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Dr. Sylwester Arabas
Department of Mathematics and Computer Science of Jagiellonian University in Krakow, Poland
Particle-based cloud microphysics: rationale, state of the art and challenges
Representation of aerosol-cloud-precipitation interactions in numerical models of atmospheric flows has recently been subject to a paradigm shift towards particle-based approaches. The particle-based microphysics models contrast the conventional computational fluid dynamics (CFD) approach of representing aerosol, cloud and precipitation particle populations as separate categories of trace constituents modelled with continuous density fields. The novel techniques termed Lagrangian Cloud Models (LCMs) feature bi-directional coupling of: (i) momentum, moisture and heat conservation law solvers (PDE-formulated, continuous phase) with (ii) particle-based probabilistic representation of aerosol, clouds and rain (ODE-formulated, dispersed phase).
Among the key advantages of the particle-based methods there are: lack of numerical diffusion in physical and size-spectral dimensions; by-design non-negativity of the derived density fields; ab-initio-like representation of particle-level processes; suitability of Monte-Carlo methods for solving particle coagulation; robustness to spatial resolution changes of the CFD solver; and favourable GPU-parallelization characteristics.
While embracement of the methodology in the community is rapidly advancing and there has been significant investments done in research software development, there are also several challenges that remain to be robustly tackled and discussed. These include numerical nuances, representation of both subgrid- and large-scale physical processes that have been already addressed in "classical" Eulerian approaches. There are also challenges that are new to Lagrangian methods including those linked with replacement of the convenient infinite-aerosol-reservoir assumption characteristic of Eulerian schemes with the by-design comprehensive representation of aerosol budget.
The talk will aim at summarizing the past decade of developments, at highlighting the novel results obtained with particle-based models, and at bringing attention to some remaining challenges and opportunities.
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