Examining Coherency Scales, Substructure, and Propagation of Whistler Mode Chorus Elements With Magnetospheric Multiscale (MMS)
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D. L. Turner↗
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A multiscale numerical study into the cascade of kinetic energy leading to severe local storms
The cascade of kinetic energy from macro- through mesoscales is studied on the basis of a nested grid system used to solve a set of nonlinear differential equations. The kinetic energy cascade and the concentration of vorticity through the hydrodynamic spectrum provide a means for predicting the location and intensity of severe weather from large-scale data sets. A mechanism described by the surface pressure tendency equation proves to be important in explaining how initial middle-tropospheric mass-momentum imbalances alter the low-level pressure field.
Paine, D. A.↗
Multiscale modeling to evaluate proposed space-based Doppler lidar sampling strategies
A proposal has been made to place a pulsed Doppler lidar on a space platform (Huffaker, et al., 1980; Emmitt, 1982) in a low earth orbit (200 to 800 km) to measure the atmospheric winds with a spatial resolution commensurate with the current continental rawinsonde network density - i.e., 300 to 500 km resolution. In the case of the space-based doppler lidar, the full range of space scales applies. Single shot pulses with dimensions of 10 x 1000 meters are used to sample areas 100,000 x 100,000 meters to resolved mass flow structure with wavelength of 1 million meters. Simulation studies, therefore, require an equally broad range of atmospheric models. A general circulation model is appropriate to answer questions regarding the impact of a global wind measuring system upon synoptic forecasts. Since the nominal resolution of the spacebased system is expected to be a few 100's of kilometers, then a numerical model with mesoscale dynamics is required. The meaning of an average Doppler shift within a laser pulse volume must be evaluated with models of turbulent/convective scale motions and aerosol gradients. Examples of how models on all these scales have been applied in an ongoing simulation study are presented. In particular, the uncertainties in a mesoscale wind estimate are separated into those arising from pulse scale variances and those due to sample distribution within a prescribed resolution volume. Trade-offs between accuracy and representativeness are discussed in terms of the model results.
Emmitt, G. D.↗
Multiscale analysis of a sustained precipitation event
Mesoscale data collected during both the satellite precipitation and cloud experiment and the microburst and severe thunderstorm program are analyzed in order to describe features associated with two distinct mesoscale precipitation events that occurred about 10 hours apart over the region of northern Alabama to central Tennessee in June 1986. Data sets used include mesobeta-scale rawinsonde data, surface mesonet data, RADAP data, and GOES images. The present mesoscale environment involved the merger of Hurricane Bonnie remnants with a preexisting midlatitude short-wave trough.
Knupp, Kevin R.↗
A mesoscale gravity wave event observed during CCOPE. I - Multiscale statistical analysis of wave characteristics
This paper presents a statistical analysis of the characteristics of the wavelike activity that occurred over the north-central United States on July 11-12, 1981, using data from the Cooperative Convective Precipitation Experiment in Montana. In particular, two distinct wave episodes of about 8-h duration within a longer (33 h) period of wave activity were studied in detail. It is demonstrated that the observed phenomena display features consistent with those of mesoscale gravity waves. The principles of statistical methods used to detect and track mesoscale gravity waves are discussed together with their limitations.
Koch, Steven E.↗
Multiscale turbulence effects in underexpanded supersonic jets
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Abdol-Hamid, Khaled S.↗
Multiscale vector fields for image pattern recognition
A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.
Low, Kah-Chan↗
Shiftable multiscale transforms
A type of translational invariance, referred to as shiftability, is defined for wavelet transforms. The property of shiftability is first discussed with respect to individual parameters: spatial position, orientation, and scale. The discussion then focuses on transformations that are simultaneously shiftable with respect to subsets of these parameters. It is shown that the critical sampling condition on the wavelet transforms must be relaxed to achieve shiftability. Two example transforms are implemented and applied to several signal and image processing problems.
Simoncelli, Eero P.↗
Multiscale Morphological Filtering for Analysis of Noisy and Complex Images
Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.
Kher, A.↗
Scientific goals of the Cooperative Multiscale Experiment (CME)
Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.
Cotton, William↗
Characterizing multiscale variability of zero intermittency in spatial rainfall
In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.
Kumar, Praveen↗
Parallel Multiscale Algorithms for Astrophysical Fluid Dynamics Simulations
Our goal is to develop software libraries and applications for astrophysical fluid dynamics simulations in multidimensions that will enable us to resolve the large spatial and temporal variations that inevitably arise due to gravity, fronts and microphysical phenomena. The software must run efficiently on parallel computers and be general enough to allow the incorporation of a wide variety of physics. Cosmological structure formation with realistic gas physics is the primary application driver in this work. Accurate simulations of e.g. galaxy formation require a spatial dynamic range (i.e., ratio of system scale to smallest resolved feature) of 104 or more in three dimensions in arbitrary topologies. We take this as our technical requirement. We have achieved, and in fact, surpassed these goals.
Norman, Michael L.↗
Linkages Between Multiscale Global Sea Surface Temperature Change and Precipitation Variabilities in the US
A growing number of evidence indicates that there are coherent patterns of variability in sea surface temperature (SST) anomaly not only at interannual timescales, but also at decadal-to-inter-decadal timescale and beyond. The multi-scale variabilities of SST anomaly have shown great impacts on climate. In this work, we analyze multiple timescales contained in the globally averaged SST anomaly with and their possible relationship with the summer and winter rainfall in the United States over the past four decades.
Lau, K. M.↗
Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data
With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.
Lam, N.↗
Grid Convergence of High Order Methods for Multiscale Complex Unsteady Viscous Compressible Flows
Grid convergence of several high order methods for the computation of rapidly developing complex unsteady viscous compressible flows with a wide range of physical scales is studied. The recently developed adaptive numerical dissipation control high order methods referred to as the ACM and wavelet filter schemes are compared with a fifth-order weighted ENO (WENO) scheme. The two 2-D compressible full Navier-Stokes models considered do not possess known analytical and experimental data. Fine grid solutions from a standard second-order TVD scheme and a MUSCL scheme with limiters are used as reference solutions. The first model is a 2-D viscous analogue of a shock tube problem which involves complex shock/shear/boundary-layer interactions. The second model is a supersonic reactive flow concerning fuel breakup. The fuel mixing involves circular hydrogen bubbles in air interacting with a planar moving shock wave. Both models contain fine scale structures and are stiff in the sense that even though the unsteadiness of the flows are rapidly developing, extreme grid refinement and time step restrictions are needed to resolve all the flow scales as well as the chemical reaction scales.
Sjoegreen, B.↗
High Order Finite Difference Methods for Multiscale Complex Compressible Flows
The classical way of analyzing finite difference schemes for hyperbolic problems is to investigate as many as possible of the following points: (1) Linear stability for constant coefficients; (2) Linear stability for variable coefficients; (3) Non-linear stability; and (4) Stability at discontinuities. We will build a new numerical method, which satisfies all types of stability, by dealing with each of the points above step by step.
Sjoegreen, Bjoern↗
Efficient Low Dissipative High Order Schemes for Multiscale MHD Flows: Minimization of Delta * B Numerical Error - II
The generalization of a class of low-dissipative high order filter finite difference schemes for long time wave propagation of shock/turbulence/combustion compressible viscous gas dynamic flows to compressible MHD equations for structured curvilinear grids has been developed. The new scheme consists of a divergence free preserving high order spatial base scheme with a filter approach which can be divergence-free preserving depending on the type of filter operator being used, the method of applying the filter step, and the type of flow problem to be considered. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field (Delta * B) numerical error in the sense that no standard divergence cleaning is required. Performance evaluation of these variants, and the key role that the proper treatment of their corresponding numerical boundary conditions can play will be illustrated. Many levels of grid refinement and detailed comparison with several commonly used compressible MHD shock-capturing schemes will be sought. For certain MHD 2-D test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.
Sjoegreen, Bjoern↗
Divergence Free High Order Filter Methods for Multiscale Non-ideal MHD Flows
Low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous MHD flows has been constructed. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field (Delta . B) numerical error in the sense that no standard divergence cleaning is required. For certain 2-D MHD test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.
Yee, H. C.↗