Global Warming Predictions, Computer Modeling, and Error Reporting 4

[TGS4]

It's been a while since we had a good AGW discussion here. I read an article yesterday that discussed the climate models and their error (in other words ±1%, 5%, 10%, etc).

http://www.skeptic.com/the_magazine/featured_articles/v14n01_climate_of_belief.html

I work with computer models (FEA) for a living, so I can appreciate the issue of error reporting. My models are approximations, so they have error such as discretization error, boundary condition error, material property error, etc. I always report on those sources of error in my reports. Why do none of these discussion about future climate modeling ever discuss the error in the models?

So, forget whether or not the planet is currently warming. Maybe it is, maybe it isn't. I personally don't have enough knowledge to know for sure. However, if the climate models that we are basing predictions on are actually on the order or +4°C ± 100°C in 100 years, then I call BS. Who cares whether or not the different models agree with each other, what about the agreement with observation?

 

[321GO]

Steve nailed it.

a engine CFD model can be predicted because of the corelation between the crankshaft position and the state of the system, i.e. between the crankshaft position and the boundry conditions.

Climate has no crankshaft. It's like Steve said, how can you predict such a system...

 

[rb1957]

what i took from the modelling comparison is that modelling inherently involves simplification, focussing your attention of the most important elements of the problem.

yes, FEA is much more of a closed loop (defined causality) compared with chaotic global weather. but a key differences with FEA are ...
1) we can define the most important elements of the problem,
2) we hae a very good handle on how these elements interact with one another, and most telling
3) we can make predictions as to how an experiment will play out, and finally
4) we can include neglected effects when the experiment doesn't go as predictd.

for the global weather models, i'd give them 4) but not ...
1) i don't think we how th most important elements (but rather focus on what we want to be the most important),
2) we eally don't know how the elements of the system interact, and
3) ok, i guess they've been making predictions (but i'd expect they'd say, with reason, that the timeframes we're looking at are too short for reliable forecasts).

just my 2c