A Warm-Bin–Cold-Bulk Hybrid Cloud Microphysical Model*

2012 ◽  
Vol 69 (5) ◽  
pp. 1474-1497 ◽  
Author(s):  
Ryo Onishi ◽  
Keiko Takahashi
Keyword(s):  
Hybrid Approach ◽  
Three Dimensional ◽  
Solid Particles ◽  
Hybrid Cloud ◽  
Shallow Convection ◽  
Computationally Efficient ◽  
One Dimensional ◽  
Mixing Ratios ◽  
Cloud Ice ◽  
Ice Phase

Abstract This study describes a newly developed bin–bulk hybrid cloud microphysical model named MSSG-Bin, which has been implemented in the Multi-Scale Simulator for the Geoenvironment (MSSG). In the hybrid approach, a spectral bin scheme is used for liquid droplets, while a bulk scheme is used for solid particles. That is, the expensive but more reliable spectral bin scheme treats the relatively well-understood physics of the liquid phase, and the computationally efficient but less robust bulk scheme is used to treat the poorly understood physics of the ice phase. In the bulk part, the prognostic variables are the mixing ratios of cloud ice, snow, and graupel and the number density of cloud ice particles. The bulk component is consistent with MSSG-Bulk, which is a conventional bulk model implemented in MSSG. One-dimensional kinetic simulations and three-dimensional cloud simulations have confirmed the reliability of MSSG-Bin for warm clouds, free from the approximations made in bulk parameterizations, and its applicability to cold clouds, without the significant additional costs required for a bin treatment of the ice phase. Compared with MSSG-Bulk, MSSG-Bin with 33 bins requires 8.3 times more floating-point operations for a one-dimensional shallow convection case, and 4.9 times more for a three-dimensional shallow convection case. Present results have shown the feasibility of using this model for a 25-m-resolution simulation of shallow cumulus on a 512 × 512 × 200 grid.

Phenomenological Approach to Flow and Volume Change in Soils and Other Media

1995 ◽  
Vol 48 (10) ◽  
pp. 650-658 ◽  
Author(s):  
J. R. Philip
Keyword(s):  
Volume Change ◽  
Colloidal Particles ◽  
Three Dimensional ◽  
Phenomenological Approach ◽  
Solid Particles ◽  
Soil Physics ◽  
One Dimensional ◽  
Component Systems ◽  
Poisson Boltzmann Equation ◽  
The One

We review the phenomenological approach, on the macroscopic or Darcy scale, to flow and volume change in clays and other swelling media. The formulation represents the generalization to media subject to volume change of the well-established phenomenological approach to flow in non-swelling media primarily established in the context of soil physics. The one-dimensional generalization to swelling media is straightforward, and may be usefully applied to practical one-dimensional systems, including three-component systems with solid particles, water, and air. On the other hand, the further generalizations to two- and three-dimensional systems have not yet been developed fully convincingly. Difficult questions include the mode of stress transmission and the tensorial stress-strain relations in multidimensional and multi-component systems. One means of gaining insight into these questions for media of high colloid content (such as clays) is through relevant solutions of the Poisson-Boltzmann equation governing electrical double-layer interactions in dense arrays of colloidal particles. These solutions give pertinent information on both the macroscopic and the microscopic scales. We present a progress report on work along these lines.

A NUMERICAL STUDY OF ROUGH-SURFACE SCATTER

2000 ◽  
Vol 08 (03) ◽  
pp. 443-458 ◽  
Author(s):  
SUZANNE T. McDANIEL
Keyword(s):  
Numerical Study ◽  
Scattering Problem ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Computationally Efficient ◽  
One Dimensional ◽  
Wide Range ◽  
Wavenumber Spectrum ◽  
Grazing Angles ◽  
Surface Scatter

A computationally efficient formulation of the method of moments is developed and applied to the problem of scattering from one-dimensional random pressure-release surfaces. Comparisons are made between the predictions of small-slope and operator expansions and a reference solution obtained by matrix inversion for surfaces characterized by a power-law wavenumber spectrum. For Fresnel parameters greater than unity, a significant increase in backscatter over a wide range of grazing angles is found that is inconsistent with composite-roughness theory, and which is only partially predicted by the various approximations. The small-slope approximation is then applied to the three-dimensional scattering problem, and it is shown that the failure of such approximations carries over from the two-dimensional case to three dimensions.

The Impact of Ice Phase Cloud Parameterizations on Tropical Cyclone Prediction

2014 ◽  
Vol 142 (2) ◽  
pp. 606-625 ◽  
Author(s):  
Yi Jin ◽  
Shouping Wang ◽  
Jason Nachamkin ◽  
James D. Doyle ◽  
Gregory Thompson ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Satellite Imagery ◽  
Hybrid Approach ◽  
Radiative Heating ◽  
Basin Scale ◽  
Single Moment ◽  
Upper Level ◽  
Cloud Ice ◽  
The Impact ◽  
Ice Phase

Abstract The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

scholarly journals A computationally efficient model for the Greenland ice sheet

2012 ◽  
Vol 6 (4) ◽  
pp. 2751-2788 ◽  
Author(s):  
J. Haqq-Misra ◽  
P. Applegate ◽  
B. Tuttle ◽  
R. Nicholas ◽  
K. Keller
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flow Line ◽  
Three Dimensional ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Computationally Efficient ◽  
Dimensional Parameter ◽  
One Dimensional ◽  
Wide Range

Abstract. We present a one-dimensional model of the Greenland Ice Sheet (GIS) for use in analysis of future sea level rise. Simulations using complex three-dimensional models suggest that the GIS may respond in a nonlinear manner to anthropogenic climate forcing and cause potentially nontrivial sea level rise. These GIS projections are, however, deeply uncertain. Analyzing these uncertainties is complicated by the substantial computational demand of the current generation of complex three-dimensional GIS models. As a result, it is typically computationally infeasible to perform the large number of model evaluations required to carefully explore a multi-dimensional parameter space, to fuse models with observational constraints, or to assess risk-management strategies in Integrated Assessment Models (IAMs) of climate change. Here we introduce GLISTEN (GreenLand Ice Sheet ENhanced), a computationally efficient, mechanistically based, one-dimensional flow-line model of GIS mass balance capable of reproducing key instrumental and paleo-observations as well as emulating more complex models. GLISTEN is based on a simple model developed by Pattyn (2006). We have updated and extended this original model by improving its computational functionality and representation of physical processes such as precipitation, ablation, and basal sliding. The computational efficiency of GLISTEN enables a systematic and extensive analysis of the GIS behavior across a wide range of relevant parameters and can be used to represent a potential GIS threshold response in IAMs. We demonstrate the utility of GLISTEN by performing a pre-calibration and analysis. We find that the added representation of processes in GLISTEN, along with pre-calibration of the model, considerably improves the hindcast skill of paleo-observations.

scholarly journals 3-D depth migration via McClellan transformations

Geophysics ◽  
1991 ◽  
Vol 56 (11) ◽  
pp. 1778-1785 ◽  
Author(s):  
Dave Hale
Keyword(s):  
Computational Efficiency ◽  
Digital Filters ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Computationally Efficient ◽  
One Dimensional ◽  
Depth Migration ◽  
Large N ◽  
The Cost ◽  
Accurate Imaging

Three‐dimensional seismic wavefields may be extrapolated in depth, one frequency at a time, by two‐dimensional convolution with a circularly symmetric, frequency‐ and velocity‐dependent filter. This depth extrapolation, performed for each frequency independently, lies at the heart of 3-D finite‐difference depth migration. The computational efficiency of 3-D depth migration depends directly on the efficiency of this depth extrapolation. McClellan transformations provide an efficient method for both designing and implementing two‐dimensional digital filters that have a particular form of symmetry, such as the circularly symmetric depth extrapolation filters used in 3-D depth migration. Given the coefficients of one‐dimensional, frequency‐ and velocity‐dependent filters used to accomplish 2-D depth migration, McClellan transformations lead to a simple and efficient algorithm for 3-D depth migration. 3-D depth migration via McClellan transformations is simple because the coefficients of two‐dimensional depth extrapolation filters are never explicitly computed or stored; only the coefficients of the corresponding one‐dimensional filter are required. The algorithm is computationally efficient because the cost of applying the two‐dimensional extrapolation filter via McClellan transformations increases only linearly with the number of coefficients N in the corresponding one‐dimensional filter. This efficiency is not intuitively obvious, because the cost of convolution with a two‐dimensional filter is generally proportional to [Formula: see text]. Computational efficiency is particularly important for 3-D depth migration, for which long extrapolation filters (large N) may be required for accurate imaging of steep reflectors.

Structure and function of neural networks in the retina

1988 ◽  
Vol 46 ◽  
pp. 26-27
Author(s):  
Peter Sterling
Keyword(s):  
Ganglion Cells ◽  
Three Dimensional ◽  
Structure And Function ◽  
Synaptic Connections ◽  
Visual Axis ◽  
One Dimensional ◽  
Cat Retina ◽  
Ultrathin Sections ◽  
And Function ◽  
Insight Into

The synaptic connections in cat retina that link photoreceptors to ganglion cells have been analyzed quantitatively. Our approach has been to prepare serial, ultrathin sections and photograph en montage at low magnification (˜2000X) in the electron microscope. Six series, 100-300 sections long, have been prepared over the last decade. They derive from different cats but always from the same region of retina, about one degree from the center of the visual axis. The material has been analyzed by reconstructing adjacent neurons in each array and then identifying systematically the synaptic connections between arrays. Most reconstructions were done manually by tracing the outlines of processes in successive sections onto acetate sheets aligned on a cartoonist's jig. The tracings were then digitized, stacked by computer, and printed with the hidden lines removed. The results have provided rather than the usual one-dimensional account of pathways, a three-dimensional account of circuits. From this has emerged insight into the functional architecture.

Exploring the Multidimensional Facets of Authoritarianism: Authoritarian Aggression and Social Dominance Orientation

2008 ◽  
Vol 67 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Stefano Passini
Keyword(s):  
Social Dominance ◽  
Factor Model ◽  
Three Dimensional ◽  
Social Dominance Orientation ◽  
Model Fit ◽  
Regression Analyses ◽  
One Dimensional ◽  
Confirmatory Factor ◽  
The One ◽  
Better Than

The relation between authoritarianism and social dominance orientation was analyzed, with authoritarianism measured using a three-dimensional scale. The implicit multidimensional structure (authoritarian submission, conventionalism, authoritarian aggression) of Altemeyer’s (1981, 1988) conceptualization of authoritarianism is inconsistent with its one-dimensional methodological operationalization. The dimensionality of authoritarianism was investigated using confirmatory factor analysis in a sample of 713 university students. As hypothesized, the three-factor model fit the data significantly better than the one-factor model. Regression analyses revealed that only authoritarian aggression was related to social dominance orientation. That is, only intolerance of deviance was related to high social dominance, whereas submissiveness was not.

Sign in / Sign up

Export Citation Format

Share Document