On one method of studying sensitivity to random fields perturbations in dynamic probabilistic modelling

Abstract

Using the variational principle, we propose and numerically estimate the method of the numerical statistical modelling of the influence domain for pollutant concentration fields against the background of climatic implementations of wind velocity fields. It is shown that when numerically modelling a pollutant spreading process as the ensemble of the corresponding climatic implementations with their subsequent averaging the estimate of the influence domain differs essentially from the estimates which are derived by using average velocity fields or separate climatic scenarios.

On one method of investigation of sensitivity to random fields perturbations in dynamic-probabilistic modelling

“…Note that the realizations from the ensemble (2) are statistically independent, which follows from the problem statement and is con rmed by the statistical analysis of the corresponding elds, they satisfy the numerical model (3) and are fully subject to the initial conditions. On the other hand, the solution of the variational assimilation problem in the general case is not unique and de ned by the extent to which the data to be assimilated is complete and by the initial value for the corresponding iterative process.…”

“…However, the ensemble (2) already contains all the meteoelement elds in accordance with the model (3). However, the ensemble (2) already contains all the meteoelement elds in accordance with the model (3).…”

“…Analysis of the statistical structure of the ensemble (2) shows that this ensemble can be used as a climatic one to solve applied problems, including the problem of pollution spreading in the atmosphere [3][4][5].…”