From the HockeySchtick: A paper published today in the Journal of Atmospheric and Solar-Terrestrial Physics finds long solar cycles predict lower temperatures during the following solar cycle. A lag of 11 years [the average solar cycle length] is found to provide maximum correlation between solar cycle length and temperature. On the basis of the long sunspot cycle of the last solar cycle 23, the authors predict an average temperature decrease of 1C over the current solar cycle 24 from 2009-2020 for certain locations.
Highlights
► A longer solar cycle predicts lower temperatures during the next cycle.
► A 1 °C or more temperature drop is predicted 2009–2020 for certain locations.
► Solar activity may have contributed 40% or more to the last century temperature increase.
► A lag of 11 years gives maximum correlation between solar cycle length and temperature.
The authors also find “solar activity may have contributed 40% or more to the last century temperature increase” and “For 3 North Atlantic stations we get 63–72% solar contribution [to the temperature increase of the past 150 years]. This points to the Atlantic currents as reinforcing a solar signal.”
A co-author of the paper is geoscientist Dr. Ole Humlum, who demonstrated in a prior paper that CO2 levels lag temperature on a short-term basis and that CO2 is not the driver of global temperature.
The paper:
The long sunspot cycle 23 predicts a significant temperature decrease in cycle 24
Jan-Erik Solheim Kjell Stordahl Ole Humlumc DOI: 10.1016/j.jastp.2012.02.008
Abstract
Relations between the length of a sunspot cycle and the average temperature in the same and the next cycle are calculated for a number of meteorological stations in Norway and in the North Atlantic region. No significant trend is found between the length of a cycle and the average temperature in the same cycle, but a significant negative trend is found between the length of a cycle and the temperature in the next cycle. This provides a tool to predict an average temperature decrease of at least 
from solar cycle 23 to solar cycle 24 for the stations and areas analyzed. We find for the Norwegian local stations investigated that 25–56% of the temperature increase the last 150 years may be attributed to the Sun. For 3 North Atlantic stations we get 63–72% solar contribution. This points to the Atlantic currents as reinforcing a solar signal.
1. Introduction
The question of a possible relation between solar activity and the Earth’s climate has received considerable attention during the last 200 years. Periods with many sunspots and faculae correspond with periods with higher irradiance in the visual spectrum and even stronger response in the ultraviolet, which acts on the ozone level. It is also proposed that galactic cosmic rays can act as cloud condensation nuclei, which may link variations in the cloud coverage to solar activity, since more cosmic rays penetrate the Earth’s magnetic field when the solar activity is low. A review of possible connections between the Sun and the Earth’s climate is given by Gray and et al. (2010).
Based on strong correlation between the production rate of the cosmogenic nucleids 14C and 10Be and proxies for sea ice drift, Bond et al. (2001) concluded that extremely weak perturbations in the Sun’s energy output on decadal to millennial timescales generate a strong climate response in the North Atlantic deep water (NADW). This affects the global thermohaline circulation and the global climate. The possible sun–ocean–climate connection may be detectable in temperature series from the North Atlantic region. Since the ocean with its large heat capacity can store and transport huge amounts of heat, a time lag between solar activity and air temperature increase is expected. An observed time lag gives us an opportunity for forecasting, which is the rationale for the present investigation.
Comparing sunspot numbers with the Northern Hemisphere land temperature anomaly, Friis-Christensen and Lassen (1991) noticed a similar behavior of temperature and sunspot numbers from 1861 to 1990, but it seemed that the sunspot number R appeared to lag the temperature anomaly. They found a much better correlation between the solar cycle length (SCL) and the temperature anomaly. In their study they used a smoothed mean value for the SCL with five solar cycles weighted 1-2-2-2-1. They correlated the temperature during the central sunspot cycle of the filter with this smoothed weighted mean value for SCL. The reason for choosing this type of filter was that it has traditionally been used to describe long time trends in solar activity. However, it is surprising that the temperature was not smoothed the same way. In a follow up paper Reichel et al. (2001) concluded that the right cause-and-effect ordering, in the sense of Granger causality, is present between the smoothed SCL and the cycle mean temperature anomaly for the Northern Hemisphere land air temperature in the 20th century at the 99% significance level. This suggests that there may exist a physical mechanism linking solar activity to climate variations.
The length of a solar cycle is determined as the time from the appearance of the first spot in a cycle at high solar latitude, to the disappearance of the last spot in the same cycle near the solar equator. However, before the last spot in a cycle disappears, the first spot in the next cycle appears at high latitude, and there is normally a two years overlap. The time of the minimum is defined as the central time of overlap between the two cycles (Waldmeier, 1939), and the length of a cycle can be measured between successive minima or maxima. A recent description of how the time of minimum is calculated is given by NGDC (2011): “When observations permit, a date selected as either a cycle minimum or maximum is based in part on an average of the times extremes are reached in the monthly mean sunspot number, in the smoothed monthly mean sunspot number, and in the monthly mean number of spot groups alone. Two more measures are used at time of sunspot minimum: the number of spotless days and the frequency of occurrence of old and new cycle spot groups.”
It was for a long time thought that the appearance of a solar cycle was a random event, which means that each cycle length and amplitude were independent of the previous. However, Dicke (1978) showed that an internal chronometer has to exist inside the Sun, which after a number of short cycles, reset the cycle length so the average length of 11.2 years is kept. Richards et al. (2009) analyzed the length of cycles 1610–2000 using median trace analyses of the cycle lengths and power spectrum analyses of the O–C residuals of the dates of sunspot maxima and minima. They identified a period of 188±38 years. They also found a correspondence between long cycles and minima of number of spots. Their study suggests that the length of sunspot cycles should increase gradually over the next 
. accompanied by a gradual decrease in the number of sunspots.
An autocorrelation study by Solanki et al. (2002) showed that the length of a solar cycle is a good predictor for the maximum sunspot number in the next cycle, in the sense that short cycles predict high Rmax and long cycles predict small Rmax. They explain this with the solar dynamo having a memory of the previous cycle’s length.
Assuming a relation between the sunspot number and global temperature, the secular periodic change of SCL may then correlate with the global temperature, and as long as we are on the ascending (or descending) branches of the 188 year period, we may predict a warmer (or cooler) climate.
It was also demonstrated (Friis-Christensen and Lassen, 1992, Hoyt and Schatten, 1993 and Lassen and Friis-Christensen, 1995) that the correlation between SCL and climate probably has been in operation for centuries. A statistical study of 69 tree rings sets, covering more than 594 years, and SCL demonstrated that wider tree-rings (better growth conditions) were associated with shorter sunspot cycles (Zhou and Butler, 1998).
-
Fig. 1.Length of solar cycles (inverted) 1680–2009. The last point refers to SC23 which is 12.2 years long. The gradual decrease in solar cycle length 1850–2000 is indicated with a straight line.
…
5. Conclusions
Significant linear relations are found between the average air temperature in a solar cycle and the length of the previous solar cycle (PSCL) for 12 out of 13 meteorological stations in Norway and in the North Atlantic. For nine of these stations no autocorrelation on the 5% significance level was found in the residuals. For four stations the autocorrelation test was undetermined, but the significance of the PSCL relations allowed for 95% confidence level in forecasting for three of these stations. Significant relations are also found for temperatures averaged for Norway, 60 European stations temperature anomaly, and for the HadCRUT3N temperature anomaly. Temperatures for Norway and the average of 60 European stations showed indifferent or no autocorrelations in the residuals. The HadCRUT3N series showed significant autocorrelations in the residuals.
For the average temperatures of Norway and the 60 European stations, the solar contribution to the temperature variations in the period investigated is of the order 40%. An even higher contribution (63–72%) is found for stations at Faroe Islands, Iceland and Svalbard. This is higher than the 7% attributed to the Sun for the global temperature rise in AR4 (IPCC, 2007). About 50% of the HadCRUT3N temperature variations since 1850 may be attributed solar activity. However, this conclusion is more uncertain because of the strong autocorrelations found in the residuals.
The significant linear relations indicate a connection between solar activity and temperature variations for the locations and areas investigated. A regression forecast model based on the relation between PSCL and the average air temperature is used to forecast the temperature in the newly started solar cycle 24. This forecast model benefits, as opposed to the majority of other regression models with explanatory variables, to use an explanatory variable–the solar cycle length–nearly without uncertainty. Usually the explanatory variables have to be forecasted, which of cause induce significant additional forecasting uncertainties.
Our forecast indicates an annual average temperature drop of 0.9 °C in the Northern Hemisphere during solar cycle 24. For the measuring stations south of 75N, the temperature decline is of the order 1.0–1.8 °C and may already have already started. For Svalbard a temperature decline of 3.5 °C is forecasted in solar cycle 24 for the yearly average temperature. An even higher temperature drop is forecasted in the winter months (Solheim et al., 2011).
Arctic amplification due to feedbacks because of changes in snow and ice cover has increased the temperature north of 70N a factor 3 more than below 60N (Moritz et al., 2002). An Arctic cooling may relate to a global cooling in the same way, resulting in a smaller global cooling, about 0.3–0.5 °C in SC24.
Our study has concentrated on an effect with lag once solar cycle in order to make a model for prediction. Since solar forcing on climate is present on many timescales, we do not claim that our result gives a complete picture of the Sun’s forcing on our planet’s climate.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
It is interesting that the solar northern magnetic field intensity two years after reversal has returned to its previous polarity. The solar wind, sunspots, and the solar coronal holes strip the magnetic flux off of the surface of the sun. If the magnetic flux tubes no longer have the magnetic field strength to survive their trip through the solar convection zone the solar large scale magnetic field will drop to very, very low levels.
http://www.solen.info/solar/polarfields/polar.html
There are cycles of warming and cooling in the paleo climatic record that correlate with the solar magnetic cycles (500 year cycle and 1500 year cycle). There are unexplained very, very, large abrupt climate changes (these abrupt climate changes initiate and terminate interglacial periods, the abrupt climate changes have a periodicity of 8000 to 10,000 years and also visible in the paleoclimatic record during the glacial period) that also correlate with solar magnetic cycle changes and that correlate with abrupt unexplained changes to the geomagnetic field.
In the 1990’s it was discovered for some unexplained reason the magnetic field strength of newly formed individual sunspots was decaying linearly. The sunspots are formed from magnetic flux tubes (there are other competing theories as to what creates sunspots, Livingston and Penn’s observation and the replacement of large sunspots with pores supports the assertion that a tachocline type mechanism is the source of the flux tubes that create sunspots) that are created by some mechanism deep within the sun at the solar tachocline. The magnetic flux tubes rise up to the surface of the sun where they form sunspots on the surface of the sun.
To avoid being torn apart by the turbulent forces in the convection zone the magnetic flux tubes require a magnetic field strength of around 40,000 gauss when they leave the tachocline (the magnetic flux tubes expand as they rise through the convection and loss magnetic flux, the magnetic field strength of sunspots on the surface of the sun is 2000 to 5000 gauss).
Observational evidence to support the assertion that the magnetic flux tubes are formed at the tachocline is large integrated sunspots (observed in past solar cycles) are being replaced by regions that contain many tiny sunspots (pores).
http://arxiv.org/abs/1009.0784
Long-term Evolution of Sunspot Magnetic Fields
Independent of the normal solar cycle, a decrease in the sunspot magnetic field
strength has been observed using the Zeeman-split 1564.8nm Fe I spectral line at the
NSO Kitt Peak McMath-Pierce telescope. Corresponding changes in sunspot brightness
and the strength of molecular absorption lines were also seen. This trend was seen to
continue in observations of the first sunspots of the new solar Cycle 24, and extrapolating
a linear fit to this trend would lead to only half the number of spots in Cycle 24 compared
to Cycle 23, and imply virtually no sunspots in Cycle 25.
[nope, don’t see it in here . . mod]
Ok, I’ll try again:
See here:
http://www.newclimatemodel.com/the-link-between-solar-cycle-length-and-decadal-global-temperature/
From April 2008 and subsequently updated.
For more detail as to the relevant mechanism, see here:
http://www.newclimatemodel.com/new-climate-model/
Changes in solar activity levels appear to alter the gradient of tropopause height between equator and poles so as to change global cloudiness and affect the proportion of solar energy that enters the oceans to drive the climate system.
The balance between El Nino and La Nina changes to cause variations in air temperatures.
jmorpuss says:
June 14, 2014 at 2:40 am
Good question, jmorpuss, and the answer is nope … but I don’t have to. The entire anthropogenic energy consumption is about 1/10,000 of the top-of-atmosphere incoming solar energy. As a result, the tiny fraction of that human consumption going into radio waves is meaninglessly small.
Regards,
w.
Willis Eschenbach says:
June 14, 2014 at 1:10 am
Extra energy comes from the higher proportion of UV in total solar irradiance, and the effects thereof. With TSI about constant, more high-energy UV means less lower-energy visible and IR, along with greater insolation, especially of tropical oceans.
I would have thought the answer to this question was obvious, now that science has discovered that TSI isn’t spectrally constant.
David Archibald says:
June 14, 2014 at 3:12 am
Thanks for that, David, and you’re right, moving too fast.
However, my point remains. You can’t explain away the lack of effect of the strength of the solar cycle on the climate by substituting the length of the solar cycle, because they are well correlated and (obviously) they run on the same time cycle.
I’ve had time to take a look at the paper. Here were my predictions before opening it:
And indeed, they use 11-year running means of temperatures, and compare them to cycle lengths, which are defined as the period between successive minima. The 11-year running mean filter is likely the worst possible choice for smoothing.
And indeed, their correlation results are for smoothed data.
They discuss the effect of autocorrelation of the residuals, but they don’t discuss the effect of autocorrelation of the data itself.
Finally, they seem totally unaware of needing to adjust for the number of trials.
I have the Armagh data, so I’ll see if I can replicate their results for Armagh.
w.
Catherine, please explain the effects thereof. The UV portion does indeed have energy, but far less than solar IR, and visible light. We can calculate how much the Sun’s insolation (the entire spectrum hitting the Earth’s surface), and in particular the much stronger portion of the energy, can affect our climate.
Consider what would happen when a small change in atmospheric transparency (IE when a really really big volcano goes off and then burps and gurgles) does to Earth. But never mind that, lets get really scared over UV.
http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCYQFjAA&url=http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1111%2Fj.2153-3490.1969.tb00466.x%2Fpdf&ei=pr2cU43SD5eqyAT0mYDACg&usg=AFQjCNFCCxh0vKlGH5j8wVUx5J916cvwYA&sig2=Km97ND9nKkLcJceliIFj8w&bvm=bv.68911936,d.aWw
Pamela Gray says:
June 14, 2014 at 2:33 pm
The point, as again I thought would be obvious, is that the UV portion of TSI is elevated for years over its low. This variance, unknown until recently, alone accounts for a big part of the solar influence on climate, unknown when the still ignorant models were designed.
Factor in solar magnetic effects & atmospheric & surface amplification thereof, & the supposed mystery of the three warming phases of the Modern Warm Period is largely solved.
Now we’re getting somewhere. Time lag effect is like an artifact from the past that still affects us in the present and dissipates in the future.
The Earth’s atmosphere and climate acts somewhat like a thermos made of Union Carbide Super insulation.
“However, Dicke (1978) showed that an internal chronometer has to exist inside the Sun, which after a number of short cycles, reset the cycle length so the average length of 11.2 years is kept.”
The average cycle length is 11.07yrs, and the chronometer is external, there is a very specific planetary progression that causes solar grand minimums and the associated longer cycles. It readily marks which cycles are effected in each solar downturn.
“Arctic amplification due to feedbacks because of changes in snow and ice cover has increased the temperature north of 70N a factor 3 more than below 60N (Moritz et al., 2002). An Arctic cooling may relate to a global cooling in the same way, resulting in a smaller global cooling, about 0.3–0.5 °C in SC24.”t
Arctic warming picked up from 1995 with the switch to a warm AMO when solar plasma forcing started waning. The Arctic Ocean region was cooling up till then:
http://snag.gy/mfOI7.jpg
Hard cooling in the Temperate Zone under increased negative AO/NAO conditions is going to see the AMO and Arctic stay warm.
OK … I give up. I can’t find anywhere in their methods section just how they are doing what they claim. Here’s the problem.
ORIGINAL CAPTION: Fig. 1.
Length of solar cycles (inverted) 1680–2009. The last point refers to SC23 which is 12.2 years long. The gradual decrease in solar cycle length 1850–2000 is indicated with a straight line.
Now, some investigation shows that the cycle length is displayed right at the middle of that cycle. But here’s the part I don’t understand.
They say that they are using an 11-year “boxcar” moving average, viz:
My problem is this. They are comparing an annual value with a greatly reduced dataset. The full annual sunspot dataset from say 1680 on contains about 330 data points. But as Figure 1 clearly shows, the number of cycle lengths for the same period is only 30 data points.
Now, note that the cycles represented by this string of cycle lengths are NOT equally spaced in time.
But their study says that they are looking at lags year-by-year … how can you do that when a) the cycle lengths are not evenly spaced, and b) there are only 30 of them?
There are several possible ways to deal with this.
One is to only use the mid-years of the cycle, the exact dataset shown in Fig. 1 above, and correlate the 30 data points with the corresponding 30 data points in the 11-year-averaged temperature data. Then you shift over by one year, and correlate that with the next corresponding 30 datapoints in the 11-year-averaged temperature datasets. I suspect that that is how they are going about it, but unfortunately, they haven’t said how they did it. And I’m reluctant to put in too much time if that’s not how they’ve done it.
There’s an additional oddity, which is that the cycle length data is in months (actually decimal years) and the temperature and lag data are in years. However, that’s not the main issue.
The main problem for me is their calculation of statistical significance. They are using a bizarre underlying measure. IF they are doing it as I suspect, this is the correlation of ~30 sunspot cycle-length values centered on their respective irregularly-spaced cycles, with a corresponding subset of ~30 11-year-averaged temperature values.
I know of no way to theoretically estimate the statistics of this situation, in part because the use of irregularly spaced samples, along with using the sample spacing itself as the amplitude, seems guaranteed to muddy the waters. Combine that with using 11-year boxcar averages at the other end, so that the aand we’re well past the statistical event horizon.
The only way I can see to reliably tell what kind of results we would expect from those strange procedures would be a “Monte Carlo” analysis. Fortunately, in this case it would be pretty easy to do. All you have to do is to shuffle the cycle lengths randomly to create pseudo-cycle-length data, use it in their procedure, and see what the correlations do or don’t look like … but they haven’t done that.
I’d take a look myself if I knew for sure that was how they did their calculations … but since their description of the method was lacking that section, I’m unwilling to do it only to find out that they used some other method.
Finally, they’ve totally ignored the data selection issue. Look, they only have 30 data points, which make a very rough 150-year curve. With so few points, the odds of finding some region on this lovely planet with a decent correlation to those thirty pathetic points is quite great. And in this case, the region covered by their Figure 2 is a whopping .. wait for it …
… the temperature stations cover a whopping 2% of the world’s surface. How about them showing us a random selection of temperature datasets from around the planet, and how well they correspond to the sunspot cycle lengths?
Until they correct those gaping lacunae, I wouldn’t advise for publication … also, the perennial lack of code and data is getting old.
Color me under-impressed … another study that’s not ready for prime time.
w.
Interesting to see that the shortest cycle was in the 1690’s, the coldest part of the Maunder Minimum: http://ars.els-cdn.com/content/image/1-s2.0-S1364682612000417-gr1.jpg
Ulric, so what. Lots of things happened during the LIA. Doesn’t mean there is a connection. During the early to late 70’s I got my Bachelors. And it was cold. Doesn’t mean I caused it. To the contrary lolol!
Catherine, no it doesn’t. UV is a very SMALL portion of the variance in temperature related to solar irradiance and insolation. Where are you getting your speculation from? Certainly not physics.
Ulric Lyons says:
June 14, 2014 at 5:19 pm (Edit)
Actually, in the dataset that it appears that they used (they don’t actually specify but this agrees completely with Fig. 1), the shortest cycle was 1610.
However, given the usual idea of shorter = stronger, it is curious that such a short cycle is in the coldest part of the Maunder Minimum. I probably should look at a scatter plot of strength vs length …
w
@ur momisugly Willis thanks for the reply
We can see the process of convection and conduction at work when looking at the sun . Heat is always trying to escape it’s strong electromagnetic pull through convection but as hydrogen cools it turns positive as it looses electrons and is drawn back to the surface to repeat the process.here’s how I see things, Earth has a sun at it’s core ,temperature wise anyway (6000 Deg’s) and is responsible for the heating process here on Earth through the same process we see the sun using, heat trying to escape (convection ) and conduction pulling it back to the surface . The solar wind is cold when it reaches Earths first line of defence , the bow shock, this is were the solar wind meets the resistance created by Earths energy release to space. The surface of the Earth is very conductive and because energy will take the path of least resistance it spreads out the electric potential ,as electric potential builds at the surface it is released as point charges to the atmosphere (low pressure system) mountains are very important for this energy release. If temperature = electric potential at work and temperature decreases with height then the energy released is passive unlike if it is released at sea level were they can spin up and cause tornados and water spouts ,a conduction pathway opens up (AC pathway) when convection stops and conduction takes over ossolation starts driven by negative ions in the up direction and positive ions in the down direction. The temperature of the tropopause (electromagnetic field line) 90 Deg’s to the sun is about 4 Deg’s C . Radio stands for Radiated Electromagnetic Wave and uses conduction to propagate. Why can’t we use rectennas to capture electrons at the antenna to help charge batteries? Solar works on the day side a rectenna would also work of a night. How much energy does the sun supply on the dark side, man pumps terrawatts of heat energy of a night when the sun provides none.
Stephen Wilde says:
June 14, 2014 at 12:16 pm
Changes in solar activity levels appear to alter the gradient of tropopause height between equator and poles so as to change global cloudiness and affect the proportion of solar energy that enters the oceans to drive the climate system.
———————————————————————-
What would a incremental increase in Earth’s rotation rate, have on the tropospheric height between the equator and poles have?
THE IERS BULLETIN C
AND THE PREDICTION OF LEAP SECONDS
Daniel Gambis*
http://www.cacr.caltech.edu/futureofutc/preprints/files/42_AAS%2013-522_Gambis.pdf
page 4
It appears that, since the year 2000, the Earth is relatively speeding up,
and the rate of introduction of leap seconds has significantly decreased.
Figure 3.
Leap seconds per year between 1972 and 2010 (courtesy of W. Dick8, 2011)
Addition to figure 3 was 1 leap second added in 2012, making the graph 1972 to 2014 (me).
Only 3 leap seconds have been added from 1999 to 2014.
Compare to the 22 leap seconds added from 1972 to 1998.
Also, appears to follow solar magnetic activity decline of solar cycles 23 and 24. There’s been a decline in high speed wind streams from high latitude coronal holes, slower overall wind speed, lower dipolar fields, fewer sunspots and related geomagnetic disturbances.
What else happens when the Earth’s rotation speeds up?
The north/south magnetic poles stop accelerating, slow down, stabilize and Earth’s dipole magnetic field begins to strengthen. Faster rotation stronger dipole field. This also a implies a stronger/larger/longer lasting planetary vortex, which will push cold air towards the equator. We saw the battle last winter. For this planet, an established atmospheric pattern, of old.
On the other hand over the solar cycle period from 1910 to 1999 we saw an increasing trend toward declining magnetic field strength at Earth with an erratic and accelerating north magnetic pole.
Slower rotation..
Rotational forces from Earth’s equator showing incremental domination over its polar rotational forces. This brought more northward moving currents and air.
Not to mention the dayside reconnection rate incrementally increasing over the same period contributing to that slow down (dayside cusps) geesh..
Increasing solar magnetic cycle, declining earth magnetic field.
Decreasing solar magnetic cycle, increasing earth magnetic field.
Earth’s dipole magnetic field is related to rotation rate.
I think the sun’s dipole field strength is related to it’s polar rotation rate also.
Willis Eschenbach says:
“Actually, in the dataset that it appears that they used (they don’t actually specify but this agrees completely with Fig. 1), the shortest cycle was 1610.”
I would take that with a pinch of salt, the start date of the following cycle could easily be a year later. The records are not very clear back that far.
“I probably should look at a scatter plot of strength vs length …”
There’s no SSN info previous to cycle -1:
http://umbra.nascom.nasa.gov/sdb/ydb/indices_flux_raw/sunspot.maxmin.tbl
I really, really, really do not need anyone to discredit this study. I’ve been stockpiling several varieties of whiskys for years now in anticipation of an ice age. I anticipate getting the ice to drink all that with for little or no cost, either monetary or energy. No Ice Age means I have to pay for the ice. Not the scenario I’ve plugged into.
oops looks like a couple duplicate posts up thar.. help..
New findings on the effect of Earth’s rotational capability. Earth rotation, playing all the way out, to the radiation belts. Gee, we barely understand the effects close to the surface..
Rotationally driven ‘zebra stripes’ in Earth’s inner radiation belt
Published online 19 March 2014
A. Y. Ukhorskiy, M. I. Sitnov, D. G. Mitchell,
K. Takahashi, L. J. Lanzerotti & B. H. Mauk
Structured features on top of nominally smooth distributions of radiation-belt particles at Earth have been previously associated with particle acceleration and transport mechanisms powered exclusively by enhanced solar-wind activity1, 2, 3, 4. Although planetary rotation is considered to be important for particle acceleration at Jupiter and Saturn5, 6, 7, 8, 9, the electric field produced in the inner magnetosphere by Earth’s rotation can change the velocity of trapped particles by only about 1–2 kilometres per second, so rotation has been thought inconsequential for radiation-belt electrons with velocities of about 100,000 kilometres per second. Here we report that the distributions of energetic electrons across the entire spatial extent of Earth’s inner radiation belt are organized in regular, highly structured and unexpected ‘zebra stripes’, even when the solar-wind activity is low. Modelling reveals that the patterns are produced by Earth’s rotation….
http://www.nature.com/nature/journal/v507/n7492/abs/nature13046.html#figures
OK.
Then,
(1) assuming you can assign “something” discrete to an end-of-cycle n-1, start of cycle n, end of cycle n, start of cycle n+1 dates (maybe odd/even values? ) then
(2) assuming you assign a strength-of-cycle value to ??? (maybe total number of sunspots in the cycle (between the cycle start and cycle end dates ?)
then your question could become very, very interesting:
Is the total number of spots/cycle about the same?
Is the total number of spots increasing/decreasing/remaining the same as cycle length changes over time?
Is cycle length changing over time?
Are the odd number cycles changing (length, total, or maximum/minimum) over time?
Are the even number cycles changing?
‘Tis interesting that the basics are not known at this time.
Dang … is nothing sacred? Now I find that in fact there is no relationship between cycle length and cycle strength …
Who knew?
This is using the SIDC data adjusted per Leif Svalgaard. However, I also ran the analysis using the dataset they used … same result. No significant trend.
w.
Catherine Ronconi said:
“Extra energy comes from the higher proportion of UV in total solar irradiance, and the effects thereof. With TSI about constant, more high-energy UV means less lower-energy visible and IR, along with greater insolation, especially of tropical oceans.”
I don’t think that is a sufficiently large effect since it results in only a tiny change in total energy delivery as Leif often points out.
That is why I go for an amplification effect involving ozone amounts in the stratosphere and consequent changes in global cloudiness which affects the proportion of all wavelengths from the sun able to enter the oceans.
“Interesting to see that the shortest cycle was in the 1690′s, the coldest part of the Maunder Minimum: http://ars.els-cdn.com/content/image/1-s2.0-S1364682612000417-gr1.jpg”
It was only one short sharp cycle amongst many much longer cycles. It has already been noted that a single cycle has little effect on its own. A run of long or short cycles is required to allow the effect to build up in the oceans over time. The effect of a single cycle is also largely swamped by inherent chaotic variability within the system due to the long lag times involved in the ocean thermohaline circulation of 1000 to 1500 years.
As to why such a short solar cycle was embedded amongst so many very different cycles is another matter.
Willis said:
“Dang … is nothing sacred? Now I find that in fact there is no relationship between cycle length and cycle strength …Who knew ?”
Well I knew if one limits one’s consideration to sunspot numbers (taking size into account) because one gets a similar figure for less sunspots over a long period as for more sunspots over a shorter period.
That is why I’ve pinned my ideas to a change in UV wavelengths and solar particles rather then sunspots. We see them change much more over the course of a single cycle and even more across multiple cycles of longer or shorter lengths.
Then there is the amplification factor of global cloudiness changes to consider.