Quantifying Uncertainty for Coherent Structures
نویسنده
چکیده
Field Alignment is a useful and often necessary preprocessing step in contemporary geophysical state and parameter estimation of coherent structures. In an advance, we introduce a new framework for using Field Alignment to quantify uncertainty from an ensemble of coherent structures. Our method, called Coalescence, discovers the mean field under non-trivial misalignments of fields with complex shapes, which is especially difficult to calculate in the presence of sparse observations. We solve the associated Field Alignment problem using novel constraints derived from turbulent displacement spectra. In conjunction with a continuation method called Scale Cascaded Alignment (SCA), we are able to extract simpler explanations of the error between fields before cascading to more complex deformation solutions. For coherent structures, SCA and Coalescence have the potential to change the way uncertainty is quantified and data is assimilated. We illustrate utility here in a Nowcasting application.
منابع مشابه
Modified Structure Function Model Based on Coherent Structures
In the present study, a modified Structure Function was introduced. In this modified Structure Function model, the coefficient of model was computed dynamically base on the coherent structure in the flow field. The ability of this Modified Structure Function was investigated for complex flow over a square cylinder in free stream and a low aspect ratio cylinder confined in a channel. The Results...
متن کاملOn Coherent Structures of Turbulent Open-channel Flow Above a Rough Bed
Present study examines turbulent structures of a rough bed open-channel flow in the context of deterministic approach. Instantaneous velocity field is measured in different hydraulic conditions using two dimensional Particle Image Velocimetry (PIV) in vertical plane and Stereoscopic PIV in horizontal plane. Different techniques and quantities such as swirl strength, two-point and cross-correlat...
متن کاملUncertainty analysis of hierarchical granular structures for multi-granulation typical hesitant fuzzy approximation space
Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...
متن کاملLagrangian coherent structures and internal wave attractors.
For a nonuniformly stratified layer of fluid, internal gravity waves propagate at varying angles depending on the local buoyancy and Coriolis (in geophysical applications) frequencies. Relatively confined geometries, such as multiple submarine ridges, can support internal wave attractors, which can be viewed as Lagrangian coherent structures for the energy density flux. Since traditional approa...
متن کاملThe effect of velocity uncertainty on migrated reflectors: Improvements from relative-depth imaging
We have studied the problem of uncertainty quantification for migrated images. A traditional migrated image contains deterministic reconstructions of subsurface structures. However, input parameters used in migration, such as reflection data and a velocity model, are inherently uncertain. This uncertainty is carried through to the migrated images. We have used Bayesian analysis to quantify the ...
متن کامل