Introduction
According to Rhoads (1999), while physical geographers do engage in debates of methodology and interpretation of scientific data and results, they seldom engage in philosophical discourse. While I agree with his notion that there is much to gain from engaging in such rhetoric, I, myself, am not often drawn to initiating such discussions. In fact, I tend to steer quite clear of them at meetings, perhaps afraid of the “impenetrable jargon” (Schneider, 2001), unless those involved are among those colleagues who I hold in the highest regard.
Chief among the opportunities for physical geographers to engage in any sort of philosophical discourse is when discussing the validity of models. Models, themselves, are highly interesting tools, which when applied correctly, can yield interesting scientific information. Most modelers are aware of the constraints of models, and are careful in their use and in the interpretation of their results. Others, however, are often guilty of using the results of models and treating them the same they would as real observations.
It is all to often, as Demeritt (2001) and Schneider (2001) agree, that model results, or the conclusions drawn from them, are touted by the media, and the model uncertainties and caveats are often disregarded. While the dangers of this are obvious, the opposite is often true when it comes to policy, as Schneider points out: “if we scientists don’t stop caveating everything so much, they won’t be able to get political support for strong action.”
Generally, I think that physical geographers look critically at models, especially their physics, sensitivities, and their abilities to simulate the real world. On the other hand, human geographers might draw into question the use of the model itself. In simpler terms, the physical geographer asks “Is this the best model, and can I trust its results?”, while the human geographer asks “Is it appropriate to use a model in this case?”
The case of Global Climate Models (GCMs)
GCMs are our best option for analyzing how the Earth’s climate might behave in the future given some forcing, such as increased greenhouse gas concentrations. Yet the climate system is highly complex, and therefore behaves chaotically, and non-linearly. Our climate history includes few instances of slow and gradual change, and instead has been punctuated by frequent abrupt changes. This suggest a highly chaotic and non-linear system. The Earth’s climate system depends on the energy balance and dynamics of the atmosphere, the hydrosphere, the biosphere, especially the interactions that plants, humans, and algae have with the atmosphere and hydrosphere, the cryosphere, and, in the case of volcanic out-gassing and eruptions, the lithosphere. Each of these five spheres on its own is highly complex, but the cris-crossing interactions between each of the spheres adds a whole new level of complexity. As such, trying to capture this whole system, including all of its complexities in a numerical model seems absurd at first.
Computer models, however, are not intended to capture every bit of complexity of the Earth systems. Instead, modelers attempt to boil this complexity down to its simplest and most significant parts. They create a model which can simulate the present climate, or the climate over the last 100 years. Then they run these models ahead another 100 years to get an estimate of what climate might do in the future. When they add certain forcings to the models, like increased CO2 concentrations, one hopes that the difference in the model results can tell us something about how those forcings might affect climate in the future.
There is a philosophical question that is still left up in the air regarding models and their results. If you create a model that represents climate, and you run this model into the future, you may be gaining little insight as to how the actual climate system may behave in the future, as the uncertainties, complexities, and feedbacks involved in the actual climate system extend far beyond what is coded in a model. Furthermore, any forcing behavior exhibited by the model is just that, forcing behavior exhibited by the model. There is no way to know if the actual climate system will behave in the same way.
But that is just it, isn’t it? There is no way of knowing how the climate system will react, but climate models may give us some clues.
Geographers who criticize models, and ask critical questions about the models and their results force the modelers to take stock in their models and to see where improvements can be made, to clarify the certainties of the model, and to illustrate any and all weaknesses and uncertainties. Schneider asserts that modelers tend to do this already, which begs the question “what can really be gained by these deconstructions?”
In conclusion, I assert that Human Geographers have no precise analog to a physical, numerical, or analytical model. They are stuck with statistical and empirical models, which in Physical Geography are often seen as second best. Accordingly, they belay their frustrations and misunderstandings by criticizing our tools and the knowledge we reap from them. How dare they sabotage our techniques? I think they are just jealous!
Rhoads, B. L. (1999), Beyond Pragmatism: The Value of Philosophical Discourse for Physical Geography, Annals of the Association of American Geographers, 89, 760-771.
Schneider, S. H. (2001), A constructive deconstruction of deconstructionists: a response to Demeritt, Annals of the Association of American Geographers, 91, 338-344.