This special session will focus on the challenges facing the global modeling community as it prepares for a disruptive change in computer architectures. High-end scientific computing has been relatively evolutionary and predictable since the adoption twenty years ago of massively-parallel, microprocessor-based, distributed memory supercomputers. From the late 1980s through the late 1990s, these systems, such as the Cray T3E and IBM-SP, ultimately replaced the large, special purpose shared-memory vector systems that were the mainstay of many scientific communities, including weather and Earth-system simulation. That disruptive decade required Earth system modelers to experiment with different architectures and programming models to sustain progress.

Analogously, high-end scientific computing has entered a new disruptive period. As microprocessors have become ever smaller, they are approaching limitations dictated by power consumption and heat generation, requiring new and experimental processor designs that are the building blocks for the next generations of high-end computers. Achieving grand challenge science goals necessitates that the Earth system modeling community adapt to unprecedented changes in the computing landscape. These challenges include a plateau in system clock speeds and increased software complexity driven by computing system heterogeneity.

Developing and running ever more complex Earth system models requires modelers to support current machines while also preparing for Exascale architectures that will appear around 2020.  Success requires a mix of short-term optimization and long-term research in algorithms and computational approaches. We will solicit papers on all aspects of global climate and Earth system models on future Exascale computing systems. This includes fully-coupled models as well as their individual components, including the atmosphere, the ocean, sea ice, land ice, and the terrestrial biosphere. We will cover topics such as software complexity, programming models, algorithms for heterogeneous computers (e.g. CPU-GPU systems), data management, and analysis methods (both post simulation and in-situ).

Embracing the challenges now, rather than reacting later, is essential to sustain scientific progress. We hope this session will further enhance the exchange of ideas and identify new approaches to these complex problems at the intersection of the Earth system and computational sciences.