In a stunning (but welcome) development, James Gentle of GMU and Karen Kafadar of IndianaUniversity have been named editors-in-chief, joining  remaining original editor David Scott.

I last discussed WIREs Comp Stat back in July, when Edward Wegman and Yasmin Said were quietly dropped as editors. I outlined the problems that apparently led to their summary dismissal.

Wegman and Said also penned two major overview articles for the WIREs Comp Stat journal. [In 2011], I documented extensive copy-and-paste scholarship in Color Theory and Design and, even more shocking, in Roadmap for Optimization, the featured article in the journal’s inaugural issue. That continued a pattern of dubious scholarship seen in the Wegman Report itself, as well as in a followup paper on climate science social networks that was retracted – twice!

Wiley received complaints concerning both WIREs articles, and dealt with them in a most peculiar way: Wegman and Said were allowed (or allowed themselves) a complete “do over” of each article in turn. Dozens of citations were added, while all traces of previously evident copy-and-paste were scrubbed away.

James Gentle is particularly well placed to restore GMU’s and Wiley’s tattered reputation.

First of all, Gentle is clearly GMU’s real computational statistics expert. He’s written a text book on the subject for Springer, and also served as an editor of the Handbook of Computational Statistics.

Second, Gentle is a stickler for rooting out plagiarism.

Academic honor

Each of my students must assume the responsibilities of an active participant in GMU’s scholarly community in which everyone’s academic work and behavior are held to the highest standards of honesty.

Make sure that work that is supposed to be yours is indeed your own.

With cut-and-paste capabilities on webpages, it is easy to plagiarize. Sometimes it is even accidental, because it results from legitimate note-taking; nevertheless, it is plagiarism and it is illegal.Although the likelihood of “getting caught” should not influence your ethical standards, you should be aware of the fact that web searches can often identify plagiarism, and that there is even specialized software to facilitate such searches. Whenever I encounter phrases in a student’s work that seem to be inconsistent with the usual language that the student uses, I routinely search the web for documents containing those phrases.

These latest moves can be seen as an implicit acknowledgment that much was amiss at WIREs Computational Statistics . Wiley clearly experienced an egregious breakdown in process, and still hasn’t properly owned up to the clear cover up that was attempted by Wegman and Said. Nevertheless, we welcome WIREs Comp Stat back to the fold of credible journals.

[h/t John Mashey]

Here are some topics that could be discussed on this open thread.

1) Margaret Munro of Post Media has reported on the latest initiative to fight muzzling of Canadian scientists by the Harper government.

Federal Information Commissioner Suzanne Legault is being asked to formally investigate the way the Harper government has been “muzzling” and restricting access to federal scientists.

The request, accompanied with a report  [7Mb PDF] on the government’s “systematic efforts” to obstruct access to researchers, was made jointly on Wednesday by the Environmental Law Centre at the University of Victoria and Democracy Watch, a national non-profit group.

2) The IEA Energy Technology Perspectives 2012 report has just been issued, together with a detailed online presentation. In my opinion, this is “must read” for anyone interested in climate policy, and realistic pathways to avoiding the worst effects of climate change. There is, of course, still a yawning gap between current government policies and policies required to limit global warming to about 2 deg C above pre-industrial levels.

3) Russell Seitz has started a very entertaining blog entitled VVattsUpWithThat (yes, that’s a double V!). A recent post discusses the conviction of Heartland Institute science director Jay Lehr for defrauding the EPA in the early 1980s.

The extraordinary 2012 Arctic sea ice melt has resulted in a September average sea ice extent of 3.61 million sq km, according to the latest monthly data from the National Snow and Ice Data Center (NSIDC), smashing the previous record of 4.30 million sq km set in 2007.

Today, I’ll quickly review the last month’s progression. I’ll then examine the plausible future course of the Arctic sea ice “death spiral” that is likely to see the Arctic virtually free of sea ice by the 2030s if not sooner, culminating with a new graphic representation of the Arctic sea ice death spiral.

At the end of August, I projected September sea ice extent of 3.56 (+/- 0.13) million sq km, based on a simple fit of  the most recent available 5-day value to the  eventual September extent, a model that had given good results over the last decade. This year was no exception, although an early flattening and moderate refreezing over the last half of September (see below) pulled the extent up slightly, albeit well within the uncertainty range of the simple model.

As the month progressed, the short-term projection (based on a fit to month-to-date described and justified as preferable in a comment here), climbed to just above 3.6 million sq km and stayed there.

So what now? When will the Arctic be virtually free of sea ice (defined as a September sea ice extent below 1 million sq km)?

First of all, I doubt that 2012 represents as clear a “regime” change as 2007 did, although it seemed to catch experts somewhat by surprise.  The 2007 September extent smashed the previous 2005 record by 23%, a scant two years later. This year’s record eclipsed 2007 by a lesser percentage (16%), and came five years on. Moreover, a quadratic fit of observations through 2012 (orange dashed curve in the chart below) is indistinguishable from that up to 2008 (green curve).

One surprise (for me anyway) was how well the 5-year average matches the quadratic fit over the last 20 years. It’s also interesting to note that 2012 is well below the quadratic curve, but not nearly as much as 2007 (or at least two years in the 1990s for that matter).

And it was already clear before 2012 that sea ice loss was accelerating much faster than the projections of the CMIP3 set of sea ice models used in IPCC AR4, (or even the CMIP5 AR5 models for that matter). 2012 does confirm that the downward trend is still accelerating, however.

The NSIDC team recently published an overview of the CMIP3, CMIP5 and observational record that makes the salient key points (Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Stroeve et al, GRL, Aug 25, 2012).

• CMIP5 models continue to underestimate rate of sea ice loss
• CMIP5 models are more consistent with observations than CMIP3
• CMIP5 suggests 60% of 1979-2011 rate of decline is externally forced

A recent presentation by Julienne Stroeve and Andrew Barrett, Assessment of Arctic Sea Ice in the CMIP5 Climate Models, contains this key graphic comparing model simulations and observations of September sea ice ice extent, to which I’ve added the September 2012 value.

Although CMIP5 (red line) does match quite a bit better than CMIP3 (blue), both 2007 and 2012 lie outside the uncertainty range of the CMIP5 model ensemble.

It’s also worth noting that the model ensembles show continued acceleration beyond the 4 million mark, so it is reasonable to postulate some continued acceleration of sea ice loss. But the models also show marked deceleration as ice free conditions are approached.

With these observations in mind, I propose a simple projection based on extending the current observational record that could be useful for discussion, if nothing else. My starting point is a quadratic fit to observations that Tamino proposed at his Open Mind blog as a way to project September sea ice extent a year in advance. However Tamino has also been quite explicit that such a model is not appropriate to project long term trends. Indeed, simple extrapolation of that trend would result in zero sea ice extent just after 2025, a decidedly unphysical result.

Clearly any reasonable projection or extrapolation will need to incorporate a deceleration of sea ice loss similar to that seen in the models.

To explore this idea further, I now turn to a just-published analysis by Muyin Wang and James Overland (A sea ice free summer Arctic within 30 years: An update from CMIP5 models, GRL Sept 25, 2012).

Using a seven-model subset subset of the CMIP5 that matched observations well from 1980 to 2005, they concluded that “a nearly sea ice free summer Arctic is projected by the 2030s”. Wang and Overland found a median value for breach of the  1 million threshold in 2035 (i.e. 28 years from the baseline of 2007, with a range across selected models from 2021 to 2041).

In my emulation of Wang and Overland’s median projection, I’ve assumed that the quadratic fit for 1980-2005 provides a reasonable extrapolation until about 2.5 million sq km. From that point on, the projection slows considerably, but it breaches the 1 million mark in 2035, just like Wang and Overland. This approach does seem to match the acceleration/deceleration profile of the CMIP5 subset fairly well, while retaining a close fit with the observations to 2005. The result can be seen in the following chart.

However, even though Overland and Wang use only the best matching CMIP5 models, there is still a marked divergence after 2005. The current fit to observations stands 700,000 sq km lower  than the emulated median projection, with 2012 still another 700,000 sq km lower. Mind you, the spread of the Overland and Wang subset is considerable, and they do not rule out nearly ice free conditions in the 2020s.

Now I’ll use the same approach as above, but this time I’ll use the quadratic fit to 2012, instead of 2005, for the first part of the projection. (As previously noted, this fit has quite stable since 2007). In this scenario, deceleration of ice loss starts in 2020, which is when the projection reaches about 2.5 million sq km.

This suggests that nearly ice free conditions are plausible, even likely, before 2030. If we postulate a similar uncertainty spread as in Wang and Overland, nearly ice free conditions could even come by 2020 (but could also be delayed into the 2030s).

The term “death spiral” was first invoked by NSIDC director Mark Serreze to describe the rapid and shocking sea ice loss in the north. Recently, Andy Revkin argued that a descent to nearly ice free Arctic seas by 2030 or later, should not really be characterized as a “death spiral”.  But when one considers the ongoing rapid loss, which has reduced sea ice to levels not seen in hundreds of years or even millenia, it seems absurd to argue about whether such a term should be reserved for the case of a 40-year period to breach the 1 million mark (as Revkin appears to imply), rather than 50 or 60 years.

For me, portraying the above observed fit and projection scenario as an actual spiral over 50 years has driven home this point. In the following chart, each revolution of the spiral represents one decade.

Would an extra spiral turn to get to the “nearly ice free” centre change anything? I don’t think so.

The serious implications of rapid Arctic warming seem clear enough to most scientists,  but have yet to penetrate public consciousness. That is surely due in no small part to concerted past and recent efforts to downplay the significance of rapid Arctic sea ice disappearance. In future posts, I’ll cover some of those efforts by the Fraser Institute, the Frontier Centre for Public Policy, as well as Lawrence Solomon and, yes, Richard Muller.

They and many other naysayers refuse to face two basic facts: Arctic sea ice has fallen to levels unprecedented in millenia [Kinnard et al, 2011, Nature] and that loss is mainly due to anthropogenic global warming   [ J J Day et al, 2012 Environ. Res. Lett.].

And, oh yes, Arctic sea ice is indeed in a death spiral.

The Berkeley Earth project is of mild scientific interest, but its leadership has proven adept at garnering intense media interest with each update (one can only imagine the media explosion once actual scientific publication is achieved). In the wake of the latest Berkeley Earth release, self-proclaimed “converted skeptic” Richard Muller has once again made the media rounds.  Thus it came to be that the CBC brought Muller into my home, and I’ve since taken in a lot of his notions about climate science from a number of sources. Those range from his 2009 “Naked Copenhagen” WSJ op-ed piece and the 2010 head-exploding i4energy presentation (where the dubious rationale for the Berkeley Earth project was first made public), to his recent New York Times op-ed, and his interviews with Diane Rehm and Amy Goodman.

But for now I’ll concentrate on the first part of Muller’s interview with CBC host Kevin Sylvester (of which I’ve  prepared a partial transcript).

Out of the gate, Muller’s appalling self-congratulation and arrogance are on display, as he hopes the Berkeley Earth team papers – none of which had even been accepted yet by a peer-reviewed journal – will “settle the science” about global warming. And why has this task fallen to Muller and the Berkeley Earth team, after thousands of papers and four comprehensive IPCC reports carefully documenting anthropogenic climate change? Well, it turns out “valid issues raised by thoughtful skeptics” had not been “clearly answered”. Those issues included station quality, data adjustments and selection of a “tiny fraction” of temperature stations.

If this were just more of Muller’s self-aggrandizement accompanied by his usual dismissal of real climate scientists, one could simply roll one’s eyes and tune out. At least this time out, Muller did not accuse other scientists of misconduct and “data hiding”, as he has done in the past.

But then Sylvester asked about Koch involvement, and things got really bizarre. Unbelievably, Charles Koch turns out to be one of those “thoughtful skeptics”. And not just “thoughtful”, but “very deep” as well.

Q:  I guess a lot of surprise for a number of people as well as was that the funding for this was from the Koch brothers. … Was there ever any influence … Was there anything that surprised them and maybe angered them about your results?

A: No not at all. I mean, they’re made caricatures in the media. They’re actually very thoughtful people. You should read some of the books  that Charles Koch has written. He’s very thoughtful, very deep. And from the beginning, he and I shared a concern there were issues that had not been addressed in a clearly transparent and objective way. And he wanted those answered. And no he never gave any hint whatsoever what answer he was hoping for, if any.

However, there is little evidence that Charles Koch has accepted the Berkeley Earth findings, especially regarding anthropogenic genesis of global warming. After the release of the Berkeley Earth findings in October 2011, the Charles Koch Foundation gave this decidedly lukewarm comment on the Berkeley Earth results.

The research examined recent global surface temperature trends. It did not examine ocean temperature data or the cause of warming on our climate, as some have claimed.

That statement is still linked from the Berkeley Earth website FAQ entry on funding. But now that Berkeley Earth has gone even beyond the IPCC in attributing warming to human greenhouse gas emissions, the Koch Foundation has issued a second, truncated statement avoiding any discussion of the most recent findings. Even more telling is the apparent absence of Koch Foundation support in the second phase of Berkeley Earth (presuming that the Anonymous Foundation donating $250,000 is not associated with the Kochs).

In the CBC interview, Muller went on to defend Charles Koch against accusations of being a climate change “denier”.

He knew that the science was in trouble, there were things wrong with it. People called him a denier because he was being properly skeptical about things that hadn’t been answered. That was silly. And from the beginning he made it absolutely clear all he wanted to do was good science.

No, despite Muller’s protestations, the Kochs have been labeled deniers, not because they are “properly skeptical”, but  because they have poured tens of millions into supporting contrarian think tanks and politicians who deny the primacy of anthropogenic influences,  chiefly greenhouse gas emissions, in current and future global warming. And the Kochs will reportedly raise up to $400 million to support a Republican Party that has increasingly committed itself to inaction on climate change, among a whole set of extreme Tea Party inspired policies.

It’s understandable that Berkeley Earth would defend its own acceptance of Koch money. And it should be emphasized that there is absolutely no hint of improper influence on the project, from Koch or anyone else.

But by linking to an official Koch statement, Berkeley Earth implicitly endorses this deceitful description of Koch funding policy (as presented in both Koch statements).

The Charles Koch Foundation has long supported and will continue to support sound, nonpartisan, scientific research.

This simply can not be squared with the Koch record, from the establishment of the Cato Institute through to Koch funding for the Heartland Institute and the Fraser Institute, to name just three examples. None of the $60 million that the Kochs have poured into such organizations over the years can conceivably be termed support for “scientific research”, let alone sound scientific research. As for the laughable claim that the “research” is non-partisan, all of the supported organizations are allied with Republican policies and politicians (or Conservative ones in the case of the Canadian Fraser Institute).

A more realistic self-assessment (and rationale) for Koch activities can be found behind closed doors. For years, the Kochs have convened secretive biannual seminars that bring together like-minded Republican patrons with politicians and media boosters, as first reported by the New York Times in 2010. Audio tapes of the January 2011 seminar in Palm Springs, obtained by Mother Jones, feature Charles Koch in full rhetorical flight, with an  oblique reference to Saddam Hussein and a warning that the 2012 election would be ”the mother of all wars.”

But the most revealing insights into the Koch mind set come from a ThinkProgress package containing the letter of invitation for the 2011 Palm Springs meeting, along with the agenda for the previous 2010 meeting held in Vail, Colorado.

Here are a couple of tidbits from the Vail agenda.

Small group dinner:

Energy and Climate: What drives the regulatory assault on energy? What are the economic and political consequences of this? How discredited is the climate change argument? What effect does this have on the electorate, especially in key states? [p. 6]

That makes the real Koch agenda very clear: climate science (or the “climate change argument” in Koch speak) must be “discredited” in order to blunt the “regulatory assault on energy”.

Another session focused on a familiar litany of “significant threats” from the Obama administration.

Understanding the Persistent Threats We Face
The current administration swept into office with a promise to “fundamentally transform America.” From the nationalization of health care to the rising power of unions, as well as a push for major new climate and energy regulations, financial regulation, and even more government spending, there is no lack of significant threats for us to understand and address. [p. 7] [Emphasis added]

The program summary for the “action oriented” 2011 meeting refers to past efforts to “counter”  such “critical threats”  as “climate change alarmism”.

This action-oriented program brings together top experts and leaders to discuss – and offer solutions to counter – the most critical threats to our free society. Recent sessions have focused on addressing rapid government growth, countering climate change alarmism and the move toward socialized healthcare, developing strategies to advance liberty on college campuses, strengthening our state-based capabilities, and promoting judicial reform. Past meetings have featured such notable leaders as Supreme Court Justices Antonin Scalia and Clarence Thomas; Governors Bobby Jindal and Haley Barbour; commentators John Stossel, Charles Krauthammer, Glenn Beck, and Rush Limbaugh; Senators Jim DeMint and Tom Coburn; and Representatives Paul Ryan, Mike Pence, and Torn Price. [Emphasis added]

The featured presence of right-wing media stars like Beck and Limbaugh is fairly predictable, but the attendance of two sitting Supreme Court Justices is frankly shocking.  And look who made a surprise appearance towards the end of that list: none other than then vice-presidential candidate in training (and climate change contrarian) Paul Ryan.

So much for “non-partisan scientific research”.

But just because Muller doesn’t accept that Koch is a “denier”, doesn’t mean “deniers” don’t exist – far from it.

If we take the standard, the consensus prior to our work  as being what the IPCC had reported, then there are deniers who say: “There’s no global warming it’s all political”.  And there are also deniers who say: “Oh, the IPCC is completely wrong – the situation is much, much worse than they say”. If they are denying the IPCC  by saying it’s worse, they should be called deniers too. And that includes Al Gore and Tom Freidman as people who deny the IPCC report.

It’s a good thing we have Muller and the Kochs to occupy the middle ground between the “deniers” on both sides.

As I’ve said before, Muller’s belated “conversion” to scientific consensus on anthropogenic climate change is positive, albeit woefully late. But he clings to many of his previous fallacious positions on a range of issues, beyond his absurd characterization of the Koch Brothers. Proper treatment of these could keep an assiduous blogger busy for a long time, so I’ll just summarize some of Muller’s most problematic points briefly.

At the top of the list is Muller’s repeated insistence that “climategate” revealed gross scientific misconduct on the part of scientists at East Anglia’s Climate Research Unit. Those accusations are completely unjustified, and based on a faulty grasp of the facts to boot. Berkeley Earth team member Zeke Hausfather has repudiated accusations of scientific malfeasance against CRU’s Phil Jones and Keith Briffa from the beginning. And even Chip Knappenberger rejected Steve McIntyre’s “analysis” of the Climategate email exchange concerning the IPCC TAR chart that showed reconstructions by Briffa and Jones, along with the MBH99 “hockey stick”, terming it “normal scientific discourse”.  (I’ve discussed this particular aspect of “climategate” and the “hide-the-decline” controversy several times, notably here and here).

Of course, it should also be pointed out that misinformation about “climategate” was assiduously promulgated by several groups funded by the Koch Brothers, notably Americans for Prosperity, the Heritage Foundation and the Cato Institute.

Climategate aside, though, here are some of the other gaffes and questionable “facts” that may occasion more detailed commentary. According to Muller:

• Hansen’s recent work on seasonal temperature extremes is “not correct” (and Hansen “predicts” his findings in Gistemp “ahead of time” which makes Muller “very uncomfortable”). [Sources: CBC, i4energy.]
• “Is the Arctic melting due to global warming? You know, the evidence for that is very, very flimsy. I’m not even sure it’s true.” Enough said  – for now. [Source: Diane Rehm show]
• China’s  greenhouse gas emissions will increase more than five-fold by 2040, even with a 4% reduction in carbon intensity each and every year. [Sources: Wall Street Journal and many others]

And, last but not least, we have an oldie but goodie (again via the CBC).

• “[T]he globe isn’t warming, at least not in recent years”.

I don’t see anything in that list to which Charles Koch would take the slightest exception.

And yes, my plan will continue to reduce the carbon pollution that is heating our planet – because climate change is not a hoax.  More droughts and floods and wildfires are not a joke.  They’re a threat to our children’s future.  And in this election, you can do something about it.

For a Canadian perspective that somehow managed to miss the point of Romney’s ill-advised, small-minded joke, check out Andrew Coyne in the National Post.

Meanwhile, Canadian environment minister Peter Kent announced regulations for coal-fired electricty that are weaker than the original proposal of a year ago, while the government met renewed accusations of creative carbon accounting.

In my previous discussion of the extraordinary 2012 melt, I noted the eclipse of the old daily record on August 24, three weeks ahead of the 2007 pace. But I also gave a series of short-term  projections for the September extent average, which is the metric typically used to track the decline in Arctic sea ice. The  2012 September projection now stands at 3.56 million sq km, slightly down from my previous projection of 3.67 million sq km. That’s more than 700,000 sq km less than the previous 2007 record of  4.30 million sq km.

As I discussed in greater detail last time out, these short-term projections are generated by regressing the most recent 5-day sea ice extent level against the eventual September average. This seems to give a very reasonable result, once one is past the first week of August or so. Here are four such projections, with the latest (purple circles) based on the five-day average for August 22-26.

This gives a September 2012 projection of 3.56 +/- 0.13 million km  (as seen in the lower right hand corner), down slightly from the previous week. Here is the whole series to date.

The confidence interval continues to tighten; past projections based on August 27 have correlation of coefficient of about 0.98. The resulting tight forecasts can be seen in the model’s simulated past projections for August 27.

Arctic sea ice continues to melt at a record pace (yesterday’s daily level was at 3.8 million sq km), so the next projection update may be slightly lower. The eventual level will depend largely on when the minimum is actually reached; recent years’ five-day minima have ranged from early September (e.g. 2010) to late September (e.g. 2011). But at this late stage, I would be surprised if the 2012 September average  went below 3.4 million sq km (or above 3.7).

I’ll not only update the September 2012 projection in a few days, but I’ll also be looking at the future course of the Arctic sea ice “death spiral“. (Unsurprising sneak preview: Virtually sea-ice free summers, defined as September extent below 1 million sq km, will likely arrive in the Arctic before 2030).

[UPDATE Sept. 3-6: The updated projections are:

• Sept. 3: 3.56 +/- 0.12 million sq km
• Sept. 6: 3.57 +/- 0.12 million sq km ]

[UPDATE Sept. 13: Sea ice extent has flattened out considerably in the last week or so; nevertheless the 5-day average is still descending, if ever so slightly. The net effect is that the short-term projections for the September average are edging upwards.

Now that we're in September, I'm tracking two short-term models, one based on the latest 5-day average (as before), and the other on September average to date (obviously, both models gave the same result on September 6). I tend to favour the latter, as it is more stable, and looks to perform a little better since 2007. Currently the "5-day" model projects a September average of 3.67 +/- 0.11 million sq km, and the "Sept to date" projects 3.63 +/- 0.11 million sq km. ]

[UPDATE Sept. 18-19: The latest available five-day extent, centred on September 16,  is at 3.43 million sq km and rose for the first time in each of the last two days.  Thus the minimum may well have been reached on the 5-day  average centered on September 14, when extent was  3.41 million sq km. As of September 17, the "5-day" model projects a September average of 3.56 +/- 0.09 million sq km, and the preferred "Sept to date" model projects 3.61 +/- 0.09 million sq km.]

And rest assured that the horrific irony of Conservative prime minister Stephen Harper’s recent tour of the Canadian North to tout growing resource extraction opportunities will get a closer look. Harper appears to have  failed to mention climate change and its devastating implications for the North – despite  ending his tour on the very day the new daily sea ice extent minimum record was set.

[UPDATE Aug 24-28:

August, 2012:

• Aug 22: 4.29 million sq km
• Aug 23: 4.19 million sq km
• Aug 24: 4.09 million sq km ***
• Aug 25: 3.97 million sq km
  
• Aug 26: 3.94 million sq km
  
• Aug 27: 3.85 million sq km

*** New record low for daily Arctic sea ice extent set on  Aug 24.]

This year’s arctic ice melt season is generating extraordinary interest. 2012′s apparent descent toward a new record low in extent and area is dramatic enough, but it also comes as new analysis shows that summer sea ice loss is 50% more than previously thought in terms of volume, according to preliminary satellite data from CyroSat 2. Virtually ice-free summers in the arctic sea could well arrive by 2030, with troubling implications for accelerated albedo feedback and possibly disruptive changes in the jet stream.

A new record low, eclipsing 2007, does seem increasingly inevitable with each passing week. National Snow and Ice data Center data showed Arctic sea ice extent at 4.29 million square km yesterday, just under 2007′s September average, and a level only reached on September 7 back then. To be sure, 2012 is starting to bottom out, but most years have seen a similar pattern around now.

Here’s a snapshot of the  2012 melt season (with the small crosses denoting recent daily values), compared to the previous five years.

Just how low could 2012 go?

To try to answer that question, I’ve tried my hand at short-term prediction. I used a rolling five-day average to generate bi-weekly projections, eight in all. The model is very simple – the most recent five-day August average is used as a predictor for the September average, based on a regression on the last 11 years.  To illustrate, the following chart shows projections generated for five-day averages centred on August 3, 10, and 17. It also shows the regression for the August 22-26 five-day average, which will become available in a few days.

The fit is not that good early in August, but improves considerably by mid-August; over that same time, 2012 has gone well below 2007. Now here are the other rolling projections, including the latest one generated today and one to come in a week.

Since daily data becomes available only the following day, the prediction for each five-day average is actually only available three days after the nominal “centre” date. So today’s projection  (August 23) is based on a five-day average from August 18 through 22 (i.e. centred on August 20).

The current projection is 3.67 +/- 0.17 million sq km. As shocking as such a breach of the 4 million mark would be, it could be argued that this might even be somewhat conservative. The most recent years all tend to hew quite close to the regression line (e.g. 2007) or else fall below it (e.g. 2008). On the other hand, the 2012 melt season might yet surprise us once again.

Here are the projections as they have evolved since the beginning of August, including today’s.

Over the course of the month, the confidence interval has narrowed and the central value has stabilized considerably. It will be interesting to see how this develops over the coming days and weeks.

[UPDATE Aug 24: Yesterday, the NSIDC extent fell 100,000 sq km and stands at 4.19 million sq km, just 30,000 sq km above the previous record of 4.16 million sq km set on September 14, 2007. The new record should come any day now, as can be seen from the updated chart.]

UPDATE Aug 25: Yesterday, the extent fell another 100,000 sq km and stands at 4.09 million sq km, setting a new record.

UPDATE Aug 26: Yesterday, the extent fell another 100,000 sq km and stands at 3.97 million sq km, breaching the 4 million mark for the first time.]

UPDATE 08/20: The 2012 GHCN-only series has been uploaded by Zeke Hausfather. Also, I have added clarifications concerning absolute temperature uncertainty and data availability. The summary has been updated accordingly.]

The recent Berkeley Earth land-surface average temperature series is based on a greatly expanded database of station temperature data, along with a completely automated statistical averaging process. In contrast, established average temperature series from NOAA, NASA and HadCrut are based primarily on the smaller Global Historical Climate Network (GHCN) database, and use empirically derived homogenization methods to remove known biases, albeit supplemented by pure statistical methods.

Here, the post-1950 Berkeley Earth “complete” land series is compared to the preliminary Berkeley series released in 2011, as well as to GHCN-only simulated series, based on overall attributes of those unreleased series provided in the Berkeley Earth companion “methods” paper. The 2011 and 2012 “full” (ALL) series Berkeley versions both fall squarely in the range of the latest comparable series from the three other groups post-1950. However, the two Berkeley ALL series diverge over the 1980-2010 period, and lie completely outside each others’ 95% confidence intervals in the 2000s, when baselined to 1950-1979. This turns out to be due to a significant error in latitudinal weighting in the 2011 ALL series; the error was not publicly disclosed at the time of correction. The GHCN 2012 series falls halfway between the 2012 ALL and 2011 ALL series in the 2000s; 2012 GHCN and 2012 ALL each appear to diverge outside the other’s confidence interval in the 2000s. As well, there is an increasing widening between the 2012 GHCN and ALL  series the further one goes back before the 1950-1979 baseline period, with the ALL series about 0.3 C cooler in the early 1800s.

Other issues requiring further analysis are also identified, particularly a reported reversal in the long-term trend of narrowing diurnal temperature range starting in 1987, which contradicts previous GHCN-based analyses.Taken together, these issues cast doubt on the robustness of the present Berkeley Earth analysis, and point up the need for more open data access and improved diagnostics in order to further assess the reliability of the Berkeley Earth approach to surface temperature analysis.

1. INTRODUCTION

The Berkeley Earth Surface Temperature project has created a stir out of all proportion with its limited scientific import. In large part, this great interest stems from the very explicit conception of the Berkeley Earth project as a counter to the alleged scientific malfeasance of existing temperature group leadership, specifically at NASA-GISS  and the U.K. Climate Research Unit at the University of East Anglia. (By the way, I’ll be eschewing the obvious – albeit oxymoronic – acronym for the Berkeley project).

I suppose the belated “conversion” of Richard Muller to full acceptance of long-established scientific findings concerning anthropogenic global warming is positive on balance. Nevertheless, Muller and other Berkeley team members have a history of parroting baseless accusations against mainstream climate scientists, while carefully avoiding criticism of clearly misleading and false statements from contrarians. That disturbing pattern continues, as seen in Muller’s recent doubling-down on accusations related to “climategate”. This problem has even affected Berkeley Earth discussions of the very recent temperature record, an issue I’ll explore another time.

For now though, I’ll discuss the Berkeley Earth findings, drawing on  the results summary and data, as well as the team’s  supporting (as yet unpublished) papers. Of primary interest are the newly released main “results” paper, A New Estimate of the Average Earth Surface Land Temperature Spanning 1753 to 2011 , and the recently revised “methods” paper, Berkeley Earth Temperature Averaging Process, along with the earlier 2011 version.

So far, Berkeley Earth has confined its analysis to land-surface temperature only (the othr groups produce global series incorporating both land and ocean). This fact alone may well inhibit citation of the Berkeley series, even if peer-reviewed publication can be achieved. In particular, the IPCC does not incorporate separate land-only analyses, so cited temperature series must be truly global.

The Berkeley approach to land temperature analysis differs from that of the three traditional groups (NOAA-NCDC, NASA-GISS and HadCRU), in two important respects:

• Berkeley uses a greatly  expanded database of station temperature histories drawn from a variety of sources (most held by the NOAA), whereas the others primarily base their analyses on the Global Historical Climatoligical Network (GHCN), managed by NOAA. The Berkeley database conatains more than 38,000 station histories (albeit some very short), as opposed to about 7200 in the GHCN.
• Berkeley uses a pure statistical approach to processing station histories, breaking the series into sub-series based on discontinuities and then weighting based on internal consistency and correlation with neighbouring series. The other groups use empirically derived homogenization methods to remove known biases (or previously homogenized data in the case of HadCrut), albeit supplemented by purely statistical methods (see for example NOAA’s USHCN/GHCN methodology) .

In October 2011, Berkeley Earth released a preliminary full land temperature series, based on the complete station database. At the end of July, an updated land temperature series was presented, along with the new “results” paper. I refer to these two series, as Berkeley ALL 2011 and Berkeley ALL 2012, respectively.

The Berkeley “methods” paper presents another temperature series, based on the GHCN data set. Here the Berkeley methodology has been applied to the “raw” GHCN station histories without regard to any subsequent GHCN homogenization, as a test and demonstration. This series provides a useful comparison to the Berkeley ALL series, on the one hand, and to the other groups’ analyses on the other. In fact, the NOAA temperature analysis is based on this exact set of stations, so any differences with Berkeley GHCN are strictly down to differences in methodology.

Unfortunately, at the time of writing Berkeley Earth had not seen fit to release the GHCN-based temperature series data. However, the attributes of the series post-1950 are sufficiently well described in the two versions of the “methods” paper to enable very approximate simulated GHCN series, in order to compare the broad trends visually. I refer to these two series as Berkeley GHCN-Sim 2011 and Berkeley GHCN-Sim 2012 respectively.

2. BERKELEY ALL 2011 and 2012, 1950 to PRESENT

The Berkeley ALL 2o12 “complete” data set is available at the main Berkeley Earth summary page. It contains monthly data points from 1755 to 2011, along with one-year, five-year, ten-year and twenty-year moving averages and associated 95% uncertainty. The earlier preliminary Berkeley ALL 2011 data set is no longer available from Berkeley Earth, but apparently can be downloaded from third-party websites (e.g. at FindThatFile.com). That series goes up to early 2010.

The Berkeley summary page compares the Berkeley 2012 ALL series with three land temperature series: NOAA-NCDC, NASA-Giss and CRUTEM4 (also available at the HadCrut data page).

The close correspondence of all four series from 1950 on is obvious, but it is somewhat difficult make out when seen along side the more variable 19th century. So let’s drill down to the centred ten-year moving averages post-1950 period and add the Berkeley ALL 2011 series for good measure. (This and all subsequent charts use a 1950-1979 baseline).

Land surface temperature comparison 1950-2011 (10-year moving average)

By the 2000s, NOAA is running a little warmer than the other three; Berkeley 2012 reached virtually identical level with CRUTEM4 and the GISS Land series in the 2000s. In contrast, Berkeley ALL 2011 tracks the NOAA  series more closely. Nevertheless, all series are quite close to one another over this entire period.

Note that both Berkeley series are at the high end of the range in the 1970s, while Berkeley ALL 2012 is at the low end in the 2000s. This is reflected in a slight lower linear trend slope in Berkeley ALL 2012 compared to the other series.

Although the trend is slightly lower in Berkeley ALL 2012 than the other series (including Berkeley ALL 2011) the trend from 1970 on has remain above 0.25 C per decade in all series since 2005.

Now let’s take a closer look at the differences between Berkeley ALL 2011 and 2012, showing their respective confidence intervals. The Berkeley methodology computes spatial and statistical uncertainty (the latter via a 7/8 “jackknife”), but does not include bias and measurement error  estimated by the other groups. Because of this narrower focus, and because of the large size of the Berkeley station database, the confidence intervals of the Berkeley series are very tight indeed, especially in recent years. To illustrate this, here are the two series from 1990 through 2011, this time displayed annually.

The confidence intervals are shown by the bounding dotted lines; circled years denote where the central value of  the 2011 series is outside the confidence interval of the 2012 series.  There are four such years in the 1990s and six in the 2000s, including all of the last five years common to both (2005-2009).  Generally speaking, the 95% confidence intervals for annual values in this period are about +/-0.04 C, with the 2011 intervals slightly higher. Several years feature no overlap of the confidence interval at all (e.g. 2007)!

The 10-year moving average shows the evolution of this divergence since 1980.

By the 2000s, the confidence intervals no longer overlap at all, and presumably would continue to widen, were both series to be extended in the future.

This divergence does not seem easy to explain. The database has presumably been stable, and the methodology does not seem to have undergone any significant changes. Yet the Berkeley ALL series has suddenly moved from the top end of the range of observed warming to the bottom post-1980, compared to the other series. The sensitivity of the Berkeley series to presumably small tweaks or corrections in the Berkeley methodology is worrisome; if this effect went unnoticed by the Berkeley team, they would be well advised to perform a sensitivity analysis for each change introduced over the last few months.

Before moving on, I should also mention some baseline curiosities in these datasets. The eagle-eyed observer may have noticed a discrepancy in this regard. Indeed, the Berkeley papers consistently cite a 1951-1980 baseline (that is, all series are given as anomolies from the average in this period). The Berkeley datasets  headers, however, state that the baseline is 1950-1980, not 1951-1980. Meanwhile, the data itself has an average of exactly 0 from 1950-1979, so I have used this baseline to avoid changing the data as given (the other series have been adjusted accordingly, of course).

To add to the confusion, the Berkeley summary charts (such as the one above) do not explicitly mention any baseline, but the baseline used is clearly later than 1951-1980 (perhaps 1961-1990).

[UPDATE 8/20: As Berkeley team member Zeke Hausfather notes in a comment below, the Berkeley 2011 series had a significant error due to incorrect latitudinal weighting. That problem resulted in an elevated trend compared to the corrected 2012 series, with a four-sigma difference in the 2000s decade. It also had a clearly unrealistic absolute average temperature a full 2 C lower than other Berkeley series, including the contemporaneous GHCN 2011 series. It is therefore somewhat surprising that the Berkeley Earth team did not realize that this series was problematic.

It is not yet clear when the error was discovered, but it seems it must have been earlier this year. At some point (I can’t recall exactly when), the Berkeley Earth data analysis page was updated with a corrected chart that showed a little less post-1980 warming, and the link to the underlying data was removed. That page is still available; it contains no indication or notice that the previous version had been corrected.

I’m inclined to give the Berkeley Earth team the benefit of the doubt and presume that the failure to disclose this error was not an intentional effort to mislead. However, it does point up a serious problem in Berkeley Earth’s science communication. And it is especially ironic that Berkeley Earth failed to disclose this information, as well as reach a minimum level of professional communication, given the unfounded attacks by the project leadership on established groups. ]

3. COMPARISON OF BERKELEY ALL and BERKELEY GHCN, 1950 to PRESENT

In the two versions of the “methods” papers, the Berkeley team used their methodology on the GHCN station data.  Unfortunately, these series remain unarchived. However, the main attributes of the series post-1950 are given in the respective paper versions. The corresponding ALL  attributes are given in the corresponding data set header or derived from the actual data, except for the 2000s increase in 2012 ALL, which is found in the “results” paper. The following table compares the general characteristics of the two Berkeley ALL and the two Berkeley GHCN series from 1950 on.

The wide variance in estimated average absolute temperature in the 1950s is striking. The 2011 ALL value appears to be an error and so has been italicized. But the other values are also well apart. In particular the difference between 2012 ALL and GHCN is a whopping 0.42 °C. Since the given standard deviation for the GHCN 1950s value is only 0.016 °C, this represents a more than 25-sigma difference!

[UPDATE 8/20: The GHCN temperature and uncertainties given in the above table came from the “methods” paper, which reads as follows at p. 24.

Applying the methods described here, we find that the average land temperature from Jan 1950 to Dec 1959 was 9.290 ± 0.032 C, and temperature average during the most recent decade (Jan 2000 to Dec 2009) was 10.183 ± 0.047 C, an increase of 0.893 ± 0.063 C.

However, later in the paper we read:

The global land average from 1900 to 2000 is 9.35 ± 1.45 C, broadly consistent with the estimate of 8.5 C provided by Peterson et al. (2011). This large uncertainty in the normalization is not included in the shaded bands that we put on our 𝑇𝑎𝑣𝑔 plots, as it only affects the absolute scale and doesn’t affect relative comparisons.

Thus, the uncertainty in the first passage appears to refer to the uncertainty of the nominal average temperature relative to other periods, not the uncertainty of absolute temperature per se. In other words, it is equivalent to the uncertainty in the anomaly. The uncertainty in the absolute temperature is considerably larger. The first sentence is poorly worded, though, and should be clarified. ]

The trend from 1970 to present is noticeably lower in the 2012 ALL series than the other three, and barely within the GHCN 2012 confidence interval.

To show all this in more visual terms, I have fixed the given GHCN series with decadal average values in the 1950s and the 2000s. I then extended from present back to 1970 at the given rate of slope and differencing that slope with the corresponding ALL series, producing the “GHCN-Sim” series seen below.

I have shown the GHCN-Sim 2012 with both a common baseline to 2012 ALL (showing the extremeley wide divergence in estimated absolute temperature) and a more conventional “internal” baseline. Evem the latter shows evidence of divergence by 2011, with the GHCN series already at the upper bound of the 2012 confidence interval.

4. BERKELEY ALL 2012 vs BERKELEY GHCN 2012 PRE-1950

4a. 1900-1950

The “methods” paper gives few hard numbers concerning Berkeley GHCN 2012 in this period. I will therefore confine my remarks to a visual comparison of the two series, as seen in charts from the respective papers.

The following is from Fig 8 in the “methods” papers and shows the Berkeley GHCN 2012 (in black) along with NOAA (green), GISS (red) and CRUTEM3 (red). We can see that GHCN 2012 is within the other three, and tracks CRUTEM3 quite closely at the bottom of the pack up until 1915 or so. By 195o, the four series are barely distinguishable with Berkeley GHCN 2012 squarely in the middle.

Contrast this with Berkely ALL 2012 as seen in the “results” paper Fig. 1 (note this a 10-year moving average, as the annual chart is very indistinct).

In the early 1900-1915 period, Berkeley 2012 ALL is way below all the others, and is still slightly below even in the 1940s.

4b. 1800-1900

In this period the divergence between Berkeley GHCN and Berkeley ALL is even wider.

First, as in the post-1950 case, we give a table of comparable attributes.

In the “methods” paper,  the GHCN  1800s trend is deemed “approximately constant” at 0.18 C/century, whereas  Berkeley ALL gives a much higher trend of 0.54 C/century. In fact, that is closer to the Berkeley 2012 ALL 20th century trend of  0.77 C/century  for that period, than to the GHCN 1800s trend.

The combination of steeper trend and lower temperatures relative to the 1950s, implies an approximately 0.3 °C divergence at the beginning of the 19th century.

In order to confirm this divergence, I compare the 1813 troughs in the respective 10-year average data sets. The Berkeley 2012 GHCN levels can be approximately determined from Fig. 1 bottom panel in the “methods” paper, while the Berekeley 2012 ALL are derived from the data set as before.

In the following table, the centred 10-year averages are given relative for the minimum centred on 1813, relative to the 1950s decade.

This confirms the approximate 0.3 °C divergence between the two series in the early 19th century.

As the authors note in a cursory manner, the Berkeley ALL 19th century temperature series is considerably cooler in general than paleoclimate reconstructions, including NH land reconstructions. However, the authors have not attempted to quantify these differences or assess them in any way, even though some of the 19th century reconstructions (e.g. Lutterbacher) are themselves largely based on instrumental data.

To be sure, estimates of past centennial variability have tended to increase over the years (compare IPCC TAR and AR4 for exzmple).  But the Berkeley 19th century portion looks like an outlier even compared to the coolest paleoclimate reconstructions such as Moberg et al.

The 19th century series portion should also be compared to paleoclimate model “hindcasts” in this era, such as presented in IPCC AR4 Chapter 6 Fig. 6-14. These capture short-term volcanic related excursions better than reconstructions from proxies (although the two approaches align well at longer timescales).

The spread between the early 1800s trough and 1950s level in the various model runs is about 0.6-0.8 °C, or  0.4-0.6 °C less than in the Berkeley ALL 2012 series. To be sure, the two are not directly comparable as Berkeley ALL is global land, and the model reconstructions are NH over land and ocean. A more precise comparison would compare Berkeley ALL NH, to NH model and proxy land reconstructions. Nevertheless, it appears that the GHCN-only series may be more plausible and in line with other evidence. Understanding the source of the large divergence between the Berkeley ALL and GHCN series becomes all the more crucial.

5. OTHER ISSUES

Beyond presentation of the new temperature series, the Berkeley Earth “results” abstract mentions two other findings, concerning (a) diurnal temperature range and (b) the ability of volcanism and anthropogenic effects to account for temperature variations.

Diurnal variations decreased from 1900 to 1987, and then increased; this increase is significant but not understood. The period of 1753 to 1850 is marked by sudden drops in land surface temperature that are coincident with known volcanism; the response function is approximately 1.5 ± 0.5 ºC per 100 Tg of atmospheric sulfate. This volcanism, combined with a simple proxy for anthropogenic effects (logarithm of the CO2 concentration), can account for much of the variation in the land surface temperature record; the fit is not improved by the addition of a solar forcing term.

5a. Diurnal temperature range

Like the NOAA, the Berkeley Earth team has studied trends in minimum and maximum temperature, not just temperature average. The majority of sites (at least since 1950) allow the construction of paired minimum/maximum series, enabling average  diurnal temperature range to be estimated over time.

Some of the climate models predict that the diurnal temperature range, that is, the difference between Tmax and Tmin, should decrease due to greenhouse warming. The physics is that greenhouse gases have more impact at night when they absorb infrared and reduce the cooling, and that this effect is larger than the additional daytime warming. This predicted change is sometimes cited as one of the “fingerprints” that separate greenhouse warming from other effects such as solar variability. Previous studies [Karl et al., 1991; Easterling et al., 1997; Braganza et al. 1998; Jones et al. 1999] reported significant decreases in the diurnal temperature range over the period 1948 to 1994. …

The figure:

The interpretation  follows:

The behavior of the diurnal range is not simple; it drops from 1900 to 1987, and then it rises. The rise takes place during a period when, according to the IPCC report, the anthropogenic effect of global warming is evident above the background variations from natural causes. Although the post-1987 rise is not sufficient to undo the drop that took place from 1901 to 1987, the trend of 0.86 ± 0.13 C/century is distinctly upwards with a very high level of confidence. This reversal is particularly odd since it occurs during a period when the rise in Tavg was strong and showed no apparent changes in behavior

… We are not aware of any global climate models that predicted the reversal of slope that we observe.

The general descending trend in diurnal temperature range is well established, as noted by the authors. However, there are at least two major problems with the above exposition, as revealed by a quick Google search on “DTR Trend” at the NOAA site.

First, the assertion that climate models show DTR is a particular feature of greenhouse gas warming appears to be without foundation. Liming Zhou’s bulletin, Asymmetric Global Warming: Day versus Night, on DTR notes:

The greenhouse gases enhanced surface downward longwave radiation (DLW) explains most of the warming of T_max and T_min while decreased surface downward shortwave radiation (DSW) due to increasing aerosols and water vapor contributes most to the decreases in DTR in the models.

So there is an anthropogenic component (i.e. aeorosols) to modelled DTR, but it is also associated with increasing water vapour, which is a feedback of warming irrespective of attribution. Thus there is no justification for claiming that DTR decrease is a specific “fingerprint” of greenhouse gas warming in climate models.

It is also worth noting that the observed decrease in DTR is well above  the small descending trend adduced in models, as noted in Zhou’s figure 2 (bottom panel – red line is modelled with all forcings, black is observed).

Second, the Berkeley Earth team cites older studies on DTR but fails to cite a more recent 2005 study by Vose et al that finds no trend in DTR from 1980 on (a feature also seen in the Zhou figure above, which derives observed trends from Vose et al).

Since this latter finding is based on analysis of NOAA GHCN temperature series, the natural question is whether the Berkeley Earth divergent finding of increasing DTR is attributable to the expanded data set, different processing algorithm or both. One obvious approach is to perform the same analysis on a GHCN-only TMax / TMin temperature series.

It is particularly worrisome is that not a single member of the Berkely team, all of whom were either co-authors or credited with useful insights, caught these major deficiencies in this section.

5b. Volcanic and other forcings

The Berkeley Earth ALL series extends back to 1755, while the GHCN-only series goes back to 1800. (In contrast, NOAA and NASA-GISS go back to 1880, while HadCrut goes back to 1850).

The extended record has been fit to a linear combination of volcanic emissions and ln CO2 levels. In the following figure reformatted from the “results” paper Fig 5, annual and decadal record and fit are shown at top and bottom respectively.

As noted above, the 19th century portion of the series is generally cooler and has a more pronounced upward trend than the Berkeley GHCN series, or comparable model and proxy paleoclimate reconstructions. This characteristic of the Berkeley ALL 2012 series appears to be related to a more pronounced downward excursion in the early 1800s, associated with the Tambora mega-volcano in 1815 (on top of a smaller volcano in 1809).

That volcanic effects play a major role in 19th century temperature and anthropgenic GHGs in the 20th, is scientifically uncontroversial (or should be). However, treating forcings as completely independent could lead to inconsistent results. At first glance, the large decadal downturns attributed to volcanic activity imply a higher climate sensitivity to those forcings than to the equivalent forcings from GHGs, a nonsensical result. Alternatively, it could imply that volcanic forcings have been severely underestimated in the past.

Once again, benchmarking against the GHCN-only series would supply much needed insight. It seems plausible that the GHCN-only series would be more consistent with previous work, as well as provide a more consistent fit to volcanic emissions and GHGs.

In any event, while linear fits may provide some qualitative confirmation of the correctness of the general shape of the 19th century portion of the Berkeley series, they are a poor substitute for proper attribution studies. (A more apt use of linear fits is to remove short-term effects of natural variation in order to ascertain the true underlying trend in the recent temperature record, as done in Foster and Rahmstorf 2011).

In a subsequent post, I’ll compare the Berkeley series to reconstructions from both models and proxies over NH land. It is hoped by then that the Berkeley Earth will have seen fit to release the GHCN 2012 series.

6. CONCLUSION AND SUMMARY

I have compared the Berkeley Erath land temperature series to other Berkeley Earth series, and series from other groups, and found many unexplained divergences and discrepancies. These include:

• Berkeley ALL 2012 is cooler post-1980 compared to all other Berkeley series and those from other groups. There is no overlap of confidence intervals in the 2000s. [This is now known to be due to a previously undisclosed error in latitudinal weighting].
• The 19th century portion of the Berkeley ALL 2012 series is considerably cooler than the GHCN series, with a divergence of about -0.3 C at the circa 1813 trough. It is also appears to be cooler than all proxy and model reconstructions.
• The analysis of diurnal temperature range (DTR) is hampered by misconceptions and ignorance of previous scientific literature. The DTR findings are at odds with the most recent credible science in this area.
• Independent fit of Berkeley ALL 2012 to volcanic emissions and CO2 atmospheric levels appears to give conflicting estimates of sensitivity to forcings, or else imply a previous underestimate of volcanic forcings.

These differences need to be reported, explained and resolved before the Berkeley Earth series can be considered a credible addition to the global surface temperature record.

Despite Berkeley Earth’s stated commitment to open access to data, much work needs to be done to improve data access. The group has released the main average, maximum and minimum temperature series and created a drill down database that can provide regional and local temperature series. However there is no data available for the minimum and maximum series which were used to analyze DTR. And no data whatsoever has been released to support the “methods” paper and the GHCN-only series presented there. Moreover, the raw data sources are poorly described and little information is available on location and number of stations in each data source.

As a first step towards more open access, the GHCN only series should be released as soon as possible. Other subsets should also be considered in order to explore possible biases lurking in the various data sets.For all released series, intermediate detailed and summary results should also be released (as NOAA does). This is especially important given the relatively opaque methods of Berkeley Earth, which bear no obvious relationship to individual station data. Thus, for example, the merged “Best Quality Stations” should be released and should probably also include diagnostic information to ascertain the weight of individual stations in each combined series over time.

[UPDATE 8/20:  Today Zeke Hausfather posted the 2012 GHCN series, as noted below. I commend him for this swift action.

The next logical step is to release other key summary data for each of the submitted papers. This will permit better public scrutiny of Berkeley Earth results and attributes, as I argue above. But just as importantly, if this policy had been in place from the beginning, the error in the Berkeley Earth 2011 results would  have been caught much earlier, as the “methods” GHCN series would have been seen to be clearly at odds with the 2011 ALL series. ]

The Berkeley approach to temperature averaging and the creation of an expanded integrated database of raw data may turn out to be useful contributions. But in the end, it is entirely possible that a pure statistical approach can not overcome deficiencies in the raw data; certainly, the automated “more is better” approach has yet to be validated.

Meanwhile, Canadian environment minister Peter Kent is touting an improved outlook for meeting Canada’s 2020 goal for GHG reduction, even though any progress is more due to luck, accounting changes and strong action by some provincial governments, rather than any concrete action by the federal government. Not to mention that current projections for 2020 still leave Canada only 3% under 2005 levels, 19% above the promised target. I’m working on a couple of related posts, but they may take a little time yet.

The latest release from the Berkeley Earth team has unleashed a major kerfuffle in the blogosphere, out of all proportion with its scientific import. (By the way, I have a post on Berkeley Earth coming very soon, looking at some curiosities in the various Berkeley results).

Getting back to the science, arctic sea ice continues to melt at an extraordinary pace, and may well set a new record low this September.

CHANGES AT WIREs COMPUTATIONAL STATISTICS …

Wiley Interdiscplinary Reviews – Computational Statistics (WIREs Comp Stat) began in 2009 as one of a series Wiley interdiscplinary journals (the WIREs stable has now reached eleven strong and includes WIREs Climate Change). Although WIRES Comp Stat itself is completely unrelated to climate studies, the original trio of editors – Wegman, Said and Rice University statistician David Scott – had collaborated earlier on the highly controversial congressional report on paleoclimatology known as the Wegman Report.

Wegman and Said also penned two major overview articles for the WIREs Comp Stat journal. Last year, I documented extensive copy-and-paste scholarship in Color Theory and Design and, even more shocking, in Roadmap for Optimization, the featured article in the journal’s inaugural issue. That continued a pattern of dubious scholarship seen in the Wegman Report itself, as well as in a followup paper on climate science social networks that was retracted – twice!

Wiley received complaints concerning both WIREs articles, and dealt with them in a most peculiar way: Wegman and Said were allowed (or allowed themselves) a complete “do over” of each article in turn. Dozens of citations were added, while all traces of previously evident copy-and-paste were scrubbed away. Here’s a small sample comparing a section on linear programming in the original version of Roadmap to Tom Ferguson’s Linear Programming: A Concise Introduction, with the large swathe of identical wording highlighted in cyan, and trivial differences in yellow .

That brings us to the current WIREs Comp Stat lineup, where all of a sudden David Scott is alone at the top of the masthead. That’s reflected in the latest  author style guide,  dated June 30, which also confirms that the change was very recent indeed.

It’s also noteworthy that the editorial board is down to only six members.

• Jerome H. Friedman, Stanford University
• Michael Friendly, York University
• Genshiro Kitagawa, Institute of Statistical Mathematics
• Carlo N. Lauro University of Naples “Federico II”
• Jae C. Lee, Korea University
• James L. Rosenberger, Pennsylvania State University

Back in 2010, there were almost double that number, but five have left in the last year or so. They include:

• Jianqing Fan (Princeton University)
• Xiao-Li Meng (Harvard University)
• Luke Tierney (University of Iowa)
• D. Michael Titterington (University of Glasgow)
• Antony Unwin (University of Augsburg)

WIREs Comp Stat, like all the WIREs journals, was conceived from the start as a “serial encyclopedia”. But as far as I know,  only the  Encyclopedia of Computational Statistics was also slated for release as an actual hard-cover encyclopedia, with a planned publication date of July 13, 2012 – today!

The Amazon U.K. website still shows the July 2012 publication date, but there is no indication as to when it will actually be released. (Google Books goes one better, happily showing a publication date of October 2010). Nevertheless, Amazon still has  the original description.

The Encyclopedia of Computational Statistics (EoCS) draws together material normally identified under the rubric of computational statistics. This includes material drawn from computationally intensive statistical methods such as bootstrapping; data visualization; machine intelligence; density estimation; data mining; pattern recognition; clustering and classification; and computational Bayesian methods such as Markov chain Monte Carlo. …

And Amazon UK is still taking orders, as they have for more than a year, although at £1,108.65 a pop (more than US $ 1700), one wonders how many pre-orders there could possibly be.

Wiley’s placeholder cover

In contrast, the Wiley.com page for the Encyclopedia of Computational Statistics has no release date or description whatsoever but merely notes: “This product is not currently available for purchase from this website”. I can’t even find the front cover anywhere (although Wiley does show the compelling graphic at right).

Not all parts of the Wiley empire have gotten the memo though. Wiley’s Iranian subsidiary, like Amazon UK and other booksellers, still has a release date of July 2012 and the original description.

… AND CHANGES AT GMU

Meanwhile, interesting changes are also afoot at George Mason University. It seems that barely over a week ago, Yasmin Said disappeared completely from the GMU online ‘People Finder” directory, as well as the full GMU directory. Her erstwhile post as Research Assistant Professor in GMU’s School of  Physics, Astronomy and Computational Sciences could be seen in the Google cache from June (but even that is gone now).

Wegman and Said had ended up in SPACS after last year’s merger of their former “home” department of  Computational and Data Sciences. Said’s departure also leaves the Wegman-led research unit Center for Computational Data Sciences (confusing, I know) down to Wegman  and six other professors (each of whom also has a primary “home” posting).

And, unlike last year, this year’s directory listing shows that the Center no longer even has an online presence; indeed, there is little evidence of much recent activity there on the entire GMU website. All this is in contrast with the heady days of 1997, when the Center had no less than 20 GMU “regular” research faculty, as well as eight “corresponding” research faculty from other institutions, such as Wegman Report co-author David Scott and Wegman Report “reviewer” Enders Robinson. Unlike the global surface temperature record, the Center for Computational Data Sciences has clearly seen a severe decline in the last fifteen years.

In fact, not only has the Center gone dark, at least on the web, but the erstwhile GMU statistics “Galaxy” server itself has  disappeared. Only a year ago, it was billed as the server for “Statistics at George Mason University”. It hosted not only the Center (albeit with badly of date information), but served as a portal to all statistics-related departments at GMU, as well as linking to professional organizations and conferences.

But as of the beginning of this month, the Galaxy front page just had a list of four courses (mostly associated with Wegman in the past), before finally going dark a few days ago.

DEVELOPMENTS AT THE INTERFACE SYMPOSIUM

And that brings us to yet another significant change involving Wegman and Said.

The Interface Symposium on statistical computing dates back to 1967, and George Mason University (and Wegman in particular) have played a leading role since its reorganization as the expanded Interface Foundation in 1988. That involvement included hosting the Interface website at GMU.  So when the GMU Galaxy server went offline, the Interface Symposia website went down too. Fortunately, we can trace its  much of its recent developments via Google cache and Archive.org.

Over the years, Wegman was a constant presence at Interface and many of his former students participated in various ways (a detailed chronology can be found in Appendix A.6.2 at p. 75 in John Mashey’s magnum opus, Strange Scholarship in the Wegman Report) .

That culminated in the 2010 Seattle conference where Wegman and Said served as co-chairs. Two Said-organized sessions on climate science and policy saw participation from contrarians Fred Singer, Don Easterbrook, Jeff Keuter (of the Marshall Institute) and Said herself holding forth on Climategate. Mark Berliner of Ohio State provided the sole “balance” from the mainstream.

As I noted at the time, this travesty was financially suppported by the computing and graphics sections of the American Statistical Association, as well as the National Institute of Statistical Sciences.

[O]ne of the conference co-chairs, Yasmin Said, accused climate scientists of “the willingness” to “bend the peer review process” and “destroy data”. And one of the invited presenters, Don Easterbrook, goes further and accuses climate scientists of outright scientific fraud …

How can the ASA allow itself to be associated with, let alone give financial grant support to, such a symposium?

Well, perhaps in the end, the ASA couldn’t, although Wegman and Said did return to co-chair the 2011 edition held at the SAS campus in Cary, NC.

In any event, the 2012 edition of Interface was notable for the complete absence of Wegman for the first time in many years; nor was there anyone else from George Mason University. As he did at WIRES Comp Stat, David Scott was there to pick up the pieces, co-chairing a fine program committee, and hosting the conference at Rice University. By all appearances, the  result was a compelling event with the theme of Future of Statistical Computing: Internet Scale Data, Flexible Modeling, and Visualization.

AN EVOLVING STORY

To be sure, one can only speculate as to the full context and significance of  Wegman and Said’s departure from Wiley, Said’s exit from GMU, and all the other changes. That will likely remain the case even when those organizations finally respond publicly to these developments. Nevertheless, it does seem that there are starting to be consequences for Wegman and Said, whether Wiley and GMU care to admit it or not.  And perhaps the coverup attempts will also start to unravel.

Still, the impact of Wegman and Said’s efforts on the politicization of climate science has yet to be addressed.And here, once again, Wegman’s longtime collaborator David Scott has a responsibility to step up once and for all.

True, Scott may well have had nothing to do with the unacceptable scholarship in the background sections of the Wegman Report, or the manifestly biased and deeply flawed analysis at its core. But that is all the more reason for him to finally do the right thing and remove his name from the report.

This story is far from over and I’ll await developments along with everyone else. Meanwhile, I’ll also be focusing future efforts on revisiting Wegman and Said’s benighted analysis of paleoclimatology and the McIntyre-McKitrick “hockey stick” critique, beginning with the ever-shifting and confused definitions of “red noise” within the Wegman Report. Stay tuned.