Tuesday, 15 December 2009

Climate and carbon

As a statistician who worked on some of the glacial Varve datasets, I have to state that the way that the results are reported has nothing to do with the calculations we did.

Carbon from human sources is less than 2% of the global emissions.

Most critically, 83% (+/-4% at a 95% CI)  of the model is attributable to water (H2O) vapor. At present, we can not model water vapor. The result is that the models are highly non-robust.

The real issue lies with water. Deforestation is impacting rainfall patterns, but we can not as yet quantify the effect. The carbon issue is drowning the issues that actually occur in a quasi-religious and definitely non-scientific paradigm. The problem is that this is actually damaging things more as we are failing to focus on the actual issue.

Add to this the filing of several solutions to the entire GW issue, and we start to see that it is really not about the climate at all. IV (Intellectual Ventures) have a number of patients for technological solutions to green house warming. A few other firms have also filed similar solutions. These solutions will require a capital investment of around $250 million dollars to have an adequate effect. Compare this with the $300 million costs associated with Al Gore in his efforts to gain himself a Nobel prize - for NOT doing anything!

Then again, we can model little of interest at present. So we SHOULD wait. We do have solutions, but we do NOT want to implement them when we have NO IDEA of what is really occurring in the world's weather. For instance, in 1974 Time reported on the coming ICE Age.

If we had responded at that time, we would have covered the poles with coal soot (the leading solution of the age) to increase the earth's temperature.

When are we going to wake up and start treating the issues as more than a religious debate?


Andrew said...

Have you looked into solar variance theory at all? Any thoughts?

Craig S Wright said...

It would seem to have an effect on the weather. There is a fair Pearson correlation value for this with statistical significance. The power of all of these results is low and the models are also not robust at present. This could be due in part to a lack of data. The data has been collected for far shorter than that in other areas of climate study.
How this relates to temperature is still conjecture. It does have an input, but we cannot determine what level of input or use this as a predictive as yet.

I think that it is one of many variables that need to be tested. The issue is that the effect that does appear is heteroscedastic and lagged. It also does not correlate directly with average or mean temp. values. Instead, it correlates to distinction regional weather patterns.

I have seen some good preliminary work with Henon maps and chaos, but personally I think that the effect will be fluid dynamical and will take a good many years of analysis. At present, there are no robust models that are both parsimonious and powerful for the input datasets, let alone robust.