Bridging Scales in Climate System Modeling

In the coming decade and beyond, the climate modeling community will be challenged to resolve scales and processes that are far beyond its current scope. The challenge to resolve these small scales and new processes will arise primarily for two reasons. The first reason is that there are likely to be currently unresolved processes that have a significant influence on the global climate system. Examples of this might include ice streams (O(km)) within large-scale ice sheets, ice shelves (O(km)) collapsing due to interaction with ocean processes, and the dependence of ocean biochemistry on ocean eddy (O(10 km)) activity. The second reason for this challenge is the desire to quantitatively characterize the regional-scale signature of anthroprogenic climate change. An example close to home is the climate-change driven impacts to hydrological processes (O(km)) in the western United States.
The ability to resolve the scales noted above throughout the relevant climate system component is beyond the current computing capacity of even the most powerful computer available today. Basic scaling arguments of computer resources available into the future indicate that this will remain true for at least the next two decades. In this talk I will outline the approaches we might take to accommodate these relevant processes, yet retain a computationally-tractable climate system model. In particular, I will compare and contrast the approach of nesting with the approach of variable resolution. When accompanied by typical finite-volume methods, both approaches lead, somewhat counter-intuitively, to an increase in local truncation error as the price-to-be-paid for regional resolution. If left unchecked, the truncation error may, in fact, completely swamp the benefit of regional resolution. Within the context of the shallow-water system, I will propose techniques to constrain the damage caused by these locally-large truncation errors. The possible paths forward to incorporate these ideas onto IPCC-class ocean and ice sheet models will be discussed.