Guest post by Dr. Leif Svalgaard
The following abstract of a poster to be presented next month at the Fall Meeting of the American Geophysical Union caught my eye:
Session Title: GC11A. Diverse Views From Galileo’s Window: Solar Forcing of Climate Change Posters Chair: Willie Soon, Nicola Scafetta, Richard C Willson
ID# GC11A-0685: Dec 14 8:00 AM – 12:20 PM
Revised Assumptions and a Multidiscipline Approach to a Solar/Climate Connection
C. A. Perry (US Geological Survey, Lawrence, KS, USA).
Abstract:
The effect of solar variability on regional climate is examined using a sequence of physical connections between solar variability , Earth albedo, ocean temperatures, ocean currents (Ocean Conveyor Belt), and atmospheric patterns that affect precipitation and streamflow. The amount of solar energy reaching the Earth’s surface and its oceans is thought to be controlled through an interaction between Galactic
Cosmic Rays (GCRs), which are theorized to ionize the atmosphere and increase cloud formation. High (low) GCR flux may promote cloudiness (clear skies) and higher (lower) albedo at the same time that Total Solar Irradiance (TSI) is lowest (highest) in the solar cycle which in combination creates cooler (warmer) ocean temperature anomalies. These anomalies have been shown to affect atmospheric flow patterns and ultimately precipitation over the Midwestern United States. A study has identified a relation between geomagnetic index aa (GI-AA), and streamflow in the Mississippi River Basin for the period 1878-2004. The GI-AA was used as a proxy for GCRs. There appears to be a solar “fingerprint” that can be seen in hydroclimatic time series in other regions of the world, with each series having a unique lag time between the solar signal and the hydroclimatic response. A progression of increasing lag times can be spatially linked to the ocean conveyor belt, which could transport the solar signal over a time span of several decades. The lag times for any one region vary slightly and may be linked to the fluctuations in the velocity of the ocean conveyor belt.
A graph is attached to the abstract (as seen above):
http://www.leif.org/research/MissGeomagGraphBW.jpg
The poster seems to report on earlier work presented here:
http://ks.water.usgs.gov/waterdata/climate/
Where the same figure appears.
Now, what is wrong about this graph [and the conclusion, of course] ?
I’ll let you all find out what.
It is an example of three things:
- The desperate need for establishing a Sun-Climate [or is it weather, when on a decadal basis?] causing this kind of sloppy work (the graph contradicts the mechanism given for it)
- The lack of internal quality control by USGS
- The lack of quality control by the conveners of the AGU session.
UPDATE:
Thanks to all the readers who so generously [some gleefully] have pointed out my misinterpretation of the figure. This, of course, makes my initial assessment of the quality control moot and void, with an apology to those involved. Perhaps this shows how important a graph can be [cf. the impact of the Hockey Stick] and how important is clear labeling of what is shown.
UPDATE2:
Since GCRs follow the the sunspot numbers and not the aa-index, the proper parameter to compare with would be the sunspot number. This also allows use of the streamflow data back to the beginning of the series in 1861. The following Figure shows the correlation with this parameter, providing a prediction of the flow to beyond 2040, should the flow indeed be correlated with the sunspot number 34 years earlier.
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Leif Svalgaard (16:10:00) :
tallbloke (15:43:36) :
Leif, wouldn’t the earth’s magnetic field modulate the effect of the GCR’s? Could it be that this might mean the aa-index is as important as the sunspot numbers?
The Earth’s magnetic field is the primary modulator of GCRs. Typically ten times as important than the Sun.
Bonzer!
So although the GCR variation follows the solar cycle closely at the decadal level, the effects of GCR’s on the Earth’s climate oin the long term is modulated much more by geomagnetism than changes in TSI.
So if Svensmark is on the money, he has identified an important climate driving mechanism on the multi-centennial scale.
I like it. 🙂
tallbloke (16:44:00) :
So if Svensmark is on the money, he has identified an important climate driving mechanism on the multi-centennial scale.
Except that the data we have don’t support any climate connection. Although a bit dated, the following Figure
http://www.leif.org/research/CosmicRays-GeoDipole.jpg
shows how the Earth’s dipole moment and 14C [GCRs] have varied the past 10,000 years. The temperature variations do not fit that pattern.
If there is no reason for a 34 year lag, then someone needs to tell the climate modelers that (there is a roughly 30 year lag built in right now due to the oceans absorbing some of the additional greenhouse forcing).
Okay that was off-topic, but I am not a big fan of smoothing and long-term lags. By the time one builds in a 36 month moving average into two different series, all kinds of spurious correlations start to show up. Now lag one of these smoothed series over any time period one wants and now you have double spurious correlations showing up.
There can be lags between indicators but one needs to have a solid physical basis for showing how that lag occurs. Smoothing is okay if there is uncertainty in the data or seasonality in the data or if it is too variable to view/study properly.
There is a rationale for smoothing the Mississippi flows over a 12 month moving average given there is a seasonal component to it. But after that, one is just begging for a correlation to show up that isn’t there. I don’t think there is any rationale for smoothing the geomagnetic index. It is already smooth enough and the solar cycle signal should be preserved anyway if one is trying to show it impacts something on Earth.
So, redo the data with no lags and smooth the Mississippi flows over 12 months and let’s see what shows up.
Bill Illis (17:46:43) :
I don’t think there is any rationale for smoothing the geomagnetic index.
There is a 20% semiannual variation, so a 12-month running mean would remove that too. The aa-index is the wrong one to work with if the GCRs are part of the equation. Then it must be the sunspot number.
So, redo the data with no lags and smooth the Mississippi flows over 12 months and let’s see what shows up.
Then there is hardly anything to write home about. It would seem yo me that the paper claims to be able to predict streamflow 34 years in advance.
To be clear, Paul, I don’t have any difficulty imagining how one might infer a lag from data. When I asked about a cause I was talking about a physical phenomenon, not a relationship between two graphs. What you describe is a criterion for identifying a candidate period, under the assumption that geomagnetic flux influences river flow after a time lag. It is no more a cause of that lag than the speedometer is the cause of a vehicle’s speed.
I was looking for something more like the following (not a serious proposal): “heat or mechanical energy caused by a spike in geomagnetic flux, stored deep in the ocean (mountain snow, upper-atmosphere moisture, etc…), then undergoes some evolutionary process that takes approximately 34 years before it ultimately produces a sudden influx of H20 to the Mississippi basin, causing higher flow.”
It’s easy to find putative correlations between roughly cyclical data by shifting until a pretty-good match shows up. But time-shift implies lag, and a specific lag burdens the interpretation of the causation–not only must one explain how flux affects flow, but why it takes exactly this amount of time, and how the signal’s shape is so well insulated from other influences over that period.
I hope that helps.
To further illustrate my thought on causation of lag, consider the well-known 800 year lag between warming/cooling changes and CO2 concentration changes in the geological/ice records.
One might say, “that’s preposterous — what could cause an 800 year lag?” Seeing the record might convince you that there is some lag-causing agent, but it certainly doesn’t constitute an “explanation”.
Fortunately, for CO2/temperature time lag, there is a ready explanation at hand (I haven’t done the calculation so I don’t know how good it is, but it seems in principle to do the trick).
It has to do with heat and carbon transfer through levels of the ocean, the tendency for the deep ocean to act as a CO2 sink, and the rate at which Henry’s law affects CO2 equalization on the boundary layer of the ocean at different temperatures.
Maybe someone better versed in fluid dynamics and the physics involved can opine as to the sufficiency of this explanation. I confess to never having seen it written up — I just assume that it’s the obvious cause for the temperature/CO2 lag.
Sorry for the digression, but I thought discussion of the problem I was considering would possibly benefit from a positive example of what I think is needed.
Ok, picking up on some of the later comments, there appear to be some plausible lag-explanations. If the earth’s magnetic field is the primary modulator, and if it responds in a resonant fashion to solar flux then we have an explanation of response at a whole number of solar cycles. I think of my coffee-cup that can overflow when I’m walking if I take 3 or 4 injudicious steps that give pulses causing constructive interference (to prevent this time one’s steps to avoid resonance and cause destructive interference).
There remains a smoothing problem: Addition of waveforms in which the signature of a pulse appears after 3 cycles also means that the energy of at least 3 (probably 6) pulses is present in each peak. Thus, there should be a 3-cycle (or more) averaging, and the variation in signatures from pulse to pulse would be more masked than in these graphs. At least SOME of the correlation must be purely coincidental, even if such a mechanism has validity.
R. Craigen (19:00:57) :
If the earth’s magnetic field is the primary modulator, and if it responds in a resonant fashion to solar flux
Some misunderstanding here. The Earth’s main field is the primary modulator of GCRs, but on time scales of thousands of years, and it does NOT respond to solar activity. Geomagnetic activity [the aa-index] does NOT modulate GCRs. Sunspot activity does. And there is no coupling between solar activity and Earth’s internal magnetic field. So no resonance.
PERFECT OPPORTUNITY TO TEST THE PREDICTIVE POWER OF HIS THEORY
Leif Svalgaard (18:07:58) :
“It would seem yo me that the paper claims to be able to predict streamflow 34 years in advance.”
Yes, as I also mentioned in my ” yonason (00:20:37) : [to] Paul Vaughan (23:29:09) : ” above.
Well, thanks to the folks at IceAgeNow, I was tipped off to a not so little scenario to test the theory. Does that theory/hpothesis find that what happened on or about 1975 can predict the massive floods currently underway?
http://www.marketskeptics.com/2009/10/rains-swamp-crops-and-wash-away-any.html
My guess is that they don’t. But I’m willing to be surprised.
Sioned L (19:53:09) : [in the Sea Surface Temperature makes a jump” posting] says:
Interesting article in the Salt Lake Tribune today 11/02/09: “Scientists Find patterns in Utah’s wet-dry cycles”
http://www.sltrib.com/ci_13681950
Note the figure comparing SST in the southwestern Pacific to precipitation in Utah.
They have a good correlation with only a 3 – 4 year lag.
Compare this to the Charles A. Perry paper
http://ks.water.usgs.gov/waterdata/climate/c.perry.asr2007.pdf
which compares SST with Great Basin precipitation lagged 3 years (fig.5)
(then he goes on to 34 year lags)
Except that the data we have don’t support any climate connection. Although a bit dated, the following Figure
http://www.leif.org/research/CosmicRays-GeoDipole.jpg
shows how the Earth’s dipole moment and 14C [GCRs] have varied the past 10,000 years. The temperature variations do not fit that pattern.
Leif,
You are out of date. Svensmark has proposed that it is NOT simply overall cosmic ray flux but HIGH ENERGY cosmic ray flux (the muons that reach the lowest levels in the atmosphere). According to Svensmark, the earth’s magnetic field does not affect the highest energy cosmic rays (it only modulates the weaker kind). Svensmark has modified his theory to say that the earth’s magnetic field has little bearing on high energy cosmic rays.
Can you comment in light of this modification of his theory….certainly he is correct that most cosmic rays DO NOT reach the lower levels of the atmosphere…
This discussion reminds me of sitting on a beach by the sea lake and watching the waves. Something like Pooh sticks.
Speed boats criss cross the middle of the lake and about 20 minutes later their wake arrives at my feet. Except there are more than one boats, their wake hits the far shore and comes back too, and here I sit, watching my flip flops floating down beach guessing which speed boat driver to grumble at.
All these correlation chasing and lags come into focus if one seriously considers chaotic behavior, and climate science is a long way off on getting a real handle on it. It needs a change of mentality to be able to start thinking in terms of chaotic models. Tsonis et al have made a start, but it is just a start.
It is the proverbial elephant and four blind men parable.
I see the discussion continues to be off-the-rails regarding lags (& now smoothing too) —- let’s try this again:
The cause of the lag is simple. All one has to do is note the amount of time that passed between the ~1900 aa index low and the 30s drought.
A little more:
There are different kinds of lags.
Say I hear a train moving through hilly terrain. If I re-hear the whistle, the lag conveys info about a physical (lag) process.
Say I note a 6 month lag between NH & SH temperatures — that conveys info about anti-phase.
Say I note cyclical (time-integrated) cross-correlation, like here…
http://www.sfu.ca/~plv/ccLaaLR1crf4532.png
http://www.sfu.ca/~plv/ccLR1CRF.PNG
…that tells me I’m dealing with cycles (with similar period).
Say I note the 34 year lag being discussed here — that tells me global minima (in the 2 series) have hijacked my best-lag (…which is what people here are failing to realize).
I’m resorting (again) to being blunt because I am pressed for time, but nonetheless it is important to get the point across (perhaps less diplomatically than I would if I had more time).
This is basic Stat 101, part 2: intro regression. The global minima & global maxima have high leverage — THAT is what is going on here …but there are other things going on here too, like 11 year cycles (not just ones of solar origin – there is confounding) & even interannual shared-variance – i.e. it is complex (speaking more broadly) – but as for the “why 34 years?” – well, that is just dead-simple – understanding it is as simple as understanding why a regression line slopes upward if the data-points do so. [I think it probably helps with intuition-development if people have programmed their own cross-correlation analyzers and run dozens of familiar series through them; I realize not everyone has time for that, so I share these brief notes.]
anna v (22:38:18) “Tsonis et al have made a start, but it is just a start.”
These guys claim this:
“This is the first time that this mechanism, which appears consistent with the theory of synchronized chaos, is discovered in a physical system of the size and complexity of the climate system.”
They are not the pioneers of the methodology (but I suppose their claim might help keep the gravy train flowing…)
Ottawa (not Ottowa)
http://www.heartland.org/bin/media/newyork09/PowerPoint/Tim_Patterson.ppt
The wavelet images don’t convince me of much as they are presented. I’d want to run my own analyses before drawing conclusions.
Another Tim Patterson article:
http://sst.rncan.gc.ca/ercc-rrcc/workshop-atelier/dallimore/pdf/dallimore_e.pdf
Comment:
Nice pictures.
yonason (20:17:52) :
“Does that theory/hpothesis find that what happened on or about 1975 can predict the massive floods currently underway?
http://www.marketskeptics.com/2009/10/rains-swamp-crops-and-wash-away-any.html
My guess is that they don’t. But I’m willing to be surprised.”
Look at the chart above. 2009 shows a spike in this 34 year delay (1975 + 34 =) comparable to the spikes of prior floods.
Leif Svalgaard (16:10:00) :
The Earth’s magnetic field is the primary modulator of GCRs.
Leif Svalgaard (19:29:26) :
Geomagnetic activity [the aa-index] does NOT modulate GCRs.
[snip ~ I believe he was asking for clarification ~ ctm]
Thanks Charles. 😉
I see what Leif means now, and in the light of the the comment about Svensmark’s theory from Jeremy to Leif above,
“You are out of date. Svensmark has proposed that it is NOT simply overall cosmic ray flux but HIGH ENERGY cosmic ray flux (the muons that reach the lowest levels in the atmosphere). According to Svensmark, the earth’s magnetic field does not affect the highest energy cosmic rays (it only modulates the weaker kind).”
I’d be interested in any ideas about the way changes in the earth’s geomagnetic field affect GCR’s and climate. I’ve watched an interesting animation of the changes in the field from 1600AD and it’s highly suggestive that variation in the field affects climate at a regional and global scale. I suspect the effect of the geomagnetic field on GCR’s of various energies is proportional, rather than cutting off at high energy levels.
Paul Vaughan (23:33:05) :
NICE FIND!
Glenn (23:43:42) :
O.K., I see that now. But look at the graph in “Update2” where the sunspot data says exactly the opposite.
My problem is that I don’t see a mechanism. Maybe I just don’t know enough background material, though it seems few others here don’t seem to either, or they could explain it.
I don’t know how they came up with 34 years, except that the two phenomena match up pretty well, mostly, when that number is used [though the great flood of 1936 is completely missed, and an event that would have been predicted for 1960 never occurred].
I feel somewhat less uncomfortable with correlations in real time, but picking what appears to be an arbitrary period of more than 3 decades virtually screams for an explanation, and I don’t see they have given any; other than some general concepts, but they don’t give details on how they all fit together. Did I just not read carefully enough, or is there other material out there? Unless I see it, and it makes sense, I can’t.
Further to Paul Vaughan (22:41:07) …
Suggested exercises:
Remove the multi-decadal patterns and then re-run the cross-correlation analysis. See how that affects the best-lag for some insight.
Based on some of the comments, I can also suggest running multi-scale cross-wavelet phase-contrasts of aa, GCR, & solar variables (for constructive insights that aren’t forthcoming via linear-correlation analysis).
Best Regards.
@Leif Svalgaard
I’ve asked you 2 times before, why there is a correlation between climate (glacier stands in the Alps and in the Andes) and the LIA-minima, and you answered me both times, that there is no such correlation for the global climate (as far as I remember).
And here again you don’t answer my questions.
Do you think that the correlation found all over Europe, Greenland and now in the Andes is pure coincidence, or “luck”? Or do you think that there is a link between climate and the sun, but not on a global level.
Pro-Agw-scientists like Stefan Rahmstorf and Georg Hoffmann don’t answer my questions at all. I feel like I’m an actor in a truman show. I really hope that some of you scientists are little nicer to us laymen and try to give us answers. Very many people have the same questions!
I read these blogs and books now for more than 10 years and I still found no answers to these questions. In my opinion the sun-climate-link is obvious in Europe.
I would be very pleased to get an answer from you.
Thank you in adavance and have a nice day
Eddy
I was astounded to follow through Dr Gerhard Loebert’s comments, rather belatedly unfortunately. I think this man is on to something big. Even if he too has his personal limitations. I’ve long had my suspicions that even back of Svensmark is something deeper in the line of “causation” and that it has to do with quantum physics, Zero Point Field material – as Lynne McTaggart explains beautifully in her book of that name, and as I’ve seen other incidental evidence for elsewhere.
I’m certain that astrophysics is ultimately going to unravel and elucidate the prime drivers for climate. Not just the Sun but behind that, the SSB. Not just the SSB, but behind that, the galactic centre and the workings of the Zero Point Field. And always, statistically significant correlations necessary first, and likely to precede explanations of causation.
Paul Vaughan, I’d love to see a post by you here.
Edouard (01:54:06) :
“@Leif Svalgaard
I’ve asked you 2 times before, why there is a correlation between climate (glacier stands in the Alps and in the Andes) and the LIA-minima, and you answered me both times, that there is no such correlation for the global climate (as far as I remember).”
I too feel frustrated that answers are not forthcoming. I don’t think it’s because scientists don’t want to give us the answers, the real reason is that big systems like climate and solar activity display much turbulent chaotic behaviour and science is poor at dealing with these sorts of systems.
Worthwhile reading the post from anna v above, as this is a good illustration of why chaos is such a big problem when it comes to trying to understand what is happing now and trying to make predictions about the future.