Time-scale dependence in numerical simulations: Assessment of physical, chemical, and biological predictions in a stratified lake at temporal scales of hours to months

2012 ◽  
Vol 35 ◽  
pp. 104-121 ◽  
Author(s):  
Emily L. Kara ◽  
Paul Hanson ◽  
David Hamilton ◽  
Matthew R. Hipsey ◽  
Katherine D. McMahon ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Time Scale ◽  
Scale Dependence ◽  
Temporal Scales ◽  
Stratified Lake ◽  
Physical Chemical

scholarly journals Time-scale dependence of correlations among foreign currencies

2004 ◽  
pp. 24-29 ◽  
Author(s):  
Takayuki Mizuno ◽  
Shoko Kurihara ◽  
Misako Takayasu ◽  
Hideki Takayasu
Keyword(s):  
Time Scale ◽  
Scale Dependence ◽  
Foreign Currencies

scholarly journals Analysis of aggregation and disaggregation effects for grid-based hydrological models and the development of improved precipitation disaggregation procedures for GCMs

1999 ◽  
Vol 3 (1) ◽  
pp. 95-108 ◽  
Author(s):  
H. S. Wheater ◽  
T. J. Jolley ◽  
C. Onof ◽  
N. Mackay ◽  
R. E. Chandler
Keyword(s):  
Soil Moisture ◽  
Time Scale ◽  
Scale Dependence ◽  
Moisture Distribution ◽  
Image Processing Technique ◽  
Simple Extension ◽  
Hydrological Models ◽  
Radar Rainfall ◽  
Spatial Coverage ◽  
Grid Based

Abstract. Appropriate representation of hydrological processes within atmospheric General Circulation Models (GCMs) is important with respect to internal model dynamics (e.g. surface feedback effects on atmospheric fluxes, continental runoff production) and to simulation of terrestrial impacts of climate change. However, at the scale of a GCM grid-square, several methodological problems arise. Spatial disaggregation of grid-square average climatological parameters is required in particular to produce appropriate point intensities from average precipitation. Conversely, aggregation of land surface heterogeneity is necessary for grid-scale or catchment scale application. The performance of grid-based hydrological models is evaluated for two large (104km2) UK catchments. Simple schemes, using sub-grid average of individual land use at 40 km scale and with no calibration, perform well at the annual time-scale and, with the addition of a (calibrated) routing component, at the daily and monthly time-scale. Decoupling of hillslope and channel routing does not necessarily improve performance or identifiability. Scale dependence is investigated through application of distribution functions for rainfall and soil moisture at 100 km scale. The results depend on climate, but show interdependence of the representation of sub-grid rainfall and soil moisture distribution. Rainfall distribution is analysed directly using radar rainfall data from the UK and the Arkansas Red River, USA. Among other properties, the scale dependence of spatial coverage upon radar pixel resolution and GCM grid-scale, as well as the serial correlation of coverages are investigated. This leads to a revised methodology for GCM application, as a simple extension of current procedures. A new location-based approach using an image processing technique is then presented, to allow for the preservation of the spatial memory of the process.

Lagrangian characteristics of turbulence and scalar transport in direct numerical simulations

2001 ◽  
Vol 427 ◽  
pp. 241-274 ◽  
Author(s):  
P. K. YEUNG
Keyword(s):  
Reynolds Number ◽  
Correlation Function ◽  
Numerical Simulations ◽  
Time Scales ◽  
Time Scale ◽  
Cross Correlation ◽  
Scalar Fields ◽  
Direct Numerical Simulations ◽  
Cross Correlation Function ◽  
Differential Diffusion

A study of the Lagrangian statistical properties of velocity and passive scalar fields using direct numerical simulations is presented, for the case of stationary isotropic turbulence with uniform mean scalar gradients. Data at higher grid resolutions (up to 5123 and Taylor-scale Reynolds number 234) allow an update of previous velocity results at lower Reynolds number, including intermittency and dimensionality effects on vorticity time scales. The emphasis is on Lagrangian scalar time series which are new to the literature and important for stochastic mixing models. The variance of the ‘total’ Lagrangian scalar value (ϕ˜+, combining contributions from both mean and fluctuations) grows with time, with the velocity–scalar cross-correlation function and fluid particle displacements playing major roles. The Lagrangian increment of ϕ˜+ conditioned upon velocity and scalar fluctuations is well represented by a linear regression model whose parameters depend on both Reynolds number and Schmidt number. The Lagrangian scalar fluctuation is non-Markovian and has a longer time scale than the velocity, which is due to the strong role of advective transport, and is in contrast to results in an Eulerian frame where the scalars have shorter time scales. The scalar dissipation is highly intermittent and becomes de-correlated in time more rapidly than the energy dissipation. Differential diffusion for scalars with Schmidt numbers between 1/8 and 1 is characterized by asymmetry in the two-scalar cross-correlation function, a shorter time scale for the difference between two scalars, as well as a systematic decrease in the Lagrangian coherency spectrum up to at least the Kolmogorov frequency. These observations are consistent with recent work suggesting that differential diffusion remains important in the small scales at high Reynolds number.

scholarly journals Editorial for Special Issue “Multiscale Turbulent Transport”

Fluids ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 185
Author(s):  
Marco Martins Afonso ◽  
Sílvio M. A. Gama
Keyword(s):  
Numerical Simulations ◽  
Turbulent Transport ◽  
Special Issue ◽  
Temporal Scales ◽  
Spatio Temporal

Turbulent transport is currently a great subject of ongoing investigation at the interface of methodologies running from theory to numerical simulations and experiments, and covering several spatio-temporal scales [...]

scholarly journals Fractal Phase Distribution and Drying: Impact on Two-Phase Zone Scaling and Drying Time Scale Dependence

2012 ◽  
Vol 30 (11-12) ◽  
pp. 1129-1135 ◽  
Author(s):  
Marc Prat ◽  
Stéphanie Veran-Tissoires ◽  
Nicole Vorhauer ◽  
Thomas Metzger ◽  
Evangelos Tsotsas
Keyword(s):  
Time Scale ◽  
Phase Distribution ◽  
Scale Dependence ◽  
Phase Zone ◽  
Two Phase ◽  
Drying Time

scholarly journals Length scale dependence in elastomers – comparison of indentation experiments with numerical simulations

Polymer ◽  
2016 ◽  
Vol 98 ◽  
pp. 201-209 ◽  
Author(s):  
Nitin Garg ◽  
Chung-Souk Han ◽  
Farid Alisafaei
Keyword(s):  
Numerical Simulations ◽  
Scale Dependence ◽  
Length Scale

Instability and Time Scale Dependence of Beta in an Emerging Market Economy: Evidence from India

2014 ◽  
Vol 39 (1) ◽  
pp. 41-56
Author(s):  
Amlendu Kumar Dubey
Keyword(s):  
Market Economy ◽  
Time Scale ◽  
Emerging Market ◽  
Systematic Risk ◽  
Equity Markets ◽  
Scale Dependence ◽  
Resource Mobilization ◽  
Secondary Market ◽  
Time Horizons ◽  
The World

This paper is an attempt in analysing time-scale dependence of systematic risk of stocks for an emerging market economy. Financial markets all over the world are characterized by heterogeneous investors. For example, different investors have different time horizons of investment which in turn is highly related to perception of risk of different investors in holding these stocks. Also, in emerging market economies, economic conditions are very fluid. Not only new firms are joining the market but existing firms themselves are changing rapidly; they are expanding into new markets, and at times with different products. Therefore, assuming that the risk in holding a firm's stock will be constant over a longer period is rather a restrictive assumption. Also, Indian equity markets are one of the most dynamic equity markets in the world today. The last decade has been the most eventful period for the Indian securities market. Resource mobilization in the primary market has increased dramatically, rising sixfold between 2000 and 2010 (NSE, 2010), which is having a very significant impact on the risk-return trade-off in the secondary market. Market capitalization has grown substantially over the period indicating that not only more companies are using the stock markets for resource mobilization today but overall market participation has also increased considerably. This paper tests for time-scale stability of beta of different trading stocks in the Indian equity market, using wavelet filters following Gencay et al (2002; 2005) and Fernandez (2006) and finds considerable instability in beta estimates. Based on this analysis, time-scale dependent beta estimates are provided for all the stocks under consideration. Time-scale dependent estimates of systematic risk embedded in different stocks will provide considerable information to practitioners in terms of benefits of diversification while constructing different portfolios using different stocks traded in Indian equity markets. Essentially, with the tools explained in this paper, practitioners will be able to incorporate their horizons of investment while planning for portfolio diversification. Also, the results emphasize the importance of a hedging strategy that varies over different time horizons of investments over a strategy where the hedge ratio is invariant to different time horizons.

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