Clarifying the Role of the Sun and Global Temperatures
Posted by jennifer, December 4th, 2008 - under Opinion, Uncategorized.
Tags: Climate & Climate Change
YESTERDAY atmospheric scientist, Professor Marvin Geller, explained to Leigh Dayton, science writer at The Australian newspaper, that the sun could not be driving “recent global warming as climate change sceptics claim” because solar radiation has not changed very much since 1978.
But climate change sceptics do not claim there has been recent global warming. They claim there has been a levelling off, or fall in temperatures, over the last 10 years since the 1998 El Nino-driven peak. [Click on the chart for a larger view of global temperature trends.]
As regards the El Nino event of 1998, according to Professor Geller, El Ninos cause a temporary increase in global temperatures, not the steady and consistent upward trend typical of warming from greenhouse gases like carbon dioxide.
But there has been no “consistent upward trend”.
Indeed, Professor Geller misrepresents the position of global warming sceptics and the available global temperature data.
It is apparent from the satellite data that there has been no consistent recent warming trend and the 1998 El Nino effect does not appear to have been temporary. Indeed since 1998 there has been a one-step warming shift of about 0.2 degrees. [Click on the chart for a larger view.]
Interestingly the same day ‘The Australian’ quoted Professor as dismissive of the role of the sun, the journal ‘Geographical Research’ published a paper suggesting a correlation between solar magnetic phases and the state of the El Nino- Southern Oscillation Index (SOI).
The paper by Robert Baker emphasis the influence of the sun’s magnetic field through the rate of ionisation – the rate of ionisation being affected by solar cosmic ray showers whose incidence follows the inverse of the sunspot cycle – not solar radiation as suggested by Professor Geller. Dr Baker claims his discovery has important implications for future drought predictions in Australia recognising the relationship between the SOI and rainfall in Australia and the periodicity of the strength of the sun’s magnetic field.
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Notes
Professor Sheds Light for Climate Change Sceptics by Leigh Dayton, The Australian, December 4, 2008, http://www.theaustralian.news.com.au/story/0,25197,24748258-11949,00.html
The chart of satellite temperatures is from Roy Spencer’s website, http://www.weatherquestions.com/Roy-Spencer-on-global-warming.htm
Robert G. V. Baker, 2008, ‘Exploratory Analysis of Similarities in Solar Cycle Magnetic Phases with Southern Oscillation Index Fluctuations in Eastern Australia’ in Geographical Research (Vol 46, pp380-398)
SJT: as you are sure you are always right, what have you to fear? My reference was of course to Hansen proposing Nuremburg for the CEOs of Exxon etc. and you are clearly a Hansenite. If the cap fits wear it. But here as ever you seize on any esxcuse to avoid answering my questions. Again, what is the optimal level of [CO2] for world food production? Is Hansen right, 350, when world food production was 50% less than it is now at 385? But if you can’t stand the heat keep out!
Best
Still digging I see, SJT. Dear God but you are breathtakingly stupid. Do you have trouble remembering how to breathe?
In other words, you have nothing. Worked out the difference between an observation and a proxy yet?
Haven’t got a clue, have you?
Wouldn’t a preference for a linear fit also involve assumptions. Specifically, it would fail to pick up any reversal in trends.
I’m not saying the trend is reversing. I’m just saying that a linear fit isn’t always appropriate.
“I’m not saying the trend is reversing. I’m just saying that a linear fit isn’t always appropriate.”
Fair enough. Are you actually trying to have a rational conversation here on the pros and cons of the actual debate? That would be nice for a change. :)
“Wouldn’t a preference for a linear fit also involve assumptions. Specifically, it would fail to pick up any reversal in trends.”
John.
There are a number of ways of testing one’s fitting of a LoBF, ranging from a simple eyeballing of the spread of points that all first-years are taught to do, through to monitoring the trend in residuals and to more complex computations of the ‘appropriateness’ of the model’s fit.
In all instances Ockham’s razor applies, and a fourth-order polynomial is hardly this.
Most important to recall is that lines of fit are only applicable to the data used to derive them, and not to portions of the x-axis that lie outside the analysed section. If such inappropriate extrapolations WERE done, linear regressions (where they fit the data) are less fraught with the confoundment of what might be happening in the near neighbourhood outside of the fitted section, compared with high order polynomials that just fall over like drunken sailors.
The higher the number of parameters you need for a fit, the fewer degrees of freedom you have (e.g. the number of data points gives a degree of freedom, if they are autocorrelated there fewer), a fit parameter takes away one degree of freedom. Given that you want to fit with as few parameters as possible consistent with the trend.
Why try to do linear regression to a non-linear system? I agree there’s been no warming over the past 11 years – 2008 certainly will drag it down. There still may be a continuing upward trend. (nothing to do with CO2).
I’m yet to find any data that substantiates the hypothesis that increasing CO2 concentration increases temperature (outside models that haven’t worked). However, it’s hard to ignore the solar/Maunder correlation. Based on solar activity, and long term historical data, I’d predict we’re now coming into a minor cooling period, with a severe cooling trough anytime in the next 1,000 years,
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