The combined motion of a rigid cylindrical tank filled with a fluid with a free surface and a moving platform attached to the tank by a spring is simulated mathematically. The nonlinear oscillations of this system cau...
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The combined motion of a rigid cylindrical tank filled with a fluid with a free surface and a moving platform attached to the tank by a spring is simulated mathematically. The nonlinear oscillations of this system caused by a harmonic force applied to the platform are studied
Recently, van der Linde (Comput. Stat. Data Anal. 53:517-533, 2008) proposed a variational algorithm to obtain approximate Bayesian inference in functional principal components analysis (FPCA), where the functions wer...
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Recently, van der Linde (Comput. Stat. Data Anal. 53:517-533, 2008) proposed a variational algorithm to obtain approximate Bayesian inference in functional principal components analysis (FPCA), where the functions were observed with Gaussian noise. Generalized FPCA under different noise models with sparse longitudinal data was developed by Hall et al. (J. R. Stat. Soc. B 70:703-723, 2008), but no Bayesian approach is available yet. It is demonstrated that an adapted version of the variational algorithm can be applied to obtain a Bayesian FPCA for canonical parameter functions, particularly log-intensity functions given Poisson count data or logit-probability functions given binary observations. To this end a second order Taylor expansion of the log-likelihood, that is, a working Gaussian distribution and hence another step of approximation, is used. Although the approach is conceptually straightforward, difficulties can arise in practical applications depending on the accuracy of the approximation and the information in the data. A modified algorithm is introduced generally for one-parameter exponential families and exemplified for binary and count data. Conditions for its successful application are discussed and illustrated using simulated data sets. Also an application with real data is presented.
[1] A new approach is presented for the modeling of the quasi-stationary circulation through the sequential application of a variational algorithm and a nonlinear diagnostic model. The model loop begins with data assi...
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[1] A new approach is presented for the modeling of the quasi-stationary circulation through the sequential application of a variational algorithm and a nonlinear diagnostic model. The model loop begins with data assimilation of temperature, salinity, surface elevation, and velocity data in a simplified geostrophic model in which transport and continuity equations are treated as weak constraints. The temperature/salinity fields and balanced open boundary conditions points are then used as input to a nonlinear primitive equation model, which employs a turbulent closure scheme. The nonlinear model is then run to produce a diagnostic flow field. A radiation open boundary condition is applied at the outflow points of the open boundaries. These two steps are organized into an iteration cycle by using output from the nonlinear model as input to the variational model. The proposed approach combines the advantages of variational data assimilation in simplified models with a complicated fully nonlinear primitive equation model. We apply the approach to Western Bank on the Scotian Shelf. Comparisons with observed current from Western Bank, in September and October 1998, show that the sequential application of the variational approach and the fully nonlinear model allow determination of the quasi-stationary circulation whose agreement with the observations is approximate to 10 - 30% better than circulation determined from the variational or the nonlinear model alone. Our calculations of the cross-shelf transport across Western Bank show that it varies from 0.20 Sv to 0.35 Sv over a 2-week period. The combined models also allow us to determine the character of the circulation over the Bank, the role of wind forcing and the implications for resident biological populations.
作者：
Reiss, CSPanteleev, GTaggart, CTSheng, JdeYoung, BDepartment of Biology
Dalhousie University Halifax NS Canada B3H 4J1 2: Department of Oceanography Dalhousie University Halifax NS Canada B3H 4J1 3: Department of Physics and Physical Oceanography The Memorial University of Newfoundland St Johns NF Canada A1B 3X7
We draw inferences about the dynamic processes responsible for the dispersal of ichthyoplankton on small marine banks using physical and biological data derived from static point-estimates of water-mass characteristic...
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We draw inferences about the dynamic processes responsible for the dispersal of ichthyoplankton on small marine banks using physical and biological data derived from static point-estimates of water-mass characteristics and ichthyoplankton collected concomitantly on the central Scotian Shelf. Where the density field evolves slowly and ageostrophic forcing is weak, the near-surface geostrophic flow can be derived from hydrographic data using the dynamic height method modified for shallow seas. We assess our interpretations of larval distributions using simple particle tracking. The hydrography of the Scotian Shelf during November of 1997 was typical of late autumn, when density is determined by surface variation in salinity. Surface isopycnals generally paralleled isobaths, and there was no evidence of strong surface fronts. Sizes of larvae of pelagic origin (e.g. cod and hake) on Western Bank (sole spawning source) increased and became skewed towards larger animals (cod, 3-10 mm; hake, 5-15 mm) in water-mass (Temperature and Salinity) space along isopycnals, consistent with gradual mixing and limited transport in the geostrophic flow (i.e. retention). Conversely, larvae of benthic origin (e.g. herring, 6-25 mm) were distributed across water-mass space, consistent with multiple origins and substantial transport. Our results indicate that dispersal from small, low-energy marine banks results from the interaction of spawning location, geostrophic currents and bathymetric steering, and requires neither convergence nor larval behaviour.
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