Our Earth’s climate system involves atmospheric processes across an enormous range of scales, ranging from the planetary to the millimeter scale. This includes not only atmospheric dynamical processes such as turbulence and convection but also the physical processes that interact with the dynamics such as clouds and radiation.
As there is no single simulation system that can incorporate the full range of all these processes, there has been a development of a variety of simulation models that attempt to describe specific sets of processes over a subset of relevant scales. These simulation techniques range from the microscale (Direct Numerical Simulation) via the mesoscale (Large Eddy and Cloud Resolving Model Simulations) to the global scale (Global Circulation Model simulations), and form a hierarchy as one attempts to include the statistical behavior of smaller scale processes in larger-scale simulation models.
The main objective of this workshop is to increase our understanding of the climate system across all these scales through developments of better consistent simulation model hierarchies. This raises questions how we can develop mean-field representations of the subgrid fine-scale, fast processes for the range of simulation models. Can these be incorporated either deterministically or stochastically, can they be made scale-adaptive, or to what extend can we employ a multi-model framework, in which high-resolution models serve as a dynamical subgrid representation embedded in a coarser grained simulation simulation. Moreover this workshop also aims exploring to what extend more simplified models and theories can be useful in reproducing, interpreting and conceptualizing the complex dynamics of the climate system. This will include models, theories and simulation techniques that have emerged from statistical physics and mathematics such as cellular automata, lattice models, percolation theory, self-organizing critical systems and dynamical systems.
(University of Massachusetts Amherst, Mathematics and Statistic)
Alan Kerstein (Sandia National Laboratories)
Boualem Khouider (University of Victoria)
Olivier Pauluis (New York University, EAPS)
Ole Peters (Imperial College)
A. Pier Siebesma (KNMI, Atmospheric Research Div.)