Whenever I hear those that deny anthropogenic global warming, they often talk about how climate science is predicated upon a bunch of 'assumptions' that are untenable. What are these assumptions and what do they actually mean, and why do they invalidate scientifically climate science?

Thanks Soren, I am actually directing this at the skeptics on this board, but it would be good to see some input from non-skeptics too.

Soren wrote on Nov 11^th, 2010 at 1:18pm:


Come on Soren, you'll have to do better than that. What are you sceptical about with respect to Al Gore?

- his existence?
- his credentials as a communicator?
- the colour of his tie?
- his taste in food?
- the fact that his eyes are too close together?

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Every time I try to explain this, you either go silent or say something like (paraphrased) "Sorry, I'm not convinced" without explaining exactly which part you had issues with.  - or was it more a case of

- "Oh it's all too complicated for me to understand therefore nobody could possibly understand this because I'm smarter than everybody else" ?

Maybe it's your philosophical background talking when you said once  (paraphrased) "There are no answers - only questions"

Well that's it then, we might as well all give up. Technology is a figment of our imaginations because Soren says it's too hard, and no questions can be answered.

The point is that you haven't attempted to understand the explanations and evidence that has already been profferred.

If all scientists suddenly became philosophers, the world would be like Monty Python's soccer match, with everybody agonising about the first move.

Weather forecasting is a great deal more complex than forecasting the temperatures and average rainfalls 50 years from now.

Regardless of that, I've been using a publically available weather forecasting model for the last 3 years that has been very accurate for rainfall prediction up to a week in advance.

Certain aspects of climate are much easier to get right than that, and relatively primitive models developed in the 1980's have largely predicted the last 25 years with remarkable accuracy. Currently we are into 4th generation climate models which now include ENSO and Solar cycle data.

We can use past recurring patterns and superimpose the effects of an average increase in Global temperatures.

If you put it very simply, increasing greenhouse gases decreases the Long Wave Infrared radiation to space, and increases the net energy of the lower atmosphere.

If you have a stepwise increase in the amount of energy going into a system (any system) you will see some kind of change.

That change can manifest itself in terms of increased temperature or the energy can be expended elsewhere (eg wind). Either way, we'll see a change.

We know how much greenhouse gases we are emitting (accountants make sure this information is accurate because of the $$$ that change hands).

We can see the effects of increasing CO2 on ocean pH and the effects this will have on a great many economically important species.

Regardless of whether it will happen in 2035 or 2060, the glaciers of this world are decreasing in size and will continue to do so, barring a super volcano erupting or something else that has not happened in the past 70,000 years or so.

The implication of the reducing size of glaciers, such as the himalayans are changes in regional climate (eg monsoons) and reduction in floodwaters.

For weather, this is an excellent precipitation model:

http://www.bom.gov.au/australia/charts/viewer/index.shtml

The financial pressures associated with business are even more complex than global climatic data, yet even there, we don't throw our arms up in the air and say "It's all too difficult"

We work on the best data we can get, and in the case of climatology that data is making some predictions which have not substatially changed (except in terms of increasing magnitude) since the mid 20th century.  

It comes down to the fact that for these high risk consequences, only a fool, or Christopher Monckton (on second thoughts,  'only a fool' says it all) would subscribe to the do-nothing option.

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I have heard similiar arguments employed against the usage of heritability analysis as well. You are demanding predictions made with near absolute certainty, and this requires a model that is a totally immaculate replication of actual climate as it exists in the real world. I thought that science was supposed to be probabilistic, and where absolute certainty cannot be established (if it can truly ever be established) we have to reply on reductionist approaches where the available models which are the most predictive of actual phenomeona with the highest probability are selected as the most favoured models. Am I off or is this supposed to be the argument Muso has always tried to make?

gizmo_2655 wrote on Nov 12^th, 2010 at 3:21pm:


Did you pull those figures regarding the inaccuracy of future climate prediction (long term climate) based on current climate models and trend projections out of your arse or do you have anything to back that up?

In other words, weather is what is actually happening while climate is statistics of what has happened.

Weather is what we actually experince. We do not experience climate.