Much alarmist ado about AMOC and the subpolar gyre collapsing

Tallbloke's Talkshop

There seems to be a buzz in the alarmosphere about the gulf stream stopping because emissions. I must admit I don’t have much time to spare at the moment for dealing with the ramped up rhetoric about ‘man made climate change’, but I spotted a typical tweet from Professor Ray Wills which I thought was worth a quick reply.

This is of course, nonsense.

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Climate Change by Numbers – Response Pt.2

Onto the last of the last of the guest presenters, David Spiegelhalter, who helps people like the NHS predict the future. I trust he is better at that than he is at assessing the past! 1 trillion tonnes of carbon he informs us, is our budget beyond which we can expect ‘dangerous’ climate change (2C rise above pre-industrial levels). We’ve already burnt around a half a trillion tonnes since the beginning of the Industrial Revolution and “that’s given us almost a degree of warming”, says Spiegelhalter. So what he is saying in effect is that Hannah’s 0.85 degree temperature rise since 1880 is all down to the burning of fossil fuels. Even the IPCC does not go this far. They say:

“Greenhouse gases contributed a global mean surface warming likely to be between 0.5°C and 1.3°C over the period 1951–2010, with the contributions from other anthropogenic forcings likely to be between –0.6°C and 0.1°C, from natural forcing likely to be between –0.1°C and 0.1°C, and from internal variability likely to be between –0.1°C and 0.1°C.

Together these assessed contributions are consistent with the observed warming of approximately 0.6°C over this period. [10.31, Figure 10.5]”

This ties in with the IPCC AR5 attribution statement:

“It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimate of the human-induced contribution to warming is similar to the observed warming over this period.”

Greenhouse gas concentrations in the atmosphere have only been measured really accurately at Mauna Loa since about 1960, when 310ppm was registered. Before that, scientists rely upon low resolution ice core data which appears to show a very gradual increase from a baseline of about 280-290ppm in 1880. It’s only during the 1950s that atmospheric CO2 concentrations really take off.

Note the very rapid 1910 to 1945 warming followed by the sharp cooling to 1950 – all when CO2 was not much above pre-industrial levels and increasing only very gradually. Therefore, we must conclude that natural variability was in charge prior to 1950, certainly with respect to major ups and downs. AGW purists might wish to claim that the general upward trend in temperatures since 1880 is also down to anthropogenic CO2 but then they would have to explain also the longer general upward trend in global temperatures since the end of the LIA, without resort to more plausible natural (solar) influences. In summary, it’s quite likely that the increase in global temperature from 1880 to 1950 can be mainly attributed to natural (internal and external) forcings. But the BBC’s Climate Change by Numbers would have its viewers think otherwise.

The so called Monte Carlo method of statistically predicting the most likely future outcome of anything from Formula 1 races to NHS medical policy/practice to CO2 induced climate change is a powerful mathematical tool involving multiple repetition of many different scenarios, Spiegelhalter tells us. I am sure it is – given the right data. The climate model runs cluster around a ‘most likely’ multi-model mean which suggests that we can expect to hit the 2C ‘dangerous’ threshold within the next 30 years or so if we burn all of that remaining 1/2 a trillion tonnes of carbon. What he neglects to mention of course is that the multi-model mean is way ahead of actual observed temperatures and in fact the vast majority of all of the climate models run significantly warmer than reality. Clearly, something is amiss with the models. The Monte Carlo method is faithfully predicting the most likely future outcome, but an outcome probably based upon incorrect assumptions/data about the real climate, about natural oceanic oscillations, cloud feedbacks, water vapour feedbacks, solar variability, and so on. However complex the climate models are, they are mere simplifications of what is actually going on in the coupled ocean-atmosphere system – and it appears that they are simply wrong. The longer the ‘faux pause’ continues, the more wrong they get.

Even if the models eventually prove to be right “why should we worry about a rise of two degrees Celsius?” asks Spiegelhalter. Because of weather, extreme weather to be more precise. Climate scientists tell us we can expect more frequent droughts, floods and storms – though the evidence for such thus far is much less than convincing (see Roger Pielke Jr.’s work). But that’s only part of the problem. Environmental engineers use a technique called Extreme Value Theory to allow for the occurrence of really extreme (e.g. once in a thousand years) events which will test their structures to the absolute limit. This relies upon collecting a lot of data about past extreme events, but in a warming world, Spiegelhalter tells us, this data becomes rapidly obsolete and hence the predictions of extreme value theory, which rely upon overall stable conditions, become increasingly unreliable. Hence our ability to plan for such events is reduced, placing society at risk. This sounds all quite reasonable but again, it is reliant upon the unproven hypothesis that patterns of extreme weather events will change/are changing due to global warming, which in fact is also not happening – for the past 15 years or so, global surface temperatures have not increased at anything like the pace that was predicted by the climate scientists’ models; indeed they have not increased by a statistically significant amount at all in any dataset.

Climate Change by Numbers? A for effort, C- for attainment.

Sorry, you’re gonna need more numbers. #CCBN2

Climate Change by Numbers Response Pt. 1

Well, after all the fuss and the feverish anticipation of this BBC program, I thought I had better get round to watching it and I have managed two thirds of the way through so far! I thought initially I might make a few (probably critical) comments on a blog post but, the more I examine this program, the more I feel I need to respond to specific (and some very unspecific) points made within. So let’s start with the grand aim of the program  – the goal of convincing us all that climate change (TM) is real via the wonder of mathematics and the analysis of three simple numbers: 0.85C, 95% and 1 trillion tonnes. Each number is assigned to one of three mathematicians (statisticians) – Dr Hannah Fry, Prof Norman Fenton and Prof David Spiegelhalter – respectively. They are “three numbers which represent what we know about the past, present and future of earth’s climate”, Professor Fenton tells us right from the off. Oh dear, not an auspicious start!

Hannah Fry (and four-legged friend Molly) tackle the mysteries of measuring global temperature and why 0.85 degrees is so important (or maybe not, as the case may be). Cue bucket talk – canvas and wooden – then on to an explanation of how errors are teased out of the historic global temperature record, using Kalman filtering. Now this, according to the program, is what enabled men to land on the Moon in 1969 and, under a different title – homogenisation – is what enables climate scientists to ‘clean up’ past temperature data and iron out irregularitiies. All sounds perfectly reasonable. But Hannah Fry tells us that “other people” will “inevitably start accusing” climate scientists of “building bias” into their data, once the raw data is cleaned up in this way and replaced with homogenised data. Those ‘other people’ sound like those nasty sceptics/deniers/contrarians which your mother warned you about. They also sound suspiciously like those conspiracy theorists which Lewandowsky warned us about – you know, the kind of people who will question the unquestionable – the global temperature record, built as it is upon the solid science which gave us the Moon landings. This subtle re-working of the infamous take home message of LOG12 – whether planned or merely coincidental – was not lost on me; but then again we ideational conspiracists often see hidden messages that others fail to detect!

Next we get on to data ‘infilling’ (named Kriging, after a South African gold-miner). Then swiftly on to the pause which is not a pause, which does or does not exist, and anyway, which is just one of a number which were always expected to appear to briefly interrupt the general man-made warming trend. No matter that the ‘expectation’ of a 15 year hiatus was just once in every 375 years of model runs (p.8)! But, you know, limited time and all; the program just couldn’t fit the explanation of this mere ‘detail’ into its breathless schedule, even though it tediously slow-burned its way through endless minutes of story-telling build-up to the main points. “Mathematical manipulation of the raw data can look like fiddling the figures”, Fry tells us, and the techniques which climate scientists have used are well understood and “all lead in the same direction”. I’m sure this phrase was an unfortunate choice, but yes, I think that’s one of the main contentions of some sceptics – the fact that, in general, these adjustments do all lead in the same direction, i.e. more warming! Summing up then, Hannah concludes that, even with all the uncertainties in the past temperature record, the scientific consensus is that the earth’s temperature has risen by 0.85C since 1880.

This is fairly uncontroversial, even amongst climate change sceptics, who generally acknowledge that the planet has indeed warmed overall (but certainly not uniformly, either spatially or temporally), since the 19th century and indeed since the Little Ice Age ended. The controversial part, as Hannah points out, is how much we are responsible for that warming, which naturally leads onto the second guest presenter, Prof Norman Fenton. He will tell us how the IPCC are 95% certain that we are responsible for virtually all of the warming, but it’s not ‘this’ warming (0.85C), it’s the warming that has taken place since 1950. So why bang on about the ‘almost a degree’ warming since 1880 when it does not relate directly to the second crucial figure? Why not bang on about the ‘slightly more than half a degree’ warming since 1950 which the IPCC tells us is all down to CO2? I’ll leave the reader to speculate on that.

Norman Fenton is a Spurs fan and a down-to-earth Londoner – so we have one thing in common at least! In order to explain the mystery that is an IPCC climate change ‘attribution study’, he chooses to model the performance of Premier league teams and finds that, in amongst a variety of factors, one stands out as having a very marked influence upon performance – the wage bill. Fenton creates a simple model which predicts the performance of teams based upon various factors. First he shows us the rather good fit of model vs. actual performance for Man City. Impressive. Then he shows us Liverpool:

FireShot Screen Capture #015 - 'BBC iPlayer - Climate Change by Numbers' - www_bbc_co_uk_iplayer_episode_p02jsdrk_climate-change-by-numbers

Hmmm, not quite so impressive, but unabashed, Prof Fenton says that this good model fit is “true for all of the teams in the Premier League”. He goes on: “Now I know I can trust my model, we can move on to the clever bit”. He really does seem to have this IPCC attribution study nailed! The “clever bit” is isolating what factor, if any, has a dominant effect upon any team’s performance, which turns out to be the wage bill. This is ‘attribution’ and the principle is the same for climate change, albeit the latter situation is far more complex, with an extremely complicated web of interacting variables needing to be taken into account rather than just a few. Most of these variables are related to natural (internally and externally forced) climate variability but, nevertheless, the IPCC has looked at them all and concluded that their net effect is near zero since 1950 – hence they can attribute to CO2 emissions with startling 95% certainty virtually all global warming since 1950 (but not since 1880). How, you may ask? Well, firstly because of depressed Swedish physicist Svante Arrhenius. He it was who, in a roundabout sort of way, first showed, “using maths”, that a doubling of CO2 could warm the globe by 4C via the so called Greenhouse Effect. So that’s one crucial piece of ‘evidence’ in place; now just to ‘prove’ the assertion that natural variability has played virtually no part in recent global warming.

“If the cycles of the Sun were a major cause of the rise in temperature we’ve measured, then what we would see would be all the layers of the Earth’s atmosphere warming together like this”:

FireShot Screen Capture #016 - 'BBC iPlayer - Climate Change by Numbers' - www_bbc_co_uk_iplayer_episode_p02jsdrk_climate-change-by-numbers I must admit, this is a new one on me which I must look into more. Even more interestingly, Fenton then presents us with what he says has actually happened over the last 60 years:

FireShot Screen Capture #018 - 'BBC iPlayer - Climate Change by Numbers' - www_bbc_co_uk_iplayer_episode_p02jsdrk_climate-change-by-numbers What this shows is accelerated warming of the troposphere and cooling of the stratosphere. The stratosphere has indeed cooled since the 1960s – though this cooling trend has halted since the mid to late 1990s.

global_upper_air Now, Fenton informs us that the that the models show that this pattern (tropospheric warming/stratospheric cooling) only fits well with anthropogenic CO2 being the principle cause of recent global warming. What he neglects to mention is:

  1. The tropical mid-tropospheric ‘hotspot’ which we clearly see in his ‘actually happening’ representation above has actually failed to materialise, even though it is one of the key predictions of the climate models. There has been no observed accelerated warming of the mid troposphere over the tropics. So even though the troposphere as a whole has warmed and the stratosphere cooled, the mid troposphere has not warmed significantly compared to the surface.
  2. There is an alternative (anthropogenic) explanation for stratospheric cooling and surface/tropospheric warming which involves CFCs. Basically, the hypothesis is that accelerated ozone loss caused by CFCs in the stratosphere has resulted in cooling of that portion of the atmosphere whilst, at the same time, UV energy which would normally be absorbed by stratospheric ozone (warming the stratosphere) has passed straight through to warm the lower troposphere. This might explain the ‘pause’ in global warming from about 1998 and the corresponding ‘pause’ in stratospheric cooling as a direct result of the decline in the concentration of ozone depleting CFCs in the upper atmosphere since the international adoption of the Montreal Protocol in January 1989.

There are also explanations which invoke natural causes for some or even most of the warming we have seen since the 1950s. None of this gets an airing though. I guess, again, lack of programming time probably precluded the mention of these facts, though apparently not the mention of the ‘facts’ of declining Arctic sea ice, increasing heatwaves and ocean acidification as further ‘compelling’ evidence for the ‘human fingerprint’ of global warming. If the viewer is not convinced up to this point, then the almost exact match of the graph of actual warming (yellow) vs. modeled (red – anthro + natural) and the very poor fit of natural only (green) modeled warming is a killer:

FireShot Screen Capture #019 - 'BBC iPlayer - Climate Change by Numbers' - www_bbc_co_uk_iplayer_episode_p02jsdrk_climate-change-by-numbers Alas, once again the tight programming schedule does not allow Fenton to explain to his viewers about the assumptions inherent within this graphic, namely a high-end climate sensitivity to CO2 (increasingly looking doubtful), negligible solar influence and internal variability which has had nearly zero net effect since about 1950. Those assumptions are challengeable. Fenton says that the AGW fingerprint in global warming is as clear as the wage bill in his Premier league performance model; in fact so clear that the IPCC assigned 99% certainty to it. It would seem that the poor dears were so embarrassed by the devastating clarity and certainty of their science that they downgraded their figure to merely ‘greater than 95%’ just in case there were any hidden errors for which they had not accounted! Now ain’t that humility and honesty! Professor Norman Fenton appears to have had a bit of a rethink with regard to his presentation in the program. In his blog post he comes across as much more guarded about the role of humans in climate change than as portrayed in the program. Well worth reading.

On Steinman et al. (2015) – Michael Mann and Company Redefine Multidecadal Variability And Wind Up Illustrating Climate Model Failings

Bob Tisdale explains how Steinman, Mann and Miller have reconstructed ‘natural’ internal oceanic oscillations using CMIP5 models as the basis!

Bob Tisdale - Climate Observations

UPDATE: I’ve changed the title. This better represents the post.
# # #
For the past few years, we’ve been showing in numerous blog posts that the observed multidecadal variations in sea surface temperatures of the North Atlantic (known as the Atlantic Multidecadal Oscillation) are not represented by the forced components of the climate models stored in the CMIP5 archive (which were used by the IPCC for their 5th Assessment Report).  We’ve done this by using the Trenberth and Shea (2006) method of determining the Atlantic Multidecadal Oscillation, in which global sea surface temperature anomalies (60S-60N) are subtracted from the sea surface temperature anomalies of the North Atlantic (0-60N, 80W-0).  As shown in Figure 1, sea surface temperature data show multidecadal variations in the North Atlantic above and beyond those of the global data, while the climate model outputs, represented by the multi-model mean of the models stored in…

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New result shows CO2 has almost no effect on temperature

Tallbloke's Talkshop

An article in the Daily Mail today piqued my interest. It trumpets empirical results which they say empirically confirm the theoretical CO2 greenhouse effect for the first time:

greenhouseeffect“Scientists have witnessed carbon dioxide trapping heat in the atmosphere above the United States, showing human-made climate change ‘in the wild’ for the first time.

A new study in the journal Nature demonstrates in real-time field measurements what scientists already knew from basic physics, lab tests, numerous simulations, temperature records and dozens of other climatic indicators.

They say it confirms the science of climate change and the amount of heat-trapping previously blamed on carbon dioxide.”

“These instruments, located at ARM research sites in Oklahoma and Alaska, measure thermal infrared energy that travels down through the atmosphere to the surface.

They can detect the unique spectral signature of infrared energy from CO2.

Other instruments at the two locations detect the unique signatures of…

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I am Under “Investigation”

Roger Pielke’s view on the nakedly political attempt to intimidate him and others. Feb 24th 2015 – a bad day for science and for academic freedom. But if Grijalva isn’t stupid, he must be extremely arrogant and self-assured. The kickback against this Salem-esque move against respected scientists is going to be huge.

The Climate Fix

As some of you will already know, I am one of 7 US academics being investigated by US Representative Raúl Grijalva (D-AZ) who is the ranking member of the House of Representatives Committee on Environment and Natural Resources. Rep. Grijalva has sent a letter to the president of my university requesting a range of information, including my correspondence, the letter is here in PDF.

Before continuing, let me make one point abundantly clear: I have no funding, declared or undeclared, with any fossil fuel company or interest. I never have. Representative Grijalva knows this too, because when I have testified before the US Congress, I have disclosed my funding and possible conflicts of interest. So I know with complete certainty that this investigation is a politically-motivated “witch hunt” designed to intimidate me (and others) and to smear my name.

For instance, the Congressman and his staff, along with compliant journalists…

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Science and Statistics – An unholy Alliance?

I came across this very interesting article the other day, written in 2010. It basically reinforces my own long held sense of unease with regard to statistical analysis. My reaction against statistics started early, in school, when first I was presented with its somewhat bizarre pseudo-mathematical methodology and nomenclature. My early rejection of the subject was more visceral and emotive rather than common sense factual and logical. It just hit a raw nerve with me somehow and all these years later, reading this article by Tom Siegfried, I begin to see perhaps why.

So let me begin by quoting a few passages from Siegfried’s text:

“During the past century, though, a mutant form of math has deflected science’s heart from the modes of calculation that had long served so faithfully. Science was seduced by statistics, the math rooted in the same principles that guarantee profits for Las Vegas casinos. Supposedly, the proper use of statistics makes relying on scientific results a safe bet. But in practice, widespread misuse of statistical methods makes science more like a crapshoot. ”

So it’s not statistics itself, but the misuse of this analytical toolbox which is the problem. To this I would add over-reliance, especially evident in the field of climate science. Too often in the peer reviewed climate science literature we find papers which base their conclusions almost totally on the results of some new statistical analysis/re-analysis of existing data. In order to fully appreciate what they are saying and, more importantly, in order to question what they are saying, one needs to be an expert not primarily in climate science, but in statistical analysis.

“Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing. ”

This does not inspire confidence.

“Experts in the math of probability and statistics are well aware of these problems and have for decades expressed concern about them in major journals. Over the years, hundreds of published papers have warned that science’s love affair with statistics has spawned countless illegitimate findings. In fact, if you believe what you read in the scientific literature, you shouldn’t believe what you read in the scientific literature.”

With the increasingly pervasive use of statistical analysis in climate science, backed up by increasingly complex computer models, the above statement is magnified 10-fold in consideration of the results of the latest peer-reviewed scientific research. Much of this said research is aimed at pointing the finger at man as being responsible for the majority of post 1950 global warming, claiming also that we will continue to drive climate significantly into the future. Yet much of it is based upon statistical reanalysis of existing data.

“Nobody contends that all of science is wrong, or that it hasn’t compiled an impressive array of truths about the natural world. Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.””

A perfect illustration: the recently released paper by Marotzke and Forster. The main impetus for the paper was to address the apparent mismatch between climate models and real world observations (in particular the ‘pause’) which sceptics use to question the validity of the AGW theory. The paper concludes:

The differences between simulated and observed trends are dominated by random internal variability over the shorter timescale and by variations in the radiative forcings used to drive models over the longer timescale. For either trend length, spread in simulated climate feedback leaves no traceable imprint on GMST trends or, consequently, on the difference between simulations and observations. The claim that climate models systematically overestimate the response to radiative forcing from increasing greenhouse gas concentrations therefore seems to be unfounded.”

So, climate models do not overestimate the response to GHG forcing, even though the CMIP5 model mean is increasingly diverging from actual recorded global mean surface temperatures (GMST) and even though almost all models clearly run ‘too hot’ when compared with actual GMSTs. Apparently, this impression is not borne out by statistically analysing the past temperature record and comparing that with the models [?] It’s opaque to me and probably a lot of other people besides. Nic Lewis thinks it is plain wrong, and says so at Climate Audit, laying out his reasons. He gave Marotzke and Forster the opportunity to reply to his concerns about their paper but they failed to respond before Nic Lewis published at Climate Audit. Instead, they have chosen to issue a rebuttal of Lewis’ rebuttal at Climate Lab Book here. I’ve no idea who will eventually be proved to be right or wrong in this kerfuffle, but I quote from statistical expert Gordon Hughes (Edinburgh University), being one of two people whom Nic Lewis asked to review his conclusions about M & F, 2015:

“The statistical methods used in the paper are so bad as to merit use in a class on how not to do applied statistics.

All this paper demonstrates is that climate scientists should take some basic courses in statistics and Nature should get some competent referees.”

 

The wider point here is that we have yet another paper which relies almost exclusively upon statistical methodology to draw conclusions about the real world – another paper which may have to be withdrawn. Science – and climate science in particular – is suffering from the all too pervasive influence of staistics. There is a place for statistics in the analysis of real world data and even I must (reluctantly) acknowledge this. However, science has, as Tom Siegfried points out, become “seduced” by the false promise of this “mutant” form of mathematics and is suffering from its misuse and its overuse.

Unfruitful Twitter Interactions with Climate Scientists

Talking with climate scientists on Twitter has never been a very enlightening or productive experience – due in no short measure to the particular limitations of the media. However, I have found it informative and worthwhile in the past, with at least some willing to engage on the science and the issues surrounding it. But these past few weeks have been particularly frustrating and unproductive and unless it’s down to me being somewhat more impolite than I have previously been – which I don’t think is the case – I do now detect a definite reluctance to engage positively, for whatever reason.

So I’ll list off a number of particularly unproductive ‘conversations’ (in many cases consisting of me tweeting and being ignored) to illustrate my point. First, and most recently, Gavin Schmidt’s tweet about the AMOC graph posted by Ed Hawkins, which shows a definite negative trend since 2004:

My response:

I linked to the actual University of Southampton et al study which produced this graph and pointed out to Gavin that they did not think the trend was ‘insignificant’ On the contrary. I quote from the paper (my emphasis):

“Model simulations predict a decrease of the AMOC in the 21st century in response to increasing greenhouse gases of the order of one half a Sverdrup per decade (IPCC, 2007). Our observations indicate that the actual change over the last decade is much greater. The magnitude of the observed changes suggests that they are a part of a cyclical change rather than being directly linked to the projected anthropogenic AMOC decrease . . . . . We have shown that there was a slowdown in the AMOC transport between 2004 and 2012 amounting to an average of 0.54 Sv yr (95 % c.i. 0.08 to 0.99 Sv yr) at 26◦N, and that this was primarily due to a strengthening of the southward flow in the upper 1100 m and a reduction of the southward transport of NADW below 3000 m. This trend is an order of magnitude larger than that predicted by climate models associated with global climate change scenarios, suggesting that this decrease represents decadal variability in theAMOC system rather than a response to climate change.”

I have yet to receive any tweet in response from Gavin or Ed Hawkins.

On the subject of ‘Europe’s warmest ever year’ and the cyclical AMO this time, Andie Mac responds to climate scientist Jonathan Overpeck’s link to the Guardian showing that European annual temperature this year is heading for a record.

John Kennedy replies and does give credit to the AMO for maybe being partly responsible for the big jump in temperatures in Europe:

Andie questions Kennedy further and then I post two tweets to Jonathan Overpeck and John Kennedy at the end of the conversation:

I have not received any response to either.

Next Prof. Iain Stewart. OK, he’s not a climate scientist, he’s a geologist, so still an earth scientist as strongly wedded to the failing CAGW hypothesis as he is to his employers, the BBC. He pointed out that the Met Office, although they accept the pause in global surface temperatures, are nevertheless at pains to stress that global warming has not stopped and there is good scientific evidence of its continuance:

I checked his link which gave a further link to this study released by the Met Office, which basically claims that the observational evidence for the continuation of CO2 climate forcing throughout the pause consists mainly of the continued downward trend of Arctic sea-ice, rising ocean heat content (OHC) and declining Northern hemisphere snow cover:

http://www.metoffice.gov.uk/media/pdf/e/f/Paper1_Observing_changes_in_the_climate_system.PDF

So, naturally, I tweeted to Prof. Stewart the following:

Which was polite and to the point. No reply. However, I note he engages with the very much less polite Crock of Socialists:

(click on date for entire twitter conversation)

Gavin Cawley is also not a climate scientist, but I’m sure he would like his audience to think that he is qualified to be one. In fact he is senior lecturer in the School of Computing Science at UEA with an interest in anthropogenic CO2 residency times. He says that sceptics seek an excuse for avoiding discussing the science:

So I thought I would try to discuss the science a little with him:

You can see how the conversation went with me asking GC to show a paper that predicted pause lengths of 15+ years:

He did (kind of) but when I challenged him on the probability of this ‘predicted’ 15 year + pause actually happening, he got irate and finally discontinued the conversation with this Tweet:

Now Mark Maslin is a climate scientist – at least that is what he claims. He is employed as Head of the Department of Geography at UCL. The following attempts to engage him in debate about climate science came a week or so before he declared his public intention not to debate the science of climate change with ‘deniers’. Here is our discussion (click on date):

A little later, Maslin produced a graph on Twitter and ignored a simple question I put to him about this graph:

He did have another go at convincing me that the earth is warming with another very silly graph:

Lastly, I phrased a straightforward question to Richard Betts, Doug McNeall and the Met Office re. FAR (Fraction of Attributable Risk) models; basically enquiring what range of transient climate response these models incorporated:

I didn’t get a reply so I answered my own question as best I could.  It is likely that the models the Met Office uses to state the probability of an extreme weather or climate event happening with and without CO2 forcing are based on assumptions of the value of TCR which are considerably in excess of the much lower estimates coming out of recent studies. But that doesn’t stop the Met Office and others ‘anthropogenically fingerprinting’ extreme weather and climate variability.

So there you have it. I’m sure that climate scientists are becoming a lot more cautious about who they interact with online and what conversations they become involved in; more so than they were a year or two ago.

Jarl Ahlbeck: A link between Low solar activity, Easterly QBO, negative AO and cold NH winters

Very topical post on Tallbloke. We’ve got the low solar activity, the easterly QBO and negative AO, but still waiting for the NAO to swing deeply negative.

Tallbloke's Talkshop

Future low solar activity periods may cause cold winters in North America, Europe and Russia.
Jarl Ahlbeck – Abo Akademi University, Finland

Historically, low solar activity periods like the Dalton and Maunder Minima have been connected to cold winters in Europe. It seems very possible that the low solar activity forced areas of low pressures into a southern route or caused a negative Arctic Oscillation, AO, which in turn allowed cold air from the North Pole to flow across Europe. But can we obtain from real measurements that low solar activity really is able to do that?

temp-turku-AO

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Magnetism and Weather: Interconnections?

Post on WUWT by Dr Tim Ball on the possible effects upon weather and climate of the Sun’s magnetic field and the interaction with Earth’s own magnetic field.

Watts Up With That?

Opinion; Dr. Tim Ball

Way back in the last century, I suggested that in this 21st century the dominant issue in science would be magnetism and in resources water. This especially applies to climatology, where, thanks to the Intergovernmental Panel on Climate Change (IPCC), they are either marginalized or ignored. It is not the only damage the IPCC have done. They kept the focus almost exclusively on CO2, and temperature within the atmosphere, at the expense of many other factors. William Kininmonth explains,

Climate models track the transfer of energy through the Earth system. The only boundary condition to the Earth system is solar intensity; everything else is dependent on the composition and physical/chemical/biological processes within the Earth system.

The recent article about the role of the “oceanic conveyor belt” in climate is nothing new, but is a reminder of IPCC narrowness. It is even worse with regard to extraterrestrial…

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