Two-particle models for the estimation of the mean and standard deviation of concentrations in coastal waters

In this paper we study the mean and standard deviation of concentrations using random walk models. Two-particle models that takes into account the space correlation of the turbulence are introduced and some properties of the distribution of the particle concentration are studied. In order to reduce the CPU time of the calculation a new estimator based on reverse time diffusion is applied. This estimator has been introduced recently by Milstein, Schoenmakers, and Spokoiny (2004). Some numerical aspects of the implementation are discussed for relative simple test problems and finally a realistic application to predict the spreading of the pollutant in the Dutch coastal zone is described

Two-particle models for the estimation of the mean and standard deviation of concentrations in coastal waters

In this paper we study the mean and standard deviation of concentrations using random walk models. Two-particle models that takes into account the space correlation of the turbulence are introduced and some properties of the distribution of the particle concentration are studied. In order to reduce the CPU time of the calculation a new estimator based on reverse time diffusion is applied. This estimator has been introduced recently by Milstein, Schoenmakers, and Spokoiny (2004). Some numerical aspects of the implementation are discussed for relative simple test problems and finally a realistic application to predict the spreading of the pollutant in the Dutch coastal zone is described

RANDOM WALK MODEL IN CASE OF ISO-AND DIAPYCNAL DIFFUSION

Abstract. In order to efficiently simulate the advection-diffusion processes along and across density surfaces, we need to deal with the diffusivity tensor containing off-diagonal element