Climate correspondents

Doug Keenan has followed up on his observations about the long-term rainfall records for England and Wales with an exchange of emails with Julia Slingo, the chief scientist at the Met Office. (Note that images can all be enlarged by clicking on them).

Dear Julia,

On November 12^th, I sent an e-mail, in which you were Cc’d, about the statistical analysis of (observational) climatic data that has been done by the Met Office. My e-mail stated that some of the analysis is so incompetent that it “is not science”. It then asked if scientists at the Met Office had training in the relevant branch of statistics—i.e. in time series.

You did not reply to that e-mail. In consequence, on November 29^th, Lord Donoughue put the following Question in the House of Lords.

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Parliament does statistical significance

Updated on Jan 2, 2013 by Bishop Hill

From Hansard:

Climate Change

Questions

Asked by Lord Donoughue

To ask Her Majesty's Government, further to the Written Answer by Baroness Verma on 30 October (WA 114-5) stating that global temperatures have risen less than 1 degree celsius since 1880, on what basis they assert that there has been a long-term upward trend in average global temperatures. [HL3048]

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Quantifying Uncertainties in Climate Science

Another date for your diaries - the Royal Met Soc's meeting on uncertainty in climate science.

Climate models produce different projections of future climate change under identical pathways of future greenhouse gases. This meeting will highlight recent studies that have attempted to quantify those uncertainties using different approaches.

Programme: 

Time	No.	Presenting author	Title
16:40		Prof Reto Knutti, (ETH Zürich)	Projection uncertainties: The multi model perspective.
17:10		Dr Paul Williams, University of Reading.	Climate models: The importance of being stochastic.
14:10		Dr Jonty Rougier, University of Bristol	Background and philosophy
14:40		Dr David Sexton, UK Met Office	UK climate projections.
15:10		Dr Tamsin Edwards, University of Bristol	Palaeo-constraints on climate sensitivity.
16:10		Dr Lindsay Lee, University of Leeds	Constraining aerosol models.

Details here.

Markonis and Koutsoyiannis

Demetris Koutsoyiannis emails to point me to his new paper. Markonis and Koutsoyiannis (Surveys of Geophysics) takes a look at climate variability over periods spanning nine orders of magnitude.

We overview studies of the natural variability of past climate, as seen from available proxy information, and its attribution to deterministic or stochastic controls. Furthermore, we characterize this variability over the widest possible range of scales that the available information allows, and we try to connect the deterministic Milankovitch cycles with the Hurst–Kolmogorov (HK) stochastic dynamics. To this aim, we analyse two instrumental series of global temperature and eight proxy series with varying lengths from 2 thousand to 500 million years. In our analysis, we use a simple tool, the climacogram, which is the logarithmic plot of standard deviation versus time scale, and its slope can be used to identify the presence of HK dynamics. By superimposing the climacograms of the different series, we obtain an impressive overview of the variability for time scales spanning almost nine orders of magnitude—from 1 month to 50 million years. An overall climacogram slope of −0.08 supports the presence of HK dynamics with Hurst coefficient of at least 0.92. The orbital forcing (Milankovitch cycles) is also evident in the combined climacogram at time scales between 10 and 100 thousand years. While orbital forcing favours predictability at the scales it acts, the overview of climate variability at all scales suggests a big picture of irregular change and uncertainty of Earth’s climate.

There is an interesting link to a discussion at BH here. That conversation ended when Prof Koutsoyiannis told commenters that he was unable to respond to further questions since the answers were contained in a draft paper that he had going through the peer review process at the time:

As per the “opportunity” to discuss the scientific part, I am afraid it must wait some time. We have produced some results related to your questions, but I do not wish to discuss them before we have them officially published. In this case the peer review may take some months or years, considering the necessary rejections.

This paper is the result. The discussion thread dates back a year, so you can see that the peer review process has been at least that long. The paper was rejected by Geophysical Research Letters and Nature Geoscience (the peer review comments are available here) although as DK notes in the discussion thread, those of his papers rejected by mainstream climate journals tend to be the ones most cited after finding a home in some less "plugged" publication.

(Hurst Kolmogorov dynamics are explained here)

Quote of the week

By Today's Moderator.

I rather liked this comment on WUWT about the spat between David Rose and the Met Office and whether global warming has recently stopped or not .

the duke October 13, 7.14pm.

So, should we all conclude that temperatures are relatively normal, or temporarily normal, or abnormally normal, or apparently normal on a continuing but wholly unpredictable basis? Or are there other possibilities?

http://wattsupwiththat.com/2012/10/13/report-global-warming-stopped-16-years-ago/

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Josh at the Royal

Josh has been at the Royal Society's conference on uncertainty in weather and climate prediction. His visual notes can be seen here.

Update on Oct 6, 2012 by Josh

The second day's notes have now been added and all the notes can be seen here.

www.cartoonsbyjosh.com

Update on Oct 8, 2012 by Josh

Most of the talks are online here on event home page - just click the name of the speaker, at the bottom of the page, to hear the talk.

Diary dates

The Royal Society is organising a conference on uncertainty in weather and climate:

This meeting follows on from the 2010 Anniversary Discussion Meeting on “Handling Uncertainty in Science” but with a focus on weather and climate prediction and downstream applications. How is uncertainty represented in weather and climate prediction? How reliable are representations of uncertainty? How can decision makers in weather and climate sensitive sectors make useful decisions in the light of uncertain input? Are current ensemble weather and climate prediction systems useful for decision making across a variety of application sectors?  How should probability forecasts be presented to the public?

Speakers include Judith Curry and Peter Webster.

Details here.

Climate heroism

More mathematically inclined readers will be interested in a discussion paper by Jonty Rougier, a colleague of Tamsin Edwards' at Bristol. I met Jonty while I was at the Met Office earlier in the year and found him very engaging as well as having a very sharp mind.

The paper is rather mathematical for me. It discusses the difficulties of getting a calibration from systems that are sensitive to initial conditions and where there is an attractor, describing the difficulties as almost intractable. It then goes on to list the further complications that are found in environmental systems and in particular in paleoclimate, and concludes:

When these additional complications are added to the intractability of palaeoclimate reconstruction (climate de finitely has sensitive dependence on initial conditions and an attractor), that enterprise must be seen as heroic in the extreme, and we must expect the uncertainties to be very large indeed. But, somewhat surprisingly, they are not; e.g., as shown in the celebrated hockey stick, which was used so much in the Third Assessment Report of the IPCC (Houghton et al., 2001); Montford (2010) provides a readable if slightly hair-raising account.

Homogenisation is the root of all evil

Well, something like that anyway. Anthony Watts is reporting a presentation by Demetris Koutsoyiannis, which finds that many of the homegenisation adjustments applied to surface temperature data are ill-founded.

Homogenization practices used until today are mainly statistical, not well justified by experiments and are rarely supported by metadata. It can be argued that they often lead to false results: natural features of hydroclimatic time series are regarded [as] errors and are adjusted.

(Lack of) warming since 1995

At the end of their chat about global warming the other day, Andrew Neil asked James Delingpole and Andrew Pendleton of FOE to send him their understandings of global temperature changes since the end of the last century. The responses have now been posted at Neil's blog.

I'm not sure they leave us any the wiser. The problem (well, one of the problems) with discussing statistical significance is that you have to have a model for what the climate does normally. Since nobody knows what model should be used, it's not clear to me that we can say anything very much about the significance of the changes in temperature in the last decades or the last hundred years.

A dangerous practice

Ed Hawkins points us to this paper, reporting a seminar on uncertainty. Specific issues considered are choice of statistical methods and openness in that regard. One possibility that was discussed was whether codes should be made available:

One obvious way to facilitate auditability and reproducibility is with provision of codes which operate on the raw measurement inputs to produce data products. Even in this relatively small subset of participants there was a wide range of perspectives regarding code provision. Some are willing to provide code, although there is doubt whether code alone will explain methodologies and whether external users can simply copy code and reproduce results. Although code provision can directly explain what and how analysis was done, it may be silent on why the particular methodology and implementation was selected. Some agencies have extremely strict requirements for code release, insisting on near commercial-grade quality, which most researchers do not have the time or resources to develop. Therefore, code release is not a feasible option under these conditions. Another subset of statisticians feel that it is better to provide inputs and outputs to interested parties. Supplying (non-peer-reviewed) code can be a dangerous practice, while leaving it to the user to develop the code and reproduce results independently encourages thought and engagement by the potential user. In this replication of results, real scientific value is realized through the analysis of structural uncertainty.

Oh well.

Jeff Masters on Mann and PCA

Jeff Masters, the meteorologist who blogs at wunderground.com, has written the standard-issue five star review of Mann's Hockey Stick and the Climate Wars.

I thought I'd highlight something Masters wrote about the infamous short-centred principal components analysis used in Mann's paper.

[Mann] takes the reader on a 5-page college-level discussion of the main technique used, Principal Component Analysis (PCA), and shows how his famed "hockey stick" graph came about. It's one of the best descriptions I've seen on how PCA works (though it will be too technical for some.)

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Nordhaus and the sixteen

Economist William Nordhaus takes a pop at the sixteen concerned scientists, in the latest skirmish kicked off by their Wall Street Journal editorial.

My response is primarily designed to correct their misleading description of my own research; but it also is directed more broadly at their attempt to discredit scientists and scientific research on climate change.¹ I have identified six key issues that are raised in the article, and I provide commentary about their substance and accuracy. They are:

• Is the planet in fact warming?
• Are human influences an important contributor to warming?
• Is carbon dioxide a pollutant?
• Are we seeing a regime of fear for skeptical climate scientists?
• Are the views of mainstream climate scientists driven primarily by the desire for financial gain?
• Is it true that more carbon dioxide and additional warming will be beneficial?

Two for BBC watchers

A couple of interesting articles for BBC watchers.

Firstly this update from the Independent on the story about BBC Worldwide accepting programming from environmental groups for free. The BBC is to issue an apology.

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Cherrypicking

There has been a lot of blog battling and twitter twootling started by a WSJ article entitled "No Need to Panic About Global Warming". A lot of the argument was about 'how to do climate graphs' with input taken from Skeptical Science. So here is a quick lesson in how to do Climate Graphs...

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