The Wettest Drought in History

One of my responsibilities as a teenager was to keep the lawn under control. Flymos had presumably not yet been invented, and petrol-driven mowers were perhaps too much hassle, so ours was manual. If the grass got too long it was hard work and it could even become necessary to resort to shears, which was back-breaking work. But mowing was also difficult if the grass was damp. There was therefore a trade-off each spring. The first mow had to be done when it was mild enough for the grass to be reasonably dry, but couldn’t be put off until it was too long. And as the grass grew it dried out more slowly each day. So it was essential to make use of any opportunity to mow in case the weather turned wet again. It probably only happened once or twice, but it seems I was always caught out. I’d wait for one more dry day to make the job easier, but the skies would open and a week later the job would be twice as difficult.

Nowadays the internet and improved forecasting allows me to monitor the weather far more effectively. Thus it was I’d already been out with the mower in March, and, seeing the long-range forecast, made sure I got a mow in just before it started raining early in April.

The point is that the 5-10 day forecast is now fairly reliable.

Why, then, was the UK drought – declared in a few regions in March, with hosepipe bans from 5th April – officially extended in mid April?

Yes, that’d be in the middle of the wettest April on record!

We’re now in the farcical situation of the “wettest drought in history”, with a succession of “experts” (and junior ministers) popping up on TV claiming the rain in April somehow doesn’t count. Apparently it’ll run off compacted ground. Yes, maybe for the first day or two, but not after a month. With the wettest April on record followed by significant rain already in May, and more forecast in a day or two, the drought risk is simply receding. We’re in one of those surreal situations where reasons are being invented not to contradict previous claims, in this case that the drought would last into next year.

What baffles me is why the drought was extended when wet weather was forecast. Surely – since most of the time it’s dry – the drought risk is receding as long as there’s significant rain in the forecast. And, as the 5-10 day forecast is fairly reliable and everything after that isn’t, you simply run the risk of looking stupid if you don’t wait until the forecast is for dry weather.

I wonder whether there’s a tendency to believe long-term forecasts more than short-term ones. But long-term forecasts only indicate a small bias one way or another, as Met Office modelling indicates:

“New three-month forecasts by the Met office suggest little respite with April, May and June expected to be drier than average. ‘With this forecast, the water resources situation in southern, eastern and central England is likely to deteriorate further during the period. The probability that UK precipitation for April-May-June will fall into the driest of our five categories is 20-25% while the probability that it will fall into the wettest of our five categories is 10-15%, it says.’ ” [my emphasis]

So 20-25% dry plays 10-15% wet plays (presumably) 60-70% around average. Not sure I’d have put a lot of money on the “expectation” of a dry spring this year (certainly wouldn’t now!). Even less after I’d looked at the Met Office report (scroll down to find PDFs) because the model runs are all over the place.

And are these “probabilities”, anyway? Isn’t the modelling signal swamped by the noise of uncertainty? It seems to me likelihoods based on model-runs are not the same as probabilities in the real world.

I’d say the Met Office and the media (the quote marks indicate the introductory sentence was written by the Guardian’s John Vidal) need to mind their language. How about “slightly more likely than not to be” rather than “expected to be”? And perhaps “indication” rather than “forecast”? And “x% of model runs gave…” rather than “the probability that…”? And definitely “might” rather than “is likely to”!

On Misplaced Certainty and Misunderstood Uncertainty

I know the climate scientists know they’re right, but a little care is called for. It’s important not to play fast and loose with the figures – especially when criticising someone else for playing fast and loose with the figures!

In a post entitled Getting things right, Realclimate yesterday addressed a piece of rogue science conducted apparently in-house by an NGO. Gavin Schmidt wrote:

The erroneous claim in the study was that the temperature anomaly in 2020 would be 2.4ºC above pre-industrial. This is obviously very different from the IPCC projections… which show trends of about 0.2ºC/decade, and temperatures at 2020 of around 1-1.4ºC above pre-industrial.

But the chance of “temperatures at 2020″ being 1.4ºC above pre-industrial seems to me pretty remote – certainly less than 2.5%, if Gavin is quoting within 2 sigma confidence limits, as is customary.

You’d think in a blog post titled “Getting things right” that it was pretty important to get things right…

So I posted a comment and was pleased to see not one, but two replies:

Now I’m confused. I understand we are currently about 0.8ºC above pre-industrial. A mean global surface temperature 1.4ºC above by 2020 implies a 0.6ºC rise over the next decade.

[Response: The range is just eyeballing the IPCC figure for the year 2020 - so there is some component of internal variability in there as well. - gavin]

[Response: GISS temperature of 2010 (which happens to be right on the long-term trend) is 0.9 ºC above the mean 1880-1920 (and the latter is probably a bit higher than "preindustrial"). -stefan]

OK, let’s take 0.9ºC, though that’s not a figure you often hear.

The IPCC graphic Gavin is referring to when he says “projections” is one I’ve never really liked:

It’s all a bit too imprecise and pretty for my liking. For example, the yellow line (constant GHG levels from 2000) diverges from the other scenarios almost immediately, even though natural variation would initially overwhelm differences between emission trajectories.

It does rather look, though, as if at least one of the scenarios could, according to the models, lead to warming of 1.4ºC above the pre-industrial level. Could this be because emissions in the scenario are much higher than we’re actually experiencing? No, Gavin notes that:

* Current CO2 is 390 ppm
* Growth in CO2 is around 2 ppm/yr, and so by 2020 there will be ~410 ppm
So far so good. The different IPCC scenarios give a range of 412-420 ppm.

The difference between 420ppm and 410ppm would only lead to a 0.1ºC extra rise in temperature over the very long term and even then the climate sensitivity (the eventual temperature increase for every doubling of the atmospheric CO2 level) would have to be on the high side – around 4ºC.

No, the problem is that the temperature hasn’t risen fast enough to 2010 for the more extreme modelling predictions in the IPCC figure for 2020 to be sufficiently likely any more. The IPCC graphic is out of date, plain and simple.

It’s a bit puzzling to be honest why Gavin used the IPCC graphic, because another Realclimate post today has trend-lines suggesting a much more accurate estimate of the likely global mean surface temperature at 2020 – around 0.2ºC higher than at present or around 1.1ºC above the pre-industrial level (as Stefan noted, 2010 is roughly on trend).

But how confident are we in this estimate? What is the range Gavin should have quoted?

Well, here’s the point: you can’t just express uncertainty by running a few models with slightly different starting conditions (the “Monte Carlo” approach) and discarding 2.5% at each extreme of the resulting distribution.

No, we have to actually think about what we’re doing.

It rather seems to me there are different kinds of uncertainty that we might want to consider when trying to predict the temperature “at 2020″.

What are the types of uncertainty we might need to take into account?

Parameter uncertainty
These are our “known unknowns”. In this case, we don’t actually know that the trend is 0.18 or 0.19ºC per decade as discussed at Realclimate. It looks like it is, but this could change when we get a bit more data – maybe we’ll find over a longer timescale that the real figure is 0.16 or 0.21ºC per decade. This makes us less certain about temperatures further out – at 2030 or 2050, say – than at 2020.

But a relatively short time into the future, parameter uncertainty is dominated by:

Calculable statistical uncertainty
Measurements of mean surface temperature show some variability about the underlying trend, as can be seen from the graphs in the Realclimate post discussing the data for 2010.

But the most any year has varied above the trend-line is about 0.2ºC in the case of 1998, which remains one of the 3 warmest years on record (with 2005 and 2010) due to the super El Nino that year. Maybe Gavin is implicitly including the possibility that there will be another strong El Nino in 2020. But that would only get us to a 1.3ºC total temperature increase (1.1ºC for the trend plus 0.2ºC for the El Nino), not 1.4ºC.

Statistical distribution uncertainty
It’s just conceivable Gavin calculated the Standard Deviation (SD) of annual temperature deviations from the trend and found it to be 0.15ºC or more so that 2 SDs includes 1.4ºC, so even if the long-term increase in temperature around 2020 is our 1.1ºC, there may still be a greater than 2.5% chance that the temperature in that one particular year is 1.4ºC or above. The only trouble is, with a mean of 1.1ºC and SD of 0.15ºC there would be an equal probability of 2020 being much colder than usual, so Gavin would have had to give a range of 0.8-1.4ºC.

Ah, but maybe Gavin expects the distribution to be skewed, so that freakishly hot years are more likely than freakishly cold ones…

The point is we don’t actually know a priori what the distribution of probabilities (often called the Probability Density – or sometimes Distribution – Function, or PDF, if that isn’t too confusing!) for the annual mean temperature of a given year actually looks like. We need a theory to tell us that – and the PDF could be complex, not a nice normal, lognormal or power curve at all.

Damn, we already have three sources of uncertainty compounding our estimate of the 2020 temperature!

It can’t get trickier than this can it?

Execution uncertainty
Yes it can.

Global temperatures are depressed following volcanic eruptions. It’s almost as if these are being ignored and that global warming projections include the implicit qualifier: “unless there’s a major volcanic eruption”. These are frequent enough for them to be included in our “2 sigma” (central 95%) range: volcanoes in 1963 (Mount Agung), 1982 (El Chichon) and 1991 (Pinatubo) depressed global temperatures by up to 0.3ºC. Despite a long-term warming trend, the temperature “at 2020″ could easily be knocked back to 2010 levels, that is, 0.9ºC above pre-industrial, or below.

I don’t want anyone coming back and saying I predicted 2020 to be warmer than 2010 and it wasn’t. Sure, I could say “the theory was right, there was just that damn eruption”. But really we need to include the possibility of volcanic activity if we’re going to make a serious forecast.

I’m beginning to think 1-1.4ºC above pre-industrial might not be that good a prediction for 2020. It seems a volcanic eruption could push us further below our central forecast of 1.1ºC than a strong El Nino could lift us above. I suspect 2 sigma confidence limits are more like 0.8-1.3ºC, with the proviso that a really serious volcanic event could leave us even cooler, without the possibility of a corresponding extreme warming event.

The point, of course, is that uncertainty in a complex system, such as the climate or the economy isn’t likely to be a simple mathematical relationship. We need to explore the theory itself. We need qualitative as well as quantitative understanding.

Unknown unknowns
So far our 2020 temperature predictions have assumed we’re certain about our theory.

But maybe we’re not as smart as we think we are.

This is where it gets really difficult. Nevertheless, we should really have a look at any developments that are bubbling up. For example, Realclimate itself has discussed modelling that suggests there could be natural cycles that affect the temperature over timescales of decades. Personally, I think there could be something in this.

Again, the risks, according to the researchers, are to the temperature downside over the next decade. How sure are we that the groups looking at these patterns of variability are wrong? Not more than 95%, surely?

Let’s make one final allowance. Let’s take account of this unknown unknown and predict that the mean global temperature at 2020 will in fact be in the range 0.7-1.3ºC above the pre-industrial level, with a central prediction of a 1.1ºC rise. That is, it will be from 0.2ºC cooler than 2010 to 0.4ºC warmer, with a median expectation in the PDF of a 0.2ºC rise, so a skewed distribution. Think of the 0.2ºC drop as maybe some cyclical cooling cancelling out some of the warming trend plus a bit of volcanic action; the 0.4ºC warming would perhaps arise with a continuation of the current trend plus a big El Nino.

This is the point I want to make: the PDF is in large part a judgement, based on understanding (so there’s plenty of people who could make a better stab at it than me). Number-crunching on its own will never do the job.

I agree with the guys at Realclimate, though: it’s important to get things right!

On Hulme on Science

This post is an addendum to my previous musings on Mike Hulme’s Why We Disagree About Climate Change. In particular I want to respond to Paul Hayne’s comment that:

“Mike Hulme’s argument is not relativist. He is arguing that there really is no argument that can leverage action, which seems pretty true.”

OK, I suppose – after re-reading Chapter 3 of Why We Disagree – my claim did go a bit far. However, I’m not sure I want to concede the point fully.

First, I’m not the only one who’s confused. What was uppermost in my mind I think were the comments about Why We Disagree made by Peter Kircher in Science (pdf), to which Hulme refers on his website, as detailed in my original post.

I concur with Kircher’s view that “Hulme’s book invites misreading” and his disquiet over Hulme’s infamous passage (p.80-2) discussing how science “must concede some ground to other ways of knowing.” There is, though, a way in which this makes sense, which Hulme doesn’t identify and which doesn’t in any way undermine science.

Second, any critique of science must always address the fundamental precept that science is about testing theories against reality. It either describes the world or it doesn’t. There’s no room for compromise with “other ways of knowing”.

There’s one little fly in the ointment, though, which is very apparent in the social sciences. Concepts are not always easy to define. What is “poverty”, for example? Before you can study “poverty” you have to get out there and translate what people mean by “poverty” into something or things that you can actually measure.

Hulme refers to “local tacit knowledge”, which he patronisingly suggests is “not conventionally classified as scientific knowledge”. He muddles strategies for coping with climate conditions with describing “environmental change” and weather-forecasting, but certainly some of what he’s driving at very much is scientific knowledge – climate science relies on interpretations of subjective historic anecdotal evidence in diaries, ships’ logs and so on.

The issue is merely about communication between scientists and those affected. In the case of climate change, science may need to translate its scientific predictions – expressed in terms of directly measurable parameters – into language that relates to people’s day to day experiences. But those experiences are not “other ways of knowing”.

Let’s take the example of “severe winter weather” in the UK, since “here’s one I prepared earlier”! As I explored recently – there is no direct correlation between measurable parameters and the common perception of, in this case, what constitutes a “cold winter”. No-one writes books about, say, February 1986, which was exceptionally cold, whereas (slightly) milder conditions with more snow, such as the Winter of Discontent (1978-9) and perhaps December 2010, linger much longer in the collective memory.

Science could, in principle, develop a “severe winter” index which included temperature extremes, averages, snowfall, lying snow days and so on. Trouble is, different people would want to constitute the index differently. Hence we all have to refer to the same variables if we want to make comparisons. This is what science is. It doesn’t stop us all making our subjective judgements, though.

So, there’s an inescapable conclusion: we have to agree on a framework, on what we can measure in order to make objective comparisons.

And this is the real weakness of Hulme’s work. In terms of both the science and making decisions on emission trajectories, we need a quantitative framework. Or we simply can’t reach any sort of agreement. It’s all very well to note that people have different values, but we can’t conceivably ever agree what is an acceptable level of climate change based on religious and political views. It is irrelevant on one level that the media distort the debate as Hulme goes on to discuss in Chapter 7, The Communication of Risk. This doesn’t alter the consequences of different courses of action and therefore the optimum path by one iota.

It might also be worth noting, en passant, that it is in fact historically somewhat unusual for public opinion to greatly matter in decision-making. The reason the media has influence is a result of our current political system. At most other times in history a ruler, or elite would simply make the decision. The long-term interest of society as a whole was the responsibility of a small group and not something actively contested between different interests. Maybe, as a civilisation, we need ways of making a clearer distinction between the general interest and the individual and sectional interests that drive our political processes. Tricky stuff!

Nevertheless, just as we can only meaningfully discuss and quantify the physical phenomena of climate change within the agreed framework that we call science we can only decide on a course of action in response to global warming by agreeing a framework that permits quantification.

And that framework is called economics.

Managing Climate Expectations

It’s rather worrying, when you think about it, that the Himalayan glaciers may be completely gone by 2350, according to the IPCC. The only trouble is, nobody cares, because they erroneously claimed they’d be gone by 2035.

I’m becoming more and more concerned by the tendency of climate change cheerleaders to try to find worse and worse evidence of climate change. Consider a couple of recent posts at Realclimate.

First we have  Recent trends in CO2 emissions. The lead author is Corinne le Quéré who is an oceanographer, not an economist.

The argument is over the extent to which actual carbon emissions have exceeded the IPCC emission scenarios – the authors of the post seem to be keen to emphasise the overshoot. But these scenarios are purely designed to illustrate how atmospheric CO2 and other GHG levels might increase over the rest of the century and therefore how much warming might occur, if corrective action isn’t taken. They are guesstimates, with no basis in science, social or otherwise.

My personal opinion is that the scenarios have outlived their useful life, since the key determinant of future emissions will be the effectiveness of corrective action, not whether future economic growth is “fossil fuel intensive” or whatever.

In 2008, as discussed in the post, the actual emissions were higher than nearly all the IPCC examples. But towards the end of 2008, remember, the global economy fell off a cliff. The economic growth and hence emission levels in 2008 were clearly unsustainable. The Realclimate post also notes – rather than emphasises – that projected emissions in 2009 exceed the bulk of the scenario projections by less than was the case for 2008. No further projections are given.

Clearly, we can only determine how close the scenarios are to reality over a long period, and especially by taking account of the business cycle.

Why we’re even discussing the fit between the IPCC scenarios and actual emissions in a given year is beyond me.

It seems to me there is a dangerous tendency on the part of advocates for action to mitigate climate change to promote data showing the situation is worse than expected. This is unwise. It polarises the debate even more. Scrupulous objectivity is essential.

The worst example of “worse than expected” syndrome is the reporting of Arctic sea-ice, as I highlighted on here some time ago (subsequent posts are linked via the comments).

A number of commentators, such as Joe Romm [see Note], report the state of the Arctic sea ice on an almost daily basis (the NSIDC provides daily data, which I see now show the ice extent is now greater than in 2007 – perhaps we should revise our whole opinion on global warming!).

When I first started investigating the possible natural cycle in the Arctic sea-ice back in February, I noted:

“If I were a climate specialist about to make a song and dance over a particular piece of evidence for GW, I think I’d make pretty sure the phenomenon in question hadn’t happened before.”

I’m currently trying to collate my thoughts on the AMO – blogging has its plus side, but it’s pants for organising information – and I’ve come across a few tidbits in the IPCC’s latest report (AR4).  Here’s what the Technical Summary has to say (section TS.3.1.2, p.37):

“The warming in the last 30 years is widespread over the globe, and is greatest at higher northern latitudes. The greatest warming has occurred in the NH winter (DJF) and spring (MAM).  Average arctic temperatures have been increasing at twice the rate of the rest of the world in the past 100 years. However, arctic temperatures are highly variable. A slightly longer arctic warming period, almost as warm as the present, was observed from 1925 to 1945, but its geographical distribution appears to have been different from the recent warming since its extent was not global.” [my italics]

As I said, notwithstanding the last desparate clause, which I don’t even recognise as a scientific statement (in my opinion the 1925-1945 warming was every bit as global), it’s happened before.

I know that even the Technical Summary of AR4 is not something you actually read, but you might expect commentators like Joe Romm to have browsed the thing.  Failing that, you’d have thought they’d at least look at the IPCC’s pictures.  Here’s one I haven’t posted on here before – check out the top panel in particular:

I say it again: claiming short-term changes in Arctic sea-ice extent “prove” GW is exceptionally foolish.  There may be a cycle – on top of the GW trend – which has overshot, which could mean a decade or more of sceptics saying the ice-melt – and hence GW – has “reversed”.  Hysterical climate change popularisers such as Joe Romm are becoming less part of the solution than part of the problem  (which reminds me that maybe I should try to get hold of Mike Hulme’s book, which I gather makes a similar point).

It should be a priority to understand (or debunk) the AMO cycle.  Which makes my attempts to raise awareness on the other Realclimate post I mentioned at the outset all the more frustrating.

————-

Note: I originally started writing this post weeks ago – I just discovered it amongst my drafts.  It was at the exact point where I’ve written “see Note” that I was distracted by the question of where the precise dividing line lies between nationalism and racism, as illustrated by the case of Joe Romm.  Since then I’ve been much amused that the search parameters used to find my blog have included “Joseph Romm asshole”!  I feel myself under no pressure to pull my punches in the rest of this post.

Cold FT

I wrote earlier, in relation to a story in today’s Guardian, that: “Solving the GW problem is difficult enough without the constant drip-feed of confusing reporting of the issue.” Even worse, though, is when influential media editors themselves appear to be confused by sceptics. A colleague has drawn my attention to a recent FT editorial and a subsequent letter by David Henderson, who, it turns out, is a campaigning sceptic.

On close inspection, the FT editorial is troubling. It appears to support sceptic attempts to undermine climate science.

The FT’s first point is that scientists “must be open about sharing the data that underlie their findings”. Fine, we’ve all long since been agreed on that. But data has not been systematically kept as secret as some would have you believe.

The FT goes on to say, though, that “scientists should devote more effort to observation”. Worryingly, the FT seems to believe there is some doubt about the veracity of the recent temperature record. This is simply not the case. There is some debate about whether it was as warm – globally, or, more likely, just regionally – several centuries ago, during the so-called Medieval Warming Period, as it has been over the last couple of decades. This question will not be resolved by gathering more data now, and in any case will become increasingly academic as the world warms over the coming decades.

The FT concludes by suggesting that “scientists should give weight to all the evidence, not just the consensus”. This is confused on two levels. Debates about “the evidence” – data – are matters of detail, and the IPCC already reports differing findings.

What the sceptics really want is for the IPCC to “give weight to” different interpretations of the data. But many possible causes of warming, for example variations in solar output, are already taken account of. They are incorporated into the energy balance model that informs mainstream climate science. As Lionel Messi reminds us mere mortals, there’s always scope for improvement, of course. The next IPCC report is likely to reflect, for example, the improved understanding gained over the past few years of how natural climate cycles affect the way the planet is warming.

What’s left are alternative paradigms such as the idea that variations in the solar wind could cause fluctuations in the flux of cosmic rays entering the Earth’s atmosphere which in turn could affect cloud cover and hence climate. At present this explanation seems a little contrived and there are serious gaps in understanding. Research may eventually determine an effect that should be included in climate models. To ask the IPCC to “give weight to” the cosmic ray theory as an alternative explanation, though, simply makes no sense. It would be like asking someone doing a jigsaw to make use of pieces that belong to a different puzzle. The only way the cosmic ray theory – or any other explanation of the data – would make sense is if it is coupled with proof that greenhouse gases will not have the warming effect predicted by the vast majority of climate scientists.

Most students of the history of science would not recognise modern climate science as in crisis. The theory remains entirely coherent, without having to invoke ad hoc means to “save the appearances”, unlike for example cosmology, which over the last few decades has had to invent dark matter, dark energy and the rapid inflation of the early universe.

The FT appears to share the general confusion following, not just “climategate”, but years of sceptic sniping and deliberately and unintentionally misleading reporting of the complex global warming issue.

Sceptics such as David Henderson are now taking advantage by dramatically exaggerating every potential flaw in the scientific process, like players on a losing football team feigning serious injury at the slightest provocation, in the hope that the referee will red card the opposition.

In fact, the way Henderson goes on in his letter you’d imagine all collective human endeavour is doomed to failure. How did we ever manage to organise ourselves to bring down a single woolly mammoth, let alone put a man on the Moon?

Ice Sickle

I continue to fret about the emphasis on the Arctic sea-ice extent as an indicator of global warming (GW).

I have to chop down (got to justify my blog entry title somehow!) a Guardian story, “Arctic sea ice still low despite winter recovery” (p.20 in today’s print edition), the online version titled incoherently “Arctic winter ice recovers slightly despite record year low, scientists say” and cryptically subtitled “Figures from the National Snow and Ice Data Centre [the NSIDC] indicate six or seven-year low over past three decades”. (They mean 2010 has had the 6th or 7th lowest maximum ice extent – which occurs in March – on record, i.e. of the last 32 years).

The story itself is garbled as well:

“Last night [NSIDC] released the data for the winter of 2009-10 showing the maximum extent reached on 31 March was 5.89m square miles (15.25m sq km). This was 250,000 square miles (650,000 sq km) below the 1979 to 2000 average for March…”

What the NSIDC actually said was that the average for March (15.10m km2 or 5.83m square miles – btw, wouldn’t it be simpler if we all standardised on km2?) was 250,000 square miles below the 1979-2000 March average. In fact, NSIDC’s news posting was titled “Cold snap causes late-season growth spurt” and noted that the maximum sea-ice extent occurred later than usual at the end of March, when the ice extent was only marginally below the 1979-2000 average for that date, as can be seen in the graph illustrating this BBC story about the launch of a satellite to monitor the situation.

I would have thought the real story was the recovery in the maximum Arctic sea ice extent compared to the last few years. “Arctic sea ice still low” is arguably a little misleading.

It is really not helpful to keep spinning Arctic sea ice shrinkage as an indicator of GW. There will be a vicious backlash should nature conspire to undermine the Arctic ice melt narrative. It will then become even more difficult to muster the political will to deal with GW.

The Guardian story goes on to note that:

“Last month, Japanese scientists reported in the journal Geophysical Research Letters that winds rather than climate change had been responsible for around one-third of the steep downward trend in sea ice extent in the region since 1979. The study did not question global warming is also melting ice in the Arctic, but it could raise doubts about high-profile claims that the region has passed a climate “tipping point” that could see ice loss sharply accelerate in coming years.”

Maybe this is what the researchers did actually say – I may have to go the library to check – but, as I pointed out before, it makes no sense to try to distinguish “winds” from “climate change”. Winds are not caused by some arbitrary external force, they are determined by differences in temperature, albedo (reflectivity), moisture content and so on between different areas of the planet. Winds are part of the climate system that is changing, so it is simply meaningless to separate the cause of ice melt into “winds” and “climate change”.

Solving the GW problem is difficult enough without the constant drip-feed of confusing reporting of the issue.

1740 And All That

The pain goes on.  The Met Office announced yesterday that they are giving up seasonal forecasts.  This is going to seem to most people – and I have to go along with the majority view on this – as if there’s something seriously wrong.  I don’t believe we’re dealing with butterflies’ wings here.  I simply don’t understand why it’s not possible to provide a broad brush indication of the weather in a coming winter or summer.  Presumably the right data is not available, and, from a cursory reading of the literature, what’s needed is a better picture of ocean temperatures at different depths.  I suggest that’s where resources must be focussed (and I gather plans are indeed afoot – codename Argo).  Because climate science needs to get out of the dog-house.

Managing the message

What we certainly don’t need is another PR disaster.

If Professor Latif’s prediction of a period of a decade or more of cooling either imminently or over the next decade or two is correct, then “we’ll have to eat crow” as one comment on a New Scientist article put it.  The expectation of what Latif terms “monotonic” – presumably meaning “steady” or “linear” – global warming has been set.

Furthermore, as I stressed before, the reliance on Arctic sea-ice as an indicator is unwise, to say the least.  The Guardian’s report of the Met Office’s latest assessment of the evidence gave prominence to the Arctic sea-ice graph yet again yesterday.

The Guardian also included a commentary by a Dr Chris Huntingford, the online title “How public trust in climate scientists can be restored” making a lot more sense than “We need to look beyond temperature” in the print version. Huntingford makes the point that:

“To preserve public confidence, we must ‘buy out’ the copyright from research journals of key papers so that these can be freely available to all for inspection. Datasets must also become more available for general scrutiny.”

Too right. I found myself this week in the British Library accessing a paper by Drs Phil Jones and Ken Briffa, yes that Phil Jones from the CRU at UAE, Dr Emailgate himself.

What I was interested in was what Jones and Briffa term the “Unusual climate in Northwest Europe during the period 1730 to 1745″. Before I report their findings, I’ll explain why I was interested in 1740 in the first place.

The 1740 Anomaly

In my last post I presented a graph of the Central England Temperature (CET) record from 1659 to 2009. I noted the cold winter of 1739-40 which occurred after the famously warm decade of the 1730s, with a run of winters as mild as anything that occurred before the globally warmed world of the last decade (though the 1920s is also comparable).

I wanted to see how anomalous 1739-40 was, so I replotted my graph with a longer running mean. In fact, I did several plots, but let’s consider the one with a 75-year running mean, which smooths out all but long-term temperature trends:

I then calculated the Standard Deviation (SD) of the winter 1739-40 temperature against the 75-year running mean. The 1739-40 winter was 3.14 SDs colder at -0.4C than the running mean (5.59C). A statistical table tells us that we should only expect such an anomalously cold winter about once every 1,100 years.  Yet a couple of centuries later 1962-3 came along and, although marginally milder, this was against a higher 75-year running mean, so was a once in nearly 5,000 years event.  It seems something non-random is going on.

Curiously, the 9-year running mean of winters from 1730-1 to 1738-9 was, at 4.81C, even more anomalous than the 1739-40 winter. It was 3.27 SDs warmer than the 75-year running mean centred on 1735 (3.58C). (Obviously, there is less deviation in 9-year means than of single year temperatures from the long-term mean so the SD is lower). If temperature fluctuations were random and normally distributed, you would only expect a run of 9 winters as mild as 1730-1 to 1738-9 about once in nearly 2,000 years.

So we had a once in 2,000 year series of mild winters followed by a once in 1,100 years cold winter. Curiouser and curiouser…

Curiousest, the annual deviation of the meteorological year Dec 1739 to Nov 1740 is even more significant (and the calendar year 1740 even more so!):

The annual mean temperature for 1740, at 6.93C was 3.72 SDs below the 75-year running mean of 9.21C. That is, a year as cold as 1740 would be expected to occur only once in 10,000 years!

The Jones and Briffa paper

Of course, winter 1740 has not escaped the attention of climate researchers.  It was a catastrophe for Ireland, as J&B note.  But J&B can only scratch their heads, noting in their Abstract that:

“Apart from evidence of a reduction in the number of explosive volcanic eruptions following the 1690s, it is difficult to explain the changes in terms of our knowledge of the possible factors that have influenced this region during the 19th and 20th centuries. The study, therefore, highlights how estimates of natural climatic variability in this region based on more recent data may not fully encompass the possible known range.”  [My stress]

Fascinating though their paper is, J&B merely describe the meteorological conditions that occurred around 1740.  The authors barely speculate on the underlying cause.

It turns out that winter 1739-40 was merely the second in a series of 6 winters when a strong high pressure developed over Scandinavia.  In several of these years this high extended far enough west to block the usual westerlies over the UK.  In the UK and Ireland, the period was generally dry as well as cold.

Lasting Effects of Cold Winters?

The dramatic winter of 1739-40 was just one in a series of 6 atypical winters.  This set me thinking.  We don’t have full instrumental records for 1740, but we do for less dramatic later examples, such as the cooling from around 1940, the start of another series of cold winters.  Here’s a hypothesis: could it be that the entire Northern Hemisphere (NH) could naturally gain heat (over and above underlying global warming) for a few years, which is then dispersed in cold years?

In a cold winter, compared to the normal circulation in the Arctic, air mixes with that from lower latitudes.  High pressure over continental land-masses (Canada, Greenland, Eurasia) pumps warm air further into the Arctic region than usual – Vancouver on the US west coast had a record mild winter for its Olympics this year – cools it and sends it south again – to northern China, the US East coast, and to the East of Greenland.  The Arctic this winter was 7C warmer than usual.

The net effect must be that more heat is radiated away than in a usual winter.   Maybe the climate modellers can calculate how much more.

One thing I can calculate reasonably easily, though, is one of the indirect effects.  I’m taken by the persistence of cold winters.  It follows that – as well as there being more of it – the snow will melt later in the spring.  My weather book (Barry & Chorley) reveals that the NH regions with 4 to 8 months snow cover extend over 10s of millions of square kilometers of NH land areas.  What if 10m km2 snow cover persists for just one extra week?  Besides taking extra energy to melt (which turns out to be relatively insignificant), such a surface would reflect around 50% of incident sunlight relative to a year when the snow cover melted earlier.  At the latitudes (between about 60N and 40N) we’re talking about, a rough, order of magnitude, estimate is that at least 100W/m2 extra energy could be reflected (or used just in melting the snow) for a week.  10m km2 is about 1/25th of the total NH surface, so the snow effect alone is of the order of a negative forcing of around 4W/m2 over the entire NH surface, that is, more than the additional forcing of greenhouse gases, but only for one week of the year.   But if my calculation is too conservative, and in fact it’s several weeks over 20m km2 then we could be talking about a serious feedback.  One cold winter might make it more likely that the next winter is also cold.

Triggers and Feedbacks

I suggested in my previous posts on the topic of the AMO (Atlantic Multi-decadal Oscillation) that the cycle is intrinsic to the system.

Indeed, cyclic behaviour is a feature of ice-sheets.  During the last ice age (and previous ones) there were a number of Heinrich events – discharges of ice-bergs from the Laurentide ice-sheet over Canada.  Brian Fagan in The Long Summer (p.47) gives this description:

“… the ice became thick enough to trap some of the earth’s heat, which thawed the base.  Mud, stones, and water resulting from the thaw allowed the ice to skate, as it were, across the underlying bedrock.  In a matter of a few centuries, Hudson Bay purged itself of the accumulated ice.  Eventually, the ice thinned enough for the cold surface layers to freeze again…  A Heinrich event, then, is a feed-back loop – a quick warming that causes its own end in a quick cooling.” [My stress]

I suggest a much quicker – decades rather than millennia – cycle could take place for Arctic sea-ice, with the common characteristic of “warming causing its own end”.

But it’s not quite as simple as that.

First, cooling events, such as volcanic eruptions which put a sunscreen into the stratosphere, or increased warming – fewer than normal eruptions, or increased greenhouse gas levels – will affect the wavelength of the cycle.  For example, cooling during a warming phase, when the Arctic ice is thinning, will extend the time until the cooling phase.

Second, there will come a point when the system is close to tipping and a sudden cooling event (warming events are more gradual) could trigger the transition from a warming to a cooling phase.

The paper by Jones and Briffa I discussed earlier mentioned an absence of volcanoes around 1740, but my textbook, Barry & Chorley, does include a graphic (Fig 2.11, p.21) showing an unidentified eruption in around 1739 (as well as a couple in the late 1720s and nothing else after 1700).  Perhaps an eruption triggered the 1739-1745 cooling phase.

Alternatively, the turn of the sunspot cycle – i.e. from increasing to decreasing insolation – might provide a trigger.  Barry & Chorley (Fig. 3.2, p.35) show a sunspot cycle peaking in around 1738.  Triggering by a combination of events is also possible, of course.

Once established, a cooling event will be self-sustaining as long as the cooling proceeds faster than underlying warming.  I suspect the thermostat is the Arctic sea-ice.  If warm North Atlantic water melts enough of it again the summer after a cold winter in Europe, then the conditions exist for another cold winter – more cooling is needed to restore equilibrium.  On the other hand, if the ice cover increases, this may be enough to tip the balance back.  Warm water will start to melt the ice from below, starting the cycle again.

I finish with a fairly ad hoc graphic, showing winter temperatures in the CET record against annual and summer temperatures (values adjusted so that the plots appear on the same graph):

Note the wide fluctuation in the difference between winter and summer temperatures (blue line) which, at 3C, exceeds that of annual, summer or (excepting the period before 1700) winter temperatures which have varied by only 2C.  When the difference is small (i.e. the winter is mild, shown by a larger value in the Figure), as in 1740 and especially the 1930s, and vice versa, this represents an imbalance that must correct itself.  As can be seen in the Figure, the difference at present is small, but the disequilibrium is not as great as in the 1930s.  On the other hand, global warming is expected to moderate winters more than it warms summers…

Because there are so many variables in the system, every cooling event will be different.  I wouldn’t rule out another cold winter next year, though!

———

9/3/10: Corrected serious typo (“even more anomalous than the 1739-40 winter” not “the 1939-40 winter”!)

Spin Snow, not Sea Ice: the AMO is Real!

How unfortunate. Back in 2000, yes, that’s not a typo, in 2000, the Independent wrote that:

“According to Dr David Viner, a senior research scientist at the climatic research unit (CRU) of the University of East Anglia, within a few years winter snowfall will become ‘a very rare and exciting event’.

‘Children just aren’t going to know what snow is,’ he said.”

In Viner’s defence, he did go on to say that rare snow events would cause chaos.

It’s No Joke

For a long time it’s seemed to me that one problem global warming (GW) is likely to throw up is that snow events, like other forms of precipitation, will become more extreme. That is, when it does snow, it’ll be heavier.

A commenter on one of my recent posts suggested I go and do some statistical analysis on temperature measurement data to see if trends are significant. In actual fact, about 5 years ago, I did exactly this with data on snowfall. If I recollect correctly, I found that there was a statistically significant trend in the number of heavy snow days (above a particular depth) in the middle of winter (i.e. not in months when, due to GW, some pf what would otherwise have been snow might fall as rain) in the data I found on the net for a particular Rocky Mountain ski resort. If I come across my notes I’ll bring the analysis up to date.

Here’s the real concern. A few decades down the line, the planet will be a lot warmer and we’ll be seeing much heavier precipitation in some regions. Some of this will be snow. Furthermore, there’s always the chance of a cold snap, for example, when a volcano goes off (and we really should be worrying more about this climate risk, IMHOP – more another time, maybe). Or after a geo-engineering accident (sorry, couldn’t resist). At the start of the cold event at least, the oceans will still be warm, because of stored cumulative GW heat, and they will therefore continue to pump moisture into the atmosphere. But the dust shroud will rapidly cool land areas, so that some places used to dealing with just heavier rain suddenly find themselves trying to cope with a foot or two of the white stuff.

It’s a shame climate scientists haven’t been warning people about the vulnerability of flat roofs to heavy snow.

Skating on Thin Ice

On the other hand, there’s been a worrying tendency over the last few years to treat the continually diminishing amount of Arctic sea ice each year (at the minimum extent in September) as a GW canary in the coal-mine, like glaciers.

It would have been better to stick to glaciers. Because changes in Arctic sea ice may well be part of a natural cycle. Of course, there’s an underlying warming trend tending to reduce the amount of Arctic sea ice. But if and when the natural cycle starts to dominate, sceptics will have another field day.

It’s worse than this. The cycle – which is called the Atlantic Multi-Decadal Oscillation, or AMO for short – could affect the temperature of the entire Northern Hemisphere (NH). [See previous post Musings of the Hemispheres - there may be similar processes in the SH, but I'm not going to discuss those just now].

Before I go on, there was a fuss a while back – serious stuff: letters to the Guardian editor, that kind of thing – when a Professor Latif was accused of explaining GW with AMO. His position, like mine, is that both GW and AMO affect the climate. I just want to make it clear that I’m with the Professor on this, even if simplistic sceptic brains find this position a logical contortion.

Evidence for the AMO (1): IPCC Data

Consider the following graph from the IPCC (AR4, the most recent report):

Global mean surface temperature relative to 1901-50, compared to climate models (IPCC Fig TS.23)

What gets me about the IPCC data is the anomaly around 1940. The average temperature was simply too high, and this is not adequately explained (if it was, I guess the models would be corrected).

We can drill down a little further:

Continental-scale breakdown of actual and modelled temperatures compared to 1901-50 (IPCC Fig TS.22)

Here we see that by and large the models represent land temperature fairly well, but that ocean temperatures were outside what are presumably intended to be some kind of confidence limits – for what looks like around an entire decade (just before mid-century).

This is not a very satisfactory state of affairs.

Note from Fig TS.22 above that the land temperature range over the past century has been around 1C, and that of the oceans perhaps 0.7C.

Consider what’s happened in the North Atlantic:

AMO from 1850-2005 (temperature relative to 1961-90 (IPCC Fig. 3.33)

The North Atlantic sea surface temperature (SST) (top graph) has increased by nearly 1C since its lowest point soon after the turn of the 20th century.

A 1C increase in ocean temperature is unsustainable. Land has a lower heat capacity (i.e. you have to put in less heat for a 1C temperature rise) than ocean, so must warm faster. The North Atlantic heat will have to dissipate.

Evidence for the AMO (2): The Historical Record

If I were a climate specialist about to make a song and dance over a particular piece of evidence for GW, I think I’d make pretty sure the phenomenon in question hadn’t happened before.

It just so happens that the area of Arctic sea ice has shrunk dramatically before, and not so long ago.

Yeap, you’ve guessed it, the Arctic warmed from around 1920 to 1940. Here’s the Abstract of a paper The early twentieth century warm period in the European Arctic that looks kosher – it must be, it costs $42! A site, www.arctic-warming.com seems to be devoted to the issue (particularly of warming around Spitsbergen in 1918-22) and cites some other papers discussing the 1920-40 episode, “one of the most spectacular climate events of the 20th century”. There’s even a book about the event.

None of these sites offer a clear explanation for the Arctic warming, so I’m going to have a bash.

Explaining the AMO

The point is that loss of Arctic sea ice – absence in summer and thinning year round – is not just a symptom of warming. It is part of a cyclic causal mechanism.

As I pointed out in a previous post, The Earth is a Fridge, the less sea ice there is at the start of winter (the Arctic ice extent is at a minimum around mid-September!), the more heat the Arctic waters can lose to the atmosphere and hence into space during the winter. Water covered by ice can’t lose heat because ice is an insulator, and the process of freezing is itself an important mechanism for losing heat.

Clearly the Arctic waters will lose most heat in winter when there is no summer ice. In a steadily warming world, you might expect first the summer ice to disappear, at which point the Arctic would have reached it’s maximum effectiveness in getting rid of heat (imported in currents from lower latitudes) and gradually the maximum extent of ice each year would reduce.

But there is an oscillation in the system.

Modelling the AMO

At first I was going to simply draw a curve on a piece of paper and scan it in, but my better half is a bit of an Excel whizz and persuaded me to do something a bit more sophisticated.

It was astonishingly easy.  Here’s the result, first without taking account of global warming (GW):

I can’t emphasise enough how easy it was to produce this graph. It’s hugely simplified, including as it does just two ocean masses and nothing else and making no attempt to distinguish between heat and temperature, and between temperatures at different times of year.  But I don’t see why it isn’t qualitatively valid – it produces the asynchronous sinusoidal temperature curves I’d deduced anyway, but with the added theoretical basis of generating them by heat exchange between the Arctic and the NA.  And since I’ve tied the temperature curves very roughly to historic data, the timescale of future temperature changes could conceivably be roughly correct.  The fact that what I wanted to show drops so easily out of the spreadsheet suggests some underlying veracity – I claim no more than that – at least to me.  End of disclaimer.

All I’ve done is calculate the temperature of the Arctic (purple line) in a given year as its temperature the previous year (times a cooling factor) plus the North Atlantic (NA) temperature the previous year times a factor (15% in this instance).  All I’m assuming is that the warmer the NA is, the warmer the Arctic will be.  After all, we know surface water flows from the NA to the Arctic.

So far, so simple.  The next bit is the critical point.

I’ve calculated the temperature of the NA (green line) similarly, but included a negative feedback.  In the model, the NA temperature is equal to its temperature the previous year (times a cooling factor) minus the Arctic temperature the previous year times a factor (6% in this instance, less than the 15% for the reverse case because the NA is bigger than the Arctic).

The minus in this calculation says that the warmer the Arctic is, the more NA heat it can absorb and disperse ultimately into space.    Remember, my argument is that the thinner and less extensive the Arctic ice, i.e. the warmer it is on average over the year, and in particular at the start of winter, the more NA heat it can disperse over the year, but in particular in winter.  [A more complex model could try to model the Arctic temperature at different times of year].

Obviously I’ve adjusted the numbers and starting conditions to fit the graph roughly to the historical record.  (The anomaly on the vertical axis is arbitrary, 0 is intended to be the long-term equilibrium – if you start with 0 for both anomalies, the graph is flat).

As well as the Arctic and NA temperatures I’ve included in my schematic an indication of the Northern Hemisphere (NH) temperature, produced by simply adding the NA and Arctic values (yellow line).  This shows a peak in 1940, which is what we’re trying to explain, as well as a peak around 2005 and, as predicted by Professor Latif, subsequent cooling for quite some time.

The good news is that we won’t have to wait too long to find out whether the AMO is real.  The bad news is, that, if it is, it’ll be like putting rocket fuel in the sceptic bandwagon.

I thought I’d go a little further and see if my model predicts anything else.  I’ve therefore included an “Arctic Oscillation” (AO) (blue line) which I’ve calculated by subtracting the NA temperature from the Arctic temperature.  The AO – represented by real-world indicators such as the North Atlantic Oscillation (NAO) and the Northern Annular Mode (NAM) – is an atmospheric phenomenon which correlates with the nature of NH winters.  My logic is that the higher the temperature of the Arctic compared to the NA, the lower the air pressure will be over the Arctic in comparison with the NA, which is in principle what the NAO and NAM measure.

Anyway, here, again from the IPCC, is the actual historical record of the NAO/NAM:

NAO/NAM indices (IPCC Fig 3.31)

Compare these real-world measurements with my model which (blue line) predicted a positive AO from 1900 to the 1930s and again from the 1960s to around 2000.  Could they possibly fit together?

Future temperatures, Global Dimming and Global Warming

I have to say I’m rather alarmed that, based on the timescales of the historic 20th century AMO cycle, my model shows temperatures falling for another 15 years.  I thought I’d better factor in a bit of global warming, so I played around in Excel a bit more:

This time I’ve allowed for GW by adding an arithmetically progressively larger term into the NA and Arctic temperatures each year.  As in the previous figure, the vertical anomaly scale is entirely arbitrary and not intended to map to real temperature deviations.

I’ve also extended the model to 2050 and calculated the NH temperature (yellow line) by adding the NA temperature (green line) to a halved, rather than the whole, Arctic temperature (purple line), since the NA is bigger than the Arctic.  Clearly the temperature cycles still exist, it’s just that the AMO is imposed on an underlying trend, so both peaks and troughs in the temperature curves are higher.

In this very rough calculation, we still see NH temperatures declining for a couple of decades.  Worrying.

I should add that the usual explanation for the cooling period from around 1940 to 1970 is “global dimming”, i.e. the blocking of sunlight by industrial pollution.   The AMO hypothesis suggests that at least some of this cooling was caused by a natural cycle.

Next Steps

A perfect computer model would accurately represent sea ice melting and freezing and the resultant exchanges of heat between the sea and the atmosphere and effect on oceanic circulation.  It would therefore predict long-term natural climate variability such as may – and I stress “may” – be caused by the AMO.

Current climate models do not correctly retrodict (i.e. predict known data) the warming up to 1940 and they have under-estimated the Arctic warming that has occurred over the last decade or so.

It seems to me that – prior to the IPCC’s next report on the science, AR5 – serious effort needs to be made to evaluate the evidence and theoretical basis for an AMO, and take account of it in projections of the future climate.

I used to be highly sceptical of long-term natural climate variability, but now I’ve realised there could be feedbacks between Arctic ice-melt and NA temperatures, I’m suddenly convinced.  I’d like to see some serious modelling of the AMO and similar decadal variability that logically should also occur in the SH.

Maybe the effect of GW will be to completely swamp the natural AMO.  But I’d like to see proof of that.

A failure to explain the AMO would lead to increased climate scepticism and a loss of political will to deal with GW.  We could be left totally unprepared for a steep rise in temperatures starting in a decade or two’s time.

The Telegraph’s Sensibly But Mysteriously Changed Climategate Story

Now I am confused. Just by chance I noticed just now that a link in my post a couple of days ago is now broken.

I quoted the Telegraph as saying:

“In an interview for the BBC’s website, Professor Jones also conceded that global temperatures may have been higher during the medieval warm period [MWP] than they are now – suggesting that climate change may not be caused by human activity.

He admitted that there has been no ’statistically significant’ global warming since 1995, but said this was a blip in a general trend of rising temperatures.” [My abbreviation]

in a story at:

http://www.telegraph.co.uk/earth/environment/globalwarming/7236406/Climategate-academic-Professor-Phil-Jones-admits-he-lost-track-of-vital-data.html

Clicking this link now results in the dreaded 404 page not found.

A bit of Googling, though, does find a story at:

http://www.telegraph.co.uk/earth/environment/7232733/Climategate-scientist-says-data-disorganised.html

“He said he stood by the view that recent climate warming was most likely predominantly man-made.

But he agreed that two periods in recent times had experienced similar warming. He also said that the debate had not been settled over whether the Medieval Warm Period was warmer than the current period.

The statements are likely to be welcomed by people sceptical of man-made climate change who have felt insulted to be labelled by government ministers as flat-earthers and deniers.”

“Insulted” now, are we? Diddums.

The change to the Telegraph story, if that’s what it is, is welcome, I suppose. Trouble is, the second story claims it was published online at 9:15am on Sunday 14th Feb which, if true, implies an impossible timeline. Since I was blogging on Monday 15th, it’s possible that one story has been deleted – maybe retracted – leaving another covering much the same material. (Or maybe they kept the time of the original story. Who knows? Who knows anything? /sigh). Anyway, I do wonder exactly what hundreds of thousands read over their Valentine’s Day breakfast in the print edition. If the story I found originally did appear in print, I wonder if the Telegraph has published a retraction. Maybe I’ll try to find out!

Harrabin’s Hamfisted Interview

In a post earlier this week, I traced back from an Express headline to a BBC Q&A with Professor Phil Jones. In fact, I only changed my title at the last minute when I realised the interview, and not just Express misreporting, was a large part of the problem.

The UK sceptic-fuelled media storm is reverberating around the world, for example at Realclimate. My comment is #50, here, but after writing it I started to wonder where Harrabin’s questions had come from. At some point, I noticed Harry Hodge’s comment #53 on the Realclimate Whatevergate (Lol) piece:

“Roger Harrabin’s (BBC’s environment correspondent) reputation is undergoing a sea change. He has moved from someone perceived as being an unimpeachable source of expert analysis to someone running around trying to defend his reputation and restating the way he will report in the future (because of the power of the blogosphere). He is in contact with the sceptic blogs and, it would appear, putting their questions to Phil Jones.” [my stress]

Too right he is. Focussing on Harrabin’s interview rather than the subsequent misleading Express reporting, we notice that the introductory paragraph – which I previously blipped over – says that:

“The BBC’s environment analyst Roger Harrabin put questions to Professor Jones, including several gathered from climate sceptics.” [my stress again]

I think I’ve already covered adequately the ridiculous question about the definition of the word “unprecedented”.

“There is a debate over whether the Medieval Warm Period (MWP) was global or not. If it were to be conclusively shown that it was a global phenomenon, would you accept that this would undermine the premise that mean surface atmospheric temperatures during the latter part of the 20th Century were unprecedented?”

Laughable.

But what’s really nagging at me is the question:

“Do you agree that from 1995 to the present there has been no statistically-significant global warming[?]“

As Jones pointed out, the warming since 1995 is not quite statistically significant, because it’s such a short period.

So why ask about the warming since 1995?

Why not ask about the warming since 1994, or 1990 or any other earlier year, which would probably pass the 95% level conventionally used to indicate statistical significance?

I can think of no other reason than to draw an answer like: “No, there’s been no significant warming since 1995″.

It might also be pertinent to point out that 1995 was quite a warm year (see the graphs in my post when the 2009 data appeared a while back).

I presume that during the forthcoming General Election campaign politicians will be allowed to send questions for their opponents to the BBC: “When did you stop beating your wife?”; “Are you over your drink problem now?”.

I’m about to register a complaint with the BBC about Harrabin’s interview and ask precisely who provided each question asked. I’ll let you know what they say.