Guest Post by Ira Glickstein
As I continue to plow through Vol 1 Issue 1 of the new Journal Nature Climate Change, I came to the following amazing statement:
Communicating the value of climate modelling … requires confronting such apparent contradictions as the fact that increasing a model’s complexity — by adding the behaviour of clouds, people or ecosystem feedbacks, for example — may actually increase the uncertainty in climate projections. Atmospheric scientist Kevin Trenberth of the US National Centre for Atmospheric Research in Boulder, Colorado, has explicitly warned that unless such seemingly paradoxical results are communicated carefully, the more complex modelling being used in climate simulations for the upcoming fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) may confuse both the public and decision-makers, thereby reducing their willingness to act. [My emphasis]
“Apparent contradictions”? Heck yes, and more than simply “apparent”! The Warmists finally understand that including the major natural cycles and processes that affect climate change in their models will make it that much harder for them to convince the public that human activities are the main cause and, therefore, changing our activities the main solution!
Yet, the title of the paper that includes the above quote is The role of social and decision sciences in communicating uncertain climate risks – as if communications was the major problem, rather than the fact it is largely nonsense they are trying to communicate.
They base their opinion on Trenberth’s 2010 paper which includes these equally amazing words:
[An IPCC AR5 chapter] will deal with longer-term projections, to 2100 and beyond, using a suite of global models. Many of these models will attempt new and better representations of important climate processes and their feedbacks — in other words, those mechanisms that can amplify or diminish the overall effect of increased incoming radiation. Including these elements will make the models into more realistic simulations of the climate system, but it will also introduce uncertainties.
So here is my prediction: the uncertainty in AR5’s climate predictions and projections will be much greater than in previous IPCC reports, primarily because of the factors noted above. This could present a major problem for public understanding of climate change. Is it not a reasonable expectation that as knowledge and understanding increase over time, uncertainty should decrease? But while our knowledge of certain factors does increase, so does our understanding of factors we previously did not account for or even recognize. …
Trial and error
It has been said that all models are wrong but some are useful. …
Performing cutting-edge climate science in public could easily lead to misinterpretation, and it will take a great deal of work communicating carefully with the public and policymakers to ensure that the results are used appropriately. … what to do about climate change is a high-profile, politically charged issue involving winners and losers, and such results can be misused. In fact — to offer one more prediction — I expect that they will be.
[My emphasis]
When confused, when in doubt, run in circles, scream and shout.
Here is what they say (and what they may be thinking):
- Including important forcings, such as clouds, will increase uncertainty. (Yeah, we were much more certain when our simple models gave nice crisp conclusions that matched our political biases. Then we added some of the complexity of the real-world climate, and now the conclusions are uncertain. Could it be that our political biases are at fault? Nope, we just have to work on our communications tactics and “social and decision sciences” to sell this load of baloney to the great unwashed public.)
- The contradictions are merely “apparent” and the results merely “paradoxical”. (Yeah, if we merely communicate this stuff carefully so as not to confuse the public and decision makers and make them unwilling to act in the politically-correct way.)
- There are mechanisms that can amplify or diminish the overall effect of increased incoming radiation. (OOPS, we forgot about those effects that diminish the overall warming. How can we include them in a way that does not add to public uncertainty about our competence?)
- Scientific knowledge and uncertainty are supposed to increase over time. (So how come we keep looking dumber?)
- All models are wrong, but some are useful. (Why is it that as our models become less wrong they become less useful to our political agenda?)
- Public disclosure of climate science research results can lead to misinterpretation and results can and will be misused. (We better keep our climate research results away from the public until we get a chance to misinterpret and misuse them before the skeptics find out the truth behind our methods.)
“”””” I can’t tell if you’re familiar with it, or if netdr2 is, but the logarithmic nature of CO2 concentrations to temperature is merely a rule of thumb. It breaks down at concentrations significantly above or below current levels, but does hold for much of Earth’s O2 containing atmosphere. “””””
Ric, that is a comletely unsupportable statement.
Based on ANY recognized mean global surface Temperature data set; and ANY recognized atmospheric CO2 abundance data set covering the same time range; there is NO analysis, that you or anyone else could do, which would show that the two are logarithmically related; or that they are NOT linearly related; or in fact that the relationship is ANY defined mathematical function you want to name. And the Logarithm function IS a precisely defined mathematical function; it is not some nebulous non-linear relationship. In fact you can’t prove that it is even ANY non-linear relationship or for that matter that they are related at all.
All of the believable available data, shows that the CO2 follows an anual cyclical periodic oscillation of about 6 ppm amplitude added to a baseline continuous increase, of about one to two PPM per year. The most believed mean global surface Temperature data sets, availabble from at least four sources, don’t show any sign of such an annual cyclical variation; nor do they show a continuous monotonic increasing value. The Temperature data, wanders up and down in sometimes periodic looking events that may last for 30 or 60 years or so, and show no correspondence to the log of the CO2 amount at all..
The available data isn’t anywhere near good enough by a long shot, to say that any relationship is linear; or non-linear in a logarithmic fashion.
There is the question of some time lag between one phenomenon and the other. There is NO time offset, that one can use between the CO2 and Temperature data that would revela a logarithmic relationship; nor any that would reveal a linear relationship. Their association is quite chaotic. It might be said that over periods of centuries, both variables may appear to be increasing; but given the extreme range of possible Temperatures on earth from around -90 c minimum to about +60 c maximum; all available simultaneously, we can’t even say reliably that we have any idea what the mean global surface temperature is.
A logartihmic curve is no some arbitrary non-linearity; it is a precise defineable mathematical function that usually has its roots in some theoretical basis for being such a curve. And there is no such theoretical basis for expecting a logarithmic relationship between CO2 abundance, and mean global surface Temperature; and many poeople are in agreement, that that is the definition of “Climate Sensitivity”; for better or for worse.
Mike Bromley the Kurd says: April 28, 2011 at 8:36 pm “Who the heck is John Galt indeed.”
Being a theme from a famous novel, that in one sense is about methods of knowledge, which is a major problem in climate “science” – it is about the efficacy of the human mind. Part of the plot is much about the results of not using the mind for human life in respect of reality – poverty, disaster, corruption, and violence. Examples abound around the world, throughout history.
The book “Atlas Shrugged” is still in print, and part 1 of it is a movie now showing in theatres: http://www.atlasshruggedpart1.com/theaters.
This genius is confusing the meaning of uncertainty Accuracy Precision, and the range of your calculated answer must be greater than the natural variability.
Short version, we have a more accurate physical model, but we are hitting the butterfly effect.
George, there is a definite logarithmic physical relationship between infrared absorption and fractional concentration (or an Arrhenius relationship with gas density), and it does break down in the very high volumes when the O2 absorption band starts decreasing. Now, this cannot be determined on a global scale due to noise, uncertainty, and an overall weak signal. However, it does exist and there is a theoretical and factual basis for the relationship.