Global Warming: A Classic Case of Alarmism April 3, 2009Posted by honestclimate in Discussions.
Tags: climate change, dr david evans, global warming
Global Warming: A Classic Case of Alarmism
From the Jo Nova website
This is a Guest Post by Dr David Evans
The big temperature picture. Graph and insight from Dr Syun Akasofu
(2009 International Conference on Climate Change, New York, March 2009).
The global temperature has been rising at a steady trend rate of 0.5°C per century since the end of the little ice age in the 1700s (when the Thames River would freeze over every winter). On top of the trend are oscillations that last about thirty years in each direction:
1882 – 1910 Cooling
1910 – 1944 Warming
1944 – 1975 Cooling
1975 – 2001 Warming
In 2009 we are where the green arrow points, with temperature leveling off. The pattern suggests that the world has entered a period of slight cooling until about 2030.
There was a cooling scare in the early 1970s at the end of the last cooling phase. The current global warming alarm is based on the last warming oscillation, from 1975 to 2001. The IPCC predictions simply extrapolated the last warming as if it would last forever, a textbook case of alarmism. However the last warming period ended after the usual thirty years or so, and the global temperature is now definitely tracking below the IPCC predictions.
The IPCC blames human emissions of carbon dioxide for the last warming. But by general consensus human emissions of carbon dioxide have only been large enough to be significant since 1940—yet the warming trend was in place for well over a century before that. And there was a cooling period from 1940 to 1975, despite human emissions of carbon dioxide. And there has been no warming since 2001, despite record human emissions of carbon dioxide.
There is no actual evidence that carbon dioxide emissions are causing global warming. Note that computer models are just concatenations of calculations you could do on a hand-held calculator, so they are theoretical and cannot be part of any evidence. Although the models contain some well-established science, they also contain a myriad of implicit and explicit assumptions, guesses, and gross approximations—mistakes in any of which can invalidate the model outputs.
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