Guest post by David Middleton
Models often get a bad rap among skeptics, largely because climate models have demonstrated an epic failure in predictive skill. However, models are extremely valuable scientific tools, particularly when used heuristically. Models are learning tools.
Generally speaking models fall into two general categories:
- Forward problems.
- Inverse problems.
From Wikipedia, the free encyclopedia
An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in computer tomography, source reconstructing in acoustics, or calculating the density of the Earth from measurements of its gravity field.
It is called an inverse problem because it starts with the results and then calculates the causes. This is the inverse of a forward problem, which starts with the causes and then calculates the results.
Inverse problems are some of the most important…
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