. A variety of extrapolations are shown at different box sizes, providing a benchmark to guide future lattice QCD calculations of the magnetic polarizabilities. A relatively precise value for the physical magnetic polarizability of the neutron is presented, βn=1.93(11)stat(11)sys×10-4 fm3, which is in agreement with current experimental results.
Nonlocal and Mixed-Locality Multiscale Finite Element Methods
Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.
2018-03-27
In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less
Nonlocal and Mixed-Locality Multiscale Finite Element Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.
In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less
On the remote sensing of cloud properties from satellite infrared sounder data
NASA Technical Reports Server (NTRS)
Yeh, H. Y. M.
1984-01-01
A method for remote sensing of cloud parameters by using infrared sounder data has been developed on the basis of the parameterized infrared transfer equation applicable to cloudy atmospheres. The method is utilized for the retrieval of the cloud height, amount, and emissivity in 11 micro m region. Numerical analyses and retrieval experiments have been carried out by utilizing the synthetic sounder data for the theoretical study. The sensitivity of the numerical procedures to the measurement and instrument errors are also examined. The retrieved results are physically discussed and numerically compared with the model atmospheres. Comparisons reveal that the recovered cloud parameters agree reasonably well with the pre-assumed values. However, for cases when relatively thin clouds and/or small cloud fractional cover within a field of view are present, the recovered cloud parameters show considerable fluctuations. Experiments on the proposed algorithm are carried out utilizing High Resolution Infrared Sounder (HIRS/2) data of NOAA 6 and TIROS-N. Results of experiments show reasonably good comparisons with the surface reports and GOES satellite images.
Incorporation of multiple cloud layers for ultraviolet radiation modeling studies
NASA Technical Reports Server (NTRS)
Charache, Darryl H.; Abreu, Vincent J.; Kuhn, William R.; Skinner, Wilbert R.
1994-01-01
Cloud data sets compiled from surface observations were used to develop an algorithm for incorporating multiple cloud layers into a multiple-scattering radiative transfer model. Aerosol extinction and ozone data sets were also incorporated to estimate the seasonally averaged ultraviolet (UV) flux reaching the surface of the Earth in the Detroit, Michigan, region for the years 1979-1991, corresponding to Total Ozone Mapping Spectrometer (TOMS) version 6 ozone observations. The calculated UV spectrum was convolved with an erythema action spectrum to estimate the effective biological exposure for erythema. Calculations show that decreasing the total column density of ozone by 1% leads to an increase in erythemal exposure by approximately 1.1-1.3%, in good agreement with previous studies. A comparison of the UV radiation budget at the surface between a single cloud layer method and a multiple cloud layer method presented here is discussed, along with limitations of each technique. With improved parameterization of cloud properties, and as knowledge of biological effects of UV exposure increase, inclusion of multiple cloud layers may be important in accurately determining the biologically effective UV budget at the surface of the Earth.
Improved Modeling Tools Development for High Penetration Solar
DOE Office of Scientific and Technical Information (OSTI.GOV)
Washom, Byron; Meagher, Kevin
2014-12-11
One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motionmore » vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.« less
Linearized radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements
NASA Astrophysics Data System (ADS)
Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego
2018-07-01
In this paper, we describe several linearized radiative transfer models which can be used for the retrieval of cloud parameters from EPIC (Earth Polychromatic Imaging Camera) measurements. The approaches under examination are (1) the linearized forward approach, represented in this paper by the linearized discrete ordinate and matrix operator methods with matrix exponential, and (2) the forward-adjoint approach based on the discrete ordinate method with matrix exponential. To enhance the performance of the radiative transfer computations, the correlated k-distribution method and the Principal Component Analysis (PCA) technique are used. We provide a compact description of the proposed methods, as well as a numerical analysis of their accuracy and efficiency when simulating EPIC measurements in the oxygen A-band channel at 764 nm. We found that the computation time of the forward-adjoint approach using the correlated k-distribution method in conjunction with PCA is approximately 13 s for simultaneously computing the derivatives with respect to cloud optical thickness and cloud top height.
Point cloud registration from local feature correspondences-Evaluation on challenging datasets.
Petricek, Tomas; Svoboda, Tomas
2017-01-01
Registration of laser scans, or point clouds in general, is a crucial step of localization and mapping with mobile robots or in object modeling pipelines. A coarse alignment of the point clouds is generally needed before applying local methods such as the Iterative Closest Point (ICP) algorithm. We propose a feature-based approach to point cloud registration and evaluate the proposed method and its individual components on challenging real-world datasets. For a moderate overlap between the laser scans, the method provides a superior registration accuracy compared to state-of-the-art methods including Generalized ICP, 3D Normal-Distribution Transform, Fast Point-Feature Histograms, and 4-Points Congruent Sets. Compared to the surface normals, the points as the underlying features yield higher performance in both keypoint detection and establishing local reference frames. Moreover, sign disambiguation of the basis vectors proves to be an important aspect in creating repeatable local reference frames. A novel method for sign disambiguation is proposed which yields highly repeatable reference frames.
A laboratory investigation of the variability of cloud reflected radiance fields
NASA Technical Reports Server (NTRS)
Mckee, T. B.; Cox, S. K.
1986-01-01
A method to determine the radiative properties of complex cloud fields was developed. A Cloud field optical simulator (CFOS) was constructed to simulate the interaction of cloud fields with visible radiation. The CFOS was verified by comparing experimental results from it with calculations performed with a Monte Carlo radiative transfer model. A software library was developed to process, reduce, and display CFOS data. The CFSOS was utilized to study the reflected radiane patterns from simulated cloud fields.
A Fourier approach to cloud motion estimation
NASA Technical Reports Server (NTRS)
Arking, A.; Lo, R. C.; Rosenfield, A.
1977-01-01
A Fourier technique is described for estimating cloud motion from pairs of pictures using the phase of the cross spectral density. The method allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. Results obtained are presented and compared with the results of a Fourier domain cross correlation scheme. Using both artificial and real cloud data show that the technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects.
APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels
NASA Astrophysics Data System (ADS)
Klüser, L.; Killius, N.; Gesell, G.
2015-10-01
The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.
Improving finite element results in modeling heart valve mechanics.
Earl, Emily; Mohammadi, Hadi
2018-06-01
Finite element analysis is a well-established computational tool which can be used for the analysis of soft tissue mechanics. Due to the structural complexity of the leaflet tissue of the heart valve, the currently available finite element models do not adequately represent the leaflet tissue. A method of addressing this issue is to implement computationally expensive finite element models, characterized by precise constitutive models including high-order and high-density mesh techniques. In this study, we introduce a novel numerical technique that enhances the results obtained from coarse mesh finite element models to provide accuracy comparable to that of fine mesh finite element models while maintaining a relatively low computational cost. Introduced in this study is a method by which the computational expense required to solve linear and nonlinear constitutive models, commonly used in heart valve mechanics simulations, is reduced while continuing to account for large and infinitesimal deformations. This continuum model is developed based on the least square algorithm procedure coupled with the finite difference method adhering to the assumption that the components of the strain tensor are available at all nodes of the finite element mesh model. The suggested numerical technique is easy to implement, practically efficient, and requires less computational time compared to currently available commercial finite element packages such as ANSYS and/or ABAQUS.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lisitsa, Vadim, E-mail: lisitsavv@ipgg.sbras.ru; Novosibirsk State University, Novosibirsk; Tcheverda, Vladimir
We present an algorithm for the numerical simulation of seismic wave propagation in models with a complex near surface part and free surface topography. The approach is based on the combination of finite differences with the discontinuous Galerkin method. The discontinuous Galerkin method can be used on polyhedral meshes; thus, it is easy to handle the complex surfaces in the models. However, this approach is computationally intense in comparison with finite differences. Finite differences are computationally efficient, but in general, they require rectangular grids, leading to the stair-step approximation of the interfaces, which causes strong diffraction of the wavefield. Inmore » this research we present a hybrid algorithm where the discontinuous Galerkin method is used in a relatively small upper part of the model and finite differences are applied to the main part of the model.« less
Periodic trim solutions with hp-version finite elements in time
NASA Technical Reports Server (NTRS)
Peters, David A.; Hou, Lin-Jun
1990-01-01
Finite elements in time as an alternative strategy for rotorcraft trim problems are studied. The research treats linear flap and linearized flap-lag response both for quasi-trim and trim cases. The connection between Fourier series analysis and hp-finite elements for periodic a problem is also examined. It is proved that Fourier series is a special case of space-time finite elements in which one element is used with a strong displacement formulation. Comparisons are made with respect to accuracy among Fourier analysis, displacement methods, and mixed methods over a variety parameters. The hp trade-off is studied for the periodic trim problem to provide an optimum step size and order of polynomial for a given error criteria. It is found that finite elements in time can outperform Fourier analysis for periodic problems, and for some given error criteria. The mixed method provides better results than does the displacement method.
Cooley, Richard L.
1992-01-01
MODFE, a modular finite-element model for simulating steady- or unsteady-state, area1 or axisymmetric flow of ground water in a heterogeneous anisotropic aquifer is documented in a three-part series of reports. In this report, part 2, the finite-element equations are derived by minimizing a functional of the difference between the true and approximate hydraulic head, which produces equations that are equivalent to those obtained by either classical variational or Galerkin techniques. Spatial finite elements are triangular with linear basis functions, and temporal finite elements are one dimensional with linear basis functions. Physical processes that can be represented by the model include (1) confined flow, unconfined flow (using the Dupuit approximation), or a combination of both; (2) leakage through either rigid or elastic confining units; (3) specified recharge or discharge at points, along lines, or areally; (4) flow across specified-flow, specified-head, or head-dependent boundaries; (5) decrease of aquifer thickness to zero under extreme water-table decline and increase of aquifer thickness from zero as the water table rises; and (6) head-dependent fluxes from springs, drainage wells, leakage across riverbeds or confining units combined with aquifer dewatering, and evapotranspiration. The matrix equations produced by the finite-element method are solved by the direct symmetric-Doolittle method or the iterative modified incomplete-Cholesky conjugate-gradient method. The direct method can be efficient for small- to medium-sized problems (less than about 500 nodes), and the iterative method is generally more efficient for larger-sized problems. Comparison of finite-element solutions with analytical solutions for five example problems demonstrates that the finite-element model can yield accurate solutions to ground-water flow problems.
Beyond multi-fractals: surrogate time series and fields
NASA Astrophysics Data System (ADS)
Venema, V.; Simmer, C.
2007-12-01
Most natural complex are characterised by variability on a large range of temporal and spatial scales. The two main methodologies to generate such structures are Fourier/FARIMA based algorithms and multifractal methods. The former is restricted to Gaussian data, whereas the latter requires the structure to be self-similar. This work will present so-called surrogate data as an alternative that works with any (empirical) distribution and power spectrum. The best-known surrogate algorithm is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm. We have studied six different geophysical time series (two clouds, runoff of a small and a large river, temperature and rain) and their surrogates. The power spectra and consequently the 2nd order structure functions were replicated accurately. Even the fourth order structure function was more accurately reproduced by the surrogates as would be possible by a fractal method, because the measured structure deviated too strong from fractal scaling. Only in case of the daily rain sums a fractal method could have been more accurate. Just as Fourier and multifractal methods, the current surrogates are not able to model the asymmetric increment distributions observed for runoff, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found differences for the structure functions on small scales. Surrogate methods are especially valuable for empirical studies, because the time series and fields that are generated are able to mimic measured variables accurately. Our main application is radiative transfer through structured clouds. Like many geophysical fields, clouds can only be sampled sparsely, e.g. with in-situ airborne instruments. However, for radiative transfer calculations we need full 3-dimensional cloud fields. A first study relating the measured properties of the cloud droplets and the radiative properties of the cloud field by generating surrogate cloud fields yielded good results within the measurement error. A further test of the suitability of the surrogate clouds for radiative transfer is evaluated by comparing the radiative properties of model cloud fields of sparse cumulus and stratocumulus with their surrogate fields. The bias and root mean square error in various radiative properties is small and the deviations in the radiances and irradiances are not statistically significant, i.e. these deviations can be attributed to the Monte Carlo noise of the radiative transfer calculations. We compared these results with optical properties of synthetic clouds that have either the correct distribution (but no spatial correlations) or the correct power spectrum (but a Gaussian distribution). These clouds did show statistical significant deviations. For more information see: http://www.meteo.uni-bonn.de/venema/themes/surrogates/
NASA Astrophysics Data System (ADS)
Sotokoba, Yasumasa; Okajima, Kenji; Iida, Toshiaki; Tanaka, Tadatsugu
We propose the trenchless box culvert construction method to construct box culverts in small covering soil layers while keeping roads or tracks open. When we use this construction method, it is necessary to clarify deformation and shear failure by excavation of grounds. In order to investigate the soil behavior, model experiments and elasto-plactic finite element analysis were performed. In the model experiments, it was shown that the shear failure was developed from the end of the roof to the toe of the boundary surface. In the finite element analysis, a shear band effect was introduced. Comparing the observed shear bands in model experiments with computed maximum shear strain contours, it was found that the observed direction of the shear band could be simulated reasonably by the finite element analysis. We may say that the finite element method used in this study is useful tool for this construction method.
An extension of the finite cell method using boolean operations
NASA Astrophysics Data System (ADS)
Abedian, Alireza; Düster, Alexander
2017-05-01
In the finite cell method, the fictitious domain approach is combined with high-order finite elements. The geometry of the problem is taken into account by integrating the finite cell formulation over the physical domain to obtain the corresponding stiffness matrix and load vector. In this contribution, an extension of the FCM is presented wherein both the physical and fictitious domain of an element are simultaneously evaluated during the integration. In the proposed extension of the finite cell method, the contribution of the stiffness matrix over the fictitious domain is subtracted from the cell, resulting in the desired stiffness matrix which reflects the contribution of the physical domain only. This method results in an exponential rate of convergence for porous domain problems with a smooth solution and accurate integration. In addition, it reduces the computational cost, especially when applying adaptive integration schemes based on the quadtree/octree. Based on 2D and 3D problems of linear elastostatics, numerical examples serve to demonstrate the efficiency and accuracy of the proposed method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mohamed, M. Shadi, E-mail: m.s.mohamed@durham.ac.uk; Seaid, Mohammed; Trevelyan, Jon
2013-10-15
We investigate the effectiveness of the partition-of-unity finite element method for transient conduction–radiation problems in diffusive grey media. The governing equations consist of a semi-linear transient heat equation for the temperature field and a stationary diffusion approximation to the radiation in grey media. The coupled equations are integrated in time using a semi-implicit method in the finite element framework. We show that for the considered problems, a combination of hyperbolic and exponential enrichment functions based on an approximation of the boundary layer leads to improved accuracy compared to the conventional finite element method. It is illustrated that this approach canmore » be more efficient than using h adaptivity to increase the accuracy of the finite element method near the boundary walls. The performance of the proposed partition-of-unity method is analyzed on several test examples for transient conduction–radiation problems in two space dimensions.« less
A quasi-Lagrangian finite element method for the Navier-Stokes equations in a time-dependent domain
NASA Astrophysics Data System (ADS)
Lozovskiy, Alexander; Olshanskii, Maxim A.; Vassilevski, Yuri V.
2018-05-01
The paper develops a finite element method for the Navier-Stokes equations of incompressible viscous fluid in a time-dependent domain. The method builds on a quasi-Lagrangian formulation of the problem. The paper provides stability and convergence analysis of the fully discrete (finite-difference in time and finite-element in space) method. The analysis does not assume any CFL time-step restriction, it rather needs mild conditions of the form $\\Delta t\\le C$, where $C$ depends only on problem data, and $h^{2m_u+2}\\le c\\,\\Delta t$, $m_u$ is polynomial degree of velocity finite element space. Both conditions result from a numerical treatment of practically important non-homogeneous boundary conditions. The theoretically predicted convergence rate is confirmed by a set of numerical experiments. Further we apply the method to simulate a flow in a simplified model of the left ventricle of a human heart, where the ventricle wall dynamics is reconstructed from a sequence of contrast enhanced Computed Tomography images.
A method for modeling finite-core vortices in wake-flow calculations
NASA Technical Reports Server (NTRS)
Stremel, P. M.
1984-01-01
A numerical method for computing nonplanar vortex wakes represented by finite-core vortices is presented. The approach solves for the velocity on an Eulerian grid, using standard finite-difference techniques; the vortex wake is tracked by Lagrangian methods. In this method, the distribution of continuous vorticity in the wake is replaced by a group of discrete vortices. An axially symmetric distribution of vorticity about the center of each discrete vortex is used to represent the finite-core model. Two distributions of vorticity, or core models, are investigated: a finite distribution of vorticity represented by a third-order polynomial, and a continuous distribution of vorticity throughout the wake. The method provides for a vortex-core model that is insensitive to the mesh spacing. Results for a simplified case are presented. Computed results for the roll-up of a vortex wake generated by wings with different spanwise load distributions are presented; contour plots of the flow-field velocities are included; and comparisons are made of the computed flow-field velocities with experimentally measured velocities.
Li, Wei; Yi, Huangjian; Zhang, Qitan; Chen, Duofang; Liang, Jimin
2012-01-01
An extended finite element method (XFEM) for the forward model of 3D optical molecular imaging is developed with simplified spherical harmonics approximation (SPN). In XFEM scheme of SPN equations, the signed distance function is employed to accurately represent the internal tissue boundary, and then it is used to construct the enriched basis function of the finite element scheme. Therefore, the finite element calculation can be carried out without the time-consuming internal boundary mesh generation. Moreover, the required overly fine mesh conforming to the complex tissue boundary which leads to excess time cost can be avoided. XFEM conveniences its application to tissues with complex internal structure and improves the computational efficiency. Phantom and digital mouse experiments were carried out to validate the efficiency of the proposed method. Compared with standard finite element method and classical Monte Carlo (MC) method, the validation results show the merits and potential of the XFEM for optical imaging. PMID:23227108
Li, Wei; Yi, Huangjian; Zhang, Qitan; Chen, Duofang; Liang, Jimin
2012-01-01
An extended finite element method (XFEM) for the forward model of 3D optical molecular imaging is developed with simplified spherical harmonics approximation (SP(N)). In XFEM scheme of SP(N) equations, the signed distance function is employed to accurately represent the internal tissue boundary, and then it is used to construct the enriched basis function of the finite element scheme. Therefore, the finite element calculation can be carried out without the time-consuming internal boundary mesh generation. Moreover, the required overly fine mesh conforming to the complex tissue boundary which leads to excess time cost can be avoided. XFEM conveniences its application to tissues with complex internal structure and improves the computational efficiency. Phantom and digital mouse experiments were carried out to validate the efficiency of the proposed method. Compared with standard finite element method and classical Monte Carlo (MC) method, the validation results show the merits and potential of the XFEM for optical imaging.
Lee, Jonathan K.; Froehlich, David C.
1987-01-01
Published literature on the application of the finite-element method to solving the equations of two-dimensional surface-water flow in the horizontal plane is reviewed in this report. The finite-element method is ideally suited to modeling two-dimensional flow over complex topography with spatially variable resistance. A two-dimensional finite-element surface-water flow model with depth and vertically averaged velocity components as dependent variables allows the user great flexibility in defining geometric features such as the boundaries of a water body, channels, islands, dikes, and embankments. The following topics are reviewed in this report: alternative formulations of the equations of two-dimensional surface-water flow in the horizontal plane; basic concepts of the finite-element method; discretization of the flow domain and representation of the dependent flow variables; treatment of boundary conditions; discretization of the time domain; methods for modeling bottom, surface, and lateral stresses; approaches to solving systems of nonlinear equations; techniques for solving systems of linear equations; finite-element alternatives to Galerkin's method of weighted residuals; techniques of model validation; and preparation of model input data. References are listed in the final chapter.
A comparative study of an ABC and an artificial absorber for truncating finite element meshes
NASA Technical Reports Server (NTRS)
Oezdemir, T.; Volakis, John L.
1993-01-01
The type of mesh termination used in the context of finite element formulations plays a major role on the efficiency and accuracy of the field solution. The performance of an absorbing boundary condition (ABC) and an artificial absorber (a new concept) for terminating the finite element mesh was evaluated. This analysis is done in connection with the problem of scattering by a finite slot array in a thick ground plane. The two approximate mesh truncation schemes are compared with the exact finite element-boundary integral (FEM-BI) method in terms of accuracy and efficiency. It is demonstrated that both approximate truncation schemes yield reasonably accurate results even when the mesh is extended only 0.3 wavelengths away from the array aperture. However, the artificial absorber termination method leads to a substantially more efficient solution. Moreover, it is shown that the FEM-BI method remains quite competitive with the FEM-artificial absorber method when the FFT is used for computing the matrix-vector products in the iterative solution algorithm. These conclusions are indeed surprising and of major importance in electromagnetic simulations based on the finite element method.
NASA Technical Reports Server (NTRS)
Endo, T.; Oden, J. T.; Becker, E. B.; Miller, T.
1984-01-01
Finite element methods for the analysis of bifurcations, limit-point behavior, and unilateral frictionless contact of elastic bodies undergoing finite deformation are presented. Particular attention is given to the development and application of Riks-type algorithms for the analysis of limit points and exterior penalty methods for handling the unilateral constraints. Applications focus on the problem of finite axisymmetric deformations, snap-through, and inflation of thick rubber spherical shells.
Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
Loganathan, Shyamala; Mukherjee, Saswati
2015-01-01
Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166
Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.
Loganathan, Shyamala; Mukherjee, Saswati
2015-01-01
Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.
Nowcasting Cloud Fields for U.S. Air Force Special Operations
2017-03-01
application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES
NASA Astrophysics Data System (ADS)
Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti
2016-04-01
Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.
The use of satellite data assimilation methods in regional NWP for solar irradiance forecasting
NASA Astrophysics Data System (ADS)
Kurzrock, Frederik; Cros, Sylvain; Chane-Ming, Fabrice; Potthast, Roland; Linguet, Laurent; Sébastien, Nicolas
2016-04-01
As an intermittent energy source, the injection of solar power into electricity grids requires irradiance forecasting in order to ensure grid stability. On time scales of more than six hours ahead, numerical weather prediction (NWP) is recognized as the most appropriate solution. However, the current representation of clouds in NWP models is not sufficiently precise for an accurate forecast of solar irradiance at ground level. Dynamical downscaling does not necessarily increase the quality of irradiance forecasts. Furthermore, incorrectly simulated cloud evolution is often the cause of inaccurate atmospheric analyses. In non-interconnected tropical areas, the large amplitudes of solar irradiance variability provide abundant solar yield but present significant problems for grid safety. Irradiance forecasting is particularly important for solar power stakeholders in these regions where PV electricity penetration is increasing. At the same time, NWP is markedly more challenging in tropic areas than in mid-latitudes due to the special characteristics of tropical homogeneous convective air masses. Numerous data assimilation methods and strategies have evolved and been applied to a large variety of global and regional NWP models in the recent decades. Assimilating data from geostationary meteorological satellites is an appropriate approach. Indeed, models converting radiances measured by satellites into cloud properties already exist. Moreover, data are available at high temporal frequencies, which enable a pertinent cloud cover evolution modelling for solar energy forecasts. In this work, we present a survey of different approaches which aim at improving cloud cover forecasts using the assimilation of geostationary meteorological satellite data into regional NWP models. Various approaches have been applied to a variety of models and satellites and in different regions of the world. Current methods focus on the assimilation of cloud-top information, derived from infrared channels. For example, those information have been directly assimilated by modifying the water vapour profile in the initial conditions of the WRF model in California using GOES satellite imagery. In Europe, the assimilation of cloud-top height and relative humidity has been performed in an indirect approach using an ensemble Kalman filter. In this case Meteosat SEVIRI cloud information has been assimilated in the COSMO model. Although such methods generally provide improved cloud cover forecasts in mid-latitudes, the major limitation is that only clear-sky or completely cloudy cases can be considered. Indeed, fractional clouds cause a measured signal mixing cold clouds and warmer Earth surface. If the model's initial state is directly forced by cloud properties observed by satellite, the changed model fields have to be smoothed in order to avoid numerical instability. Other crucial aspects which influence forecast quality in the case of satellite radiance assimilation are channel selection, bias and error treatment. The overall promising satellite data assimilation methods in regional NWP have not yet been explicitly applied and tested under tropical conditions. Therefore, a deeper understanding on the benefits of such methods is necessary to improve irradiance forecast schemes.
Cloud Service Provider Methods for Managing Insider Threats: Analysis Phase 1
2013-11-01
of Standards and Technology (NIST) Special Publication 800-145 (NIST SP 800-145) defines three types of cloud services : Software as a Service ( SaaS ...among these three models. NIST SP 800-145 describes the three service models as follows: SaaS —The capability provided to the consumer is to use the...Cloud Service Provider Methods for Managing Insider Threats: Analysis Phase I Greg Porter November 2013 TECHNICAL NOTE CMU/SEI-2013-TN-020
An efficient global energy optimization approach for robust 3D plane segmentation of point clouds
NASA Astrophysics Data System (ADS)
Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian
2018-03-01
Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man
2006-01-01
A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.
NASA Astrophysics Data System (ADS)
Wu, Zedong; Alkhalifah, Tariq
2018-07-01
Numerical simulation of the acoustic wave equation in either isotropic or anisotropic media is crucial to seismic modeling, imaging and inversion. Actually, it represents the core computation cost of these highly advanced seismic processing methods. However, the conventional finite-difference method suffers from severe numerical dispersion errors and S-wave artifacts when solving the acoustic wave equation for anisotropic media. We propose a method to obtain the finite-difference coefficients by comparing its numerical dispersion with the exact form. We find the optimal finite difference coefficients that share the dispersion characteristics of the exact equation with minimal dispersion error. The method is extended to solve the acoustic wave equation in transversely isotropic (TI) media without S-wave artifacts. Numerical examples show that the method is highly accurate and efficient.
A simple finite element method for non-divergence form elliptic equation
Mu, Lin; Ye, Xiu
2017-03-01
Here, we develop a simple finite element method for solving second order elliptic equations in non-divergence form by combining least squares concept with discontinuous approximations. This simple method has a symmetric and positive definite system and can be easily analyzed and implemented. We could have also used general meshes with polytopal element and hanging node in the method. We prove that our finite element solution approaches to the true solution when the mesh size approaches to zero. Numerical examples are tested that demonstrate the robustness and flexibility of the method.
A simple finite element method for non-divergence form elliptic equation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mu, Lin; Ye, Xiu
Here, we develop a simple finite element method for solving second order elliptic equations in non-divergence form by combining least squares concept with discontinuous approximations. This simple method has a symmetric and positive definite system and can be easily analyzed and implemented. We could have also used general meshes with polytopal element and hanging node in the method. We prove that our finite element solution approaches to the true solution when the mesh size approaches to zero. Numerical examples are tested that demonstrate the robustness and flexibility of the method.
An adaptive finite element method for the inequality-constrained Reynolds equation
NASA Astrophysics Data System (ADS)
Gustafsson, Tom; Rajagopal, Kumbakonam R.; Stenberg, Rolf; Videman, Juha
2018-07-01
We present a stabilized finite element method for the numerical solution of cavitation in lubrication, modeled as an inequality-constrained Reynolds equation. The cavitation model is written as a variable coefficient saddle-point problem and approximated by a residual-based stabilized method. Based on our recent results on the classical obstacle problem, we present optimal a priori estimates and derive novel a posteriori error estimators. The method is implemented as a Nitsche-type finite element technique and shown in numerical computations to be superior to the usually applied penalty methods.
1983-03-01
AN ANALYSIS OF A FINITE ELEMENT METHOD FOR CONVECTION- DIFFUSION PROBLEMS PART II: A POSTERIORI ERROR ESTIMATES AND ADAPTIVITY by W. G. Szymczak Y 6a...PERIOD COVERED AN ANALYSIS OF A FINITE ELEMENT METHOD FOR final life of the contract CONVECTION- DIFFUSION PROBLEM S. Part II: A POSTERIORI ERROR ...Element Method for Convection- Diffusion Problems. Part II: A Posteriori Error Estimates and Adaptivity W. G. Szvmczak and I. Babu~ka# Laboratory for
NASA Astrophysics Data System (ADS)
Hakoda, Christopher; Lissenden, Clifford; Rose, Joseph L.
2018-04-01
Dispersion curves are essential to any guided wave NDE project. The Semi-Analytical Finite Element (SAFE) method has significantly increased the ease by which these curves can be calculated. However, due to misconceptions regarding theory and fragmentation based on different finite-element software, the theory has stagnated, and adoption by researchers who are new to the field has been slow. This paper focuses on the relationship between the SAFE formulation and finite element theory, and the implementation of the SAFE method in a weak form for plates, pipes, layered waveguides/composites, curved waveguides, and arbitrary cross-sections is shown. The benefits of the weak form are briefly described, as is implementation in open-source and commercial finite element software.
Least-squares finite element methods for compressible Euler equations
NASA Technical Reports Server (NTRS)
Jiang, Bo-Nan; Carey, G. F.
1990-01-01
A method based on backward finite differencing in time and a least-squares finite element scheme for first-order systems of partial differential equations in space is applied to the Euler equations for gas dynamics. The scheme minimizes the L-sq-norm of the residual within each time step. The method naturally generates numerical dissipation proportional to the time step size. An implicit method employing linear elements has been implemented and proves robust. For high-order elements, computed solutions based on the L-sq method may have oscillations for calculations at similar time step sizes. To overcome this difficulty, a scheme which minimizes the weighted H1-norm of the residual is proposed and leads to a successful scheme with high-degree elements. Finally, a conservative least-squares finite element method is also developed. Numerical results for two-dimensional problems are given to demonstrate the shock resolution of the methods and compare different approaches.
Free Mesh Method: fundamental conception, algorithms and accuracy study
YAGAWA, Genki
2011-01-01
The finite element method (FEM) has been commonly employed in a variety of fields as a computer simulation method to solve such problems as solid, fluid, electro-magnetic phenomena and so on. However, creation of a quality mesh for the problem domain is a prerequisite when using FEM, which becomes a major part of the cost of a simulation. It is natural that the concept of meshless method has evolved. The free mesh method (FMM) is among the typical meshless methods intended for particle-like finite element analysis of problems that are difficult to handle using global mesh generation, especially on parallel processors. FMM is an efficient node-based finite element method that employs a local mesh generation technique and a node-by-node algorithm for the finite element calculations. In this paper, FMM and its variation are reviewed focusing on their fundamental conception, algorithms and accuracy. PMID:21558752
Response of deep and shallow tropical maritime cumuli to large-scale processes
NASA Technical Reports Server (NTRS)
Yanai, M.; Chu, J.-H.; Stark, T. E.; Nitta, T.
1976-01-01
The bulk diagnostic method of Yanai et al. (1973) and a simplified version of the spectral diagnostic method of Nitta (1975) are used for a more quantitative evaluation of the response of various types of cumuliform clouds to large-scale processes, using the same data set in the Marshall Islands area for a 100-day period in 1956. The dependence of the cloud mass flux distribution on radiative cooling, large-scale vertical motion, and evaporation from the sea is examined. It is shown that typical radiative cooling rates in the tropics tend to produce a bimodal distribution of mass spectrum exhibiting deep and shallow clouds. The bimodal distribution is further enhanced when the large-scale vertical motion is upward, and a nearly unimodal distribution of shallow clouds prevails when the relative cooling is compensated by the heating due to the large-scale subsidence. Both deep and shallow clouds are modulated by large-scale disturbances. The primary role of surface evaporation is to maintain the moisture flux at the cloud base.
CO2 forcing induces semi-direct effects with consequences for climate feedback interpretations
NASA Astrophysics Data System (ADS)
Andrews, Timothy; Forster, Piers M.
2008-02-01
Climate forcing and feedbacks are diagnosed from seven slab-ocean GCMs for 2 × CO2 using a regression method. Results are compared to those using conventional methodologies to derive a semi-direct forcing due to tropospheric adjustment, analogous to the semi-direct effect of absorbing aerosols. All models show a cloud semi-direct effect, indicating a rapid cloud response to CO2; cloud typically decreases, enhancing the warming. Similarly there is evidence of semi-direct effects from water-vapour, lapse-rate, ice and snow. Previous estimates of climate feedbacks are unlikely to have taken these semi-direct effects into account and so misinterpret processes as feedbacks that depend only on the forcing, but not the global surface temperature. We show that the actual cloud feedback is smaller than what previous methods suggest and that a significant part of the cloud response and the large spread between previous model estimates of cloud feedback is due to the semi-direct forcing.
NASA Astrophysics Data System (ADS)
Nar, Sevda Yeliz; Cakir, Altan
2018-02-01
Particles produced by nuclear decay, cosmic radiation and reactions can be identified through various methods. One of these methods that has been effective in the last century is the cloud chamber. The chamber makes visible cosmic particles that we are exposed to radiation per second. Diffusion cloud chamber is a kind of cloud chamber that is cooled by dry ice. This traditional model has some application difficulties. In this work, Peltier-based cloud chamber cooled by thermoelectric modules is studied. The new model provided uniformly cooled base of the chamber, moreover, it has longer lifetime than the traditional chamber in terms of observation time. This gain has reduced the costs which spent each time for cosmic particle observation. The chamber is an easy-to-use system according to traditional diffusion cloud chamber. The new model is portable, easier to make, and can be used in the nuclear physics experiments. In addition, it would be very useful to observe Muons which are the direct evidence for Lorentz contraction and time expansion predicted by Einsteins special relativity principle.
Estimation of Cloud Fraction Profile in Shallow Convection Using a Scanning Cloud Radar
Oue, Mariko; Kollias, Pavlos; North, Kirk W.; ...
2016-10-18
Large spatial heterogeneities in shallow convection result in uncertainties in estimations of domain-averaged cloud fraction profiles (CFP). This issue is addressed using large eddy simulations of shallow convection over land coupled with a radar simulator. Results indicate that zenith profiling observations are inadequate to provide reliable CFP estimates. Use of Scanning Cloud Radar (SCR), performing a sequence of cross-wind horizon-to-horizon scans, is not straightforward due to the strong dependence of radar sensitivity to target distance. An objective method for estimating domain-averaged CFP is proposed that uses observed statistics of SCR hydrometeor detection with height to estimate optimum sampling regions. Thismore » method shows good agreement with the model CFP. Results indicate that CFP estimates require more than 35 min of SCR scans to converge on the model domain average. Lastly, the proposed technique is expected to improve our ability to compare model output with cloud radar observations in shallow cumulus cloud conditions.« less
NASA Technical Reports Server (NTRS)
Reddy, C. J.; Deshpande, M. D.; Cockrell, C. R.; Beck, F. B.
1995-01-01
A combined finite element method (FEM) and method of moments (MoM) technique is presented to analyze the radiation characteristics of a cavity-fed aperture in three dimensions. Generalized feed modeling has been done using the modal expansion of fields in the feed structure. Numerical results for some feeding structures such as a rectangular waveguide, circular waveguide, and coaxial line are presented. The method also uses the geometrical theory of diffraction (GTD) to predict the effect of a finite ground plane on radiation characteristics. Input admittance calculations for open radiating structures such as a rectangular waveguide, a circular waveguide, and a coaxial line are shown. Numerical data for a coaxial-fed cavity with finite ground plane are verified with experimental data.
NASA Astrophysics Data System (ADS)
Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong
2018-03-01
This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.
Mohammadi, Amrollah; Ahmadian, Alireza; Rabbani, Shahram; Fattahi, Ehsan; Shirani, Shapour
2017-12-01
Finite element models for estimation of intraoperative brain shift suffer from huge computational cost. In these models, image registration and finite element analysis are two time-consuming processes. The proposed method is an improved version of our previously developed Finite Element Drift (FED) registration algorithm. In this work the registration process is combined with the finite element analysis. In the Combined FED (CFED), the deformation of whole brain mesh is iteratively calculated by geometrical extension of a local load vector which is computed by FED. While the processing time of the FED-based method including registration and finite element analysis was about 70 s, the computation time of the CFED was about 3.2 s. The computational cost of CFED is almost 50% less than similar state of the art brain shift estimators based on finite element models. The proposed combination of registration and structural analysis can make the calculation of brain deformation much faster. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Toth, L. V.; Mattila, K.; Haikala, L.; Balazs, L. G.
1992-01-01
The spectra of the 21cm HI radiation from the direction of L1780, a small high-galactic latitude dark/molecular cloud, were analyzed by multivariate methods. Factor analysis was performed on HI (21cm) spectra in order to separate the different components responsible for the spectral features. The rotated, orthogonal factors explain the spectra as a sum of radiation from the background (an extended HI emission layer), and from the L1780 dark cloud. The coefficients of the cloud-indicator factors were used to locate the HI 'halo' of the molecular cloud. Our statistically derived 'background' and 'cloud' spectral profiles, as well as the spatial distribution of the HI halo emission distribution were compared to the results of a previous study which used conventional methods analyzing nearly the same data set.
A particle finite element method for machining simulations
NASA Astrophysics Data System (ADS)
Sabel, Matthias; Sator, Christian; Müller, Ralf
2014-07-01
The particle finite element method (PFEM) appears to be a convenient technique for machining simulations, since the geometry and topology of the problem can undergo severe changes. In this work, a short outline of the PFEM-algorithm is given, which is followed by a detailed description of the involved operations. The -shape method, which is used to track the topology, is explained and tested by a simple example. Also the kinematics and a suitable finite element formulation are introduced. To validate the method simple settings without topological changes are considered and compared to the standard finite element method for large deformations. To examine the performance of the method, when dealing with separating material, a tensile loading is applied to a notched plate. This investigation includes a numerical analysis of the different meshing parameters, and the numerical convergence is studied. With regard to the cutting simulation it is found that only a sufficiently large number of particles (and thus a rather fine finite element discretisation) leads to converged results of process parameters, such as the cutting force.
A Least-Squares-Based Weak Galerkin Finite Element Method for Second Order Elliptic Equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mu, Lin; Wang, Junping; Ye, Xiu
Here, in this article, we introduce a least-squares-based weak Galerkin finite element method for the second order elliptic equation. This new method is shown to provide very accurate numerical approximations for both the primal and the flux variables. In contrast to other existing least-squares finite element methods, this new method allows us to use discontinuous approximating functions on finite element partitions consisting of arbitrary polygon/polyhedron shapes. We also develop a Schur complement algorithm for the resulting discretization problem by eliminating all the unknowns that represent the solution information in the interior of each element. Optimal order error estimates for bothmore » the primal and the flux variables are established. An extensive set of numerical experiments are conducted to demonstrate the robustness, reliability, flexibility, and accuracy of the least-squares-based weak Galerkin finite element method. Finally, the numerical examples cover a wide range of applied problems, including singularly perturbed reaction-diffusion equations and the flow of fluid in porous media with strong anisotropy and heterogeneity.« less