The Summit is expected to:

• Bring together leading scientists from all over the world to rigorously assess and discuss the capabilities of current model systems to fulfill the great expectations society has in them for guiding future adaptation and mitigation activities.
• Develop a visionary strategy that will enable and accelerate progress in the modelling and prediction of regional climate change and variations from days to decades.
• Recommend a realistic roadmap how this revolution in climate prediction can be achieved for the benefit of society.

In order to achieve these goals, it is expected that the Summit will address important scientific and organizational questions related to each theme as for example:

• Current generation climate models have serious limitations in simulating regional features, for example, rainfall, mid-latitude storms, organized tropical convection, ocean mixing, and ecosystem dynamics. What is the scientific strategy to improve the fidelity of climate models?
• Is the low resolution of current climate models due to limitations of scientific understanding or lack of powerful computers and scientific staff?
• Several current operational Numerical Weather Prediction (NWP) centers are using global models with resolutions of 25-50 km. During the next 3-5 years, it is expected that several global NWP models will have spatial resolution of about 10 km. Should the next IPCC assessment include at least a few climate models at about 10 km resolution for oceans and atmosphere?
• What is the strategy to ensure enhanced and sustained modeling efforts and computing power at the existing modeling centers of the world? Or, is the scale of the challenge so large that in addition to the current national efforts, a far more comprehensive, and internationally coordinated approach is needed?
• A large body of evidence based on modeling experiments suggests that as models improve their parameterizations and increase their spatial resolution, the model’s ability to simulate the current climate as well as the model’s skill in predicting daily and seasonal fluctuations improves. What is the likelihood that if the spatial resolution of climate models is sufficiently increased so that deep convective cloud systems, ocean overflows and mesoscale eddies, and heterogeneous land surface processes can be explicitly resolved, and therefore, do not need to be parameterized, the fidelity of climate models in simulating the current climate will improve?

Likewise, how can we ensure that if we replace the traditional strategy of parameterizing unresolved small scale processes (viz deep convection in the atmosphere and mesoscale eddies in the oceans) by resolving the unpredictable scales, the rapid growth of the inherently unpredictable small scale systems does not overwhelm the predictable large-scale flow?

• Will a major enhancement in computing power and dedicated scientific staff to develop data assimilation systems for very high resolution models enhance the value of space observations that are being made at a significant cost?
• It is well recognized that if the global models, from which lateral boundary conditions for regional models are prescribed, do not have reliable simulation of planetary waves and the statistics of tropical and extratropical storms, blocking and other regional phenomena, the use of high resolution regional models to downscale regional climate change is questionable. Is there a less questionable alternative? Are time-slice experiments using very high resolution (as high as regional models) global atmospheric models with surface boundary conditions from global change experiments, less questionable than regional downscaling? How important is coupling with the ocean and land at time and space scales commensurate with those of the atmosphere model? Are there more effective techniques available, perhaps in other disciplines, that could be employed to resolve the relevant features of the climate system?
• How accurate must simulations of the physical climate system be to justify the extension of climate models to include additional complexity due to chemical and biological processes? What time and space scales of coupling are fundamental to the system? What are the appropriate metrics to evaluate climate models?
• What are the current trends in computing? What is the best strategy to foster collaboration and interaction among the weather and modelling community, computational fluid dynamics community and computer (and chip) manufacturers to achieve a million fold increase in the effective computing power for climate and weather modelling and prediction?
• What is the best strategy to foster collaborations among modelling centers around the world? Has the time come for the climate modeling community of the world to establish a dedicated supercomputing facility and a collaborative research framework for climate and weather modelling and prediction that is beyond the capability of a single nation?

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