In a study in the Journal of Geophysical Research a paper, Influence of the Southern Oscillation on tropospheric temperature, researchers Chris de Freitas, John McLean, and Bob Carter find that the El Niño-Southern Oscillation (ENSO) is a key indicator of global atmospheric temperatures seven months later. By their analysis they have shown that natural forces related to ocean heat cycles are the dominant influence on climate. See the WUWT post on it here and the original paper here.
This guest post by Bob Tisdale is a response of interest to both critics and supporters of the paper and illustrates how the multiyear processes of an El Nino event such as occurred in 1998 are missed. – Anthony
Regression Analyses Do Not Capture The Multiyear Aftereffects Of Significant El Nino Events
Guest post by Bob Tisdale
INTRODUCTION
This post illustrates why regression analyses do not capture the multiyear aftereffects of significant El Nino events. To emphasize this, I’ve provided a detailed explanation of the processes that take place before, during, and after those significant El Nino events, using graphics and videos from earlier posts.
EXAMPLE OF RESULTS FROM A REGRESSION ANALYSIS
Regression analyses are used by climatologists to determine and illustrate the impact on global temperature of one or more variables, such as ENSO, Solar Irradiance, and Volcanic Aerosols. Figure 1 shows the results of one such study. It is a multi-cell illustration of “Surface Temperature Variability Components” from Lean and Rind (2008) “How Natural and Anthropogenic Influences Alter Global and Regional Surface Temperatures: 1889 to 2006” [GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L18701, doi:10.1029/2008GL034864, 2008].
Link to Paper:
http://pubs.giss.nasa.gov/docs/2008/2008_Lean_Rind.pdf
http://i32.tinypic.com/2lmw477.png
Figure 1
My Figure 1 is Figure 2 from Lean and Rind (2008). Under the heading of “Datasets”, Lean and Rind write, “Monthly fluctuations in ENSO, volcanic aerosols, solar irradiance and anthropogenic influences are shown in Figure 2. The multivariate ENSO index, a weighted average of the main ENSO features contained in sea-level pressure, surface wind, surface sea and air temperature, and cloudiness [Wolter and Timlin, 1998], extends from 1950 to 2006. It is augmented with an index derived from Japan Meteorologial Agency sea surface temperatures from 1868 [Meyers et al., 1999]. Volcanic aerosols in the stratosphere are compiled by [Sato et al., 1993] since 1850, updated from giss.nasa.gov to 1999 and extended to the present with zero values. The adopted solar forcing, consistent with IPCC [2007], is less than half that reported in prior IPCC assessments. Monthly irradiances since 1882 are estimate d from competing effects of sunspots and faculae in observations made by space-based radiometers, extended into the past using solar flux transport simulations [Wang et al., 2005]. The anthropogenic forcing is the net effect of eight different components, including greenhouse gases, landuse and snow albedo changes, and (admittedly uncertain) tropospheric aerosols [Hansen et al., 2007] (inset, Figure 2d).”
Lean and Rind then go on to detail the analyses they performed. Under the heading of “Amplitudes and Patterns of Natural and Anthropogenic Influences,” they state, “Natural changes cannot account for the significant long-term warming in the historical global surface temperature anomalies. Linear trends in temperature attributed to ENSO, volcanic aerosols and solar irradiance over the past 118 years (depicted by the lines in Figure 2) are, respectively, 0.002, -0.001 and 0.007 K per decade. Only by associating the surface warming with anthropogenic forcing is it possible to reconstruct the observed temperature anomalies.”
Basically, using a short-term comparison of NINO3.4 SST anomalies and Global RSS MSU TLT anomalies, my Figure 2, regression analyses like those used by Lean and Rind argue that natural variables cannot explain the upward divergence of global temperature from NINO3.4 SST anomalies. And if natural variables cannot explain the additional rise in global temperature, then the anthropogenic global warming hypothesis dictates that anthropogenic forcings must cause the rest. BUT…
http://i32.tinypic.com/2rw9pbq.png
Figure 2
REGRESSION ANALYSES TREAT ENSO AS A “FORCING”, NOT AS A PROCESS WITH MULTIYEAR AFTEREFFECTS
Regression analyses regard El Nino events as a climate forcing of varying frequency and magnitude, the same way they consider other natural forcings such as volcanic aerosols and solar irradiance. They do not consider the multiyear processes that can occur after those El Nino events. Before presenting these, I’ll first provide a detailed description of the processes that take place before, during, and after significant El Nino events.
EL NINO OVERVIEW
For those new to the process of El Nino events, Bill Kessler and David B. Enfield, both of NOAA, provide excellent descriptions of ENSO in their ENSO Q&A web pages. Link to Bill Kessler’s:
http://faculty.washington.edu/kessler/occasionally-asked-questions.html
Link to David B. Enfield’s:
http://www.aoml.noaa.gov/general/enso_faq/
I’ll expand on their descriptions.
During non-El Nino years (La Nina and ENSO-neutral years), warm water accumulates in an area of the western tropical Pacific known as the Pacific Warm Pool (PWP); also known as the Indo-Pacific Warm Pool (IPWP). Refer to Figure 3.
http://i30.tinypic.com/b3tpah.gif
Figure 3 (Source CRCES. Link to follow.)
Some of the warm water in the Pacific Warm Pool is water that returns there after El Nino events (the Equatorial Countercurrent in the Pacific relaxes after an El Nino and the North and South Equatorial Currents move the warm water back from the eastern to the western equatorial Pacific). More on that later. Some of the warm water in the Pacific Warm Pool results from solar radiation that warms the tropical Pacific and from the trade winds that push those warm surface waters from east to west in the Pacific during La Nina events and during ENSO-neutral periods. And some of the buildup of warm water in the Pacific Warm Pool occurs during the El Nino event itself, when cloud amounts over the Pacific Warm Pool drop significantly, causing a major rise in downwelling shortwave radiation (visible light). During the 1997/98 El Nino, it has been estimated that downwelling shortwave radiation rose as much as 25 watts/sq meter over the PWP. Refer to Figure 4. (This change in downwelling shortwave radiation was discussed in my post Recharging The Pacific Warm Pool Part 2.)
http://i41.tinypic.com/2435kbb.jpg
Figure 4
Figure 4 is from the Pavlakis et al (2008) paper “ENSO Surface Shortwave Radiation Forcing over the Tropical Pacific”:
http://www.atmos-chem-phys-discuss.net/8/6697/2008/acpd-8-6697-2008-print.pdf
The accumulation of warm water in the Pacific Warm Pool over months and years from trade winds pushing surface waters west, the periodic transport of the warm water out of the PWP by El Nino events, the blast of downwelling shortwave radiation during El Nino events, and the replenishment of the warm water during the subsequent La Nina all cause the size and temperature of the Pacific Warm Pool to vary.
Figure 5 illustrates the variations in area and temperature of the Pacific Warm Pool. The illustration is from the CRCES webpage “Natural decadal-multidecadal variability of the Indo-Pacific Warm Pool and its impacts on global climate” by Mehta and Mehta:
http://www.crces.org/presentations/dmv_ipwp/
http://i28.tinypic.com/6e3skg.png
Figure 5
CRCES also provides a Quicktime movie (2.7MB) of the annual variations in Indo-Pacific Warm Pool area and SST anomalies here:
http://www.crces.org/presentations/dmv_ipwp/images/SST_WP.MOV
The variability of the Pacific Warm Pool can also be seen in the Western Equatorial Pacific Warm Water Volume, Figure 6, which is from my post Equatorial Pacific Warm Water Volume.
http://i34.tinypic.com/xfyro1.jpg
Figure 6
Note how, during the 1997/98 El Nino, the Western Equatorial Pacific Warm Water Volume (light blue curve) drops as NINO3.4 SST anomalies (black curve) rise. This is one indication that the warm water is being carried away from the Pacific Warm Pool during the El Nino event. Also note how quickly the Western Equatorial Pacific Warm Water Volume replenishes itself. It has “recharged” by the second phase of the 1998/99/00 La Nina.
The direction shifts in the Pacific Equatorial Currents that are part of an El Nino show how the warm water volume of the Pacific Warm Pool is lowered during those events. The Equatorial Countercurrent increases in size and carries the warm water from the Pacific Warm Pool to the east. When the El Nino ends, the Equatorial Countercurrent ebbs, and the North and South Equatorial Currents carry the warm water back to the west, to the Pacific Warm Pool. These shifts can be seen in Video 1 “Equatorial Currents Before, During, and After The 1997/98 El Nino” from my post of the same name:
http://bobtisdale.blogspot.com/2009/02/equatorial-currents-before-during-and.html
Video 1
And there are subsurface changes that take place during an El Nino event. The warm water that was in the Pacific Warm Pool, most of it below the surface, shifts east during the El Nino, where it rises to the surface. These changes in the subsurface waters of the Pacific can be seen in my Video 2 “Cross-Sectional Views of Three Significant El Nino Events – Part 1”. Link to post:
http://bobtisdale.blogspot.com/2009/02/cross-sectional-views-of-three.html
Video 2
Though not discussed in Video 2, the rise of the thermocline at the end of the 1997/98 El Nino is visible. “Rewind” to minute 3:00 and start the video. After the commentary, the thermocline rises, further illustrating that warm water that was once below the surface of the Pacific Ocean has been brought to the surface by the El Nino.
Some BUT NOT ALL of the warm water that had sloshed east during the El Nino returns to the Pacific Warm Pool during the subsequent La Nina. And the warm water that doesn’t return to the Pacific Warm Pool is carried westward by the Equatorial Currents of the Pacific, Figure 7, to the surface of the Western Pacific and the Eastern Indian Oceans.
http://i30.tinypic.com/wvzu6r.png
Figure 7
There, the warm water raises the surface temperature of the Western Pacific and the Eastern Indian Oceans, Figure 8.
http://i29.tinypic.com/2a75q2t.png
Figure 8
The transport of this warm water and its aftereffects can be seen in Video 3 “Recharging The Pacific Warm Pool”. Link to post:
http://bobtisdale.blogspot.com/2008/11/recharging-pacific-warm-pool.html
Video 3
In other words, warm water that was below the surface of the Pacific Warm Pool (and not included in the calculation of global temperature anomaly) is redistributed around the surface of the nearby oceans by the El Nino, (and it is now included in the calculation of global temperature). Phrased yet another way, before that El Nino, the warm water was not included in surface temperature record but afterward the warm water was included in surface temperature record. This raises global temperature anomalies without any heat input. Keep in mind that the rearranging of waters during an El Nino does not in and of itself create heat; it only shifts warm water from below the surface of the Pacific Ocean to the surface where it impacts temperature measurements.
THIS CAN BE SEEN AS UPWARD STEP CHANGES IN THE SEA SURFACE TEMPERATURE OF ~25% OF THE GLOBAL OCEANS
And those upward step changes after the 1986/87/88 and 1997/98 El Nino events can be seen in the sea surface temperatures of the East Indian and West Pacific Ocean, the black curve in Figure 9. Also illustrated in Figure 9 are scaled NINO3.4 SST anomalies (purple curve) and Sato Index data (green curve), which I’ve added to illustrate the timing of explosive volcanic eruptions that impact sea surface temperature (and global temperature).
http://i31.tinypic.com/24l5rlw.png
Figure 9
The area represented by the East Indian and West Pacific Ocean SST anomalies (the black curve in Figure 9) is shown in Figure 10.
http://i39.tinypic.com/5n55as.jpg
Figure 10
Refer to my posts for further information:Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1
Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2
SEA SURFACES OUTSIDE OF THE EQUATORIAL PACIFIC ARE ALSO WARMED BY THE EL NINO THROUGH THE EXCHANGE OF HEAT FROM THE ATMOSPHERE TO THE OCEAN
During the El Nino events, heat from the surplus of warm surface waters along the equatorial Pacific is pumped into the atmosphere where it is carried around the globe. This raises land surface temperatures, (not illustrated). And the higher atmospheric temperature also raises the surface temperature of the oceans outside of the tropical Pacific. These increases in SST can be seen in Video 4 “Global SST Anomaly Animation 1996 to 2009”. Video 4 is from my post “Animations of Weekly SST Anomaly Maps from January 3, 1996 to July 1, 2009.” There is no narrative with Video 4. The description is included in the post.
http://www.youtube.com/watch?v=1ir1w3OrR4U
Video 4
The exchange of heat from atmosphere to ocean in the East Indian and West Pacific Oceans adds to the elevated surface temperatures that are caused by the warm water that had been carried there by ocean currents, discussed earlier. The El Nino also warms the East Pacific, South Atlantic, and West Indian Oceans through the atmosphere. Those portions of ocean basins are in turn cooled by the La Nina event that follows. But there is another portion of an ocean basin where the heat from the El Nino lingers; that is, the SSTs of that ocean basin are not impacted proportionately by the La Nina. And that ocean basin is the North Atlantic.
THE SST ANOMALIES OF THE NORTH ATLANTIC ALSO HAVE UPWARD STEP CHANGES AFTER SIGNIFICANT EL NINO EVENTS
The title of the linked post “There Are Also El Nino-Induced Step Changes In The North Atlantic” explains the content. And these SST anomaly step changes in the North Atlantic correlate well with the step changes in the East Indian and West Pacific Oceans, though they result from different aftereffects of the significant El Nino events. Refer to Figure 11. Keep in mind that the North Atlantic is also impacted by the Atlantic Multidecadal Oscillation.
http://i39.tinypic.com/15cocop.jpg
Figure 11
Assuming the North Atlantic represents approximately 15% of the global ocean surface area, then the East Indian and West Pacific plus the North Atlantic account for approximately 40% of the global ocean surface area. In the years that follow significant El Nino events, ocean currents and atmosphere-ocean processes “mix” the lingering elevated SST anomalies of the East Indian, West Pacific and North Atlantic Oceans with the remaining 60% of the global oceans. This causes the rise in global SST anomalies that presents itself as the divergence of Global SST anomalies from NINO3.4 SST anomalies, similar to that shown in Figure 2. That natural increase in SST anomalies is mistaken for warming due to anthropogenic causes.
THESE STEP CHANGES ALSO APPEAR IN GLOBAL LOWER TROPOSPHERE TEMPERATURE (TLT) ANOMALIES
The RSS MSU Time-Latitude Plots of Global TLT illustrate the transport of heat from the tropics toward the poles that result from significant El Nino events. This is illustrated and discussed in detail in my post “RSS MSU TLT Time-Latitude Plots…Show Climate Responses That Cannot Be Easily Illustrated With Time-Series Graphs Alone”. In that post, I combined Time-Series Graphs with the Time-Latitude Plots to show the effects of the significant El Nino events. But even without the time-series graphs, the 1997/98 El Nino is easy to find in Figure 12. It appears as an area of elevated tropical TLT anomalies that begins in 1998 and ends about a year later. Note that most of the heat that had been in the tropics is transported to the mid-to-high latitudes of the Northern Hemisphere, where it lingers through the 1998/99/00 La Nina. Regression analyses cannot capture that lingering aftereffect of an El Nino.
http://i42.tinypic.com/2hfukjm.jpg
Figure 12
The Time-Latitude Plots also show the impacts of the 1986/87/88 El Nino and limited TLT response to the 1982/83 El Nino. Refer to Figure 13. The 1982/83 El Nino was counteracted by the explosive eruption of El Chichon.
http://i41.tinypic.com/2vwzmdj.jpg
Figure 13
THE DIFFERENCE BETWEEN SIGNIFICANT EL NINO EVENTS AND THE OTHERS
This post primarily discussed the processes and aftereffects of the significant El Nino events of 1986/87/88 and 1997/98, using the 1997/98 El Nino as reference in many of the discussions and links. There were two other significant El Nino events since 1970, the 1972/73 and 1982/83 El Nino events. The 1982/83 El Nino was counteracted by the eruption of El Chichon, which turned it into a nonentity. As illustrated in Figure 14, there are striking similarities between the multiyear periods that followed the 1972/73, 1986/87/88, and the 1997/98 El Nino. This was discussed in detail in my post “Similarities of the Multiyear Periods Following Significant El Nino Events Since 1970.” Are these lesser El Nino events simply aftereffects of the significant El Ninos?
http://i27.tinypic.com/2gt6k5t.png
Figure 14
CLOSING
Regression analyses do not account for the multiyear aftereffects of significant El Nino events and do not account for the resulting El Nino-induced step changes in SST, TLT, and Land Surface Temperatures.
Regression analyses falsely attribute the divergence of global temperature anomalies from NINO3.4 SST anomalies to anthropogenic causes when, in fact, the divergence is caused by the lingering aftereffects of significant El Nino events.
The additional rise in global temperatures after the significant El Nino events is in reality caused by subsurface waters from the Pacific Warm Pool being transported to the surface and remaining there after the El Nino event has ended.
SOURCES
Sources of the data used in the graphs are provided in the linked posts.
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David: You wrote, “So the step changes are really a result of the ocean dumping stored energy into the atmosphere…”
The step changes I presented in this post are caused by warm water that was once below the surface of the Pacific Warm Pool remaining on the surface after the El Nino. The amount of heat being pumped into the atmosphere by the El Nino is also being supplemented by the higher lingering SSTs, which help keep the TLT anomalies elevated.
You continued, “and La Nina does not have step changes because the heat is forced to leave the system the same way all other heat does, by going to space.”
A La Nina is not the reverse of an El Nino. During a La Nina, trade winds increase above “normal”, and this “exposes” more cool water in the eastern equatorial Pacific. It raises the thermocline there.
Where does the ocean’s energy come from, and why does it collect in the PWP?
The ocean’s energy ultimately comes from the sun, but in addition to changes in TSI, there are many things that cause it to vary: cloud amount is the primary one.
Didn’t I discuss why it collects in the Pacific Warm Pool in the post? Nope, I just said it collects in the PWP. The Pacific trade winds “pile up the warm water” against Papua New Guinea and the Malay Archipelago.
timetochooseagain (09:18:15) : Leif Svalgaard (08:34:17) : “Yeah yeah, okay, but maybe we could focus on the point of this post rather than a figure in it’s illustration (one which is not the one we are intended to focus on, incidentally). It’s your hobby horse but not the point here.”
If you read carefully Figure 1 was one which the author of this abstract was proffering as being in error.
Thus Leif was just pointing out flawed methodology [as he always does]…and pretty much stating that Figure 1 was even MORE flawed than first presented as already being in error. Get it?
Hold your fire. He’s on your side.
Chris
Norfolk, VA
Bob Tisdale,
Nick Stokes made a good point regarding ocean heat.
Actually the ’98 super El Nino caused a prompt reduction in ocean heat content, between 1998 and 1999, with a small recovery by 2000 and a subsequent large increase after that.
http://bobtisdale.blogspot.com/2008/11/revised-ocean-heat-content.html
If El Nino is the answer to surface temperature increases, because of a sea surface temperature after effect, what explains the subsequent increase in ocean heat. It must be due to a radiation forcing factor of some kind.
From the solar irradience plot, it is clear that it is not the sun.
It is true that simple regression analysis can miss a phenomenon. The El Nino index may not be a direct measurement of sea surface area x temperature. But how large an error is there?
As you mentioned, the alternative to a simple regression analysis is a GCM.
It may not be predictive but it is the best alternative tool available.
It is also instructive that you say that higher surface temperature reduced the albedo over the ocean due to clouds. This is an argument for positive cloud feedback, which increases climate sensitivity. This agrees with the recent literature on this subject.
“It is also instructive that you say that higher surface temperature reduced the albedo over the ocean due to clouds. This is an argument for positive cloud feedback, which increases climate sensitivity. This agrees with the recent literature on this subject.”
Until you consider that higher SSTs are a result of El Nino phenomenon, and that El Nino can occur without extra heat additions. Therefore, the higher SST leads to less albedo from clouds, which causes more energy to enter the oceans, which causes a higher probability for ENSO, which causes higher SST, which causes….
Let’s see what the next few years bring.
timetochooseagain (09:18:15) :
It’s your hobby horse but not the point here.
If this is not the point here, what does Figure do here? What is the point of that?
DR (09:29:08) :
The TSI values appear to come from Lean […]
Apparently not everyone agrees with Leif.
When Lean has a ‘weak’ moment she concedes that “longer-term variations not yet detectable – do they occur?” see this slide from her talk at SORCE 2008:
http://www.leif.org/research/TSI-LEAN2008.png
tallbloke (14:08:41) :
believe all the sunspot counts were too low in the past as you do.
I believe that the count at maxima were too low, the minimum counts are close to zero anyway and can’t be lower. This issue is about what the values were at minima.
The science is not settled in this area.
And so is not settled in favor of a rise either. This is what I said: there is no observational evidence for upwards trend.
Robert Wood (15:50:29) :
bill (16:51:03) :
Robert Wood (15:50:29) :
TSI is the TOTAL solar irradiance from x rays to longwave IR and beyond.
i.e. it is the total energy from the sun, excluding gravity and magnetic.
The ‘other’ forms of energy are 100,000 times smaller, so hardly counts. Put differently: TSI is the amount of energy that heats a body when exposed to raw solar radiation in space. This is also how TSI is measured: you simply let sunlight fall on your detector and measure how hot it gets, to see what happens when you let sunlight fall on the Earth in order to see how hot it gets.
Lief,
I was just browsing your TSI reconstructions and you are definitely the odd man out (at least as of today’s accounting, time will tell).
What is the fundamental/primary difference between your reconstructions vs others that causes such a significant difference in overall slope since the LIA? All averaged peaks are very even (at least w/22yrs averaging).
My apologies for being off topic…
Ed
Bob –
Have you ever found thermohaline slope timeseries data?
I have worked on the percentage of hematite stained grains in sand of the Pacific coast, from the upper 2.5 cm sedimentary layer, and found a percentage of 6.25. This layer represents the last 30 years of climate, so this percentage of HSG reveals that the TSI is increasing since the last measurement of HSG percentage made by Dr. Bond and colleagues. I cannot determine how the Sun is doing this, but the proportion of HSG fluctuates proportionally with the TSI fluctuations. The formula for obtaining the trend is as follows:
%HSG = 2.052*Ln (TSI) + 1361.5
I must tell you that I obtained directly the proportion of HSG from sand taken from two places of the Pacific coast.
Bob Tisdale (13:34:06) You wrote: what causes the trade winds to relax? And that’s one of Mother Nature’s best kept secrets.
Stephen Wilde (14:10:43) : You wrote:
“Would you go with the proposition that the Trade Winds relax because the warmer waters (from an internal change within the oceans) speed up the hydrological cycle which changes the size and position of the major air circulation systems (slackening the Trade Winds) which in turn allows the warm water to slosh east ?”
Stephen, I got lost in your question. I was thinking that if the hydrological cycle speeded up the Trade Winds would have to strengthen. Yet, you came to the opposite conclusion. I trust you and Bob T. will have another go at this issue and clear up my confusion. Thanks, John
Ed (21:07:53) :
I was just browsing your TSI reconstructions and you are definitely the odd man out
Not entirely, Preminger et al. agree closely with me. They use sunspot and facular areas rather than the uncertain counts.
What is the fundamental/primary difference between your reconstructions vs others that causes such a significant difference in overall slope since the LIA? All averaged peaks are very even (at least w/22yrs averaging).
There are two important differences:
1) almost all the others are fitted to reproduce a doubling of the Sun’s open magnetic flux the past 100 years. This determines TSI at minimum. Work by several people [including the ones that proposed such a doubling in the first place] have now shown that said doubling did not happen and that the Sun’s magnetic field is now back to where it was 108 years ago.
2) almost all the others assume that the sunspot number is a measure of the ‘extra’ TSI at solar maximum. Lots of evidence shows that the sunspot number was too low before 1945 and again even more before ~1880. This influences the maximum values of TSI. You can see the effect clearly here: http://s5.tinypic.com/mmuclk.jpg if you compare the 11-year wiggles early on with the current wiggles. Note how small they were before ~1950. This shows the second effect.
My apologies for being off topic…
Ed
Nasif Nahle (21:20:40) :
%HSG = 2.052*Ln (TSI) + 1361.5
is nonsense. look at it yourself, and correct it.
Somehow I missed this:
By Nasif Nahle
http://biocab.org/Hematite_Stained_Grains_and_TSI.html
Correlation Between Total Solar Irradiance and Hematite Stained Grains During the Last 420 Years
Ed (21:07:53) :
I was just browsing your TSI reconstructions and you are definitely the odd man out
Not entirely, Preminger et al. agree closely with me. They use sunspot and facular areas rather than the uncertain counts.
What is the fundamental/primary difference between your reconstructions vs others that causes such a significant difference in overall slope since the LIA? All averaged peaks are very even (at least w/22yrs averaging).
There are two important differences:
1) almost all the others are fitted to reproduce a doubling of the Sun’s open magnetic flux the past 100 years. This determines TSI at minimum. Work by several people [including the ones that proposed such a doubling in the first place] have now shown that said doubling did not happen and that the Sun’s magnetic field is now back to where it was 108 years ago.
2) almost all the others assume that the sunspot number is a measure of the ‘extra’ TSI at solar maximum. Lots of evidence shows that the sunspot number was too low before 1945 and again even more before ~1880. This influences the maximum values of TSI. You can see the effect clearly here: http://s5.tinypic.com/mmuclk.jpg if you compare the 11-year wiggles early on with the current wiggles. Note how small they were before ~1950. This shows the second effect.
Nasif Nahle, See Pamela Gray (09:28:05) :
Leif Svalgaard (21:37:23) :
Nasif Nahle (21:20:40) :
%HSG = 2.052*Ln (TSI) + 1361.5
is nonsense. look at it yourself, and correct it.
Yes, I made a mistake, but it is not “nonsense”:
TSI= 2.052*Ln (%HSG) + 1361.5
Thanks for the observation, Leif.
John F. Hultquist (21:47:54) :
Nasif Nahle, See Pamela Gray (09:28:05):
She’s quite correct…
Leif Svalgaard (21:41:49) :
Ed (21:07:53) :
I was just browsing your TSI reconstructions and you are definitely the odd man out
Not entirely, Preminger et al. agree closely with me. They use sunspot and facular areas rather than the uncertain counts.
What is the fundamental/primary difference between your reconstructions vs others that causes such a significant difference in overall slope since the LIA? All averaged peaks are very even (at least w/22yrs averaging).
There are two important differences:
There are two Lean’s databases released in 2001. One of them is similar to your reconstruction, i.e. the reconstruction where Lean took only 11 years cycle of sunspots number, without considering proxies. The other one, which is quite disimilar with respect to your reconstruction was based on sunspots number and proxies.
Nasif Nahle (22:02:14) :
Yes, I made a mistake, but it is not “nonsense”:
TSI= 2.052*Ln (%HSG) + 1361.5
As stated it was. And even in its corrected form there is a fundamental problem. What would TSI be if %HSG was zero?
Bob,
Your discussion was food for thought. El Nino is clearly a cooling event in that the global system loses stored energy into space at a higher rate than “normal” (whatever that is) while El Nina is a heat storage event for the opposite reason. Has the heat balance for these events been calculated over their known history ? Do the last 100 years of the oscillation produce a net storage, a net loss, or no change in the heat content of the global system?
Nasif Nahle (22:32:40) :
The other one, which is quite disimilar with respect to your reconstruction was based on sunspots number and proxies.
She knows now that that one was no good.
Leif Svalgaard (22:54:25) :
Nasif Nahle (22:02:14) :
Yes, I made a mistake, but it is not “nonsense”:
TSI= 2.052*Ln (%HSG) + 1361.5
As stated it was. And even in its corrected form there is a fundamental problem. What would TSI be if %HSG was zero?
We (a mathematician and I) have considered HSG = 0% into the formula used for extrapolations. 0 is not a valid entry for the second term (Ln (%HSG), so it is considered equal to 0. Consequently, the result would be 1361.5 W/m^2, over the corresponding maximum or minimum fluctuation. Anyway, I think there is not a sedimentary layer dragged by ice drift absent of stained grains, although it could be possible in some zones of the planet.
Nasif Nahle (23:12:16) :
We (a mathematician and I) have considered HSG = 0% into the formula used for extrapolations. 0 is not a valid entry for the second term (Ln (%HSG), so it is considered equal to 0. Consequently, the result would be 1361.5 W/m^2, over the corresponding maximum or minimum fluctuation.
And if %HSG was 0.1 or 0.0001, those are clearly valid… Then TSI would be a lot higher than 1361.5… It is the very form with a logarithm that is not right.
Re: eric (19:46:20)
eric, I recommend that you take a very careful look at the following (including figure 4):
http://climatechange1.wordpress.com/2009/05/12/climate-change-a-la-naturale/
Regression analysis is a flexible tool. The problem is not with regression analysis, but rather with its application.
Maybe some of the carpenters need retraining.
John F. Hultquist (21:30:54)
A strengthening of the hydrological cycle globally does not result in stronger winds everywhere although it does move the main air circulation systems poleward and changes their relative sizes and intensities.
The initial stage is an expansion of the equatorial air masses which results in larger equatorial areas of warm air and a displacement of the Trade Winds so that they become weaker in the regions where they were initially situated.
That then allows the warm water to ‘slosh’ eastwards.