MARKOV CHAIN STOCHASTIC PARAMETRIZATIONS OF ESSENTIAL VARIABLES

作者：Nimsaila K^*; Timofeyev I

来源：Multiscale Modeling and Simulation, 2010, 8(5): 2079-2096.

DOI：10.1137/090770394

• Markov chain
• effective model
• stochastic parametrization

We analyze the performance of the novel Markov chain stochastic modeling technique for derivation of effective equations for a set of essential variables. This technique is an empirical approach where the right-hand side of the essential variables is modeled by a Markov chain. We demonstrate that the Markov chain modeling approach performs well in a prototype model without scale separation between the essential and the nonessential variables. Moreover, we utilize the truncated Burgers-Hopf model to show that the Markov chain should be properly conditioned on the essential variables to reproduce the structure of two-point statistical quantities. On the other hand, the conditioning can be rather straightforward and unsophisticated.

• 出版日期2010