Saturday, November 28, 2009

Central England Temperature series

The very long thermometer-reading series from central England (from 1659 on) is of huge interest because it does NOT rely on dubious proxies -- and it shows the 20th century as being unexceptional. I have therefore made a number of allusions to it on this blog.

The Warmists have noted it too and one of them -- Tamino -- has gone to work and made a hockey stick out of it -- using the expected dubious statistical techniques. Tamino is one of the guys mentioned in the hacked CRU emails.

That his results are incredible can I think most convincingly be seen from his plot of the raw data (below)

It is clearly a random walk and any trend up or down is a statistical creation rather than anything real. One of my readers taken an interest in tracking down just what Tamino did to get his magical result. He offers the following graphic:

LARGER VERSION of the graphic HERE

He comments: Tamino's work takes a bit of following. I initially thought his moving average had been moved to match a "mere smoothing function". I was wrong. He simply used a centered average. The "mere smoothing function" is one of the most important breakthroughs of all time. The Savitzky-Golay filter of 1964 can remove noise without softening peaks. I next thought he had smoothed the moving average instead of the data. A second mistake. With more serious software I easily reproduced his graph from original data. He has taken advantage of a severe end-effect which requires lots of homework to comprehend. He also used a lowest order filter setting so peaks *are* in fact quashed in the middle as well! Higher order settings let peaks breathe but still have huge end effects. End effect means his upswing in today's news may be retroactively pulled back down if cooler years are added in the future. It will take 15 years for that part of the graph to become etched in stone. Over 200 commenters failed to detect such subterfuge

As an old FORTRAN-using statistical analysis programmer myself, I am well aware of how you can lie with statistics. That is why it is important to do courses in statistics -- so you can spot it when you are being "had". And much of my academic writing was devoted to pointing out how statistical nullities were being paraded as if they told us something. So it is no surprise to see the statistical jiggery-pokery that has been going on in climate science. Mountains are regularly made out of pimples and if there are not even pimples to be had, one will be created.

Patterns of Change

Below is an attempt by "Bristlecone" Mann to support the Warmist contention that the Medieval Warm Period and Little Ice Age were "local" events. Given his chronic reliance on discredited proxies, however, this should detain no-one. Amusing that he starts his data survey immediately AFTER the Roman Warm Period. Did that period not fit the pattern he claims to find?

The global climate record of the past 1500 years shows two long intervals of anomalous temperatures before the obvious anthropogenic warming of the 20th century: the warm Medieval Climate Anomaly between roughly 950 and 1250 A.D. and the Little Ice Age between around 1400 and 1700 A.D. It has become increasingly clear in recent years, however, that climate changes inevitably involve a complex pattern of regional changes, whose inhomogeneities contain valuable insights into the mechanisms that cause them. Mann et al. (p. 1256) analyzed proxy records of climate since 500 A.D. and compared their global patterns with model reconstructions. The results identify the large-scale processes—like El Niño and the North Atlantic Oscillation—that can account for the observations and suggest that dynamic responses to variable radiative forcing were their primary causes.


The journal abstract:

Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly

By Michael E. Mann et al.

Global temperatures are known to have varied over the past 1500 years, but the spatial patterns have remained poorly defined. We used a global climate proxy network to reconstruct surface temperature patterns over this interval. The Medieval period is found to display warmth that matches or exceeds that of the past decade in some regions, but which falls well below recent levels globally. This period is marked by a tendency for La Niña–like conditions in the tropical Pacific. The coldest temperatures of the Little Ice Age are observed over the interval 1400 to 1700 C.E., with greatest cooling over the extratropical Northern Hemisphere continents. The patterns of temperature change imply dynamical responses of climate to natural radiative forcing changes involving El Niño and the North Atlantic Oscillation–Arctic Oscillation.

Science 27 November 2009: Vol. 326. no. 5957, pp. 1256 - 1260

The New Zealand Warmists are crooks too

From Anthony Watts through a report from the Climate Science Coalition of New Zealand, we find some more climate alarmist chicanery
The New Zealand Government’s chief climate advisory unit NIWA is under fire for allegedly massaging raw climate data to show a global warming trend that wasn’t there.

The scandal breaks as fears grow worldwide that corruption of climate science is not confined to just Britain’s CRU climate research centre.

In New Zealand’s case, the figures published on NIWA’s [the National Institute of Water and Atmospheric research] website suggest a strong warming trend in New Zealand over the past century:

The figure they released

But, taking a look at the real, raw data, we get

As Anthony points out
Gone is the relentless rising temperature trend, and instead there appears to have been a much smaller growth in warming, consistent with the warming up of the planet after the end of the Little Ice Age in 1850.

The house of cards is falling, climate alarmists. It will be interesting to see what happens when NASA and the Goddard Center are forced to release their raw data. Look, we "skeptics" and "deniers" do not deny that there has been warming since the end of the Little Ice Age. We deny that Mankind is mostly, or solely, responsible for it, and, if you were really interested in real science, rather then agenda based science, you would have our same opinion. You've created a tenuous link between CO2 release and rising temps, and, when that didn't pan out fully, what with the cooler years, you started calling it climate change, to somehow hide how the release of greenhouse gasses, things that hold in, to put it imprecisely, heat, can cause a decline or stagnant temps. You've faked links to all around, such as with Mt. Kilimanjaro. Perhaps it's time for you to be honest, and get interested in real science, eh?

Meanwhile, it appears that several of the gents involved in the ClimateGate emails might have broken laws.


CRU data-fudging again

A French scientist’s fine-grain temperature data show results quite different from CRU

By Phil Green, a statistician

The global average temperature is calculated by climatologists at the Climatic Research Unit (CRU) at the University of East Anglia. The temperature graph the CRU produces from its monthly averages is the main indicator of global temperature change used by the International Panel on Climate Change, and it shows a steady increase in global lower atmospheric temperature over the 20th century. Similar graphs for regions of the world, such as Europe and North America, show the same trend. This is consistent with increasing industrialization, growing use of fossil fuels, and rising atmospheric concentrations of carbon dioxide.

It took the CRU workers decades to assemble millions of temperature measurements from around the globe. The earliest measurements they gathered came from the mid 19th century, when mariners threw buckets over the side of their square riggers and hauled them up to measure water temperature. Meteorologists increasingly started recording regular temperature on land around the same time. Today they collect measurements electronically from national meteorological services and ocean-going ships.

Millions of measurements, global coverage, consistently rising temperatures, case closed: The Earth is warming. Except for one problem. CRU’s average temperature data doesn’t jibe with that of Vincent Courtillot, a French geo-magneticist, director of the Institut de Physique du Globe in Paris, and a former scientific advisor to the French Cabinet. Last year he and three colleagues plotted an average temperature chart for Europe that shows a surprisingly different trend. Aside from a very cold spell in 1940, temperatures were flat for most of the 20th century, showing no warming while fossil fuel use grew. Then in 1987 they shot up by about 1 C and have not shown any warming since. This pattern cannot be explained by rising carbon dioxide concentrations, unless some critical threshold was reached in 1987; nor can it be explained by climate models.

Courtillot and Jean-Louis Le Mouël, a French geo-magneticist, and three Russian colleagues first came into climate research as outsiders four years ago. The Earth’s magnetic field responds to changes in solar output, so geomagnetic measurements are good indicators of solar activity. They thought it would be interesting to compare solar activity with climatic temperature measurements.

Their first step was to assemble a database of temperature measurements and plot temperature charts. To do that, they needed raw temperature measurements that had not been averaged or adjusted in any way. Courtillot asked Phil Jones, the scientist who runs the CRU database, for his raw data, telling him (according to one of the ‘Climategate’ emails that surfaced following the recent hacking of CRU’s computer systems) “there may be some quite important information in the daily values which is likely lost on monthly averaging.” Jones refused Courtillot’s request for data, saying that CRU had “signed agreements with national meteorological services saying they would not pass the raw data onto third parties.” (Interestingly, in another of the CRU emails, Jones said something very different: “I took a decision not to release our [meteorological] station data, mainly because of McIntyre,” referring to Canadian Steve McIntyre, who helped uncover the flaws in the hockey stick graph.)

Courtillot and his colleagues were forced to turn to other sources of temperature measurements. They found 44 European weather stations that had long series of daily minimum temperatures that covered most of the 20th century, with few or no gaps. They removed annual seasonal trends for each series with a three-year running average of daily minimum temperatures. Finally they averaged all the European series for each day of the 20th century.

CRU, in contrast, calculates average temperatures by month — rather than daily — over individual grid boxes on the Earth’s surface that are 5 degrees of latitude by 5 degrees of longitude, from 1850 to the present. First it makes hundreds of adjustments to the raw data, which sometimes require educated guesses, to try to correct for such things as changes in the type and location of thermometers. It also combines air temperatures and water temperatures from the sea. It uses fancy statistical techniques to fill in gaps of missing data in grid boxes with few or no temperature measurements. CRU then adjusts the averages to show changes in temperature since 1961-1990.

CRU calls the 1961-1990 the “normal” period and the average temperature of this period it calls the “normal.” It subtracts the normal from each monthly average and calls these the monthly “anomalies.” A positive anomaly means a temperature was warmer than CRU’s normal period. Finally CRU averages the grid box anomalies over regions such as Europe or over the entire surface of the globe for each month to get the European or global monthly average anomaly. You see the result in the IPCC graph nearby, which shows rising temperatures.

The decision to consider the 1961-1990 period as ‘normal’ was CRUs. Had CRU chosen a different period under consideration, the IPCC graph would have shown less warming, as discussed in one of the Climategate emails, from David Parker of the UK meteorological office. In it, Parker advised Jones not to select a different period, saying “anomalies will seem less positive than before if we change to newer normals, so the impression of global warming will be muted.” That’s hardly a compelling scientific justification!

It is well known to statisticians that in any but the simplest data sets, there are many possible ways to calculate an indicator using averages. Paradoxically, and counter-intuitively, they often contradict each other. As a simple example of how the same data can be teased to produce divergent results, consider the batting averages of David Justice and Derek Jeter. For each of three years in 1995-97, Justice had a higher batting average than Jeter did. Yet, overall, Jeter had the highest batting average.

In addition to calculating temperature averages for Europe, Courtillot and his colleagues calculated temperature averages for the United States. Once again, their method yielded more refined averages that were not a close match with the coarser CRU temperature averages. The warmest period was in 1930, slightly above the temperatures at the end of the 20th century. This was followed by 30 years of cooling, then another 30 years of warming.

Courtillot’s calculations show the importance of making climate data freely available to all scientists to calculate global average temperature according to the best science. Phil Jones, in response to the email hacking, said that CRU’s global temperature series show the same results as “completely independent groups of scientists.” Yet CRU would not share its data with independent scientists such as Courtillot and McIntyre, and Courtillot’s series are clearly different.

At the upcoming Copenhagen conference, governments are expected to fail to agree to an ambitious plan to cut greenhouse gas emissions. Here’s a more modest, if mundane goal for them: They should agree to share the data from their national meteorological services so that independent scientists can calculate global climatic temperature and identify the roles of carbon dioxide and the sun in changing it.

SOURCE (See the original for graphics)

UN scientists turn on each other

UN Scientist Declares Climategate colleagues Mann, Jones and Rahmstorf 'should be barred from the IPCC process' -- They are 'not credible any more'

A UN scientist is declaring that his three fellow UN climate panel colleagues "should be barred from the IPCC process." In a November 26, 2009 message on his website, UN IPCC contributing author Dr. Eduardo Zorita writes: "CRU files: Why I think that Michael Mann, Phil Jones and Stefan Rahmstorf should be barred from the IPCC process."

Zorita writes that the short answer to that question is: "Because the scientific assessments in which they may take part are not credible anymore."

Zorita indicates that he is aware that he is putting his career in jeopardy by going after the upper echelon of UN IPCC scientists. "By writing these lines I will just probably achieve that a few of my future studies will, again, not see the light of publication," Zorita candidly admits, a reference to the ClimateGate emails discussing how to suppress data and scientific studies that do not agree with the UN IPCC views.

Zorita was a UN IPCC Contributing Author of the Fourth Assessment Report in 2007. Since 2003, Zorita has headed the Department of Paleoclimate and has been a senior scientist at the Institute for Coastal Research of the GKSS Research Centre in Germany. Zorita has published more than 70 peer-reviewed scientific studies.

Zorita's stunning candor continued, noting that scientists who disagreed with the UN IPCC climate view were "bullied and subtly blackmailed."

"In this atmosphere, Ph D students are often tempted to tweak their data so as to fit the 'politically correct picture'. Some, or many issues, about climate change are still not well known. Policy makers should be aware of the attempts to hide these uncertainties under a unified picture. I had the 'pleasure' to experience all this in my area of research," Zorita explained.

Zorita's revelations are the latest in a series of continuing fallout to the global warming establishment and to the United Nations Intergovernmental Panel on Climate Change (IPCC), since the email and data scandal dubbed "ClimateGate" broke earlier this month.

Zorita's defection from the global warming establishment comes after the shocking news today that one of the scientists employed at ground zero of what has been termed "ClimateGate" has suggested disbanding the United Nations climate panel, the IPCC. See: Pressure Mounts From Inside: Disband IPCC? Scientist from U. of East Anglia Suggests 'UN IPCC has run its course...politicizes climate science...authoritarian, exclusive form of knowledge production' - Mike Hulme. Excerpt: "ClimateGate reveals science has become 'too partisan, too centralized...more usually associated with social organization within primitive cultures'

SOURCE (See the original for links)

My version of the hockey stick

A rather sarcastic post from a very naughty person

I present to you my own version of the Hockey Stick, made famous by Michael Mann. Can you guess what it represents?

I'll admit that I have cheated here and hidden the data at the end of the series to "hide the decline".

This is a graph of the grants provided to the CRU from 1991 to the present, in UK pounds. You can find the original figures here.

In the interests of openeness, this is what I did:

  1. I took each grant, and calculated how many months it ran for
  2. I then divided the total grant by the number of months, giving an average "income" from that grant per month over the life of the grant
  3. I then summed up the total income per month from all the grants and plotted it, fiddling with the trendline until it produced a hockey stick. I had to use a 6 order polynomial to get a hockey stick - if you use anything less than that, a hockey stick fails to appear
  4. I then pulled a "trick" to eliminate the data after August 2004, as the budget went into a sad decline



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1 comment:

Anonymous said...

Please replace my Tamino graphic with this one that delves deeper into the depths of statistics to than my original one and finally nails it for sure: