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Much of today's environmental public policy is based on junk science
March 11, 2013
EDMONTON, AB, Mar. 11, 2013/ Troy Media/ – Several leading warmists – including Rajendra Pachauri, chairman of the UN’s Intergovernmental Panel on Climate Change, James Hansen of NASA, and the Met Office – now:
1) admit that mean global temperatures have not risen since 1997 and that the warming trend has stalled
2) accept that there was only a modest temperature rise in the 20th century, a continuation of the warming trend that began 200 years ago as the world naturally emerged from those centuries of cooling known as the Little Ice Age, and
3) concede that the 0.5C rise between 1976 and 1998 was no greater than the 0.5C rise between 1910 and 1940 (with 35 years of cooling between them, so that the net rise in the past century has been only 0.8C).
But this hasn’t stopped them from suggesting that the end is still nigh and that we have only months to act to reduce CO2 emissions to prevent catastrophic global warming beyond the 2C ‘threshold’ picked to signal doom.
So if it isn’t the actual evidence driving their continued concern, what is it?
They are relying on the virtual science – computer models that point to continued warming and the need to be alarmed at the rate of CO2 emissions – to support their warmist view.
Yet some 700 scientists in 400 different institutions in 40 countries in peer reviewed papers disagree. They point out that the medieval warm period was much warmer than at present.
Computer models, after all, depend on the data and analysis framework programmed into them. Currently, none of the models in use to replicate the climate for the last 100 years can do so. A paper published in January in the Journal of Climate finds that climate models have little to no ability to provide skillful forecasts of global surface temperatures on timescales of a decade or more. According to the author, Matthew Newman (University of Colorado), “these results suggest that current coupled model decadal forecasts may not yet have much skill beyond that captured by multivariate red noise.” In plain English: not much better than a table of random numbers.
A paper published last December in the Journal of Geophysical Research compares observations of wind speeds over China from 1971 to 2005 to the results from nine IPCC AR5 climate models for the same period and finds that all nine models show a “substantial positive bias,” i.e. a substantial exaggeration, of wind speeds. The paper adds to many other peer-reviewed papers demonstrating that IPCC climate models greatly exaggerate extreme weather, cyclone activity, wind storms, droughts, and floods. (Read The Hockey Shtick)
Also last December, several scientists reported in the American Meteorological Society’s peer-reviewed Journal of Climate that they:
‘. . . examined the annual cycle and trends in Antarctic sea ice extent (SIE) for 18 Coupled Model Intercomparison Project 5 models that were run with historical forcing for the 1850s to 2005. Many of the models have an annual SIE cycle that differs markedly from that observed over the last 30 years. The majority of models have too small a SIE at the minimum in February, while several of the models have less than two thirds of the observed SIE at the September maximum. In contrast to the satellite data, which exhibits a slight increase in SIE, the mean SIE of the models over 1979 – 2005 shows a decrease in each month, with the greatest multi-model mean percentage monthly decline of 13.6 per cent dec-1 in February and the greatest absolute loss of ice of -0.40 Ã— 106 km2 dec-1 in September. The models have very large differences in SIE over 1860 – 2005. Most of the control runs have statistically significant trends in SIE over their full time span and all the models have a negative trend in SIE since the mid-19th Century. The negative SIE trends in most of the model runs over 1979 – 2005 are a continuation of an earlier decline, suggesting that the processes responsible for the observed increase over the last 30 years are not being simulated correctly.’ (my emphasis).
I could go on. There are hundreds of critiques of these models, including some from those responsible for them. Gary Strand, a software engineer at the federally-funded National Center for Atmospheric Research (NCAR), admitted climate model software ‘doesn’t meet the best standards available’. In a comment he posted on the website Climate Audit, he said: ‘as a software engineer, I know that climate model software doesn’t meet the best standards available. We’ve made quite a lot of progress, but we’ve still quite a ways to go,’ (July 5, 2009). NASA’s GISS model E is written on some of the worst FORTRAN coding ever seen and it is a challenge to even get running. NASA GISTEMP is even worse. Yet governments around the world have legislation and regulations enacted or under consideration based on model output from these kind of poor systems.
It is these models that are driving the agenda for climate change warmists, not the evidence from direct observations, with one notable exception made by some scientists: that extreme weather events are increasing as climate warms. At the opening of the 18 annual United Nations climate summit held in Doha, Qatar, UN climate chief Christiana Figueres urged governments around the world to ‘do something about’ extreme weather. ‘We have had severe climate and weather events all over the world and everyone is beginning to understand that is exactly the future we are going to be looking about if they don’t do something about it,’ she said. Former U.S. Vice President Al Gore summed up this view when he wrote: ‘Every night on the news now, practically, is like a nature hike through the book of Revelations’.
The difficulty here is that this is not the view of scientists, like Roger Pielke Jr of Colorado, whose work is dedicated to the study of extreme weather events. This area of science has been his life’s work and he makes clear that the consensus of science is that extreme weather events are not connected to climate change and also that their incidence is, in fact, in decline. While noting that the models say something different (because they are programmed to do so), the observations would suggest that the extreme weather events globally are not as frequent or as severe as they have been in the past.
So here is the issue: do we want to make public policy on the basis of flawed and generally wrong models or do we want a policy that is based on more traditional forms of scientific practice?
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