Some people cite scientists saying there is a “CO2 control knob” for Earth. No doubt there is, but due to the logarithmic effect of CO2, I think of it like a fine tuning knob, not the main station tuner. That said, a new data picture is emerging of an even bigger knob and lever; a nice bright yellow one.
A few months back, I found a website from NOAA that provides an algorithm and downloadable program for spotting regime shifts in time series data. It was designed by Sergei Rodionov of the NOAA Bering Climate and Ecosystem Center for the purpose of detecting shifts in the Pacific Decadal Oscillation.
Regime shifts are defined as rapid reorganizations of ecosystems from one relatively stable state to another. In the marine environment, regimes may last for several decades and shifts often appear to be associated with changes in the climate system. In the North Pacific, climate regimes are typically described using the concept of Pacific Decadal Oscillation. Regime shifts were also found in many other variables as demonstrated in the Data section of this website (select a variable and then click “Recent trends”).
But data is data, and the program doesn’t care if it is ecosystem data, temperature data, population data, or solar data. It just looks for and identifies abrupt changes that stabilize at a new level. For example, a useful application of the program is to look for shifts in weather data, such as that caused by the PDO. Here we can clearly see the great Pacific Climate Shift of 1976/77:
Another useful application is to use it to identify station moves that result in a temperature shift. It might also be applied to proxy data, such as ice core Oxygen 18 isotope data.
But the program was developed around the PDO. What drives the PDO? Many say the sun, though there are other factors too. It follows to reason then the we might be able to look for solar regime shifts in PDO driven temperature data.
Alan of AppInSys found the same application and has done just that, and the results are quite interesting. The correlation is well aligned, and it demonstrates the solar to PDO connection quite well. I’ll let him tell his story of discovery below. – Anthony
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Climate Regime Shifts
The notion that climate variations often occur in the form of ‘‘regimes’’ began to become appreciated in the 1990s. This paradigm was inspired in large part by the rapid change of the North Pacific climate around 1977 [e.g., Kerr, 1992] and the identification of other abrupt shifts in association with the Pacific Decadal Oscillation (PDO) [Mantua et al., 1997].” [http://www.beringclimate.noaa.gov/regimes/Regime_shift_algorithm.pdf]
Pacific Regime Shifts
Hare and Mantua, 2000 (“Empirical evidence for North Pacific regime shifts in 1977 and 1989”): “It is now widely accepted that a climatic regime shift transpired in the North Pacific Ocean in the winter of 1976–77. This regime shift has had far reaching consequences for the large marine ecosystems of the North Pacific. Despite the strength and scope of the changes initiated by the shift, it was 10–15 years before it was fully recognized. Subsequent research has suggested that this event was not unique in the historical record but merely the latest in a succession of climatic regime shifts. In this study, we assembled 100 environmental time series, 31 climatic and 69 biological, to determine if there is evidence for common regime signals in the 1965–1997 period of record. Our analysis reproduces previously documented features of the 1977 regime shift, and identifies a further shift in 1989 in some components of the North Pacific ecosystem. The 1989 changes were neither as pervasive as the 1977 changes nor did they signal a simple return to pre-1977 conditions.”
[http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V7B-41FTS3S-2…]
Overland et al “North Pacific regime shifts: Definitions, issues and recent transitions”
[http://www.pmel.noaa.gov/foci/publications/2008/overN667.pdf]: “climate variables for the North Pacific display shifts near 1977, 1989 and 1998.”
The following figure from the above paper show analysis of PDO and Victoria Index using the Rodionov regime detection algorithm. A regime shift is also detected around 1947-48.
The following figure shows regime shift detection for the summer PDO, showing shifts at 1948, 1976 and 1998.
[http://www.beringclimate.noaa.gov/data/Images/PDOs_FigRegime.html]
(For detailed information on the 1976/77 climate shift,
see: http://www.appinsys.com/GlobalWarming/The1976-78ClimateShift.htm)
Regime Shift Detection in Annual Temperature Anomaly Data
The NOAA Bering Climate web site provides the algorithm for regime shift detection developed by Sergei Rodionov [http://www.beringclimate.noaa.gov/regimes/index.html]. The following analyses use the Excel VBA regime change algorithm version 3.2 from this web site.
The following figure shows the regime analysis of the HadCRUT3 annual global annual average temperature anomaly data from the Met Office Hadley Centre for 1895 to 2009 [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/annual].
The analysis was run based on the mean using a significance level of 0.1, cut-off length of 10 and Huber weight parameter of 2 using red noise IP4 subsample size 6. Regime changes are identified in 1902, 1914, 1926, 1937, 1946, 1957, 1977, 1987, and 1997. Running the analysis based on the variance rather than the mean results in regime changes in the bold years listed above.
Regime Shift Relationship to Solar Cycle
The NASA Solar Physics web site provides the following figure showing sunspot area.
[http://solarscience.msfc.nasa.gov/SunspotCycle.shtml]
The following figure compares the Hadley (HadCrut3) monthly global average temperature (from [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/]) overlaid with the regime change line (red line) shown previously, along with the sunspot area since 1900. The sunspot cycle is approximately 11 years. The sun’s magnetic field reverses with each sunspot cycle and thus after two sunspot cycles the magnetic field has completed a cycle – a Hale Cycle – and is back to where it started. Thus a complete magnetic sunspot cycle is approximately 22 years. The figure marks the onset of odd-numbered cycles with a vertical red line, even-numbered cycles with a green line.
From the figure above it can be seen that the regime changes correspond to the onset of solar cycles and occur when the “butterfly” is at its widest. The most significant warming regime shifts occur at the start of odd-numbered cycles (1937, 1957, 1977, 1997). Each odd-numbered cycle (red lines above) has resulted in a temperature-increase regime shift. Even-numbered cycles (green lines above) have been inconsistent, with some resulting in temperature-decrease regime shifts (1902, 1946) or minor temperature-increase shifts (1926, 1987).
An unusual one is the 1957 – 1966 cycle, which in the monthly data shown above visually looks like a temperature-increase shift in 1957 followed by a temperature-decrease shift in 1964 but the regime detection algorithm did not identify it. This is likely due to the use of annually averaged data in the regime detection algorithm.
The following figure shows the relative polarity of the Sun’s magnetic poles for recent sunspot cycles along with the solar magnetic flux [www.bu.edu/csp/nas/IHY_MagField.ppt]. The regime change periods are highlighted by the red and green boxes. Each one occurs on as the solar cycle is accelerating. The onset of an odd-numbered sunspot cycle (1977-78, 1997-98) results in the relative alignment of the Earth’s and the Sun’s magnetic fields (positive North pole on the Sun) allowing greater penetration of the geomagnetic storms into the Earth’s atmosphere. “Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned with that of the Earth compared to when the two magnetic fields are oppositely directed” [http://www.nasa.gov/mission_pages/themis/news/themis_leaky_shield.html]
The following figure shows the longitudinally averaged solar magnetic field. This “magnetic butterfly diagram” shows that the sunspots are involved with transporting the field in its reversal. The Earth’s temperature regime shifts are indicated with the superimposed boxes – red on odd numbered solar cycles, green on even.
[http://solarphysics.livingreviews.org/open?pubNo=lrsp-2010-1&page=articlesu8.html]
The Earth’s temperature regime shift occurs as the solar magnetic field begins its reversal.
Solar Cycle 24
Solar cycle 24 is in its initial stage after getting off to a late start. An El Nino occurred in the first part of 2010. This may be the start of the next regime shift.
Climate Regime Shifts
[last update: 2010/07/04]
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“The notion that climate variations often occur in the form of ‘‘regimes’’ began to become appreciated in the 1990s. This paradigm was inspired in large part by the rapid change of the North Pacific climate around 1977 [e.g., Kerr, 1992] and the identification of other abrupt shifts in association with the Pacific Decadal Oscillation (PDO) [Mantua et al., 1997].” [http://www.beringclimate.noaa.gov/regimes/Regime_shift_algorithm.pdf]
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Pacific Regime Shifts
Hare and Mantua, 2000 (“Empirical evidence for North Pacific regime shifts in 1977 and 1989”): “It is now widely accepted that a climatic regime shift transpired in the North Pacific Ocean in the winter of 1976–77. This regime shift has had far reaching consequences for the large marine ecosystems of the North Pacific. Despite the strength and scope of the changes initiated by the shift, it was 10–15 years before it was fully recognized. Subsequent research has suggested that this event was not unique in the historical record but merely the latest in a succession of climatic regime shifts. In this study, we assembled 100 environmental time series, 31 climatic and 69 biological, to determine if there is evidence for common regime signals in the 1965–1997 period of record. Our analysis reproduces previously documented features of the 1977 regime shift, and identifies a further shift in 1989 in some components of the North Pacific ecosystem. The 1989 changes were neither as pervasive as the 1977 changes nor did they signal a simple return to pre-1977 conditions.” [http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V7B-41FTS3S-2…]
Overland et al “North Pacific regime shifts: Definitions, issues and recent transitions” [http://www.pmel.noaa.gov/foci/publications/2008/overN667.pdf]: “climate variables for the North Pacific display shifts near 1977, 1989 and 1998.”
The following figure from the above paper show analysis of PDO and Victoria Index using the Rodionov regime detection algorithm. A regime shift is also detected around 1947-48.
The following figure shows regime shift detection for the summer PDO, showing shifts at 1948, 1976 and 1998. [http://www.beringclimate.noaa.gov/data/Images/PDOs_FigRegime.html]
(For detailed information on the 1976/77 climate shift, see: http://www.appinsys.com/GlobalWarming/The1976-78ClimateShift.htm)
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Regime Shift Detection in Annual Temperature Anomaly Data
The NOAA Bering Climate web site provides the algorithm for regime shift detection developed by Sergei Rodionov [http://www.beringclimate.noaa.gov/regimes/index.html]. The following analyses use the Excel VBA regime change algorithm version 3.2 from this web site.
The following figure shows the regime analysis of the HadCRUT3 annual global annual average temperature anomaly data from the Met Office Hadley Centre for 1895 to 2009 [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/annual].
The analysis was run based on the mean using a significance level of 0.1, cut-off length of 10 and Huber weight parameter of 2 using red noise IP4 subsample size 6. Regime changes are identified in 1902, 1914, 1926, 1937, 1946, 1957, 1977, 1987, and 1997. Running the analysis based on the variance rather than the mean results in regime changes in the bold years listed above.
|
|
Regime Shift Relationship to Solar Cycle
The NASA Solar Physics web site provides the following figure showing sunspot area. [http://solarscience.msfc.nasa.gov/SunspotCycle.shtml]
The following figure compares the Hadley (HadCrut3) monthly global average temperature (from [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/]) overlaid with the regime change line (red line) shown previously, along with the sunspot area since 1900. The sunspot cycle is approximately 11 years. The sun’s magnetic field reverses with each sunspot cycle and thus after two sunspot cycles the magnetic field has completed a cycle – a Hale Cycle – and is back to where it started. Thus a complete magnetic sunspot cycle is approximately 22 years. The figure marks the onset of odd-numbered cycles with a vertical red line, even-numbered cycles with a green line.
From the figure above it can be seen that the regime changes correspond to the onset of solar cycles and occur when the “butterfly” is at its widest. The most significant warming regime shifts occur at the start of odd-numbered cycles (1937, 1957, 1977, 1997). Each odd-numbered cycle (red lines above) has resulted in a temperature-increase regime shift. Even-numbered cycles (green lines above) have been inconsistent, with some resulting in temperature-decrease regime shifts (1902, 1946) or minor temperature-increase shifts (1926, 1987).
An unusual one is the 1957 – 1966 cycle, which in the monthly data shown above visually looks like a temperature-increase shift in 1957 followed by a temperature-decrease shift in 1964 but the regime detection algorithm did not identify it. This is likely due to the use of annually averaged data in the regime detection algorithm.
The following figure shows the relative polarity of the Sun’s magnetic poles for recent sunspot cycles along with the solar magnetic flux [www.bu.edu/csp/nas/IHY_MagField.ppt]. The regime change periods are highlighted by the red and green boxes. Each one occurs on as the solar cycle is accelerating. The onset of an odd-numbered sunspot cycle (1977-78, 1997-98) results in the relative alignment of the Earth’s and the Sun’s magnetic fields (positive North pole on the Sun) allowing greater penetration of the geomagnetic storms into the Earth’s atmosphere. “Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned with that of the Earth compared to when the two magnetic fields are oppositely directed” [http://www.nasa.gov/mission_pages/themis/news/themis_leaky_shield.html]
The following figure shows the longitudinally averaged solar magnetic field. This “magnetic butterfly diagram” shows that the sunspots are involved with transporting the field in its reversal. The Earth’s temperature regime shifts are indicated with the superimposed boxes – red on odd numbered solar cycles, green on even. [http://solarphysics.livingreviews.org/open?pubNo=lrsp-2010-1&page=articlesu8.html]
The Earth’s temperature regime shift occurs as the solar magnetic field begins its reversal.
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Solar Cycle 24
Solar cycle 24 is in its initial stage after getting off to a late start. An El Nino occurred in the first part of 2010. This may be the start of the next regime shift.
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Basil replied, “Here the mechanism is straight-forward: the broader amplitudes are governed by variations in TSI, and the frequencies are related to the solar cycle and the lunar nodal cycle.”
Please explain how the lunar nodal cycle would cause variations in global temperatures.
tony b asked:
“Does your theory presuppose a continually cold period or can it accommodate an era when the temperatures ‘bounced around’ and showed great variabilty, although in general winters became warmer?”
I envisage lots of shorter term bouncing around because of the interplay of two independently varying influences on the air circulation systems sometimes supplementing and sometimes offsetting one another. One also sees wide regional variations in the short term despite any global trend. That’s why I say that the pattern only becomes really clear on the 500 year timescale with shifts such as those from MWP to LIA to date.
This has been one interesting thread but perhaps it is time to put out a roster of the players and their field of expertise along with a very short statement of their main view on the sun-earth relationship. It would certainly help me keep track of who is coming from what angle during technical discussions.
oneuniverse wrote:
My strictly casual understanding was that a collision following a photon absorption (before the molecule has had time to emit) redistributes the absorbed energy as kinetic energy amongst the colliding molecules. So if this is the case, collision before emission increases the temperature of the gas.
I also seem to remember reading that lab experiments by Neils Bohr determined that the vibrational energy of the molecule doesn’t increase after photon absorption, rather the internal energy is altered by a change in electron levels, which is reset once a photon is absorbed.
Point is, as you said earlier, that there can’t be both. You can’t store the photon energy in the CO2 molecule to be released later as a photon of the same energy AND have the photon energy increase the vibrational kinetic energy of the molecule as well.
We might maybe think of molecules as springs. Sometimes a photon hits a spring and compresses it and its energy gets stored as potential energy in the compressed spring. This potential energy isn’t transferred to adjacent springs. Other times, maybe, a photon hits a spring sideways and doesn’t compress it, but increases the kinetic energy of the spring (which can then be transferred to adjacent springs). Conservation of energy means it can’t do both.
“Bob Tisdale says:
July 6, 2010 at 3:05 am
Stephen Wilde wrote:
“Bob Tisdale has responded elsewhere but objects to my suggestion that PDO is caused by influences other than ENSO…”
Bob Tisdale replied:
“Of course the PDO is influenced by variables other than ENSO.”
That begs the question as to whether it is ultimately caused by influences other than ENSO. That it may also be influenced by other variables is taken as a given.
I use the term PDO in the general sense that has entered common currency but I am aware of the more restricted definition that you use.
I consider that something other than ENSO creates the PDO via the ENSO process. It does so by gradually altering the relative strengths of El Nino and La Nina over time.
I propose that the main underlying cause is changes in the winds above the equatorial oceans as they respond to latitudinal shifts in the global air circulation systems as per my hypotheses. Those air circulation shifts being the result of an interplay between oceanic and solar cycles.
So the PDO is caused by underlying oceanic cycles modified by solar cycles which move the air circulation systems to change the winds and induce ENSO.
It would then follow that PDO would be a statistical artifact of ENSO as you aver but that does not derogate from the seperate chain of causation.
#
#
Tom in Florida says:
July 6, 2010 at 5:04 am
This has been one interesting thread but perhaps it is time to put out a roster of the players and their field of expertise along with a very short statement of their main view on the sun-earth relationship. It would certainly help me keep track of who is coming from what angle during technical discussions.
_____________________________________________
Google their names, and you can get a pretty good feel for who they are and where they are coming from. Many have links so you can click on the name and see their website. Otherwise you need to read a lot and have a good memory.
Generally most have a degree in Science, Engineering or Math or a lot of practical experience using math and logic on the job. The site stats show a higher proportion of older males with a graduate degree compared to the norm. (the no degree crowd has increased since Climategate and Monbiot’s call to arms for CAGW trolls) http://www.alexa.com/siteinfo/wattsupwiththat.com
idlex: Point is, as you said earlier, that there can’t be both. You can’t store the photon energy in the CO2 molecule to be released later as a photon of the same energy AND have the photon energy increase the vibrational kinetic energy of the molecule as well.
If the photon’s absorbed energy is redistributed as kinetic energy, if such an event can occur, then there wouldn’t be a corresponding photon emission.
re: rate of emission
From Enc.Britannica : “For many excited states of atoms, the average time before the spontaneous emission of a photon is on the order of 10^−9 to 10^−8 second.”
That’s at about the same order as the collision rate of atmospheric molecules.
We need the emission time for CO2, though – I haven’t found it yet.
The general equation for the probability of a transition to a different energy state in unit time is apparently given by Fermi’s Golden Rule, just in case anyone has all the parameter values at hand..
tallbloke says:
July 6, 2010 at 1:00 am
TSI varies around 0.1% over the solar cycle, and maybe by around that over the 1930-2000 period? And it is amplified at the surface by a drop in cloud cover from 1980-1998 according to ISCCP data. Those empirical observations are backed up by Nir Shaviv’s work on using the oceans as a calorimeter.
The reason this cannot be corrected is that you have not made a definitive statement by “maybe by around that over the 1930-2000 period”. What does that mean? that TSI in 2000 is 0.1% higher than in 1930? Then you switch to a different period 1980-1998 and make the argument that TSI is amplified by a by a drop in cloud cover. Well, first you’ll have to show that TSI changed the cloud cover. And then quantify by how much. A change in albedo by 0.005 corresponds to a temperature change of 0.5K.
The ISCCP shows the cloud cover, temperatures, and albedo here http://isccp.giss.nasa.gov/climanal1.html and the changes do not match any TSI/solar activity related changes. You can, of course, claim that their data isn’t any good, but then you can’t in the same breath use them as long as they fit [which they actually do not] your purpose.
So, as I said, there is not enough meat and precision in your ‘calculation’ to replicate it, let alone correct it.
Stephen Wilde says:
July 6, 2010 at 5:27 am
Logic is forcing me to question both scenarios and the climate feature that is most significant is that latitudinal shift in all the air circulation systems beyond normal seasonal variability.
The same criticism of tallbloke’s ‘calculation’ applies to you. You have no numbers, no equations, no quantifications.
” “Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned with that of the Earth compared to when the two magnetic fields are oppositely directed””
Nice tidbit.
Leif Svalgaard says:
July 6, 2010 at 6:54 am
Stephen Wilde says:
July 6, 2010 at 5:27 am
Logic is forcing me to question both scenarios and the climate feature that is most significant is that latitudinal shift in all the air circulation systems beyond normal seasonal variability.
The same criticism of tallbloke’s ‘calculation’ applies to you. You have no numbers, no equations, no quantifications.
So? He has a theory, and a testable one at that. If (indicative mode) the data to fully assess the theory are not currently available, that is not itself a reason to discredit it. I should think that you, of all people, know how hard it can be to develop the sensors needed to test theories. Now if you think there is some deductive flaw in the theory that justifies rejecting it out of hand, do tell us. Otherwise, it seems as though you are just being glib.
“Leif Svalgaard says:
July 6, 2010 at 6:54 am
Stephen Wilde says:
July 6, 2010 at 5:27 am
Logic is forcing me to question both scenarios and the climate feature that is most significant is that latitudinal shift in all the air circulation systems beyond normal seasonal variability.
The same criticism of tallbloke’s ‘calculation’ applies to you. You have no numbers, no equations, no quantifications.”
I have something far better. A logical coherence describing and linking varied observations, according with ongoing events and hopefully providing some predictive skill and all without any obvious abuse of the basic laws of physics.
I do not accept your assertion that the laws of physics necessarily prevent changes in the energy flux from Earth to space as a result of solar surface variability. One can only explain observations if such variability does occur.
The history of science is replete with over confident assertions such as yours which were often maintained for decades in the face of observational evidence to the contrary until eventually the diehards were brought to a realisation of their arrogance.
““For many excited states of atoms, the average time before the spontaneous emission of a photon is on the order of 10^−9 to 10^−8 second.” ”
Not the same class of interaction, orbit exitation versus bond-length vibration. Good luck with finding that CO2 absorption does not increase heterogenous gas temperature linearly(or nearly so).
gary gulrud says:
July 6, 2010 at 7:24 am
“Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned […]”
Nice tidbit.
Yes, but hardly relevant as the solar magnetic field’s north-south component [the one that aligns with the Earth’s field] seen at Earth varies at random from hour to hour, see e.g. the red curve here: http://www.swpc.noaa.gov/ace/MAG_SWEPAM_7d.html
So, it is misleading to talk about the ‘sun’s magnetic field’ in this connection as what we see at Earth is not the large-scale solar field but a very irregular, strongly fluctuating field, varying from hour to hour, minute to minute.
oneuniverse says:
July 6, 2010 at 6:44 am
The general equation for the probability of a transition to a different energy state in unit time is apparently given by Fermi’s Golden Rule, just in case anyone has all the parameter values at hand.
Very interesting oneuniverse, thanks for passing this along. Reading through the material I found the General expectation value formula particularly interesting:
General expectation value = initial wave function x (some operator function) x final wave function integrated over the volume under consideration.
http://hyperphysics.phy-astr.gsu.edu/hbase/quantum/fermi.html
If I understand the basics of this correctly we would expect the energy transfer from CO2 other systems to decrease with altitude in the atmosphere due to decreasing densities. The more important piece of the puzzle is to define the operator function that couples CO2 to other neighboring systems. Would you agree that if a temperature variable is found in the denominator of the operator function, then we would expect a negative feedback mechanism and conversely if temp variable is found in the numerator then a positive feedback mechanism would occur. It seems to me that to satisfy the CAGW alarmist theories we must have the temp variable in the numerator to get the runaway heating positive feedback shown in the hockey stick.
Typing too fast
s/b
If I understand the basics of this correctly we would expect the energy transfer from CO2 to other systems to decrease with altitude in the atmosphere due to decreasing densities.
Leif Svalgaard says:
July 6, 2010 at 6:50 am (Edit)
tallbloke says:
July 6, 2010 at 1:00 am
TSI varies around 0.1% over the solar cycle, and maybe by around that over the 1930-2000 period? And it is amplified at the surface by a drop in cloud cover from 1980-1998 according to ISCCP data. Those empirical observations are backed up by Nir Shaviv’s work on using the oceans as a calorimeter.
The reason this cannot be corrected is that you have not made a definitive statement by “maybe by around that over the 1930-2000 period”. What does that mean? that TSI in 2000 is 0.1% higher than in 1930? Then you switch to a different period 1980-1998 and make the argument that TSI is amplified by a by a drop in cloud cover. Well, first you’ll have to show that TSI changed the cloud cover. And then quantify by how much. A change in albedo by 0.005 corresponds to a temperature change of 0.5K.
The ISCCP shows the cloud cover, temperatures, and albedo here http://isccp.giss.nasa.gov/climanal1.html and the changes do not match any TSI/solar activity related changes. You can, of course, claim that their data isn’t any good, but then you can’t in the same breath use them as long as they fit [which they actually do not] your purpose.
So, as I said, there is not enough meat and precision in your ‘calculation’ to replicate it, let alone correct it.
Thanks for the more thorough criticism Leif. That’s more useful to me. I’ve got a discussion about it going on my blog, and it’s proving fruitful. There has been a great link posted to a thorough examination of ocean heat content measurement.
http://tallbloke.wordpress.com/2010/07/06/help-needed-with-global-warming-maths/
Bob Tisdale says:
July 6, 2010 at 4:32 am (Edit)
tallbloke replied, “I’m not sure where you’re going with that one either, do you think those factors and nothing else account for the variability of the OHC anomalies of the Atlantic over the period of record?”
No, I don’t think the factors I wrote and nothing else account for the variability of OHC anomalies of the North Atlantic. As you are aware, the South Atlantic is the only basin where heat transport is from the pole to the tropics, so the North Atlantic OHC is impacted by the South Atlantic OHC. North Atlantic also has exaggerated Cloud Amount anomalies variations.
http://i50.tinypic.com/294ihsk.jpg
But the 2005 peak of North Atlantic OHC appears to coincide with the peak of the North Atlantic SST anomalies, and in turn the peak of the AMO, which is why I would attribute the recent decline in North Atlantic OHC to AMO/AMOC.
And other than the variables I’ve listed so far, what other factors are you suggesting account for the variations in North Atlantic OHC?
Hi Bob,
Whatever it is that caused increasing cloudiness from 1998 would have to be a contender for an important role I would have thought.
Respect
Rog
Basil says:
July 6, 2010 at 7:33 am
Now if you think there is some deductive flaw in the theory that justifies rejecting it out of hand, do tell us. Otherwise, it seems as though you are just being glib.
We have discussed this ad nauseam on other threads
Stephen Wilde says:
July 6, 2010 at 7:37 am
The history of science is replete with over confident assertions such as yours which were often maintained for decades in the face of observational evidence to the contrary until eventually the diehards were brought to a realisation of their arrogance.
It seems to me that your assertions are far more confident than mine [“I have something far better”, “logical coherence”, etc], so you may fall victim to the above…
tallbloke says:
July 6, 2010 at 9:38 am
Thanks for the more thorough criticism Leif. That’s more useful to me.
You can always count on fair, unbiased, scientifically correct, and useful criticism from me. It is there for the taking.
Steven (Mosher), I think you are overselling the “nothing to see here meme” based on your observations about evil code. Perhaps this is data-massaging code, and perhaps in general its conclusions are worth little or at least subject to great skepticism. However, unless I seriously misunderstand this particular experiment, any “massaging” that happened in this analysis of temperatures was blind — i.e., without reference to the eventually correlated solar data. So, regardless of how much hanky-panky may lie behind the handling of the code, it is hard to escape the conclusion that the correlation revealed is quite genuine. Had the regime-shift analysis permitted intervention related to this outcome I would have been happy to dismiss it outright, but I don’t think that can be done here. If you are right about this particular algorithm, then we should regard this piece as a good argument for a similar analysis to be done by a more robust method. I’d lay good money on the same outcome resulting.
As far as needing a mechanism, this is just silly. Correlation is correlation; either it’s genuine or not. As for causation, in general it’s dubious to draw that conclusion from mere correlation, but in this case we must argue either that the correlation is an enormous coincidence or that there must be an element of causation, whose direction is pretty certain. No mechanism is required for this. A great deal of scientific knowledge about correlated phenomena does not hinge upon knowledge of mechanisms. Psychology, for example, would be void if we required detailed knowledge of all the processes intermediate between fundamental brain chemistry and cognitive states. Nobody could design planes if we required complete solutions to the differential equations describing the mechanisms of turbulence needed in airfoil design. It suffices to know how to correlate controllable variables with outcomes. Knowledge of mechanisms commonly comes long after knowledge of laws concerning the behavior of related variables.
Popped over realclimate to try to get their take. Response was:
Ray Ladbury says:
6 July 2010 at 8:15 AM
idlex, one thing you are missing is that most CO2 molecules relax not by emitting a photon by by colliding with, say a Nitrogen, molecule and imparting the extra energy to that molecule. You can look at this in terms of equipartition. The IR flux from the warmer surface excites much of the CO2–much more than would be excited at thermal equilibrium at the temperature of the atmospheric layer where the photon is absorbed. To move toward equilibrium, the CO2 then has to impart energy to the surrounding gas. Make sense?
And that in turn brought a response:
Gilles says:
6 July 2010 at 11:03 AM
Ray : “The IR flux from the warmer surface excites much of the CO2–much more than would be excited at thermal equilibrium at the temperature of the atmospheric layer where the photon is absorbed.”
actually if the medium is optically thick , the IR flux has a characteristic radiation temperature from the location where it was emitted, that is around one mean free path away. It may be not “much more” if the optical depth is high enough (the order of magnitude is ∆T = l.grad T = grad T .h/tau ) ; it can be a small difference for high tau , but it insures the gradual transfer of heat from one layer to another one. That’s the essence of diffusion approximation.
The fact that the energy of a photon is most often transferred by collisions to other molecules does not really matter, since it means that collisions can also excite molecules that will sometime emit a photon – both process cancel exactly in LTE. In thermal equilibrium, there is no net “heating” in the sense that the atmosphere would gain temperature, the temperature is steady on average everywhere. This is really a transport process, heat flows throughout the atmosphere but without temperature variation. Locally, absorption and emission do cancel exactly : only the DIRECTION of photons is slightly anisotropic : a little bit more photons come from the lower, hotter layers and a little bit less from the upper, colder ones. They are reemitted isotropically, so the budget is slightly positive outwards and negative inwards , but vanishes when integrated on all directions. The net result is a transport outwards.
Leif,
You shifted the ground.
“no numbers, no equations, no quantifications” is what you referred to.
“A logical coherence describing and linking varied observations, according with ongoing events and hopefully providing some predictive skill and all without any obvious abuse of the basic laws of physics.” is what I contend is far better.
Though both would be nice in an ideal world but in the absence of data beggars cannot be choosers as Basil points out.
Nonetheless I have said several times that there are lots of ways to falsify my propositions. It’s just that the world is refusing to cooperate in the way you would like (so far at least).
And we have discussed it ad nauseam elsewhere but all that that nausea amounts to is a belief on your part that solar variability cannot possibly affect the upward energy flux from Earth to space.
In my opinion that is not good enough because the temperature of the stratosphere clearly changes cyclically and not in a way that correlates well with changes in energy flux only from below.
Introducing the issue of CFCs and anthropogenic CO2 to explain away that observation and at the same time to blame it on humans is looking weaker the longer we see negative polar oscillations with more equatorward jets, a warming stratosphere (since the late 90s), a quiet sun, increasing albedo and a cessation of global warming (if not yet a clear fall) all happening simultaneously and all being the reverse of the late 20th century trends.
Lots to go wrong there for my hypotheses and when it does I’ll be the first to acknowledge it.
I might try to explain it away though but only if there are reasonable alternative explanations for any diversion from my expectations. I won’t be going for arcane explanations to salvage it.
R. Craigen says:
July 6, 2010 at 10:53 am
Correlation is correlation; either it’s genuine or not. As for causation, in general it’s dubious to draw that conclusion from mere correlation, but in this case we must argue either that the correlation is an enormous coincidence or that there must be an element of causation, whose direction is pretty certain.
This hangs on how good the correlation is. If the correlation coefficient [over a sufficiently large number of independent data points – and there are established ways of deciding what is needed] is high enough, e.g. 0.99, then no mechanism is needed a priori [and one has an incentive to go find one]. If the correlation is poor, e.g. 0.5, then you do not have an ‘enormous’ coincidence and without a theory there is not much one can do. With a good theory [e.g. physically viable] a poor correlation can be accepted, just showing that there are other factors at work. But this does not carry over to the case of no mechanism. So, it all depends on the goodness of the correlation and [this is most important] on the number of degrees of freedom.
Leif Svalgaard says:
July 6, 2010 at 11:07 am
This hangs on how good the correlation is. If the correlation coefficient [over a sufficiently large number of independent data points – and there are established ways of deciding what is needed] is high enough, e.g. 0.99, then no mechanism is needed a priori [and one has an incentive to go find one]. If the correlation is poor, e.g. 0.5, then you do not have an ‘enormous’ coincidence and without a theory there is not much one can do. With a good theory [e.g. physically viable] a poor correlation can be accepted, just showing that there are other factors at work. But this does not carry over to the case of no mechanism. So, it all depends on the goodness of the correlation and [this is most important] on the number of degrees of freedom.
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Leif and R. Craigen ,
Ahhhhh, don’t stop at mentioning “number of degrees of freedom!! This looks like a very useful dialog for my continuing effort to understand. Please go on.
John