The rigidity of long-existing models and the lack of efforts to remove inferior or flawed physical representations hinder progress by preventing opportunities for new, fresh thinking.
These trends could cloud the future of the fields of atmospheric science, climate, and oceanography. Models are widely used, perhaps much more so than could have been anticipated at the dawning of the computer age some 40 years ago. The growing user community includes many nonspecialists who are not prepared to assess or question the reliability of model predictions. As computers become larger and allow even finer model resolution, some local model forecasts will become increasingly stochastic. It was not clear to the workshop participants that the atmosphere, climate, and oceanography communities are prepared or even constituted to make the required adjustments, refinements, and improvements in model parameterizations that this will require. It is particularly troubling that if our unresponsiveness to the parameterization challenge is indeed culturally driven, its implications carry an aspect of inevitability.
Atmospheric scientists and oceanographers understand both the practical and scientific importance of the parameterization problem. But we also need to bestow it academic dignity by acknowledging it as a difficult and important problem in mathematical physics. Indeed, it involves, among other things, turbulence, which is commonly referred to as the outstanding unsolved problem in classical physics. The parameterization problemwhich could be defined as the identification and understanding of the physics of unresolved processes and the compact, optimal representation of this physics in numerical modelsdeserves serious attention from the best and brightest.
This report summarizes the discussions of the workshop participants on parameterization approaches and frameworks and on specific targets for parameterization improvement. Among the key issues identified by the participants were the following:
An important field of parameterization science has emerged over the past 40 years as a result of the computer revolution. Workshop participants believe that our educational, research, and funding institutions need to recognize, accommodate, and foster this new field.