A rash of stunning turnarounds have vindicated years of effort by climate sceptics. The day after ClimateGate broke I made three predictions:

. Disband the entire Federal Department of Climate Change along with all the individual State Departments of Climate Change.

. Vote down the Emissions Trading Scheme Legislation.

. Cancel Copenhagen.

Australia’s Department of Climate Change has been ‘watered down’ to become the Department of Climate Change, Energy Efficiency and Water. The ETS was voted down, and Copenhagen was such a net negative they are probably sorry they didn’t cancel it.

In another successful prediction, the end of drought in Australia came from a massive upswing in rainfall in 2010. This was done using the EMD algorithm and the assumption of stationarity of rainfall: i.e. long-term oscillations with zero trend, in contrast to a non-stationary drying trend as assumed by CSIRO climate models.

In another stunning vindication of Steve McIntyre, the Met Dept are proposing to take over global temperature data from the CRU. Steve has of course been railing for years about the sloppy, good old boys science in Jones’ department, and clearly the professionals agree with his assessment. Gladly the proposal includes a transparent verification process.

In efforts that are long overdue, Lucia reports that various people are attempting to verify the absence of bias in the CRU surface dataset in various ways. Whatever the result, this can only be a good thing, and I hope it becomes a habit.

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Please discuss the new paper by Michael Beenstock and Yaniv Reingewertz here.

Way back in early 2006 I posted on an exchange with R. Kaufmann, whose cointegration modelling is referenced in the paper, entitled Peer censorship and fraud. He was complaining at RealClimate about the supression of these lines of inquiry by the general circulation modellers. The post gives a number of examples that were topical at the time. ClimateGate bears it out.

Steve McIntyre wrote a long post on the affair here.

[R]ealclimate’s commitment to their stated policy that “serious rebuttals and discussions are welcomed” in the context that they devoted a post to criticize Ross and me and then refused to post serious responses. In this case, they couldn’t get away with censoring Kaufmann, but it’s pretty clear that they didn’t want to have a “serious” discussion online.

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An issue in question here is whether the recent snowfall at Law Dome is unusually high relative to the 750 year long record (and therefore, so the argument goes, probably due to AGW).

Below is the snowfall at Law Dome from the ice core. Above is the actual snowfall, and below is the accumulation of the series minus the mean (using the R function cumsum) indicating where snowfall is above or below average.

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The latest submission to arXiv:physics.ao-ph is entitled Interglacials, Milankovitch Cycles, and Carbon Dioxide by Gerald E. Marsh. Here is a review of the evidence regarding the timing of Termination II, the penultimate interglacial transition 140k years ago, and factors that may have caused it: CO2, Milankovitch induced insolation changes, or changes in solar magnetic flux, altering the Earth’s albedo through cosmic ray flux.

To appreciate the importance of this period, and a clear logical analysis of it, consider the recent lecture tour of Australia by Lord Monckton and Prof. Plimer. Lord Monckton argues strongly that climate sensitivity to CO2 is very low, too low to be of concern, and an increasing number of peer-reviewed papers using independent observational methods — Douglass, Lindzen, Spencer, Schwartz, Pinker, Shaviv — back him up. Prof. Plimer argues that the history of climate has been enormously variable, and not related to CO2 levels in the atmosphere.

This contrast of low sensitivity but high natural variation has prompted criticism on the irony of a tour by sceptics with contradictory viewpoints. As I understand their view, they maintain “the sensitivity of the climate to CO2 cannot be as low as suggested by these results because low sensitivity cannot explain the large glacial-interglacial transitions”. A solar cause for the penultimate transition has been scoffed at because the timing is wrong. It must have been a volcano or something that kicked off the chain of CO2 feedback that resulted in the warm interglacial.

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Innovation is not dead as Dyson eliminates the fan (maybe there is one inside though), showing the power of careful attention to shape.

Rational policy analysis is not an oxymoron, as Peter Gallagher deconstructs the emissions trading scheme (ETS).

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My comments on the topical ‘Yamal’ issue:

My AIG article demonstrating reconstruction of a hockey stick with red noise, neatly illustrated the possibility of circular reasoning in screening trees by their response to temperature. Around 20% of random series (or 40% if you count the inverted ones) correlate significantly with the temperature instrument record of the last 150 years, and when averaged back beyond the present create the straight handle of the stick.

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Many of my numerate readers will have read the account by Rick Trebino of Georgia Tech of trials and tribulations of responding to an error in the public record of the peer-reviewed literature, and have ideas of their own on what they would like to see.

Record ideas for what you would like to see below. (I am on vacation on the Great Barrier Reef right now, so excuse the brevity, typing this from the resort.) My wish list is below.

1. Code and data allow replication
2. Reviewers can act as coaches, where appropriate
3. Journals dedicated entirely to review of others’ studies

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Here is the abstract for our comment submitted to Geophysical Research Letters today. Bob Tisdale is acknowledged as the source of the idea in the first paragraph. Lets see how it goes. If you would like a copy, contact me via the form above.

Update: Now available from arXiv

Comment on “Influence of the Southern Oscillation on tropospheric temperature” by J. D. McLean, C. R. de Freitas, and R. M. Carter

David R.B. Stockwell and Anthony Cox

Abstract

We demonstrate an alternative correlation between the El Nino Southern Oscillation (ENSO) and global temperature variation to that shown by McLean et al. [2009]. We show 52% of the variation in RATPAC-A tropospheric temperature (and 59% of HadCRUT3) is explained by a novel cumulative Southern Oscillation Index (cSOI) term in a simple linear regression model and 65% of RATPAC-A variation (67% of HadCRUT3) when volcanic and solar effect terms are included. We review evidence from physical and statistical research in support of the hypothesis that accumulation of the effects of ENSO can produce natural multi-decadal warming trends. Although it is not possible to reliably determine the relative contribution of anthropogenic forcing and SOI accumulation from multiple regression models due to collinearity, these results suggest a residual accumulation of around 5 ± 1% and up to 9 ± 2% of ENSO-events has contributed to the global temperature trend.

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Below are my replications of Figure 4 and Figure 5 of the controversial paper “Influence of the Southern Oscillation on tropospheric temperature” by J. D. McLean, C. R. de Freitas, and R. M. Carter.

Above is the comparison of global atmospheric temperature (RATPAC-A) with the SOI, smoothed with a flat 12 month filter.

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The revision of the Copenhagen Synthesis Report was advertised at the ANU Climate Change Institute, directed by Prof. Will Steffen. But they just can’t seem to get it right. The ANU web site refers to Stefan Rahmstorf as Stefan Rahmonstorf.

Ian Castles on the July 5th, 2009 compiled the list of amendments of errors. Below is an update of the current situation.

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Renewable energy is a nice idea, but Peter Lang crunches the numbers and finds solar and wind power are crushingly expensive, do little for greenhouse gas reduction, and are ecologically dangerous. Cap and trade is actually a giant scheme to tax and redistribute, for the benefit of political insiders.

A letter submitted by Peter Lang argues that the numbers prove nuclear power is the only way.

Solar realities: Solar power is uneconomic. The capital cost of solar power would be 25 times more than nuclear power to provide for demand. The minimum power output, not peak or average, is the main factor governing solar power’s economic viability. The least cost solar option would emit 20 times more CO2 (over the full life cycle) and use at least 400 times more land area compared with nuclear Government mandates and subsidies hide the true cost of renewable energy.

Wind realities: Wind power does not avoid significant amounts of greenhouse gas emissions. Wind power is very high cost way to avoid greenhouse gas emissions. Wind power, even with high capacity penetration, can not make a significant contribution to reducing greenhouse gas emissions.

Nuclear power is the least-cost, low-emission electricity generation technology that can provide the large amounts of electricity needed to power modern economies.

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Published in Science, this Rahmstorf 2007 article provides a high-end estimate of sea level rise of over a meter by the end of the century (rate of 10mm/yr). Linear extrapolation puts the rate of increase at only 1.4mm and 1.7mm per year depending on start date (1860 or 1950).

The paper was followed by two critical comments, both bashing the statistics, and these are attached to the link above. Rahmstorf replied to those comments. The issues raised are familiar to readers of this, CA, Lucia, and other statistical blogs: significance, autocorrelation, etc. and worth a read.

Worthwhile as the comments are, they do not look into the problem of the end-treatment used by Rahmstorf, and I look at that here.

All of the papers projecting these high end rates, and they all depend on the assumption of recent ‘acceleration’ in sea levels. That is, seem to depend on the rate of increase getting faster and faster.

Rahmstorf 2007 paper uses the smoothing method most recently savaged at CA here, where it was shown despite all the high-falutin’ language to be equivalent to a simple triangular filter of length 2M, padded with M points of slope equal to the last M points. My main concern is that at this crucial end-section, the data has been duplicated by the padding, effectively increasing the number of data points of very high slope.

The figure below shows a replication of the Rahmstorf smoothing with and without padding (moved down for clarity) (code below). Two sea level data sets are shown, one by Church “A 20th century acceleration in global sea level rise” (used in Rahmstorf, data available from CSIRO here) another by Jevrejeva “Recent global sea level acceleration started over 200 years ago?” (data here)

It should be noted this data ends in 2001-2, a truncation bound to maximize recent temperature increases.

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Download: Structural break models of climatic regime-shifts: claims and forecasts

Anthony asked if it would be difficult to statistically justify the breaks in temperature between 1976 and 1979 proposed by Quirk (2009) for Australian temperature. He has an interest in oceanographic regime-shifts and climate change. Sure, I said, a simple Chow test.

We ended up rebutting the Easterling & Wehner (2009) claim that describing temperatures since 1998 as declining is ‘cherry picking’, finding a major regime shift occurred in 1997, statistically justifying the use of 1997 as a starting point for temperature trends.

A regime-shift based temperature forecast follows logically from identification of significant breaks. Our paper, “Structural break models of climatic regime-shifts: claims and forecasts“, has been submitted to the International Journal of Forecasting, and is downloadable from arXiv.

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Appearing in Energy and Environment (ee-20-4_7-stockwell2) is a note by myself on a paper by IPCC lead authors Rahmstorf, S., Cazenave A., Church J.A., Hansen J.E., Keeling R.F., Parker D.E., and R.C.J. Somerville, Recent climate observations compared to projections published in Science in 2007.

As shown by 102 citations in Google Scholar already, Rahmstorf et al 2007 has been one of the main references for alarmist calls to action because the “climate system is responding more quickly than the climate models indicate”. Taking the first one off Google:

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are …

Adapting agriculture to climate change – pnas.org, SM Howden, JF Soussana, FN Tubiello, N Chhetri, M … Proceedings of the National Academy of Sciences, 2007 – National Acad Sciences.

Respected on-line authors like Peter Gallagher, Mark Lawson and Lucia were concerned with the paper. Lucia attacked the ’slide and eyeball’ approach. I engaged with Rahmstorf at RealClimate and wrote a number of articles on the uncertainty, until he told me in effect to ’sod off and publish’. But rather than try to diagnose a sloppy methodology and be ignored, time and evidence has done the job instead. Here is my abstract.

Abstract: The non-linear trend in Rahmstorf et al. [2007] is updated with recent global temperature data. The evidence does not support the basis for their claim that the sensitivity of the climate system has been underestimated.

Its gratifying to read that the authors of the Copenhagen Synthesis Report do not seem to agree with Rahmstorf et al 2007 either, in reference to analysis in a figure that ostensibly used the same method as Rahmstorf et al 2007.

Figure 3 … shows the long-term trend of increasing temperature is clear and the trajectory of atmospheric temperature at the Earth’s surface is proceeding within the range of IPCC projections.

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Given the way the components of the surface temperature record extracted from the SSA (singular spectrum analysis) line up with various potential causes of climate change in the previous post here, the temptation is to latch onto series 2, and say, aha, there is the forcing due to increase in CO2. It’s the right shape, exponential. Its the right size, about 0.6C.

But looking into fractal data is like seeing pictures in clouds. Be suspicious of magic methods that pull explanations out of the air. Below I have plotted SSA decompositions of the the monthly global temperature anomaly from the HadCRU dataset from 1976 to the present, the period of most recent rise, and attributed largely to GHGs. Kind of zooming in.

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A feel-good story of nature’s resiliency, “Doom and Boom on a Resilient Reef: Climate Change, Algal Overgrowth and Coral Recovery” has been making press with headlines focusing on the state of mind of the authors:

Marine scientists say they are astonished at the spectacular recovery of certain coral reefs in Australia’s Great Barrier Reef Marine Park from a devastating coral bleaching event in 2006.

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This post was submitted by David Stockwell.

Still on my way home, after the lecture at Newcastle University by Miklós Zágoni and myself, this will be short. The lecture was well attended, with around 50 people — surprising considering the campus is on a break and parking at a premium. The lectures were well received with a very engaged and relevant question time. There were some suggestions of disruption by anti-skeptics, but they did not eventuate.

Transcript: errors-of-agw-science

Powerpoint: newcastle-presentation

Press Release: herald-article-14-4-09

Miklós Zágoni talk: long version

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Some time ago I had a brief discussion with Leif Svalgaard on ClimateAudit blog inspired by an exchange between Leif and David Archibald when the latter complained that Leif’s TSI reconstruction was “too flat”.

The sunspots exhibited cyclic variability in terms of the frequency of the cycles and that most thermostats work by pulse width modulation and some digital music with pulse frequency modulation. Both these work in a similar manner the thermal inertia of whatever the thermostat is controlling smooths the temperature variability and the pulse frequency modulation’s demodulator is a simple low pass filter often just a series resistor and shunt capacitor. In both these cases only the duty cycle or the frequency varies but not the amplitude. Below is a description of how this behaviour can be simulated with an electrical circuit emulator called ‘qucs’.

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Here is a graph that suggests something intriguing about climate dynamics — global temperature from 1979-2009 from UAH satellite records for land, southern hemisphere ocean, and globe, each fit with a 3rd order polynomial. Also plotted is the difference between SH Ocean and Global temperatures, and the difference between SH Ocean and Land temperatures. Notice that the 3rd order polynomial of the differences is almost dead straight! The Ocean-Land difference tends to drop a bit in the last 5 years.

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Nir is is not a keynote speaker at the Heartland Conference, though billed as one on the poster. Here is the program. He is listed as a speaker around 4pm Monday on the program. This is a placeholder for news of his address when it comes in.

TC Hamish has intensified to a Category 5 and will make landfall somewhere in the Hervey Bay region if it continues on its present course. On 24 January, 1974, Cyclone Wanda crossed the coast near Hervey Bay, caused significant flooding in Brisbane resulting in the inundation of over 6000 houses.

Radar loop
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A concerned reader sent me this recent paper Water-vapor climate feedback inferred from climate fluctuations, 2003-2008, writing:

The following (ala Hansen) IMO should never have been accepted in a "peer reviewed" journal. "The existence of a strong and positive water-vapor feedback means that projected business-as-usual greenhouse gas emissions over the next century are virtually guaranteed to produce warming of several degrees Celsius. The only way that will not happen is if a strong, negative, and currently unknown feedback is discovered somewhere in our climate system."

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Abstract

A review by independent Accredited Statisticians, Brewer and Other [KB09], suggested that some claims in the report “Tests of Regional Climate Model Validity in the Drought Exceptional Circumstances Report” [DS08] were premature. Additional tests suggested by KB09 support the claim made in the original report of “no credible basis for the claims of increasing frequency of Exceptional Circumstances declarations”. The contributions of KB09 and DS08 to the evaluation of skill of climate model simulations with, arguably, weakly validated idiosyncratic statistics are discussed. These include recommendations for more rigor in evaluating the performance of climate effects simulations, such as those used in standardized forecasting practices [AG09]. Read the rest of this entry…

1. K.R.W. Brewer is an Accredited Statistician of the Statistical Society of Australia Inc. (SSAI) and a long term Visiting Fellow at the School of Finance and Applied Statistics within the College of Business and Economics at the Australian National University.
2. A.N. Other is a pseudonym for another Accredited Statistician of the SSAI who prefers to remain anonymous. Full responsibility for the content is taken by K.R.W. Brewer.

Abstract

The Drought Exceptional Circumstances Report (DECR) was authored by a team drawn from the CSIRO and Australia’s Bureau of Meteorology, and was publicly released in July 2008. Almost immediately it became a source of controversy. This evaluation, both of the Report itself and of the critique of it written by Dr David Stockwell, finds good mixed with less than good in both. The DECR itself is criticized for its poor delineation of Regions within Australia, for the choices made of statistics to be constructed, for the manners of their construction, and for not getting the best out of the relevant available data. Dr Stockwell is criticized for his inappropriate choices of methodology and of time periods for analysis, and also for misunderstanding some parts of what the DECR’s authors had chosen to do. Nevertheless, both the Report itself and Dr Stockwell’s critique of it are welcome stimuli to further investigate a serious issue within the climate change debate.

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Below are Peter Gallagher’s thoughts on the reviews of the submission to AMM. Contrast this with ac’s impressions that “To my reading the reviewer’s criticisms are reasonable and pertinent.” It goes to show, that reasonable and unrelated people can see things in different ways. Where is the resolvability of fact in the review process? Consensus?

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Here are the second reviewers comments. This is quite short, so I have only a few remarks to make, mainly that I tried as much as possible to mimic the analysis used in the DECR, so any criticisms of the methodology are also criticisms of the report. Perhaps the reviewer would like to inform the authors of the DECR about their thoughts on that?

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The Financial Times recently reported on the Australian bushfires, linking them to increases in greenhouse gases. We take another look at the data in the DECR and find Australia is getting wetter not drier:

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Here are my comments on the reviewers 1 comments on the manuscript submitted to AMM about the DECR. The summary of the manuscript stated:

The 2008 Drought Exceptional Circumstances Report (DECR) makes a number of bold claims in its assessment of likely changes in the frequency and severity of severe rainfall deficiencies over the next 20-30 years. This review presents an analysis which brings into question whether these claims can be sustained by the data. Taking into account the poor performance of climate models, as evidenced by simulations of area of exceptionally low rainfall trending in the opposite direction to observations, a more valid interpretation of the data would be for drought frequency and severity in Australia to remain largely unchanged in the future, with no expectation of a change in the climatological basis for EC declarations.

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A number of familiar tests, often used to evaluate the performance of models: R2 correlation, Nash-Sutcliffe efficiency and similarity of trends and return period, were reported here, noting not much evidence of skill in the DECR models compared with observations at any of these. I also said what a better treatment might entail but left that for another time:

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Prediction is dangerous to your reputation.

If you don’t make a clear prediction (a climate cycle, a solar cycle, a financial trend…) then you are just doing your best. What comes does not damage your reputation.

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