arXiv subjects

Stamen I. Dolaptchiev

Publications and source records attributed to Stamen I. Dolaptchiev.

3 recordsLinked to original sources

arXiv2023

Interactions between gravity waves and cirrus clouds: asymptotic modeling of wave induced ice nucleation

We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GW) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and mid-frequency GW in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GW including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and provide a simple expression for the nucleated number of ice crystals. The present approach is extended to allow for superposition of GW, as well as, for variable mean mass in the ice crystal distribution. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed.

physics.ao-ph↗

arXiv2018

Stochastic subgrid-scale parameterization for one-dimensional shallow water dynamics using stochastic mode reduction

We address the question of parameterizing the subgrid scales in simulations of geophysical flows by applying stochastic mode reduction to the one-dimensional stochastically forced shallow water equations. The problem is formulated in physical space by defining resolved variables as local spatial averages over finite-volume cells and unresolved variables as corresponding residuals. Based on the assumption of a time-scale separation between the slow spatial averages and the fast residuals, the stochastic mode reduction procedure is used to obtain a low-resolution model for the spatial averages alone with local stochastic subgrid-scale parameterization coupling each resolved variable only to a few neighboring cells. The closure improves the results of the low-resolution model and outperforms two purely empirical stochastic parameterizations. It is shown that the largest benefit is in the representation of the energy spectrum. By adjusting only a single coefficient (the strength of the noise) we observe that there is a potential for improving the performance of the parameterization, if additional tuning of the coefficients is performed. In addition, the scale-awareness of the parameterizations is studied.

physics.flu-dyn↗

arXiv2016

Parametrization of stochastic multiscale triads

We discuss applications of a recently developed method for model reduction based on linear response theory of weakly coupled dynamical systems. We apply the weak coupling method to simple stochastic differential equations with slow and fast degrees of freedom. The weak coupling model reduction method results in general in a non-Markovian system, we therefore discuss the Markovianization of the system to allow for straightforward numerical integration. We compare the applied method to the equations obtained through homogenization in the limit of large time scale separation between slow and fast degrees of freedom. We look at ensemble spread from a fixed initial condition, correlation functions and exit times from domain. The weak coupling method gives better results in all test cases, albeit with a higher numerical cost.

cond-mat.stat-mech↗