Intercomparison of 3D turbulence parameterizations for dispersion models in complex terrain derived from a circulation model

A procedure for estimating 3D turbulent parameters from the outputs of a circulation model to be used as input of a random flight model for complex terrain dispersion simulation is presented. It is based on parameterization schemes for surface layer parameters and wind velocity standard deviation profiles available in the literature. The predictions of various schemes (two for surface layer quantities and three either for the PBL depth or standard deviation profiles) have been compared to observations carried out in the alpine region (south Switzerland) during the second TRANSALP campaign by three Doppler Sodar and two sonic anemometers

An intercomparison of two turbulence closure schemes and four parameterizations for stochastic dispersion models

Two Lagrangian particle models, developed by Luhar and Britter (Atmos. Environ., 23 (1989) 1191) and Weil (J. Atmos. Sci., 47 (1990) 501), satisfying the “well-mixed” condition as prescribed by Thomson (J. Fluid. Mech., 180 (1987) 529), are compared. They differ in the closure scheme used in calculating the probability density function of the random forcing in a convective boundary layer. Four different turbulent parameterizations were used as input to both models. Their performances are evaluated against one of the well-known Willis and Deardorff water tank experiments (Atmos. Environ., 12 (1978) 1305). Predicted and measured ground-level concentrations (g.l.c.), maximum g.l.c. distance, mean plume height and plume vertical spread are presented and discussed

Statistical analysis of three series of daily rainfall in North-Western Italy

In this work we study three long series of daily rainfall measured in North-Western Italy. We analyze the global statistical properties of the three data sets and we discuss both the seasonal distribution of rainfall intensity and the long-term variation in rainfall properties. We show that the three series display a vanishingly small autocorrelation for periods longer than one or two days, consistent with the absence of multifractality in these records. These time series are largely consistent with the output of a simple chain-dependent stochastic process

Estimation of emission rate from experimental data

The estimation of the source pollutant strength is a relevant issue for atmospheric environment. This characterizes an inverse problem in the atmospheric pollution dispersion studies. In the inverse analysis, a time-dependent pollutant source is considered, where the location of such source term is assumed known. The inverse problem is formulated as a non-linear optimization approach, whose objective function is given by the least-square difference between the measured and simulated by the mathematical model, pollutant concentration, associated with a regularization operator. The forward problem is addressed by a Lagrangian model, and a quasi-Newton method is employed for minimizing the objective function. The second-order Tikhonov regularization is applied and the regularization parameter is computed by using the L-curve scheme. The inverse-problem methodology is verified with data from the tracer Copenhagen experiment

MICROSPRAY SIMULATION OF DENSE GAS DISPERSION IN COMPLEX TERRAIN

An extended validation of the new Lagrangian particle model MicroSpray version for dense gas simulation is proposed. MicroSpray simulates the dense gas dispersion in situations characterized by the presence of buildings, other obstacles, complex terrain, and possible occurrence of low wind speed conditions. Its performances are compared to a chlorine railway accident (Macdona), to a field experiment (Kit Fox) and to an atmospheric CFD model

Structure of quantum correlations in momentum space and off diagonal long range order in eta pairing and BCS states

The quantum states built with the eta paring mechanism i.e., eta pairing states, were first introduced in the context of high temperature superconductivity where they were recognized as important example of states allowing for off-diagonal long-range order (ODLRO). In this paper we describe the structure of the correlations present in these states when considered in their momentum representation and we explore the relations between the quantum bipartite/multipartite correlations exhibited in k space and the direct lattice superconducting correlations. In particular, we show how the negativity between paired momentum modes is directly related to the ODLRO. Moreover, we investigate the dependence of the block entanglement on the choice of the modes forming the block and on the ODLRO; consequently we determine the multipartite content of the entanglement through the evaluation of the generalized "Meyer Wallach" measure in the direct and reciprocal lattice. The determination of the persistency of entanglement shows how the network of correlations depicted exhibits a self-similar structure which is robust with respect to "local" measurements. Finally, we recognize how a relation between the momentum-space quantum correlations and the ODLRO can be established even in the case of BCS states.Comment: 11 pages, 3 figure

A model based on Heisenberg’s theory for the eddy diffusivity in decaying turbulence applied to the residual layer

The problemof the theoretical derivation of a parameterization for the eddy diffusivity in decaying turbulence is addressed. This derivation makes use of the dynamical equation for the energy spectrum density and the classical statistical diffusion theory. The starting point is Heisenberg’s elementary decaying turbulence theory. The main assumption is related to the identification of a frequency, lying in the inertial subrange, characterizing the inertial energy transfer among eddies of different size. The resulting eddy diffusivity parameterization is then applied to the decay of convective turbulence in the residual layer. Besides the intrinsic scientific interest, this topic has relevance for mesoscale transport and diffusion simulations. The resulting expression for the eddy diffusivity cannot be solved analytically. For this reason an algebraic approximated formulation, giving nearly the same results as the exact expression, is also proposed

An automatic methodology for estimating eddy diffusivities from experimental data

A technique for estimating eddy diffusivities in a turbulent atmospheric layer is presented; the scheme adopted is based on an inverse-problem methodology. The inverse problem is formulated as a nonlinear constrained optimization problem, where the objective function is defined through the square differences between experimental and model data. The direct mathematical model is given by the advection-diffusion equation, which is solved by second-order finite-difference method. In the presence of noise it is necessary to use some regularization term; the Tikhonov function and an entropic regularization of zeroth, first and second orders are used in this paper. In addition, two inversion strategies are used: alternate and simultaneous eddy diffusivities estimation. Numerical experiments show a good performance of the proposed methodology