Short notice, but an interesting talk tomorrow by Balaji of Princeton University and NOAA/GFDL. Balaji is head of the Modeling Systems Group at NOAA/GFDL. The talk is scheduled for 4 p.m., in the Physics building, room MP408.
Climate Computing: Computational, Data, and Scientific Scalability
Climate modeling, in particular the tantalizing possibility of making projections of climate risks that have predictive skill on timescales of many years, is a principal science driver for high-end computing. It will stretch the boundaries of computing along various axes:
- resolution, where computing costs scale with the 4th power of problem size along each dimension
- complexity, as new subsystems are added to comprehensive earth system models with feedbacks
- capacity, as we build ensembles of simulations to sample uncertainty, both in our knowledge and representation, and of that inherent in the chaotic system. In particular, we are interested in characterizing the “tail” of the pdf (extreme weather) where a lot of climate risk resides.
The challenge probes the limits of current computing in many ways. First, there is the problem of computational scalability, where the community is adapting to an era where computational power increases are dependent on concurrency of computing and no longer on raw clock speed. Second, we increasingly depend on experiments coordinated across many modeling centres which result in petabyte-scale distributed archives. The analysis of results from distributed archives poses the problem of data scalability.
Finally, while climate research is still performed by dedicated research teams, its potential customers are many: energy policy, insurance and re-insurance, and most importantly the study of climate
change impacts — on agriculture, migration, international security, public health, air quality, water resources, travel and trade — are all domains where climate models are increasingly seen as tools that
could be routinely applied in various contexts. The results of climate research have engendered entire fields of “downstream” science as societies try to grapple with the consequences of climate change. This poses the problem of scientific scalability: how to enable the legions of non-climate scientists, vastly outnumbering the climate research community, to benefit from climate data.
The talks surveys some aspects of current computational climate research as it rises to meet the simultaneous challenges of computational, data and scientific scalability.
Update: Neil blogged a summary of Balaji’s talk.