From the blog Serendipity as useful discussion on calibration
..ask what is the purpose of a climate model. The second half of the George Box quote is “…but some models are useful”. Climate models are tools that allow scientists to explore their current understanding of climate processes, to build and test theories, and to explore the consequences of those theories. In other words we’re dealing with three distinct systems:
We're dealing with relationships between three different systems
There does not need to be any clear relationship between the calculational system and the observational system – I didn’t include such a relationship in my diagram. For example, climate models can be run in configurations that don’t match the real world at all: e.g. a waterworld with no landmasses, or a world in which interesting things are varied: the tilt of the pole, the composition of the atmosphere, etc. These models are useful, and the experiments performed with them may be perfectly valid, even though they differ deliberately from the observational system.
What really matters is the relationship between the theoretical system and the observational system: in other words, how well does our current understanding (i.e. our theories) of climate explain the available observations (and of course the inverse: what additional observations might we make to help test our theories). When we ask questions about likely future climate changes, we’re not asking this question of the the calculational system, we’re asking it of the theoretical system; the models are just a convenient way of probing the theory to provide answers.
By the way, when I use the term theory, I mean it in exactly the way it’s used in throughout all sciences: a theory is the best current explanation of a given set of phenomena. The word “theory” doesn’t mean knowledge that is somehow more tentative than other forms of knowledge; a theory is actually the kind of knowledge that has the strongest epistemological basis of any kind of knowledge, because it is supported by the available evidence, and best explains that evidence. A theory might not be capable of providing quantitative predictions (but it’s good when it does), but it must have explanatory power.
I redid the above graphic in Powerpoint
In terms of SWMM 5 and other models let me paraphrase the above:
We're dealing with relationships between three different systems
There does not need to be any clear relationship between the calculational system and the observational system – I didn’t include such a relationship in my diagram. For example, hydrology/hydraulic models can be run in configurations that don’t match the real world at all: e.g. a watershed without detail or simple assumptions, or a watershed in which interesting things are varied: the modeling detail for catchment complexity, slope, overland path length, impervious connections, soil and infiltration detail and methodology. You can also leave out important components such as ground water and water quality. These models are useful, and the experiments performed with them may be perfectly valid, even though they differ deliberately from the observational system.
What really matters is the relationship between the theoretical system and the observational system: in other words, how well does our current understanding (i.e. our theories) of hydrology/hydraulics explain the available observations (and of course the inverse: what additional observations might we make to help test our theories). When we ask questions about likely future watershed changes, we’re not asking this question of the the calculational system, we’re asking it of the theoretical system; the models are just a convenient way of probing the theory to provide answers.
