When 95% of the models don't accurately predict the outcome, isn't it time to try a different model?
Or do we simply acknowledge that there is obviously more to the picture than what we can currently account for, i.e. that our refusal to admit our own ignorance is our own worst enemy!
Let see now, suspect models, suspect data, and suspect motives. I'm surprised they agree as much as they do.
Nortmally the generation of a model of the sort needed to approach the complexity of a problem like Global Warming is the work of multiple teams each focusing on certain elements of the problem and communicating constantly with the other teams. there could be as many as 100 variables needed to specify a particular data point or series of data points.
All of the data must be analyzed and vetted prior to use. The things that must be done take incredible amounts of work. Once all of this has been assembled and validated through several stages, then the prediction can be mad.
The predictions would be check against the real world and against other models. Variations must be examined and explained before moving on to the next set of trials.
I will grant I don't follow the Global warming models so I cannot say for certain this protocol was not followed, but the variability between models leads me to wonder.
And yes I do know what I’m talking about. Send me a private message if you want credentials.
The whole climate change "industry" is build on the foundation of lies created to destroy capitalism and support statist control.
Here's another link for those interested on atmospheric composition:
http://en.wikipedia.org/wiki/Atmosphere_...