Readers may find the title familiar, that’s because Basil Copeland and I also did a paper looking at solar signatures in climatic data, which has received a lot of criticism because we made an analytical error in our attempt. But errors are useful, teachable moments, even if they are embarrassing, and our second attempt though, titled,
hasn’t been significantly challenged yet that I am aware of. Basil and I welcome any comments or suggestions on that work.
In our work, we used Hodrick-Prescott filtering to extract the solar cycle signal from the HadCRUT temperature dataset. In this paper the data are extracted from the ECA&ECD database (available via http://eca.knmi.nl ). According to the paper, they are “using a nonlinear technique of analysis developed for time series whose complexity arises from interactions between different sources over different time scales”. Read more about it in the paper. In both our paper, and in this one, a solar signature is evident in the temperature data. – Anthony
Evidence for a solar signature in 20th-century temperature
By Jean-Louis Le Mouel, Vincent Courtillot, Elena Blanter, Mikhail Shnirman (PDF available here)
J.-L. Le Mouël et al., Evidence for a solar signature in 20th-century temperature data from the USA and Europe, C. R. Geoscience (2008), doi:10.1016/j.crte.2008.06.001
Abstract
We analyze temperature data from meteorological stations in the USA (six climatic regions, 153 stations), Europe (44 stations, considered as one climatic region) and Australia (preliminary, five stations). We select stations with long, homogeneous series of daily minimum temperatures (covering most of the 20th century, with few or no gaps).We find that station data are well correlated over distances in the order of a thousand kilometres. When an average is calculated for each climatic region, we find well characterized mean curves with strong variability in the 3–15-year period range and a superimposed decadal to centennial (or ‘secular’) trend consisting of a small number of linear segments separated by rather sharp changes in slope.
Our overall curve for the USA rises sharply from 1910 to 1940, then decreases until 1980 and rises sharply again since then. The minima around 1920 and 1980 have similar values, and so do the maxima around 1935 and 2000; the range between minima and maxima is 1.3 °C. The European mean curve is quite different, and can be described as a step-like function with zero slope and a ~1 8°C jump occurring in less than two years around 1987. Also notable is a strong (cold) minimum in 1940. Both the USA and the European mean curves are rather different from the corresponding curves illustrated in the 2007 IPCC report.We then estimate the long-term behaviour of the higher frequencies (disturbances) of the temperature series by calculating the mean-squared interannual variations or the ‘lifetime’ (i.e. the mean duration of temperature disturbances) of the data series.We find that the resulting curves correlate remarkably well at the longer periods, within and between regions. The secular trend of all of these curves is similar (an S-shaped pattern), with a rise from 1900 to 1950, a decrease from 1950 to 1975, and a subsequent (small) increase. This trend is the same as that found for a number of solar indices, such as sunspot number or magnetic field components in any observatory. We conclude that significant solar forcing is present in temperature disturbances in the areas we analyzed and conjecture that this should be a global feature.
…
We find that station data are well correlated over distances in the order of a thousand kilometres. When an average is calculated for each climatic region, we find well characterized mean curves with strong variability in the 3-15-year period range and a superimposed decadal to centennial or ‘secular’ trend consisting of a small number of linear segments separated by rather sharp changes in slope. Our overall curve for the USA rises sharply from 1910 to 1940, then decreases until 1980 and rises sharply again since then. The minima around 1920 and 1980 have similar values, and so do the maxima around 1935 and 2000; the range between minima and maxima is 1.38C. The European mean curve is quite different, and can be described as a step-like function with zero slope and a 1.8C jump occurring in less than two years around 1987. Also notable is a strong (cold) minimum in 1940. Both the USA and the European mean curves are rather different from the corresponding curves illustrated in the 2007 IPCC report.
…
We then estimate the long-term behaviour of the higher frequencies (disturbances) of the temperature series by calculating the mean-squared interannual variations or the ‘lifetime’ (i.e. the mean duration of temperature disturbances) of the data series. We find that the resulting curves correlate remarkably well at the longer periods, within and between regions. The secular trend of all of these curves is similar (an S-shaped pattern), with a rise from 1900 to 1950, a decrease from 1950 to 1975, and a subsequent (small) increase. This trend is the same as that found for a number of solar indices, such as sunspot number or magnetic field components in any observatory.
…
We conclude that significant solar forcing is present in temperature disturbances in the areas we analyzed and conjecture that this should be a global feature.
We have also shown that solar activity, as characterized by the mean-squared daily variation of a geomagnetic component (but equally by sunspot numbers or sunspot surface) modulates major features of climate. And this modulation is strong, much stronger than the one per mil variation in total solar irradiance in the 1- to 11-year range: the interannual variation, which does amount to energy content, varies by a factor of two in Europe, the USA and Australia. This result could well be valid at the full continental scale if not worldwide. We have calculated the evolution of temperature disturbances, using either the mean-squared annual variation or the lifetime. When 22-year averaged variations are compared, the same features emerge, particularly a characteristic centennial trend (an S-shaped curve) consisting of a rise from 1920 to 1950, a decrease from 1950 to 1975 and a rise since. A very similar trend is found for solar indices. Both these longer-term variations, and decadal and sub-decadal, well-correlated features in lifetime result from the persistence of higher frequency phenomena that appear to be influenced by the Sun. The present preliminary study of course needs confirmation by including regions that have not yet been analyzed.
anna v (05:20:01) :
” Solar variations are huge between day and night, winter and summer and latitudes.”
“The seasonal variations evidently make a large difference, from monsoons and trade winds to jet streams and ENSO and PDO, these are collective excitation modes by the sun’s energy beating in various rhythms ( day/night winter/summer,coriolis, tides) on the oceans and land. ”
But those variations are not caused by the sun’s output but rather conditions of the Earth. The Earth rotation creates the day and night, the Earth’s tilt creates the seasons and the Earth’s shape creates the difference in solar insolation at latitudes. The Sun doesn’t do anything different.
Jeff Larson (04:51:01) :
Has anyone done a spectral analysis of the various aspects of climate data? I think there are some powerful statistical analyses that could be done which could identify correlations that otherwise get lost in the noise.
I have posted these plots many times
http://img162.imageshack.us/img162/84/hadcrutnhshlsgiscetssna.jpg
http://img15.imageshack.us/img15/1127/ffts.jpg
http://img403.imageshack.us/img403/861/averageffttempcftsi.jpg
Leif has posted similar. No one seems to believe them! (there is no 11 year cycle present).
The plots are of stations with long continuous (FFTs do not like missing data) records, monthly data, some detrended to remove the “noise” generated at long periods by the FFT algorithm. There is no filtering done on the temperature values. There are plots of US areas included which presumably average the temperatures for the particular area.
The average is made by averaging the FFT output of the named locations.
anna v (05:20:01) :
Solar variations are huge between day and night, winter and summer and latitudes. In addition the average solar radiation change of 0.1% between solar maxima and minima has a variation within the spectrum: UV changes by 8% for example and it is UV that penetrates the ocean depths
These solar features are constant day night summer winter occur in a repeating pattern of 365.25 approx days (obviously)
TSI varies on an 11 approx years cycle, but each cycle is different amplitude so will be a variablke to the insolation.
O3 of course has been implicated in the cooling of the anarctic (lack of o3 = greater loss of heat) – see BAS website.
O3 changes over the rest of the globe would add/subract from the UV reaching ground level. What is the power of UV in the TSI data?
O3 loss has been attributed to human activity.
Jeff Larson (04:51:01) :
Most of the reports I’ve seen are based on time-series plots, matching up peaks & valleys with various offsets, etc. Has anyone done a spectral analysis of the various aspects of climate data? I think there are some powerful statistical analyses that could be done which could identify correlations that otherwise get lost in the noise.
Anthony and I did spectral analysis in our paper. Follow the link Anthony posted near the top of this blog post, and look particularly at Figure 5. Spectral analysis is actually quite common in the analysis of climate data. One of Leif’s principal criticisms of our paper is that it was just another in a number of papers he put at ~2000 showing climate cycles of this nature. Ours was a little more unique than Leif’s remark suggested, but it is true that there are countless papers showing cycles in climate data that seem to correspond to solar cycles.
The best overall book on the subject, if you are interested, is William Burroughs’ “Weather Cycles: Real or Imaginary?” (link below). Burroughs is more open to the possibility of a solar-climate connection than our resident expert Leif, while still acknowledging the limitations of what the data show.
An Amazon link to Burroughs’ book:
http://www.amazon.com/Weather-Cycles-William-James-Burroughs/dp/0521820847
Anybody want a Nobel prize in 12 years? Put the puzzle together and show cause and effect mechanisms between sun and earth climate. Leif and others will keep disregarding these articles until the link is made. You may also put the final nails in the global warming agenda.
Richard Mackey 01:28:04
That’s good stuff, and thanks for reposting it. I’m sure you are aware of the study by Ruzmaiken, Feynman, and Yung showing a correlation between Nile River levels and aurorae borealis.
anna v 05:20:01
Do you think it is possible that the multiplicity of agents enhancing, in different ways, the small change in TSI can account for the lack of runaway sensitivity that has so worried Leif?
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Britannic no-see-um (03:06:33) :
Those old boys knew their onions, and I’ll bet their temperature readings were spot on and should stand, not be ‘adjusted’ in cavalier fashion.
I agree. A good friend of mine is now 81 and he has been keeping weather records on Loch Tayside in Scotland for about 50 years now. It’s a labour of love for him. Unlike the automated weather recording, adjusting (dare I say fiddling?) that prevails today.
I’m not an expert in things solar but to me it is inconceivable that the sun does not have an effect on our weather/climate? It just seems like common sense to me. I mean, imagine if it wasn’t there?
Jimmy…..
You won’t get any answers on why the earth cools and heats. To me Roy Spencer has it all correct….it has to do with the cloud formations which are caused by the Sun. The delays in cooling and heating that we see had to do with the great ocean heat sink. I expect we are for an extended cooling period.
The AGW people know this but are taking an advantage of propaganda. Large government and it’s ability to control the wealth of the world is the real agenda.
From:
http://arxiv.org/ftp/arxiv/papers/0809/0809.3762.pdf
“Vincent Courtillot et al (2007) encountered a similar problem. (Courtillot, it should be noted, is the director of the Institute for the Study of the Globe at the University of Paris.) They found that time series for magnetic field variations appeared to correlate well with temperature measurements – suggesting a possible non-anthropogenic source of forcing. This was immediately criticized by Bard and Delaygue (2008), and Courtillot et al were given the conventional right to reply which they did in a reasonably convincing manner. What followed, however, was highly unusual. Raymond Pierrehumbert (a professor of meteorology at the University of Chicago and a fanatical environmentalist) posted a blog supporting Bard and Delaygue, accusing Courtillot et al of fraud, and worse. Alan Robock (a coauthor of Vinnikov et al mentioned in the preceding section) perpetuated the slander in a letter circulated to all officers of the American Geophysical Union. The matter was then taken up (in December of 2007) by major French newspapers (LeMonde, Liberation, and Le Figaro) that treated Pierrehumbert’s defamation as fact. As in the previous case, all references to the work of Courtillot et al refer to it as ‘discredited’ and no mention is made of their response. Moreover, a major argument against the position of Courtillot et al is that it contradicted the claim of the IPCC.”
Ah, “discreditation”…such a lovely process!
Richard Mackey (01:28:04) :
A NASA organised conference in 1973 (at which Leif Svalgaard presented a significant paper) surveyed the entire area of Sun/climate research.
At that time John Wilcox jointly with myself and others [most notably the very founder of NCAR: Walt Orr Roberts http://adsabs.harvard.edu/abs/1992BAAS…24.1331E ] sort of had revived the solar/weather/climate field with a series of papers on the possible effect of solar variables on the ‘Vorticity Area’ [a storminess index] Science, Volume 180, Issue 4082, pp. 185-186, 1973. Those papers were generally viewed positively and were actually the impetus for NASA to hold that conference. A historical note: Charles Greeley Abbot http://en.wikipedia.org/wiki/Charles_Greeley_Abbot gave the introductory talk at the meeting. He was 101 years old, but gave the talk with verve and passion. He died a few days later [perhaps he felt his work was done].
As more data became available, the Vorticity Area Index effect weakened and eventually died [as so often happens with sun/weather effects]. Brian Tinsley whom you mentioned is trying to keep it alive by showing that the effect is only visible when volcanoes have provided enough aerosols…
Lockwood and Frohlich ignore completely the established findings about the role of the gravitational fields of the Sun and the Moon in the regulation of the Earth’s climate.
And what might that role be?
It is as if NASA has dementia and all the work in the above mentioned NASA publications of 1978 and 1975, which has in the intervening 30 years advanced enormously, is lost to NASA’s corporate memory. Why is this?
It is because when ideas don’t pan out, they are [as they should be] quickly forgotten [people ‘move on’ as it it said].
If it was fully utilised in these two fields of inquiry the disconnectedness noted by Leif (and before him by John Wilcox) might finally vanish.
The disconnectedness is caused by research not holding up [and/or being of low quality].
[snip]
4th of July, now the new national dependence day. Obama, congress and senate supports the us gov ruling every aspect of your lives.
bill (06:50:14) :
…
I have posted these plots many times
And I’ve responded just as many times. The solar signal will be harder to extract from the “noise” when you use regional data like you are doing. (But not always.) In the global temperature data, there is a well-defined peak at 20-22 years, and another, less well defined, at ~9 years. There is a voluminous literature on the bidecadal signal, and whether or not it is solar. Rather than just trumpet your fft charts, why not immerse yourself in the relevant literature, and see if you can relate what you see in the data to that literature. That’s why Anthony and I did. Our bibliography might be a good starting place for you.
I will match your fft’s, and raise you with Figure 5 of our paper. 😉
anna v (05:20:01) :
UV changes by 8% for example and it is UV that penetrates the ocean depths
The same UV of course lands on plants/earth/houses. this would heat the “land” and hence the air above. A change in UV should show up as a temperature change (it does not in the FFTs). Or would you postulate that the UV is reflected from the earth?
Jimmy Haigh (08:13:23) : “I’m not an expert in things solar but to me it is inconceivable that the sun does not have an effect on our weather/climate? It just seems like common sense to me. I mean, imagine if it wasn’t there?”
The Sun has helped create the climates of our Earth simply due to it’s being there. However, the differences in weather/climate conditions on Earth are a result of other circumstances. Let’s try this example. You go to the eye doctor because you think you have a vision problem. The Dr sits you down in the chair and has you look at the eye chart on the wall. He then places the refraction equipment in front of your eyes and begins the process of changing lenses and asking you which lens is better for you. Now the eye chart on the wall doesn’t change, it’s image is picked up by your eyes from the light it gives off. What changes are the conditions that the light must pass through to get to your retina and that causes the changes in the way the chart appears. So it is with the Sun, it changes very little, but the conditions of the Earth change all the time. Those changing conditions are the drivers of weather/climate differences. Fortunately for you, the Dr will know if you have a problem and because correcting vision has a long, tried and true history he will know exactly how to fix your problem. Unfortunatley for us, that is not true with climate scientists and politicians.
Leif Svalgaard (09:04:22):
The problem is that you disconnect the obvious solar influence on local Weather and global Climate from other remainder domains which are more clearly affected by the intensity of solar irradiance and show the mechanisms through which the Sun drives climate.
At this pace, you’ll end believing that the Earth is an isolated system 100% protected from the fury of the Sun, if this has not occurred already.
I’m always irritated by outdated graphs. Just look at Wikipedia. This article is the same. What has happened up to 2009.5?
There is ‘low quality’ research in climate science due to politicisation. The attempts to link hurricanes with global warming is one example (Holland and Webster, 2007 has been declared ‘statistically invalid’ in BAMS). Stefan Rahmstorf’s ‘smoothing’ of temperature observations in Copenhagen is another. The question about the sun-climate link is not ‘if’ but ‘how’ and ‘how big.’ I’m sure no one needs reminding that the AR4 LOSU for solar irradiance is ‘Low’ and even lower for other solar factors. Lockwood & Frohlich pointed to a solar amplifier and claimed that it wasn’t relevant ‘now’ even though they didn’t know the mechanism. Shaviv (2008) has provided more evidence of a solar amplifier:
Shaviv: “Yes, I pulled finger nails until the data said “I give up, I give up!”
o.k., now seriously.
In order to get the cleanest data I used the 24 tide gauges chosen by Douglas 1997 for different stringent criteria (e.g., in geologically stable locations, long records, consistent with other gauges nearby, etc). I used someone else’s tide gauges so that I could not be accused of cherry picking.
Secondly, because I am not interested in long term trends, but I am interested in short term derivatives, I treated the data differently than what other people do. Instead of averaging the station heights and then differentiating, I first differentiated the data for each station and then added the derivatives. The reason is that this way I avoid getting spurious jumps from the start or end of individual station data. Because it can give rise to spurious long term trends and because I don’t care about long term trends, I simply removed any linear trend from the data.
In the graph from 1870 that Lief Svalgaard points to, one cannot see the 11-year signal because the latter only amounts to a few cm amplitude (3.5 mm/yr!). It obviously drowns in the annual noise or the long term trends in Leif’s particular graph. Note that at least over the past 50 years, Holgate sees consistently the same 11-year variations in the data (e.g., referenced here). Of course, because he uses a lot of lower quality stations (177) and/or is not careful to first differentiate and then add the tidal gauge data, he sees somewhat different variations before 1950, than what I find. (Of course, this is not a problem because he does not care about 11-year variations). Anyway, did Holgate torture his data too?
Oh, and the fact that Lean 2000 is used for the TSI is totally meaningless. The correlation with any signal synchronized with the 11-year solar cycle would give the same result. Note that I removed any long term trends from the tide data and from the solar proxies (whether TSI or cosmic rays).”
I have been careful enough on writing the next article on the influence of the solar irradiance upon some stratigraphic units. The article was classified like a “didactic article”. I am not mad at this classification, although I think its level is higher than a “didactic article”:
http://www.biocab.org/Hematite_Stained_Grains_and_TSI.html
Nasif Nahle (10:07:06) :
Leif Svalgaard (09:04:22):
The problem is that you disconnect the obvious solar influence on local Weather and global Climate
What obvious influence?
Basil (09:31:06) :
The solar signal will be harder to extract from the “noise” when you use regional data like you are doing. (But not always.)
There are plenty of hadcruts there – honest, even a giss!
If the signal is in the noise and usually so far below the noise that it is invisible then surely it is having no effect. Remember you are not looking for, or trying to extract the signal in the noise you are trying to show that the signal is actually affecting the temperature. I will freely admit that somewhere way down in the noise there will be a TSI spectrum – but as it is so small it will be insignificant.
In the global temperature data, there is a well-defined peak at 20-22 years,
At this period there is very little time accuracy and to relate this to the TSI cycle is not a sensible task. To me the plots I made show peaks somewhat to either side of 22 years.
see if you can relate what you see in the data to that literature.
The Oxford data I believe showed a reasonable peak at the NAO 7.7years, but on averaging this disappears. But I thought this was about TSI = 10 – 14 years? There is no significant peak!
I will match your fft’s, and raise you with Figure 5 of our paper
I had a look at the MTM site with a view to using this software. But it is not available for Windows and I do not consider it worth linuxing my puter just for this!.
Perhaps you can explain how fig 5 compares to fig 2 Fig 5 shows a sudden drop at >56 years and more detail than my FFTs show at these periods. (but the same data is used!.
To me it looks as if a band pass filter has been used centred on the 22 year period?
The HP filter is a nice agorithm for smoothing data (ive used it rather than arunning average as they seemed to produce a similar output) but I would hesitate to use it not knowing how it mungs the data! I assume you had a look at its workings?
The MTM software seems to put little hats in black on the trace are these peaks actually present at these amplitudes or is this just the software pointing out where peaks could be if they were harmonically related?
Jeff Larson (04:51:01):
Yes, proper power spectrum analysis (not just FFTs, whose results, called “raw periodograms,” presume strict periodicity and vary as chi-square with only 2 degrees of freedom) has been applied often in search of a connection between the 11-yr Schwabe sunspot cycle and terrestrial temperature variations. The results of proper analysis have been almost uniformly negative, for the simple reason that surface temperature records usually have little spectral density near that fundamental frequency.
The situation becomes much more interesting, however, at the harmonics and subharmonics of the sunspot cycle–and all the more so when solar factors besides the TSI are considered.
In the present paper, a pronounced downward swing from the late 50’s to the mid-70’s is evident in both the solar metric and the (rather obscure) surface temperature metric. Both metrics employed then rise in concert from the trough, manifesting coherence at frequencies well below not only the Scwabe, but below that of the Hale (~22yr) cycle. Cross-spectrum analysis using different metrics consistently shows this multi-decadal coherence. Thus a necessary–but by no means sufficient–condition for a solar link to surface temperatures has been established.
The sufficent condition, i.e., an unambiguous physical mechansim, has yet to be discovered. I suspect that it is only a matter of time that accumulation of global satellite data reveals that mechanism–provided that the AGW crowd doesn’t totally hijack the science.
Moderator: Please eliminate the paragraph break before the “Thus a necessary…”
Done – A
Leif Svalgaard (10:40:27) :
Nasif Nahle (10:07:06) :
Leif Svalgaard (09:04:22):
The problem is that you disconnect the obvious solar influence on local Weather and global Climate
What obvious influence?
Actually, the obvious influences are from primary school lessons:
1. Local temperatures depend on the intensity of solar irradiance, though local conditions could modify it.
2. Solar irradiance heats up the surface of oceans and land and the surface of oceans and land heats up the atmosphere.
3. The geographical distribution of biomes on Earth depends on latitudinal climate. Curiously, the distribution of biomes follows the line of the angle of incidence of the solar photon stream.
4. Evaporation from oceans is determined by the load of incident solar energy upon the ocean’s surface. Evaporation determines cloudiness, rainfall frequency and rainfall coverage, local temperatures and global temperatures.
5. As the Sun appears each morning on the horizon, the temperature of the surface exposed to the solar beams starts increasing and it starts decreasing as the Sun declines into the horizon.
6. The seasonal succession is due to the angle of incidence of the sunbeams upon Earth.
7. The champion on this issue is the iron stained grains, which definitely are shaped by the solar radiation. Its proportion is higher as the solar irradiance increases and gets lower as the solar irradiance decreases. Iron stained grains, curiously, are also used for knowing the climatic conditions prevailing at any geological era.
8. Winds are driven by the unequal heating of the surface, which is driven by the solar radiation.
The higher sophisticated our knowledge is, the higher our blindness on simple things.
Howard
I found this Received 16 February 2009; revised 24 April 2009; accepted 6 May 2009. Available online 18 May 2009 at Science Direct