by Verity Jones and Tony Brown (Tonyb)
Back in October Tony asked me to help with a big idea. Searching Norwegian climate site Rimfrost (www.rimfrost.no) Tony had found many climate stations all over the world with a cooling trend in temperatures over at least the last thirty years – which is significant in climate terms. You see Tony had a grand vision of a website with blue dots on a map representing these “cooling stations”, where clicking on the dots brought up a graph of the data and the wonderful cooling trend. Would this not persuade people to look again at the notion of worldwide global warming?
I asked Tony how many stations he had in mind. “Oh two hundred or so…” He suggested breaking it down into bite-sized chunks and sending me sets of ten at a time. I was to compare the data with that on the GISS site and/or those of national met agencies where available to verify the source, and produce graphs to a standard template.
We were concerned that this could be seen as ‘cherrypicking’ nonetheless it was an attractive idea. In many cases it was not just cherrypicking the stations, but also the start dates of each cooling trend. Despite these reservations we decided to go ahead, although ultimately we have not completed the project, partly for these reasons, but also because it is a case where the journey became more important than the destination and it is worth sharing.
The first 10 (Set 1) of Tony’s target stations, which at this point I should say seemed to be a randomly chosen set, were:
- Brazil – Curitiba (1885 to 2009) Cooling 1955 to 2009
- Canada – Edmonton (1881-2009) Cooling from 1886 to 2009
- Chile – Puerto Montt (1951-2009) Cooling from 1955
- China – Jiuquan (1934-2009) Cooling all years
- Russia – Kandalaska (1913-2009) Cooling 1933-2009
- Iceland – Haell (1931-2009) Cooling all years
- India – Amritsar (1948-2009) Cooling all years
- Morocco – Casablanca (1925-2009) Cooling all years
- Adelaide – Australia (1881-2008) Cooling all years
- Abilene, Texas – USA (1886-2009) Cooling 1933-2009
The comparisons in many cases were not straightforward. While many matched GISS data, some of the graphs in Rimfrost used unadjusted data, others homogenised data. For some such as Kandalaska, there was a close but not exact match to either GISS data set. The data for Haell was clearly from the Icelandic Met Office, but I could find no match for Edmonton to any GISS series or data from Environment Canada (although having looked at Canadian data further since I am not entirely surprised). The first set took much longer than we had anticipated; however, I drew the graphs to a template and prepared to start on Set 2.
Tony also wanted a ‘spaghetti’ graph for the anomaly data of the first set, and this is where it got most interesting. In fact we were blown away by what the graph looked like. Taking these ten locations from across the globe and superimposing the anomaly data produced a sine wave-like pattern (Figure 2) with distinct cooling from the early 1940s to mid-1970s followed by warming to present; for many of the locations the older data was warmer, or at least as warm as present. Now I had seen this before with many individual stations, but it really impressed me to see the pattern matching from such far-flung locations.
But in the meantime there were other developments. Tony knew I was interested in putting the GHCN v2.mean temperature data from stations all over the world into a database. As usual, this exceeded my own knowledge and capabilities, but I had made a start and was learning as I went along. Tony, whose contacts and connections never cease to amaze me, put me in touch with a computer professional, database, web and mapping expert who was well known to commenters on The Air Vent, Climate Audit and WUWT as “KevinUK”. Kevin was also keen to put climate data into a database.
By now this was the end of November. Kevin and I rapidly established a good rapport by email and voip and, with really only a few pointers to GHCN and GISS datafiles from me (and probably lots of hindrance), he rapidly built a fully functional database. Not only that but he set about writing software to plot graphs and calculate trends from the data and put the whole lot on an interactive map – and all this in a period of about 6 weeks. It is still a work in progress, fixing glitches and preparing Version 2.0; for more information see blog post Mapping Global Warming and the website itself: www.climateapplications.com.
I did deliver 40 graphs for Tony in the end, but I was quite slow about it (and that “sine wave” pattern kept showing up again and again and stuck in my mind). Tony had moved on to researching other climate projects and Kevin’s maps meanwhile showed so much more than we ever could. With the “sine wave” climatic pattern in mind, the following maps (focussing on North America and Europe) show how climate has cooled, warmed, cooled and warmed again since 1880.
So is this “sine wave” the true climate signal? It would seem so, although we can’t expect it always to be so regular. Choosing stations that are more closely geographically located does give a more homogeneous shape to the wave.
It is most extreme in the high Arctic – Figure 4a shows the graph for six stations above 64N where the magnitude of change is +/- several degrees Celsius. Further south (e.g. Figure 4b – four stations in the US) the magnitude is smaller, and close to the equator (Figure 5, Madagascar) the magnitude is less still.
A final point – with the exception of the Madagascar graph, which was prepared for a blog post (link), all these graphs were part of different sets (the first 40 stations for which data was examined). Although the original data was chosen for its cooling trend this, in many cases, results from warmer temperatures in the period 1930-1940 than present.
The wave pattern is still present in many data sets worldwide, no matter what the overall trend. In some the date of the onset of warming or cooling is later or earlier, depending on location – as would be expected with the oceans moving warmth around the globe. In others however the wave pattern is not present or is obliterated by something – in these sets should it be present or not? Is it wiped out by anthropogenic effects on the temperature record such as growth of cities and even small rural communities though the otherwise cooling 40s, 50s and 60s?
For us the take-home message of this study was simply how widespread and consistent the wave pattern is, and this, ultimately is very convincing of the veracity of the arguments against CO2 as a primary cause of current warming. From the physics I don’t doubt it has a role in warming, but its role needs to be disentangled from the large magnitude natural climate swings that are clearly present all over the world – a pattern that is not widely disseminated.
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You have picked your year breaks badly. The most suspect range of station data is 1977 to 1997 where their curve shows rising temperatures that do not exist. That is the range that should be separately analyzed from the range of 1999 to 2010. 1998 is an outlier – a super El Nino that should not be averaged with any other year because it is not part of the ENSO system. You should find two horizontal trends, one before and one after that super El Nino. Get back to the drawing board and do it right this time.
rbateman says:
September 4, 2010 at 1:17 pm
The Constant Sun is an illusion
I said ‘almost constant’, and for the things that affects the change of seasons and regulated the ancient Egyptians way of life, the solar cycle etc would not be discernible. Even today, it is hard to tease the tiny solar cycle effect out of the climate [or weather].
Re: Leif Svalgaard
Thank you for reminding us of the following:
Brajsa, R.; Wohl, H.; Ruzdjak, D.; Vrsnak, B.; Verbanac, G.; Svalgaard, L.; & Hochedez, J.-F. (2007). On the solar rotation and activity. Astronomische Nachrichten 328(10), 1013-1015. doi:10.1002/asna.200710867.
http://www.leif.org/research/ast10867.pdf
Regarding Figure 1:
a) Can the plot be extended back to 1865 (for example by using other data sources)?
b) Are the plotted data available via plain-text webpage?
Paul Vaughan says:
September 4, 2010 at 1:30 pm
a) Can the plot be extended back to 1865 (for example by using other data sources)?
b) Are the plotted data available via plain-text webpage?
a) difficult. There is data for 1862-1866, but not digitized.
b) no, but I could, of course, make such a page. The day only has 24 hours, though…
Bruce Long says:
September 4, 2010 at 11:27 am
“Many geophysical phenomena expressed as a time series of measurements exhibit what is called flicker noise characteristics.”
Having spectrum analyzed several hundred century-long temperature records, I disagree entirely with your speculative premise. The dominant spectral feature is usually a strong peak at multi-decadal periods, without any sign of the f-inverse monotonic decay of spectral density characteristic of flicker noise. That doesn’t mean that the multidecadal oscillations are strictly periodic, but they are quite persistent in most records from stations at latitudes of ~50 degrees or less.
DirkH says:
September 4, 2010 at 8:10 am
Yeah, aerosols. Aerosols are nice. We can assign a positive or a negative forcing to them, any way we need it to make the GCM hindcasting fit. And as long as we don’t do real science to find out the real influence of aerosols, we stay free to use them to fudge our models any way we need to to achieve our political goals, right? So just let’s not do real science. Knowledge always gets in the way of the cult leaders.
———————–
Different types of aerosols have different radiative properties – carbon black absorbs radiation, sulphates reflect it – so the sign of their forcing differs. Was that too complicated? Cold years after large volcanic eruptions demonstrate the cooling properties of sulphates, why should anthropogenically derived sulphates behave any differently? If this goes against your creed, design an experiment to falsify these ideas.
Ignorance is much less useful than knowledge.
This is a great post! And I think its getting closer to the true picture.
It always concerned me that the cooling reported in the 1970s (with concommittant fear of a new ice age) doesnt show up enough in the temperature data – plus there is a nice graph of temperature trend by population of county in California which suggests that low population counties have seen virtually no warming I just cant see how those counties could be effectively cooling when the rest of the world is supposed to be in a global warming trend.
Yeah, brilliant work – and good to see Adelaide in there as a trend setter.
Re: Leif Svalgaard
If you can find the time to put up a page (whether plain-text or Excel-file), I am sure many (myself included) would appreciate such access to the data. I will watch for a link…
Best Regards.
Congratulations to Verity and TonyB, for producing a good piece of work which shows how our climate oscillates up and down naturally, thus refuting the conjecture that CO2 has a warming effect.
This sort of quasi-cyclic behaviour is typical of a driven pendulum and trying to use linear trends on systems like our climate is futile.
The more smart and open-minded people are looking at the reality (=data), the more the “it’s only CO2” fantasyland falls apart. I am lovin’ it. Thank you, guys.
Peter Ellis, Ulric Lyons, richard telford,
None of you addressed that it was warmer in the 30’s, in many cases, than now. Being warmer in the 30’s does not support the global warming hypothesis.
Don Easterbrook
Here is a video of you covering the same things you have in your comment. Watching on video is easier to follow for readers. Things that seemed docile in print come alive on video:
Thanks again to all for the great encouragement and suggestions. This will spur us on to continue “looking differently” at the climate record. I’ve been reminded this evening of my own response to seeing the spaghetti graph (Figure 2) for the first time and it was much the same as the response here.
Bruce:
“This is not to say there is no climate periodicity, just that eyeball identification of said periodicity in time series data is far from conclusive.”
yup. we are wired to see patterns so I’ll wait for the math on this.
When NM sites were trending up, Japanese sites were trending down. WUWT?
The likely explanation is that ocean heat release is the primary driver of atmospheric temperatures over these timescales. Different ocean regions release heat over different cycles (periods) as you would expect from variations in ocean heat distribution or ocean circulation.
Any global effect is merely the sum of regional effects. That is, global scale forcings (CO2, sun, etc) have little effect.
Further, I am sceptical that regional ocean heat release is globally synchronize, and therefore think any global warming/cooling signal is largely spurious.
Get away from the forcings model of climate and there is little reason to think in terms of a global climate (over a century timescale).
I’d be interested to see the same data graphed separately for Europe, N America, Australasia, S America and see if the same sinusoidal pattern (in synchronization) still occurs. If it does, then I’m wrong about no globally synchronized ocean heat release. If it doesn’t, then I’m probably right.
Jim G
Thank you, I think?
If you know any control system engineers, ask them to look at the temperature vs CO2 concentration for:
Ice core data
Earth’s temp and CO2 concentrations for the past 200 years
Anyone who has dynamic process control experience will immediately see that CO2 concentration is not a driver, but is a lagging variable. This is very basic process loop tuning analysis and I can’t believe that climate scientists could ever look at those tend lines and believe that CO2 was a forcing. Don’t believe the outputs from computers until it pasts a “common sense” check. GIGO has been known ever since digital computers were first developed. When the biggest source/sink for CO2 covers 70% of the Earth’s surface, it’s hard to give much credience to pump mankind!
Last point: we know the Earth has been warmer over the past 5 million years (evenwarmer in the Holocene Optimum, the Roman Warm Period and the MWP) and that CO2 concentrations have been higher in the past by up to a factor of 5-7 times. We have ice ages and interglacials, but the Earth’s temperature never ran away to the up side. If it hasn’t happened once in the geologic history of the world, the probability of this time being different is practically nil! As I said, the “common sense” test.
Bill
The data seems to support a theory I have that lower level particuate pollution causes the atmosphere to warm while higher level particulate pollution causes the atmosphere to cool. During the dust bowl years (1910-1939) low level particulate pollution, caused the atmosphere to warm (mostly in the center of the USA).
During the war years (1940-1969), with bombs (including atomic testing) causing high level particulate pollution, the atmosphere cooled.
Above ground testing of nuclear devices ended in the 1970s lowering the amount of high level particulate pollution, thus causing the atmosphere to warm (1970-2010).
High level particulate pollution absorbs the sun’s radiant energy and radiates the energy into space. Low level particulate energy absorbs the sun’s radiant energy and transfers the energy to the atmosphere.
Paticulate pollution absorbs most of the radiant energy it receives while GHG only affect a tiny part of the spectrum. Particulate pollution seems to me, to be a far greater factor than GHG.
Excellent work, guys!
Yet again, further proof that when you look at something closer to raw data rather than averages of averages of averages, the truth is more likely to emerge.
The signals are there for anyone who chooses to see them, rather than blindly accepting the orthodoxy favoured by those who ‘believe’ there is a ‘consensus’. This periodicity of ~30 year (and other) natural cycles has been noted elsewhere many times, but the warmistas’ PR establishment seems reluctant to bring them to the public’s attention, and when they do grudgingly concede their existence (after retrospectively screwing the data to downplay previous cycles), insist that the most recent cycle is ‘unprecedented in human history’. Your efforts here add to the evidence that this is not the case.
The compliant, disaster-seeking mainstream media has accepted and promulgated the myth for so long that a substantial proportion of the general public has, understandably, fallen for it. Mann’s ‘hockey stick’ graphic and others like it have been very effective in manipulating Joe Public’s opinion on these matters, and it’s high time that the man in the street had the opportunity to see less-tortured representations of our climate history.
I guess what really bugs so many of us on this side of the fence is the fact that, unlike the purest practise of science as a relentless pursuit of the truth, however it pans out, climatology has become, more so than any other discipline, a shameless branch of QED science: the facts and interpretations are selected and twisted to fit the conclusion that has already been drawn.
It is analogous to a topical subject here in Australia at the moment. A new toll-based road tunnel in Brisbane has become the latest financial disaster, following the example of two similar tunnels in Sydney in recent years. They are all victims of “work-back modelling”, where the starting parameter for the feasibility study is an attractive return to investors and the end result is the number of motorists needed to use the tunnel every day. When the tunnel is opened and only a fraction of the wildly optimistic, model-derived number of motorists choose to avail themselves of the latest insult to their daily expense possibilities, the whole project becomes a financial toilet.
So it is with AGW models. They begin with the “CO2 is evil and we westerners should all be ashamed of ourselves” trope, and fiddle the models backwards to prove it, even resorting to crappy, discredited factors such as aerosols to prove their point.
I don’t know what you call that, but it ain’t science.
One cannot argue with the necessity to use statistical methods to try to find patterns in data that has a lot of noise. But after all, we don’t experience climate, we only get weather, and weather is all noise. Only when we scrutinise the base data can we see it as it is, whereas models are better at concealing the truth than revealing it.
Tony B,
for some time I have been looking at the long term temperature data, and using Fourier Convolution, or Spectral analysis signal conditioning methods to see what would fall out. The following graphs show three data groups. A data group is one with records starting before a point in time. These include records starting before 1650, 1750 and 1800. Most of the data comes from the Rimfrost ( http://www.rimfrost.no ) site.
For each station a anomaly series was computed. These anomalies were then averaged to form a composite anomaly for that group. Each group was then filtered with a fourier convolution lo-pass filter, with a cut-off period of 40 years. The following graph are the result, including a comparison with the Hadcet data. One thing that was striking is the almost periodic cycles around the 50 year point.
Ave1- i.e. Central England
http://www.imagenerd.com/uploads/lt-temp-1650-2008-1-Rxrdy.gif
Ave4 Anomaly data from 1750-2008 – including Cen Eng., Debilt, Uppsalla
http://www.imagenerd.com/uploads/lt-temp-1750-2008-4-EyvXd.gif
Ave14 Anomaly data from prior to 1800 to 2008
http://www.imagenerd.com/uploads/lt-temp-1800-2008-14-9ZSv8.gif
One of the things I would like to look at in the future would be to ocean and solar cycles.
Jaypan says:
————-
the more the “it’s only CO2″ fantasyland falls apart. I am lovin’ it.
————
Nope. It was never “only CO2”. There was always a bunch of other stuff happening at the same time. The important questions are:
1. how important is the other stuff?
2. can we do anything about the other stuff?
3. If the other stuff is cyclical and CO2 is trending linear upwards, how much trouble are we going to be in on the peak of the next cycle, if we dismiss CO2 because we are in the bottom of a cycle now.
As the other guy says; naysayers have to grow up about attributing single causative factors in climate. The climatlogists are certainly not that naive.
Leif Svalgaard says:
September 4, 2010 at 11:30 am
“There seems to be a very weak dependence on activity in the sense that more activity slows the surface rotation down [Figure 2]. This is what would be expected: the more magnetic the Sun is, the more rigid is its rotation.”
Thank you Lief, for that information on the surface rotation variance. pg
Verity Jones and Tony Brown; Thank you for shareing the fruits of your work. At least those of us on the fringe can see the data for what it is and not what a driven agenda needs. pg
Leif Svalgaard says:
September 4, 2010 at 9:19 am
The link does not contain the words ‘solar velocity power wave’…
No, but it is shown in figure 5. The wave lining up with the PDO wave.
The solar modulation wave as you know works in parallel but skips a phase. From trough to peak is around 90 years and is confused with the Gleissberg cycle, these two cycles stay in phase because they are a product of the gas giants. The sunspot cycle follows the AM cycle which has the PDO cycle linked in.
http://www.landscheidt.info/images/Powerwavesm.png
phlogiston says:
September 4, 2010 at 10:50 am
“Solar velocity power waves” – are these related in any way to oscillation in the relative position of the barycentre and the sub-Jupiter point – i.e. oscillation of the sun’s angular momentum? As described in this paper:
No, Ian is talking about solar rotation changes, unfortunately this is a difficult area to measure. Scaffeta is showing the solar velocity as it fluctuates as it travels around the SSB. Figure 5 shows how this fluctuation lines up with the PDO. My theory is that because both power waves are linked the neg PDO most likely always occurs during solar grand minima
LazyTeenager
would you prove co2 does what ‘global warming’ says it does?
Despite weather and climate to be driven by chaotic inputs I would expect natural climate to be cyclic as feed backs, both negative and positive depending on cycle stage, take over. ie. as it gets warmer radiation increases as does cloud which has a negative feedback. As it cools so cloud will lessen and radiation reduce so warming will follow. This is assuming a constant solar input. But as we all know this is not correct so variations in solar input will add to the chaotic mix. Non of this shows any anthropomorphic input. Town and cities will be warmer but heat loss from these will be greater, to comply with 2nd law of thermodynamics, so the overall effect is probably zero.