A word of caution

Is computer-based modeling in general the best way to handle complex associations of processes controlling landscape and climate ? 

Climate and landscape processes are in a continuous dynamic state of flux, representing an analogue system, where everything is happening simultaneously. In contrast to this, computer models are digital, trying to solve a problem by repetitive calculations (iterations), before moving on to solving the next problem, etc. This is clearly a significant drawback for computer-based modeling of nature.

While the laws of physics may be immutable, it is not always predictable which law or process will predominate over which when a maelstrom of competing laws are acting simultaneously as is the case of climate and landscapes. The description of the individual laws in a model are hopefully correct defined in the equations used, but the dominance or subservience of one law to dozens of others is defined by the modeler, not by the model itself. The modeler decides that issue in the way the code is written. 

In the end, the computer model therefore simply mirrors the intellectual choices of the modeler and only puts numbers to them. If those choices are based on flawed reasoning or insufficient observational evidence, it is naive to believe that the model will somehow iron out the problem through sheer number crunching power. That would be to attribute qualities of judgment to models which they simply do not have. In essence, a model does not relieve the intellectual burden of determining which variable is dominant over which. The modeler has to choose when writing the code, and this choice then becomes integral to the model. Anybody who plan to make use of a model not coded by him- or herself should consider this scientific aspect very carefully.

For those simple reasons, computer models can never be superior to the knowledge based understanding derived from experiments and classic field observations. Models may prove powerful instruments in developing our understanding of complicated laws and process associations. However, until the empirical knowledge coded into them is perfect they still have to be considered as predictive tools with many limitations. Never put the chart before the horse !

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Latest update: 13. March 2003.