May 28, 2003

Predicting the Future

Someone once said, "Predicting is hard, especially the future." That said, much of the rhetoric around relating science to policy making is based on the hope / belief that scientists and their models will be able to predict the future and it is the job of the policy maker to move society out of harm's way or to alter the future in beneficial ways. There are at least tow interesting things here: First, can scientists predict the future? and second, can policy makers alter the future?

Can scientists predict the future?
Consider climate: The US Global Climate Research Program (USGCRP) has invested more than a billion dollars in the development of General Circulation Models (GCMs).

GCMs are a class of computer models that attempt to simulate the circulation patterns of the oceans and the atmosphere. These models vary in how they represent the underlying physical processes. These variations reflect choices on the part of the modeling groups and in turn effect the kinds and details of the output produced by the model. Intercomparison of models and efforts to understand why model results differ is a major area of research.

GCMs are becoming more detailed with respect the processes that are included and with respect to the output that is produced. These models are often tested by hindcasting. In hindcasting, models are initialized with known conditions from some time in the past. The model output is then compared with observations from the subsequent climate history. The thinking is that if a model successfully "predicts" the past, it might be trusted to predict the future.

I said a while ago that weather prediction is not likely to go further out than it currently does (although I recently read an article suggested that understanding certain long wavelength waves in the atmosphere may extend certain kinds of weather prediction out beyond the current 5-7 days). So assuming we do trust GCMs to predict the future, the future of what? Well in the case of GCMs it would be climate with its inherently time and spatially averaged characteristics and related uncertainties. In general, the finer the spatial or temporal resolution we ask of a model the greater the uncertainty associated with the output.

Much of this line of thought is driven by conversations with Dan Sarewitz. In particular, beneath this description of models are some very fundamental questions having to to with the relationship between models and the systems that they represent.

Can policy makers alter the future?

Implicit in our faith in model-as-oracle is one of the following two conditions: either 1) the mdoel adequately represents all of the important processes; or 2) assumptions about external conditions remain true through out the prediction period.

I would argue that condition 1) is unlikely to ever be true with respect to cliamte models. This is because human behavior is a fundamental element of the climate systemand human behavior cannot be modeled on the scales of GCMs. Current climate models inlcude human behavior as an input primarily in the form of scenarios of expected GHG emissions and other forcing behavior.

So policy makers can alter the future by putting in place structures that alter the human forcing of climate. This would violate condition 2) in our current modeling infrastructure.

One more detail to be cleaned up
In my initial formulation I not only had policy makers altering the future, but also altering it for the better. This is a pretty serious caveat to have brushed over. To be true it too requires two things (all 3 "tos" in one sentence!): 1) we can successfully predict the outcomes of our policies; and 2) we can agree on what "beneficial" means. (Now you can see why I brushed over them.)

At any given time there is a closed (?) set of possible futures. Some of these futures are more likely than others. More likely futures are "closer" to our current trajectory than less likely futures. As our society evolves, the probability distribution of possible futures changes; some become impossible (avoided disasters / missed opportunities) other become more likely. I think that one of our guiding ideas should be to keep the space of possible futures as large as possible and the probability map skewed in ways that reflect as best as possible our collective vision of better world.