Dr. Roger Pielke Sr. writes about a new paper from Nicola Scafetta.:
A new paper has just appeared
Nicola Scafetta 2011: A shared frequency set between the historical mid-latitude aurora records and the global surface temperature. Journal of Atmospheric and Solar-Terrestrial Physics In Press doi:10.1016/j.jastp.2011.10.013
This paper is certainly going to enlarge the debate on the role of natural climate variability and long term change.
The abstract reads [highlight added]
Herein we show that the historical records of mid-latitude auroras from 1700 to 1966 present oscillations with periods of about 9, 10–11, 20–21, 30 and 60 years. The same frequencies are found in proxy and instrumental global surface temperature records since 1650 and 1850, respectively, and in several planetary and solar records. We argue that the aurora records reveal a physical link between climate change and astronomical oscillations. Likely in addition to a Soli-Lunar tidal effect, there exists a planetary modulation of the heliosphere, of the cosmic ray flux reaching the Earth and/or of the electric properties of the ionosphere. The latter, in turn, has the potentiality of modulating the global cloud cover that ultimately drives the climate oscillations through albedo oscillations. In particular, a quasi-60-year large cycle is quite evident since 1650 in all climate and astronomical records herein studied, which also include a historical record of meteorite fall in China from 619 to 1943. These findings support the thesis that climate oscillations have an astronomical origin. We show that a harmonic constituent model based on the major astronomical frequencies revealed in the aurora records and deduced from the natural gravitational oscillations of the solar system is able to forecast with a reasonable accuracy the decadal and multidecadal temperature oscillations from 1950 to 2010 using the temperature data before 1950, and vice versa. The existence of a natural 60-year cyclical modulation of the global surface temperature induced by astronomical mechanisms, by alone, would imply that at least 60–70% of the warming observed since 1970 has been naturally induced. Moreover, the climate may stay approximately stable during the next decades because the 60-year cycle has entered in its cooling phase.
The highlights listed in the announcement of the paper read
► The paper highlights that global climate and aurora records present a common set of frequencies. ► These frequencies can be used to reconstruct climate oscillations within the time scale of 9–100 years. ► An empirical model based on these cycles can reconstruct and forecast climate oscillations. ► Cyclical astronomical physical phenomena regulate climate change through the electrification of the upper atmosphere. ► Climate cycles have an astronomical origin and are regulated by cloud cover oscillations.
========================================================
Dr. Scafetta writes in and attaches the full paper in email to me (Anthony) this week saying:
I can forecast climate with a good proximity. See figure 11. In this new paper the physical link between astronomical oscillations and climate is further confirmed.
What the paper does is to show that the mid-latitude aurora records present the same oscillations of the climate system and of well-identified astronomical cycles. Thus, the origin of the climatic oscillations is astronomical what ever the mechanisms might be.
In the paper I argue that the record of this kind of aurora can be considered a proxy for the electric properties of the atmosphere which then influence the cloud cover and the albedo and, consequently, causes similar cycles in the surface temperature.
Note that aurora may form at middle latitude or if the magnetosphere is weak, so it is not able to efficiently deviate the solar wind, or if the solar explosions (solar flare etc) are particularly energetic, so they break in by force.
During the solar cycle maxima the magnetosphere gets stronger so the aurora should be pushed toward the poles. However, during the solar maxima a lot of solar flares and highly energetic solar explosions occurs. As a consequence you see an increased number of mid-latitude auroras despite the fact that the magnetosphere is stronger and should push them toward the poles.
On the contrary, when the magnetosphere gets weaker on a multidecadal scale, the mid-latitude aurora forms more likely, and you may see some mid-latitude auroras even during the solar minima as Figure 2 shows.
In the paper I argue that what changes the climate is not the auroras per se but the strength of the magnetosphere that regulates the cosmic ray incoming flux which regulate the clouds.
The strength of the magnetosphere is regulated by the sun (whose activity changes in synchrony with the planets), but perhaps the strength of the Earth’s magnetosphere is also regulated directly by the gravitational/magnetic forces of Jupiter and Saturn and the other planets whose gravitational/magnetic tides may stretch or compress the Earth’s magnetosphere in some way making it easier or more difficult for the Earth’s magnetosphere to deviate the cosmic ray.
So, when Jupiter and Saturn get closer to the Sun, they may do the following things: 1) may make the sun more active; 2) the more active sun makes the magnetosphere stronger; 3) Jupiter and Saturn contribute with their magnetic fiend to make stronger the magnetic field of the inner part of the solar system; 4) the Earth’ magnetosphere is made stronger and larger by both the increased solar activity and the gravitational and magnetic stretching of it caused by the Jupiter and Saturn. Consequently less cosmic ray arrive on the Earth and less cloud form and there is an heating of the climate.
However, explaining in details the above mechanisms is not the topic of the paper which is limited to prove that such kind of mechanisms exist because revealed by the auroras’s behavior.
The good news is that even if we do not know the physical nature of these mechanisms, climate may be in part forecast in the same way as the tides are currently forecast by using geometrical astronomical considerations as I show in Figure 11.
The above point is very important. When trying to predict the tides people were arguing that there was the need to solve the Newtonian Equation of the tides and the other physical equations of fluid-dynamics etc. Of course, nobody was able to do that because of the enormous numerical and theoretical difficulty. Today nobody dreams to use GCMs to predict accurately the tides. To overcome the issue Lord Kelvin argued that it is useless to use the Newtonian mechanics or whatever other physical law to solve the problem. What was important was only to know that a link in some way existed, even if not understood in details. On the basis of this, Lord Kelvin proposed an harmonic constituent model for tidal prediction based on astronomical cycles. And Kelvin method is currently the only method that works for predicting the tides. Look here:
http://en.wikipedia.org/wiki/Tide-predicting_machine
Figure 11 is important because it shows for the first time that climate can be forecast based on astronomical harmonics with a good accuracy. I use a methodology similar to Kelvin’s one and calibrate the model from 1850 to 1950 and I show that the model predicts the climate oscillations from 1950 to 2010, and I show also that the vice-versa is possible.
Of course the proposed harmonic model may be greatly improved with additional harmonics. In comparison the ocean tides are predicted with 35-40 harmonics.
But this does not change the results of the paper that is: 1) a clearer evidence that a physical link between the oscillations of the solar system and the climate exists, as revealed by the auroras’ behavior; 2) this finding justifies the harmonic modeling and forecast of the climate based on astronomical cycles associated to the Sun, the Moon and the Planets.
So, it is also important to understand Kelvin’s argument to fully understand my paper.
…
This work is the natural continuation of my previous work on the topic.
Nicola Scafetta. Empirical evidence for a celestial origin of the climate
oscillations and its implications. Journal of Atmospheric and Solar-Terrestrial Physics Volume 72, Issue 13, August 2010, Pages 951-970
http://www.sciencedirect.com/science/article/pii/S1364682610001495
Abstract
We investigate whether or not the decadal and multi-decadal climate
oscillations have an astronomical origin. Several global surface temperature
records since 1850 and records deduced from the orbits of the planets
present very similar power spectra. Eleven frequencies with period between 5
and 100 years closely correspond in the two records. Among them, large
climate oscillations with peak-to-trough amplitude of about 0.1 and 0.25°C,
and periods of about 20 and 60 years, respectively, are synchronized to the
orbital periods of Jupiter and Saturn. Schwabe and Hale solar cycles are
also visible in the temperature records. A 9.1-year cycle is synchronized to
the Moon’s orbital cycles. A phenomenological model based on these
astronomical cycles can be used to well reconstruct the temperature
oscillations since 1850 and to make partial forecasts for the 21st century.
It is found that at least 60% of the global warming observed since 1970 has
been induced by the combined effect of the above natural climate
oscillations. The partial forecast indicates that climate may stabilize or
cool until 2030–2040. Possible physical mechanisms are qualitatively
discussed with an emphasis on the phenomenon of collective synchronization
of coupled oscillators.
=======================================================
The claims here are pretty bold, and I’ll be frank and say I can’t tell the difference between this and some of the cycl0-mania calculation papers that have been sent to me over the last few years. OTOH, Basil Copeland and I looked at some of the effects of luni-solar on global temperature previously here at WUWT.
While the hindcast seems impressive, a real test would be a series of repeated and proven short-term future forecasts. Time will tell.
Leif, my papers do not adopt circular reasoning and I do not build the solar models on the temperature data. My papers adopts TSI model proposed by several other people and contain numerous tests to check that the models have reconstructiong and forecasting climatic capabilities. And my models are shown to actually get the data as well as it could be done.
Your models instead do not explain anything, no climate change patterns as known during any time scale can be reproduced by your TSI model because the variation is too small.
“The 0.1% variation of TSI depends on the magnetic field as evidenced by the very close fit of observed TSI to observed magnetic activity”.
Well, it is not so close. It depends on the TSI records that you are using. Remember that PMOD alters some TSI observations to make its composite to fit the decadal trending of the observed magnetic activity. That is true circular reasoning! ACRIM presents a very different pattern.
“Since the energy generated in the core takes ~250,000 years to diffuse out through the radiative zone, variations of a time scale much shorter than that are completely washed out.”
The things may not be so simple, the solar interior may not be in perfect equilibrium 🙂
Who knows why there is a variation in the solar cycle 🙂
If you change idea about the travel reinboursement offer, let me know.
Nicola Scafetta says:
December 19, 2011 at 1:28 pm
Leif, my papers do not adopt circular reasoning and I do not build the solar models on the temperature data. My papers adopts TSI model proposed by several other people and contain numerous tests to check that the models have reconstructiong and forecasting climatic capabilities. And my models are shown to actually get the data as well as it could be done.
You pick the TSI reconstruction [e.g. involving ESS2] that fits the temperature best. This is circular reasoning. The TSI models you cherry pick have been constructed based on a myth, namely that solar activity now is the highest in the last several thousand years and that the group sunspot number is correct plus that there is a background that varies with the envelope of the solar cycle. All of these assumptions are dubious, if not outright wrong.
Your models instead do not explain anything, no climate change patterns as known during any time scale can be reproduced by your TSI model because the variation is too small.
Which simply shows that the sun does not control the climate.
It depends on the TSI records that you are using.
You tend to cherry pick to get a match with the temperature, thus circular reasoning.
Remember that PMOD alters some TSI observations to make its composite to fit the decadal trending of the observed magnetic activity. That is true circular reasoning! ACRIM presents a very different pattern.
TSI comes from the magnetic network so must match that. If it doesn’t it is wrong. ACRIM has recently been recalibrated. ACRIM disagrees with DIARAD and PMOD so must be discarded.
“Since the energy generated in the core takes ~250,000 years to diffuse out through the radiative zone, variations of a time scale much shorter than that are completely washed out.”
The things may not be so simple, the solar interior may not be in perfect equilibrium 🙂
‘may’ not be? The interior does not have to be in ‘perfect equilibrium’ for the diffusion wash-out to work.
Who knows why there is a variation in the solar cycle 🙂
There is a growing body of knowledge on this, e.g. the work by Choudhuri and Nandy. Even Babcock and Leighton had it right: The build up to maximum is deterministic [which is why precursor prediction works], but the movement of flux to the polar regions is a random process which can fluctuate due to contingencies. Only 1/1000 to 1/100 of the erupting flux makes it to the poles. One should not build theories on ignorance: “who knows, so anything goes”.
If you change idea about the travel reinboursement offer, let me know.
It is not my decision to make. You could approach the organizers and ask them.
Nicola Scafetta says:
December 19, 2011 at 1:28 pm
my papers do not adopt circular reasoning and I do not build the solar models on the temperature data.
In your paper you assume that the TSI record is a proxy for climate changes:
“The above equations assume that the TSI record is used as a proxy for the overall climate sensitivity to solar changes”. It is therefore not a surprise that you find it is. That is but one of the several examples of circular reasoning.
Nicola Scafetta says:
December 19, 2011 at 1:28 pm
“The 0.1% variation of TSI depends on the magnetic field as evidenced by the very close fit of observed TSI to observed magnetic activity”.
Well, it is not so close. It depends on the TSI records that you are using.
As Lean pointed out at Sedona [you were there so should know]:
“Solar Irradiance Decadal Trends: Real Variability (unlikely) or Instrument
Instability (likely)?
Decadal trends in solar irradiance are not yet detectable from uncertainties caused by instrument instabilities in the measurements.
Total Solar Irradiance: – differences between successive solar minimum are smaller than measurement uncertainties”
At the same conference Gary Chapman concluded:
“These results provide further support for the hypothesis that the quiet Sun is constant over solar cycle time intervals”
Nicola Scafetta says:
December 19, 2011 at 1:28 pm
My papers adopts TSI model proposed by several other people
GEOPHYSICAL RESEARCH LETTERS, VOL. 36, L20101, 4 PP., 2009
doi:10.1029/2009GL040707
ACRIM-gap and total solar irradiance revisited: Is there a secular trend between 1986 and 1996?
N. A. Krivova, S. K. Solanki, T. Wenzler
“A gap in the total solar irradiance (TSI) measurements between ACRIM-1 and ACRIM-2 led to the ongoing debate on the presence or not of a secular trend between the minima preceding cycles 22 (in 1986) and 23 (1996). It was recently proposed to use the SATIRE model of solar irradiance variations to bridge this gap. When doing this, it is important to use the appropriate SATIRE-based reconstruction, which we do here, employing a reconstruction based on magnetograms. The accuracy of this model on months to years timescales is significantly higher than that of a model developed for long-term reconstructions used by the ACRIM team for such an analysis. The constructed ‘mixed’ ACRIM — SATIRE composite shows no increase in the TSI from 1986 to 1996, in contrast to the ACRIM TSI composite.”
So much for that. Down the drain goes your argument.
Leif, your comments above just prove your numerous biases and personal ostility.
Possible that you are not able to read a paper with fairness and open mind?
1) “You pick the TSI reconstruction [e.g. involving ESS2] that fits the temperature best.” No, I used the TSI reconstruction that was considered sufficiently accurate and represents more or less an average among the proposed TSI reconstructions. My ESS2 and ESS1 curve use the same TSI reconstruction. The difference is in the two detected time constants of the climate system. The final solar signature is given by the sum of ESS1 and ESS2. The free parameters of the model are only calibrated during the period 1980-2000 and the validation of the model goes back to 1600 when the cooling associated to the Maunder minimum and the other major pattern are recovered!
2) “In your paper you assume that the TSI record is a proxy for climate changes”. That is a strarting assumption which is confirmed by the final results which are depicted in this figure
http://pielkeclimatesci.files.wordpress.com/2011/11/figure3.gif
3)”ACRIM disagrees with DIARAD and PMOD so must be discarded. ”
What kind of reasoning is this? PMOD alters the satellite TSI data, while DIARAD uses a naive average among all records which makes its composite different from all available observations.
You may be interested in this paper
http://www.fel.duke.edu/~scafetta/pdf/Scafetta-easterbrook.pdf
read section 3 and look careful at figure 7 around 1989 to understand the error made by PMOD in dealing with the Nimbus record.
4) “Krivova, S. K. Solanki, T. Wenzler”. Their argument is foolish. First they calibrate their SATIRE model on PMOD, and then they claim to have disproven ACRIM.
You need to read our paper N. Scafetta and R. Willson, “ACRIM-gap and Total Solar Irradiance (TSI) trend issue resolved using a surface magnetic flux TSI proxy model”, Geophysical Research Letter 36, L05701, doi:10.1029/2008GL036307 (2009).
http://www.fel.duke.edu/~scafetta/pdf/2008GL036307.pdf
To understand that Krivova, S. K. Solanki, T. Wenzler were not able to disprove our original argument, so they changes their model of reference. We will respond, do not worry.
5) “It is not my decision to make. You could approach the organizers and ask them.”
You can suggest them to invite me and cover the expenses.
Nicola Scafetta says:
December 20, 2011 at 6:19 am
The free parameters of the model are only calibrated during the period 1980-2000
That is your mistake. You pick a model where there is a large difference between the minima. As Lean, Krivova, Chapman, and Willson agree there is no difference within the uncertainty of the data.
2) “In your paper you assume that the TSI record is a proxy for climate changes”. That is a starting assumption which is confirmed
So circular as I said. Your Figure caption also has an error [try to see if you can spot it]
3)”ACRIM disagrees with DIARAD and PMOD so must be discarded. ”
What kind of reasoning is this? PMOD alters the satellite TSI data
Nobody can alter the data. Everybody adjusts the data to make a composite, as the data has offsets that are different for every satellite. As reported at Sedona, the systematic errors are so large that there is no now evidence for any difference between minima. The null-hypothesis must then be that, indeed, there is no difference. With no difference your arguments are invalid.
4) “Krivova, S. K. Solanki, T. Wenzler”. Their argument is foolish.
Yet you cherry pick a model made by fools then. It is telling that the very people who construct your TSI series say that you misuse their data. But then, you label them fools. But are happy to use their reconstruction even in the face of them telling you is is misuse.
To understand that Krivova, S. K. Solanki, T. Wenzler were not able to disprove our original argument, so they changes their model of reference. We will respond, do not worry.
No need to respond as nobody would care.
5) “It is not my decision to make. You could approach the organizers and ask them.”
You can suggest them to invite me and cover the expenses.
Since you will not bring anything of value [to wit: your circular reasoning here] I cannot in good conscience do so.
Nicola Scafetta says:
December 20, 2011 at 6:19 am
PMOD alters the satellite TSI data
In case you are not following the science involved, here is Willson’s presentation at AGU 2011:
ABSTRACT FINAL ID: GC21C-04
TITLE: Revision of ACRIMSAT/ACRIM3 TSI results based on LASP/TRF diagnostic test results for the effects of scattering, diffraction and basic SI scale traceability
SESSION TITLE: GC21C. Climate Change and the Sun: Quantifying Solar Terrestrial Contributions to Global Change Including Updated Total Solar Irradiance Records I
AUTHORS (FIRST NAME, LAST NAME): Richard C Willson
ABSTRACT BODY: The ACRIMSAT/ACRIM3 – SORCE/TIM TSI scale difference was investigated through diagnostic testing of ACRIM3 flight backup instrumentation in the Laboratory for Atmospheric and Space Physics Total Solar Irradiance Radiometer Facility (LASP/TRF). A preliminary downward correction of 5000 ppm was derived to conform ACRIM3 results to the TRF indicated effects of scattering, diffraction and basic radiation scale traceability to the international system of units (SI). Additional testing and analysis is required to reduce the uncertainties of these results which is estimated to be +/- 500 ppm [0.7 W/m2]. The net effect of the TRF corrections places average ACRIM3 TSI results slightly lower than those of SORCE/TIM but within the uncertainty of the TRF comparisons.
Let me repeat: there is no evidence that there is any difference between minima. There is no evidence [as you claim: “Increasing TSI between 1980 and 2000 could have contributed significantly to global warming during the last three decades”] that TSI has increased. On the contrary, there is lots of evidence to the contrary. Of course, such falsifications will always be ignored by true believers of a cause.
Nicola Scafetta says:
December 20, 2011 at 6:19 am
1) “You pick the TSI reconstruction [e.g. involving ESS2] that fits the temperature best.” No, I used the TSI reconstruction that was considered sufficiently accurate
In their careful analysis of TSI http://www.leif.org/EOS/2010GL045777.pdf Kopp and Lean conclude:
“[29] In addition to the offsets, published irradiance observations composing the 32‐year TSI database lack coherent temporal structure because of inconsistent trends that indicate the presence of uncorrected instrumental drift and are not explained by known sources of solar irradiance variability. A regression model that determines the relative proportion of sunspot and facular influences directly from the SORCE/TIM data accounts for 92% of observed variance and tracks the observed trends to within TIM’s stability. This close agreement provides further evidence that TSI variations are primarily due to surface magnetic activity. Uncorrected instrumental drifts are the likely reason that none of the irradiance composites show consistency in their trends nor achieve the high level of agreement with the model as the TIM does.
[30] Climate change studies that use published TSI time series to accredit solar responses must be cognizant of the possible errors in the record; otherwise climate variability is incorrectly attributed to solar variations that are in fact instrumental drifts. The current database is too short and imprecise to establish the magnitude of long‐term irradiance changes, or to alleviate conflicting claims of irradiance variations driving significant climate change in recent decades. Achieving 0.01% uncertainties with stabilities <0.001% per year (the future TIM instrument measurement goals) will help discern secular changes in solar irradiance, making the 32‐year TSI climate data record more robust against potential measurement gaps and more reliable for climate change applications."
So, your 'findings' are built on the shifting sands of measurements uncertainty. Pay special attention to Kopp and Lean's admonition: " Climate change studies that use published TSI time series to accredit solar responses must be cognizant of the possible errors in the record; otherwise climate variability is incorrectly attributed to solar variations that are in fact instrumental drifts". You seem to fail in this regard.
“Nobody can alter the data. Everybody adjusts the data to make a composite”
Dear Leif,
Everybody adjust the data moving the entire record up or down for creating a TSI composite. But Frohlich in addition to that has seriously manipulated the Nimbus data to make his PMOD composite.
See figure 6 in
http://www.fel.duke.edu/~scafetta/pdf/Scafetta-easterbrook.pdf
to understand how big is the manipulation of the data made by Frohlich.
Read the statement from Hoyt where he strongly criticize Frohlich for the manipulation. Hoyt says:
“Frohlich’s PMOD TSI composite is not consistent with the internal data or physics of the Nimbus7 cavity radiometer.”
About ACRIM record you are quite confused.
The ACRIM adjustment did not change the TSI composite trending at all. See the figure in
http://acrim.com/TSI%20Monitoring.htm
About Kopp and Lean, I wrote time ago to Kopp explaining him the physical errors in Lean’s model he adopted in his paper with Lean. This was his response (on Nov/01/2011):
Hi Nicola,
your point is valid. In answering your question, I was focused on the 11-year solar cycle frequency only, where allowing for lags in the regression would deal with heat storage. But you’re right, that neglects any possible long-term trend in solar forcing, which would have a greater impact, a different lag, and a different sensitivity because of the different (low) frequency.
Thanks for the question — I’ll keep in mind both the long-term and the 11-year frequencies (and others) next time! Greg
So, learn to be more objective. Yours is nothing but an arrogant and closed mind behavior. Greg said that I am right.
“Since you will not bring anything of value [to wit: your circular reasoning here] I cannot in good conscience do so.”
did you change idea now?
Nicola Scafetta says:
December 20, 2011 at 11:59 am
to understand how big is the manipulation of the data made by Frohlich.
Read the statement from Hoyt where he strongly criticize Frohlich for the manipulation. Hoyt says:
“Frohlich’s PMOD TSI composite is not consistent with the internal data or physics of the Nimbus7 cavity radiometer.”
The ACRIM adjustment did not change the TSI composite trending at all. See the figure in
http://acrim.com/TSI%20Monitoring.htm
None of this matters as the uncertainties are so great that there is no evidence for any changes.
But you’re right, that neglects any possible long-term trend in solar forcing, which would have a greater impact, a different lag, and a different sensitivity because of the different (low) frequency.
And this does not matter either as all Greg was pointing out was that there is no data for the long-term variation. You calibrated using 1980-2000, so also did not use any long-term data.
did you change idea now?
????
Pay special attention to Kopp and Lean’s admonition: ” Climate change studies that use published TSI time series to accredit solar responses must be cognizant of the possible errors in the record; otherwise climate variability is incorrectly attributed to solar variations that are in fact instrumental drifts”. You seem to fail in this regard.
Nicola Scafetta says:
December 20, 2011 at 11:59 am
See the figure in http://acrim.com/TSI%20Monitoring.htm
which falsifies your claim that “Increasing TSI between 1980 and 2000 could have contributed significantly to global warming during the last three decades” as TSI as per this figure did not increase.
Nicola Scafetta says:
December 20, 2011 at 11:59 am
to understand how big is the manipulation of the data made by Frohlich.
Who cares what Frohlich did? I don’t use his data. In fact I have shown that the Virgo data are not correctly calibrated: http://www.leif.org/research/PMOD%20TSI-SOHO%20keyhole%20effect-degradation%20over%20time.pdf
At Sedona, Schmutz admitted that much and at AGU we learned that the keyhole spikes are due to uncompensated thermal changes introduced by turning over the spacecraft.
The fundamental issue is “This close agreement provides further evidence that TSI variations are primarily due to surface magnetic activity. Uncorrected instrumental drifts are the likely reason that none of the irradiance composites show consistency in their trends nor achieve the high level of agreement with the model as the TIM does”. Are you now claiming that Greg is wrong on that.
Leif,
there is not a “close” agreement between TSI and magnetic activity. The agreement is approximate as the agreement among any solar records. You find a vague agreement in the sense that all present an 11-year cycle, for example.
The major difference between PMOd and ACRIM composite is during the ACRIM gap. PMOD alters the NImbus data to make it to fit his models. One major reason for the correction is the claim that at the end of september 1989 Nimbus sensor suddenly increased theirsensitivity by 0.4 W/m^2. As I have proven in my paper this “sudden-one-day- shift did not occur. Thus, PMOD composite is wrong. The huge degradation of Virgo does not have anything to do with this issue.
“which falsifies your claim that “Increasing TSI between 1980 and 2000 could have contributed significantly to global warming during the last three decades” as TSI as per this figure did not increase.”
No, Leif, TSI increased from 1980 to 2000 as I said. Even a small increase of TSI can be magnified by ten times by the climate system through the cloud response.
Don’t you see that you do not know much about these things while my partecipation to the conference woud be much appreciated?
Nicola Scafetta says:
December 20, 2011 at 7:55 pm
there is not a “close” agreement between TSI and magnetic activity.
Greg finds for TIM [which is the best we have] that 92% of the variation of TSI matches that of magnetic activity. For RMIB it is 85%, for PMOD 83%, but for ACRIM we are down to a low 66%. So TSI matches magnetic activity very well, except that ACRIM is so poor that it only captures 66%.
Chapman and Ulrich also find that the variation matches the magnetic field extremely well. Here is Chapman’s Sedona abstract:
Modeling TSI Variations from SORCE/TIM
Gary A. Chapman [gary.chapman@csun.edu], A. M. Cookson, and D. G. Preminger, San
Fernando Observatory, California State University, Northridge
Total Solar Irradiance (TSI) measurements have been available from the TIM instrument
on the SORCE spacecraft since 2003. We compare TSI data with photometric indices from red
and K-line images obtained on a daily basis at the San Fernando Observatory (SFO). For 1375
days of data from 2003 March 02 to 2010 May 05 we compare the data in linear multiple
regression analyses. The best results come from using only two photometric indices, the red
and K-line photometric sums, and SORCE TSI 6-hour averages interpolated to the SFO time of
observation. For this case, we obtain a coefficient of multiple correlation, R^2 of 0.94798 and a
quiet-Sun irradiance, S_o = 1360.778 +/- 0.004 W/m^2. These results provide further evidence against hypotheses that link TSI variations to assumed changes in the quiet Sun.
and
Modeling Total Solar Irradiance Variations Using Automated Classification Software on Mount Wilson Data
Ulrich, R. K.; Parker, D.; Bertello, L.; Boyden, J.
Solar Physics, Volume 261, Issue 1, pp.11-34 (2010)
doi: 10.1007/s11207-009-9460-4
“We present the results using the AutoClass analysis application available at NASA/Ames Intelligent Systems Div. (2002) which is a Bayesian, finite mixture model classification system developed by Cheeseman and Stutz (1996). We apply this system to Mount Wilson Solar Observatory (MWO) intensity and magnetogram images and classify individual pixels on the solar surface to calculate daily indices that are then correlated with total solar irradiance (TSI) to yield a set of regression coefficients. This approach allows us to model the TSI with a correlation of better than 0.96 for the period 1996 to 2007. These regression coefficients applied to classified pixels on the observed solar surface allow the construction of images of the Sun as it would be seen by TSI measuring instruments like the Solar Bolometric Imager recently flown by Foukal et al. ( Astrophys. J. 611, L57, 2004). As a consequence of the very high correlation we achieve in reproducing the TSI record, our approach holds out the possibility of creating an on-going, accurate, independent estimate of TSI variations from ground-based observations which could be used to compare, and identify the sources of disagreement among, TSI observations from the various satellite instruments and to fill in gaps in the satellite record. Further, our spatially-resolved images should assist in characterizing the particular solar surface regions associated with TSI variations. Also, since the particular set of MWO data on which this analysis is based is available on a daily basis back to at least 1985, and on an intermittent basis before then, it will be possible to estimate the TSI emission due to identified solar surface features at several solar minima to constrain the role surface magnetic effects have on long-term trends in solar energy output.”
As you can see, you are several years behind the curve on this.
The major difference between PMOd and ACRIM composite is during the ACRIM gap
Since I, Dora Preminger, and Wang don’t use PMOD that straw man is irrelevant. So you should not waste everybody’s time harping on that. Yet ACRIM leaves 34% [=100-66] unexplained, while for PMOD the number is 17%, so PMOD is twice as good as ACRIM. But none is as good as TIM with only 8% unaccounted for [which is within the stated uncertainty of the stability, so might even by 0%].
No, Leif, TSI increased from 1980 to 2000 as I said.
The difference between you and I is that I provide evidence to back up what I say. Here is the ACRIM data: http://www.leif.org/research/ACRIM-TSI.png The pink squares show the old record [the one you worked with] while the blue symbols shows the latest adjustments to the published data. It should be plain that the blue symbols show that 2000 is lower than 1980. The green line is the overall trend which is downwards, in spite of the temperature trend for 1979 to the present which is upwards. But again, that doesn’t matter because ACRIM has severe uncertainty.
Don’t you see that you do not know much about these things while my partecipation to the conference woud be much appreciated?
On the contrary, I have to educate you on even the most trivial points and continuously point out your errors and circular reasonings. Let me tell you that my analysis of TIM showed that their correction for the varying solar distance was incomplete [they fixed the error in going to version 9 of the software] and that I discovered the keyhole problem in PMOD. I don’t think [as I have said repeatedly] that you’ll bring anything worthwhile, but you can try your luck with the organizers.
Nicola Scafetta says:
December 20, 2011 at 7:55 pm
there is not a “close” agreement between TSI and magnetic activity.
Modeling Total Solar Irradiance Variations Using Automated Classification Software on Mount Wilson Data, Ulrich, R. K.; Parker, D.; Bertello, L.; Boyden, J.
Solar Physics, Volume 261, Issue 1, pp.11-34 (2010)
“This approach allows us to model the TSI with a correlation of better than 0.96 for the period 1996 to 2007.”
The autoclass method shows how good the modeling is: http://www.leif.org/research/Autoclass-TSI-1996-2008.png
You can even see the slow degradation of VIRGO [the red curve] compared to the magnetic data [brown points]. Note that there is no difference between the 1996 and 2008 minima, falsifying the ACRIM [and your] claim.
Leif, you use a lot of modelling and refuse to look at the data.
Let us look at your own figure
http://wattsupwiththat.com/2011/11/10/aurora-borealis-and-surface-temperature-cycles-linked/
Don’t you see the increaese in the minima from 1986 to 1996 and the decrease from 1996 to 2008?
Look at your green line. In 1996 it almost coincides with the solar minima, while in 1986 the green line is almost at the middle of the cycle. This means that TSI was on average lower during the period 1980-1990 than during the period 1990-2000, the period 1990-2000 was higher than the period 2000-now, and it appears that the period 1980-1990 was sligtly lower than the period 2000-now.
Possible that you are so blind?
Moreover, you are so confused about ACRIM, PMOD and TIM that you do not even understand the differences. TIM is too short for a multidecadal analysis of the TSI trending, for example. This trendig can only be studied with the ACRIM and PMOD composites and the difference between the two in during the ACRIM gap when PMOD alters the available NImbus data in a wa that I proved to be wrong.
You will mislead the Japanises with your refusal to be honest and objective. The best that you can do is to bring me there.
Nicola Scafetta says:
December 21, 2011 at 7:07 am
Don’t you see the increase in the minima from 1986 to 1996 and the decrease from 1996 to 2008?
Just shows how wrong ACRIM is.
and it appears that the period 1980-1990 was slightly lower than the period 2000-now.
Appears? Average 1980-1990 = 1360.8, 2000-Now = 1360.8. They are the same.
Possible that you are so blind?
The difference between you and I is that I bring numbers to bear, while you do not.
trending can only be studied with the ACRIM and PMOD composites and the difference between the two in during the ACRIM gap when PMOD alters the available NImbus data in a wa that I proved to be wrong.
Regardless, The 1996 and 2008 PMOD data are plain Virgo data and the Nimbus data does not enter at all, so it is time you stop attacking that straw man.
You will mislead the Japanises with your refusal to be honest and objective. The best that you can do is to bring me there.
Based on your poor performance here, that seems to be a bad idea. You can always register and sit in the audience with the rest of the folks.
Nicola Scafetta says:
December 21, 2011 at 7:07 am
“and it appears that the period 1980-1990 was slightly lower than the period 2000-now.”
Appears? Average 1980-1990 = 1360.8, 2000-Now = 1360.8. They are the same.
Why cherry pick 1980. ACRIM has data for 1979 too. Average 1979-1990 is 1360.9.
Leif,
you are seriously misleading the scientific community and the society with your unfair, ideological and obtuse understanding of reality.
As I have explained to you again and again your model does not explain anything and runs against the direct TSI measurements. In the history of science models like yours have always being find, before or later, severely misleading and based on naive assumptions.
“Why cherry pick 1980. ACRIM has data for 1979 too.”
First, ACRIM does not have data before 1980.
Those data are from Nimbus and may be partially corrupted because of the early degradation problem.
Second, you need to measure a cycle from, for example, solar maxima to solar maxima, not from where you wish to where you wish.
You just need to read my papers were I discuss both ACRIM and PMOD implications on climate.
Nicola Scafetta says:
December 21, 2011 at 8:18 am
As I have explained to you again and again your model does not explain anything and runs against the direct TSI measurements
They don’t explain anything because there is no effect to explain.
Those data are from Nimbus and may be partially corrupted because of the early degradation problem.
Yet they are part of the ACRIM composite, but I’ll accept that that composite has problems.
Second, you need to measure a cycle from, for example, solar maxima to solar maxima, not from where you wish to where you wish.
You didn’t yourself. And measuring on a faulty data series is not helpful to begin with.
You just need to read my papers were I discuss both ACRIM and PMOD implications on climate.
Those papers are not any good to begin with. The main issue is the errors in ACRIM. Those are clear starting in 1996 and the PMOD composite before that does not enter the equation. There is no difference between the minima in 1996 and 2008, so if ACRIM finds one, ACRIM is wrong. Accept that.
Nicola Scafetta says:
December 21, 2011 at 8:18 am
you are seriously misleading the scientific community and the society with your unfair, ideological and obtuse understanding of reality.
The scientific community is perfectly capable of deciding for itself what is wheat and what is chaff. One way the community expresses its appreciation and acceptance is by asking scientists to deliver keynote, invited, or solicited papers at scientific symposia and meetings [i.e. excluding activist and propaganda meetings, such as Heartland and the like]. Since I started this particular line of research in 2002 I have given 27 such papers [2.7 per year on average] (how many have you been invited to give?).
Nicola Scafetta says:
December 21, 2011 at 8:18 am
As I have explained to you again and again your model does not explain anything and runs against the direct TSI measurements
Explain that to Kopp and Lean, Chapman, Preminger, Krivova, and Ulrich… Not my model, their models.
“There is no difference between the minima in 1996 and 2008, so if ACRIM finds one, ACRIM is wrong. ”
Leif now you are getting quite lunatic again.
Your own TSI reconstruction shows a decreasing trending between the minima in 1996 and 2008.
You get
1995.5 1365.60
1996.5 1365.53
1997.5 1365.62
2007.5 1365.35
with a difference of about 0.2-0.3 W/m^2 between the two minima which is what ACRIM get, more or less.
Or perhaps, your arguing proves that your TSI reconstruction is based on a kind of Mike’s Nature Trick. You were getting with your model a totally flat TSI with no difference between the minima in 1996 and 2008, so in your TSI reconstruction since 1980 you have added not the data from your own model but you have attached to your model since 1980 a combination of the TSI composites to give the impression that your data approximately agree with the observations?
Tell the truth, Leif, are you using the famous Mike’s Nature Trick?
Nicola Scafetta says:
December 21, 2011 at 12:06 pm
You get
1996.5 1365.53 […]
2007.5 1365.35
or a difference of 0.18. ACRIM has a difference of 0.383 or more than twice that. So your “what ACRIM get, more or less” must be seen for what it is: a blatant distortion or worse.
My reconstruction is admittedly crude. The much more accurate ones by Kopp and Lean, Chapman, Preminger, Krivova, and Ulrich show no differences. ACRIM is simply not good enough be base any conclusions about climate on, which makes moot all your papers on that.
2011
– Global warming extreme.
– Two scientists lost in a time warp.
2111
– New Ice age of the millennium.
– Two skeletons found in an abandoned WordPress server still rattling at each other.