OK, given that the evidence is now out on climate change, I am very disappointed that the Government of Canada insists on going along with the charade of Copenhagen by committing us, in a non-binding way, to a reduction of 17% in CO2 emissions from 2005 levels by 2020…

Let’s work out how much that is going to cost…  Since we didn’t reduce emissions from 2005 through 2009 (they went up, even with the reductions from economic contraction), we have to cut deeper now.  That means that to meet the goal, reductions must be of 1.75% every year starting in 2010.   The total reduction in emissions will need to be 744 Million tonnes.  From studies I’ve been involved with indicate carbon capture and storage will cost between $40 – 100 per tonne.  So this will cost at a minimum $30 Billion (today, inflation will drive this up).  The government’s own study in 2007 said that the price of CO2 (carbon tax or credit value) needed to change behaviour sufficiently to reduce emissions would be $195/tonne.  That pushes up the cost over the next 10 years to $145 Billion.  That’s $14.5 billion per year that will be REMOVED from the economy.  And that excludes any knock-on effects that reduce economic growth because investors would rather spend their money in countries that don’t waste money on things like this.  Or impose such regulations.   And it excludes the knock-on effects of the blackouts we are going to have because we can’t build enough nuclear plants in 10 years to counter-act the shutdown of all the coal-fired power plants we will have to shutdown to meet the goal.  An wind and solar aren’t going to replace the coal-fired because they aren’t reliable enough (wind) or don’t work well in the darkness that is a Canadian winter (solar).

Do you want to pay $15 Billion a year to make us “look kinda ok” on the world stage?  Or should we say no and stop chasing this non-existent problem?

So, some climate scientists have published a study showing that the feared feedback loop whereby rising CO2 levels would raise temperatures which would raise CO2 levels, ad infinitum, is not as pronounced as previously believed or modeled.

It is interesting though that the scientists are very quick to discount their own research:

The authors warn, though, that their research will not reduce projections of future temperature rises.

Further, they say their concern about man-made climate change remains high.

Huh?  Why would that be?  Let’s look at another statement they make:

The report’s lead author, David Frank from the Swiss Federal Institute for Forest, Snow and Landscape Research, told BBC News that many of the calculations for the IPCC assessment report did not include an integrated carbon cycle.

He said that if the results his paper were widely accepted, the overall effect on climate projections would be neutral.

“It might lead to a downward mean revision of those (climate) models which already include the carbon cycle, but an upward revision in those which do not include the carbon cycle.

“That’ll probably even itself out to signify no real change in the temperature projections overall,” he said.

Wait – so you are telling me that the climate models used by the IPCC don’t consider the carbon cycle?  But since we know there is a carbon cycle, isn’t ignoring it questionable?  Based on what Frank is saying, including the carbon cycle decreases the warming…  Unless of course you wanted to amplify the warming effect for reasons other than scientific inquiry…

Since the models should incorporate the carbon cycle, it should have a downward revision of projected temperatures. But that wouldn’t get you more research money from the IPCC supporting governments now would it?

And the same reason is likely behind their “concern” remaining high…  Concern for their grant money, not the climate itself.

The “uncertainty” behind global warming science that got its real start with the ClimateGate emails is getting legs as more and more “questionable” things start to pop up.  Here is the latest:

Glaciergate

The IPCC and it’s chairman, Rajendra Pachauri, are starting to take real heat, particularly in India and the UK for promoting the completely speculative idea that the Himalayan glaciers would melt away by 2035 (90% probability).  This was a complete failure to follow their own rules of only using peer-reviewed literature, since they got this from an interview with one of Pachauri’s TERI scientists, Hasnain, in New Scientist, via the World Wildlife Fund.  TERI is now facing serious questions for claiming as recently as 15 January 2010 in a request for funding that the Himalayan glaciers will soon be gone…  Even the lead author on the IPCC AR4 section is now distancing himself from this

Amazongate?

Similar to the aforementioned problem with Himalayan glaciers, it also appears that the IPCC relied on WWF and the International Union for the Conservation of Nature as the primary source for their claim that the Amazon rainforest would dry up and disappear…

IPCC using non-peer reviewed primary sources?

The IPCC AR4 report draws heavily on publications by the World Wildlife Fund, which is most definitely NOT peer-reviewed science.

Cherry-picking weather stations…

The NASA GISS group that puts together the GHCN temperature measurement database appears to have been cherry-picking which weather stations they use, discarding those at high altitude or latitude.  This includes: using four stations for all of California, all of which are located near the beach; 35 stations in Canada, instead of the 600 that were used in the 1970s, and no stations in Bolivia on the odd basis that the Bolivians were late every month in submitting the data (couldn’t you go back an insert the missing data???).  The result is that temperatures far from the few weather stations are being interpolated from the limited dataset in use.  A NASA staffer is quoted as saying:

Schmidt also said a smaller sampling of weather stations in the Canadian Arctic wouldn’t have a significant impact on the data. He said any long-term temperature changes recorded at the high Arctic station at Eureka, would likely be “representative” of changes elsewhere in the region, even in a sub-Arctic city like Yellowknife.

“Temperature anomalies don’t vary that much from one (nearby) station to another,” he said. “You don’t need thousands of stations across Canada to know what the monthly anomalies are.”

This is like saying that temperature measurements in Edmonton, Alberta are a good guidance for Houston, Texas…  And why does Bolivia always seem so warm in the NASA databases…

Or just adjusting the data…

The NASA GISS group also appears to have scrambled around trying to cover up a change in how they handled data post 2000, by altering the previous data in the same way and then denying that it changes their results…  McIntyre has more on this one.

No basis for linking global warming and natural disasters:

The IPCC claimed in it’s 2007 AR4 document that “the world has suffered rapidly rising costs due to extreme weather-related events since the 1970s” and “One study has found that while the dominant signal remains that of the significant increases in the values of exposure at risk, once losses are normalised for exposure, there still remains an underlying rising trend.”

The problem is that the “one study” wasn’t yet published, nor peer-reviewed, and when it was finally published in 2008, it contained this caveat:

We find insufficient evidence to claim a statistical relationship between global temperature increase and catastrophe losses.

Interesting.  So there isn’t any science behind this either.  h/t to Jonathon Leake at the Times.

It is also interesting that this same paper was the source for much of the doom and gloom in the Stern Report.   Interesting too that the UK government has been “editing” the Stern Report very recently to try to make some of the “false claims” disappear.  Too bad their math doesn’t add up.

I hope that the government in Ottawa is reading all of this…

OK, so I’ve crunched the numbers on the non-agreement made at Copenhagen, using data from the IEA on emissions.

In 2006, CO₂ emissions from the world were about 28.4 billion tonnes, of which about 51.5% were from the “developed world”.  This compares to about 21 billion tonnes in 1990, when 66% were from developed countries.

So the non-treaty drafted Copenhagen indicates a goal of reducing global emissions to 50% of 1990 levels by 2050, with developed nations cutting 80% by that date.  Meeting this goal requires:

• Developed nations must reduce emissions at a rate of just about 4% a year, every year, until 2050.
• Developing nations must reduce emissions at a rate of just about 1.5% a year, every year, until 2050.

Delay in reducing emissions immediately will result in much larger cuts being required later.   For instance, if business as usual continues until just 2015, then the cuts would need to be 4.8% and 2.7% a year from then on.  It’s like compounding interest.  Time is the big factor.

When the developing nations spoke at Copenhagen (through the G77), they spoke of reducing emissions intensity.  China, India, others all spoke of reducing the emissions per unit of GDP, not gross reductions.  But the math doesn’t support them.  Even if the developed world cut emissions by 100%, the developing world will overtake global 1990 emissions by 2050 with only 1% growth in gross emissions.   And since we know that China, India and Brazil have emissions rising at rates well above 1%, this seems unlikely.

This is why China killed any agreement at Copenhagen and will do so at Mexico City in 2010.  They will refuse to reduce emissions at all, because of the negative impact on their economy.  Why?  Because reduced economic growth in China will result in political problems.

It is interesting to me that the dream of the socialist left (be they red or green) is being derailed by the largest communist nation – in the name of capitalism!

In the draft proposal leaked in Copenhagen yesterday apparently suggests:

… that developing countries would not be allowed to emit more than 1.44 tonnes of annual carbon dioxide equivalent emissions per person by 2050, but that developed countries would be allowed to emit up to 2.67 tonnes of annual carbon dioxide equivalent emissions per person in 2050.

By comparison, the average Canadian now emits about 23 tonnes per year and the average passenger vehicle generates about five tonnes of emissions per year, according to recent data compiled by Statistics Canada.

Now, that means that Canada would need to reduce emissions by 90% from current levels.  What does that really mean.

Well, first of all, the 23 t/y per person isn’t really a fair number.  Because individuals and households only directly and indirectly account for 46% of the nations emissions (according to Statscan).  So the individual is really about 11 t/y.  But if a car emits 5 t/y, then a family of four with two cars is emitting HALF of their emissions just from the cars.  And the other half comes from heating the house, keeping the lights on and transporting food and goods that they use.

Now, if we assume that households and industry will fairly share the burden (not a bet I’d take, as government will screw the non-voting businesses first), then a family of four will have to reduce their emissions from 44 t/y to just 6 t/y.  Well, that means that they will only get to have one car (maybe), an it will need to be electric (hybrids won’t cut it), and the electricity will have to come from wind, solar or nuclear.  Even hydroelectric will be dodgy at this point because of the methane emissions from rotting vegetation in the reservoirs.

Now, let us turn to heating the house (important in a country like Canada).   Heating a house emits about 4-10 tonnes per year of CO2, with natural gas at the low end and electricity (from fossil fuels) and fuel oil at the top.  One option touted by some is to burn wood, because they are taking credit for the regrowing trees…. but the world doesn’t grow trees fast enough to justify this.  But even with natural gas, a family of four can’t even afford 4 t/y to heat the house.  And forget A/C in the summer.  Therefore, the only alternative is to switch to electric heat powered by wind, solar or nuclear.  And since wind and solar are intermittent (solar being particularly problematic in northern latitudes in winter), nuclear is the option.

This leaves us with a few tonnes/y for transportation of food and goods.  But there will be no more fresh fruit in Canada in winter.  The CO2 emissions from transportation from warmer climes will put us over.  So back to the era of canned foods through the winter.  And we will probably have to cut back on meats and fish – too energy intensive…  So vegetarianism for us all.

And industry will be shutting down.  The oil sands won’t need to be curtailed by government directly.   The cost of gasoline and diesel will have to be VERY high to prevent people from using it (or ban it outright).  The oil sands will die simply because no one will be allowed to use fossil fuels.   As will mining.  And major construction projects.

Are you ready Canada?  I will be nearly 80 when this will purportedly come to pass, but I am not looking forward to the next 40 years.  John Ivison is right…  Canadians want all the climate progress they can get for free.

Thanks to Kate over at SDA for this:  Understanding Climategate’s Hidden Decline.  As she said – a MUST READ.

Key to the problem is:

The truth is that the proxy data was scrapped because unlike those measured, reconstructed temperatures showed a marked decline after 1980.  And, as the chart plotted temperature anomalies against what the plotters selected as the “normal” period and temperatures of 1961 to 1990, the reconstruction would have been quite unremarkable otherwise.  So at the 1980 mark, the actual post-1980 measurements were actually attached to the truncated proxy series to create the illusion they were one.

So not only did conspirators cherry-pick the one series of the four that approximated measured temperatures the longest, they also terminated that series at the point that it too, began to trend down.  They then joined it to the actual 1980-1999 temperatures to “hide the decline” in the final product, as that decline created an inexplicable divergence between the reconstructed and measured temperatures.   The existence of which challenges the entire series dating back to 1000 AD.

This invalidates the idea that the warming of the last 150 years (up to 1998) was unprecedented.  Which means that trying to blame human activity for it is ridiculous.  And it is even more ridiculous to think we can change it.

So, the Roman and Medieval Warm Periods were warmer than the current day in the North Atlantic.  All while CO2 concentrations in the atmosphere were lower.  Correlation is that higher temperatures are not necessarily caused by high CO2.  So does high CO2 today matter?
Also – see Lord Monckton’s latest paper on ClimateGate!

Ronald Bailey has a very good editorial on the subject.  A couple of key portions on the climate change science:

In an email to University of Alabama climatologist John Christy I asked, “Is there a possibility that the teams that compile temperature data could all be making the same set of errors which would result in them finding similar (and perhaps) spurious trends?” Christy replied that he believed this was possible and cited some recent work he had done on temperature trends in East Africa as evidence. In that article he found that using both the maximum and minimum temperature rather than the mean temperature (TMean) used by the three official data sets gives a better indication of actual temperature trends in the region.

Christy found that the maximum temperature (TMax) trend has been essentially zero since 1900 while the minimum temperature (TMin) trend has been increasing. In his email to me, Christy explained, “As it turns out, TMin warms significantly due to factors other than the greenhouse effect, so TMean, because it is affected by TMin, is a poor proxy for understanding the greenhouse effect of ‘global warming’.” Or as his journal article puts it, “There appears to be little change in East Africa’s TMax, and if TMax is a suitable proxy for climate changes affecting the deep atmosphere, there has been little impact in the past half-century.” So if Christy’s analysis is correct, much of the global warming in East Africa reported by the three official data sets is exaggerated. Christy has found similar effects on temperature trend reporting for other regions of the world.

And on the subject of scientific knowledge and credibility:

One thing more transparency won’t fix: the complications and uncertainty inherent in the policy debate about global warming. “In the end, I would hypothesize that the result of the freeing of data and code will necessarily lead to a more robust understanding of scientific uncertainties, [and] that may have the perverse effect of making the future less clear,” emails Pielke Jr.

I think this is the best outcome.  If science cannot make it clear beyond a reasonable doubt, we should not act – because we cannot know the outcome.  And don’t get me on about the “precautionary principle”, because that is like throwing darts in the dark.

This is a very good graph

To my readers, There are three items of interest on this subject in this post.

1. There are some new postings from Steve McIntyre (and here) that show us the hidden decline in Briffa’s tree ring data – basically it appears that Briffa only published the data up to 1960, and that ignoring the tree ring proxies past 1960 because they don’t match the instrument data!   In McIntyre’s re-plot there is a distinct decline in the tree ring proxy data.  Now to me this doesn’t show us that the world was actually cooling – the instrument data appears to indicate warming.  But what is does show is that the tree ring proxies are not good proxies to global temperature.  So we should be loathe to trust them as a historical record of temperature.

This of course makes sense to me.   How can the density of tree rings be correlated to temperature without knowing the levels of precipitation, sunlight intensity.  Also, tree ring data give annual average tree growth so information about whether a year started dry, wet, cold or warm and CHANGED during the year cannot be easily detected in the tree rings.  I’m no dendro-chronologist, but I see unanswered questions.

2. Phil Green published a good article in the National Post today, mostly comparing the daily average minimum temperatures for Europe and North America to the monthly average anomaly temperatures that CRU published for the IPCC.    He makes some very good points about data sharing – if Courtillot has data that doesn’t match the CRU data, why won’t CRU share the data so he can compare more closely?

Green also makes some very good points about the averaging/smoothing of data that CRU has done.  If you have a bunch of data, averaging it out will remove a lot of the information.  If Courtillot has daily data from 44 European stations and 153 US stations for most of the 20th century, then CRU must have at least that much data.  But why then do they average the data out on monthly and annual bases?  I recognize the need to grid the planet for the computer models, and that there has to be some relationship between the measured stations and the grid locations (which is an interesting mathematical challenge) – but the gross averaging of data seems questionable to me.

Further, the use of anomalies instead of actual temperatures is misleading because the selection of the normal period changes the appearance and interpretation of the results.

3. Along the lines of these posts, Chemical Engineering Progress, published by AIChE, has a great article (membership required) this month about numerical errors and gives a great example about how different plotting methods can provide very different assessments of how well two datasets are correlated.  This has a lot to do with data fitting and explains why using the wrong method can obscure the important information.    Here are two graphs from that article:

The captions of the two figures are self explanatory.  In this case, the first method appears to show good correlation, whereas in the second it is clear that there is a distinct curvature, indicating the correlation is not very good.   This is exactly the same problem as comparing Courtillot’s daily data with the heavily smoothed CRU data.  The clearly significant averaging and smoothing of the data (and the use of “anomalies”) has obscured the useful information.