Guest Post by Willis Eschenbach
I hear a lot of folks give the following explanation for the vagaries of the climate, viz:
It’s the sun, stupid.
And in fact, when I first started looking at the climate I thought the very same thing. How could it not be the sun, I reasoned, since obviously that’s what heats the planet.
Unfortunately, the dang facts got in the way again …
Chief among the dang facts is that despite looking in a whole lot of places, I never could find any trace of the 11-year sunspot cycle in any climate records. And believe me, I’ve looked.
You see, I reasoned that no matter whether the mechanism making the sun-climate connection were direct variations in the brightness of the sun, or variations in magnetic fields, or variations in UV, or variations in cosmic rays, or variations in the solar wind, they all run in synchronicity with the sunspots. So no matter the mechanism, it would have a visible ~11-year heartbeat.
I’ve looked for that 11-year rhythm every place I could think of—surface temperature records, sea level records, lake level records, wheat price records, tropospheric temperature records, river flow records. Eventually, I wrote up some of these findings, and I invited readers to point out some record, any record, in which the ~ 11-year sunspot cycle could be seen.
Nothing.
However, I’m a patient man, and to this day, I continue to look for the 11-year cycle. You can’t prove a negative … but you can amass evidence. My latest foray is into the world of atmospheric pressure. I figured that the atmospheric pressure might be more sensitive to variations in something like say the solar wind than the temperature would be.
Let me start, however, by taking a look at the elusive creature at the heart of this quest, the ~11-year sunspot cycle. Here is the periodogram of that cycle, so that we know what kind of signature we’re looking for:
Figure 1. Periodogram, showing the strengths of the various-length cycles in the SIDC sunspot data. In order to be able to compare disparate datasets, the values of the cycles are expressed as a percentage of the total range of the underlying data.
As you’d expect, the main peak is at around 11 years. However, the sunspot cycles are not regular, so we also have smaller peaks at nearby cycle lengths. Figure 2 shows an expanded view of the central part of Figure 1, showing only the range from seven to twenty-five years:
Figure 2. The same periodogram as in Figure 1, but showing only the 7 – 25 year range.
Now, there is a temptation to see the central figure as some kind of regular amplitude-modulated signal, with side-lobes. However, that’s not what’s happening here. There is no regular signal. Instead of there being a regular cycle, the length of the sunspot cycle varies widely, from about nine to about 15 years, with most of them in the 10-12 year range. The periodogram is merely showing that variation in cycle length.
In any case, that’s what we’re looking for—some kind of strong signal, with its peak value in the range of about 10-12 years.
As I mentioned above, when I started looking at the climate, like many people I thought “It’s the sun, stupid”, but I had found no data to back that up. So what did I find in my latest search? Well, sweet Fannie Adams, as our cousins across the pond say … here are my results:
Figure 3. Periodograms of four long-term atmospheric pressure records from around the globe.
There are some interesting features of these records.
First, there is a very strong annual cycle. I expected annual cycles, but not ones that large. These cycles are 30% to 60% of the total range of the data. I assume they result in large part from the prevalence of low-pressure areas associated with storms in the local wintertime, combined with some effect from the variations in temperature. I also note that as expected, Tahiti, being nearest to the equator and with little in the way of either temperature variations or low-pressure storms, has the smallest one-year cycle.
Other than semi-annual and annual cycles, however, there is very little power in the other cycle lengths. Figure 4 shows the expanded version of the same data, from seven to twenty-five years. Note the change in scale.
Figure 4. Periodograms of four long-term atmospheric pressure records from around the globe.
First, note that unlike the size of the annual cycle, which is half the total swing in pressures, none of these cycles have more than about 4% of the total swing of the atmospheric pressure. These are tiny cycles.
Next, generally there is more power in the ~ 9-year and the ~ 13-14 year ranges than there is in the ~ 11-year cycles.
So … once again, I end up back where I started. I still haven’t found any climate datasets that show any traces of the 11-year sunspot cycles. They may be there in the pressure data, to be sure, it is impossible to prove a negative, I can’t say they’re not there … but if so, they are hiding way, way down in the weeds.
Which of course leads to the obvious question … why no sign of the 11-year solar cycles?
I hold that this shows that the temperature of the system is relatively insensitive to changes in forcing. This, of course, is rank heresy to the current scientific climate paradigm, which holds that ceteris paribus, changes in temperature are a linear function of changes in forcing. I disagree. I say that the temperature of the planet is set by a dynamic thermoregulatory system composed of emergent phenomena that only appear when the surface gets hotter than a certain temperature threshold. These emergent phenomena maintain the temperature of the globe within narrow bounds (e.g. ± 0.3°C over the 20th Century), despite changes in volcanoes, despite changes in aerosols, despite changes in GHGs, despite changes in forcing of all kinds. The regulatory system responds to temperature, not to forcing.
And I say that because of the existence of these thermoregulatory systems, the 11-year variations in the sun’s UV and magnetism and brightness, as well as the volcanic variations and other forcing variations … well, they make little difference.
As a result, once again, I open the Quest for the Holy 11-Year Grail to others. I invite those that believe that “It’s the sun, stupid” to show us the terrestrial climate record that has any sign of being correlated with the 11-year sunspot cycles. I’ve looked. Lots of folks have looked … where is that record? I encourage you to employ whatever methods you want to use to expose the connection—cross-correlation, wavelet analysis, spectrum analysis, fourier analysis, the world is your lobster. Report back your findings, I’d like to put this question to bed.
It’s a lovely Saturday in spring, what could be finer? Gotta get outside and study me some sunshine. I wish you all many such days.
w.
For Clarity: If you disagree with someone, please quote their exact words that you disagree with. It avoids all kinds of pernicious misunderstandings, because it lets us all know exactly where you think they went off the rails.
Why The 11-year Cycle?: Because it is the biggest cycle, and we know all of the other cycles (magnetism, TSI, solar wind) move in synchronicity with the sunspots. As a result, if you want to claim that the climate is responding to say a slow, smaller 100-year cycle in the sunspot data, then by the same token it must be responding more strongly to the larger 11-cycle in the sunspot data, and so the effect should be visible there.
The Subject Of This Post: Please do not mistake this quest for the elusive 11-year cycle in climate datasets as an opportunity for you to propound your favorite theory about approximately 43-year pseudo-cycles due to the opposition of Uranus. If you can’t show me a climate dataset containing an 11-year cycle, your hypothesis is totally off-topic for this post. I encourage you to write it up and send it to Anthony, he may publish it, or to Tallbloke, he might also. I encourage everyone to get their ideas out there. Here on this thread, though, I’m looking for the 11-year cycle sunspot cycle in any terrestrial climate records.
The Common Cycles in Figures 3 and 4: Obviously, the four records in Figs. 3 & 4 have a common one-year cycle. As an indication of the sensitivity of the method that I’m using, consider the two other peaks which are common to all four of the records. These are the six-month cycle, and the 9-year cycle. It is well known that the moon raises tides in the atmosphere just as it does in the ocean. The 9-year periodicity is not uncommon in tidal datasets, and the same is true about the 6-month periodicity. I would say that we’re looking at the signature of the atmospheric tides in those cycle lengths.
Variable-Length Cycles, AKA “Pseudocycles” or “Approximate Cycles”: Some commenters in the past have asserted that my method, which I’ve nicknamed “Slow Fourier Analysis” but which actually seems to be a variant of what might be called direct spectrum analysis, is incapable of detecting variable-length cycles. They talk about a cycle say around sixty years that changes period over time.
However, the sunspot cycle is also quite variable in length … and despite that my method not only picks up the most common cycle length, it shows the strength of the sunspot cycles at the other cycle lengths as well.
A Couple of my Previous Searches for the 11-Year Sunspot Cycle:
Looking at four long-term temperature records here.
A previous look at four more long-term temperature records.
Atmospheric Pressure and Sunspot Data:
Tahiti to 1950 and Tahiti 1951 on (note different units)
Darwin to 1950 and Darwin 1951 on (note different units)
Sunspots These are from SIDC. Note that per advice from Leif Svalgaard, in the work I did above the pre-1947 values have been increased by 20% to adjust for the change in counting methods. It does not affect this analysis, you can use either one.
For ease of downloading, I’ve also made up a CSV file containing all of the above data, called Long Term Atmospheric Pressure.csv
And for R users, I’ve saved all 5 data files in R format as “Long Pressure Datasets.tab”
Code: Man, I hate this part … hang on … let me clean it up a bit … OK, I just whacked out piles of useless stuff and ran it in an empty workspace and it seemed to fly. You need two things, a file called madras pressure.R and my Slow Fourier Transform Functions.R. Let me know what doesn’t work.
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From Wikipedia (I know, take it with a large spoonful of salt):
“The Pacific Decadal Oscillation (PDO) is the leading EOF (empirical orthogonal function) of monthly sea surface temperature anomalies (SSTA) over the North Pacific (poleward of 20° N) after the global mean SSTA has been removed, [and] the PDO index is the standardized principal component time series.[1]
The PDO is detected as warm or cool surface waters in the Pacific Ocean, north of 20° N. During a “warm”, or “positive”, phase, the west Pacific becomes cool and part of the eastern ocean warms; during a “cool” or “negative” phase, the opposite pattern occurs. It shifts phases on at least inter-decadal time scale, usually about 20 to 30 years.”
It is derived from ENSO processes and SST anomaly data, meaning it cannot drive anything or be the cause of an ENSO event. It isn’t a thing. It is a statistic from ENSO event data. It is not a “climatic phenomenon” in itself. If it shows a multi-decadal oscillation, then the data used to derive it must also have oscillation swings of that magnitude.
Mike says:
May 26, 2014 at 4:09 am
Say what? Not true. I don’t delete anything. I’m a guest author, not a moderator.
w.
Notice that I say the PDO is derived from ENSO processes. Our Pacific Ocean systems are felt all over the globe. So if the PDO statistic is taken from global SST anomalies, it can be said to be derived from ENSO processes, in my opinion. Bob may say that is a stretch too far. I will bow to his superior knowledge in this area.
TimTheToolMan says:
May 26, 2014 at 4:32 am
Thanks, Tim. The UV no different at all from the sunspot data. Sunspots too are lower in some cycles and higher in other cycles
But the fact that there are more spots in some cycles and less in others doesn’t stop the sunspots from having ~11-year cycles, which my method detects. Similarly, the fact that UV varies, greater in some cycles than in others, doesn’t stop the UV from having ~11 year cycles, cycles which my method would detect.
w.
Bruce Murray says:
May 25, 2014 at 4:35 pm
beng says:
May 26, 2014 at 11:01 am
Mmm … basically correct with some mistakes. The eccentricity does indeed cause an increase and decrease in TSI, with peak insolation in early January and minimum insolation in early July. So far, so good.
However, the variation peak-to-peak is actually 20.2 W/m2 (per CERES measurements), not 90 W/m2.
In addition, there’s an oddity. You’d think the southern hemisphere would receive more solar energy than the northern hemisphere, because the SH is facing the sun when we are nearest to it, in the SH summer month of January.
But in fact, both hemispheres receive exactly the same amount of energy on average over the year … how can that be?
The answer is that when the earth is closer to the sun it’s moving faster in its orbit, and when it is farther from the sun, it is moving slower. As a result, we spend less time in the hotter area and more time in the cooler area, so the total amount of sunlight comes out the same.
It’s a curious universe indeed … in any case, beng, that’s why the variation in solar intensity from January to July mostly doesn’t show up in the climate records. They get counteracted by the corresponding variations in orbital speed.
w.
beng says:
May 26, 2014 at 11:01 am
Some are commenting that Willis’ “I hold that this shows that the temperature of the system is relatively insensitive to changes in forcing.” isn’t demonstrated in this post. Maybe not, but here’s a simple example of his statement.
The earth’s eccentricity causes 90 watts/m2 more sun-power to the earth in January than July (for comparison CO2 causes a few watts/m2 extra forcing worldwide so far). Yet there doesn’t seem to be any semi-annual signal in the temp data.
=====================================
and Willis says, that’s why the variation in solar intensity from January to July mostly doesn’t show up in the climate records. They get counteracted by the corresponding variations in orbital speed.
(Willis also asserted that the difference was only 20 watts/m2, as opposed to 90 in beng post.
===================================
And yet they do show up in the climate records, and it is far more complicated then the variation in orbital speed, which after all is not related to earths 24 hour rotation.
From here, http://www.applet-magic.com/insolation.htm
“The insolation per day is measured in kilowatt-hours of energy per square meter (kW-hr/m²). The rate of energy input varies from 1.412 kW/m² at the closest approach to the Sun to 1.321 kW/m² at the furthest. If an area is receiving energy at a rate of 1.4 kW/m² for one hour that is 1.4 kW-hr/m² of energy input. If its energy input falls from 1.4 kW/m² to 1.3 kW/m² for an hours then the combined energy received is 2.7 kW-hrs/m²”
So for top of atmosphere insolation beng appears to be more correct. However both beng and Willis appear incorrect in saying as Willis did, “the variation in solar intensity from January to July mostly doesn’t show up in the climate records” It does and quiet clearly.
The average temperature of the whole earth at perihelion is about 2.3oC lower than it is at aphelion, despite the fact that it is receiving immensely more insolation. This fact, where a strong solar signal shows up as a lower atmospheric T, should give pause for any expectation that a much smaller factor, the solar cycle would over only 11 years over only 11 years, show up against all the other disparate factors affecting GAT.
One reason the GAT is lower at perihelion is that the insolation is entering the far greater SH oceans, and so is lost to the atmosphere, as Konrad, Monckton, Richard Courtney, and myself have repeatedly pointed out.
“The average temperature of the whole earth at perihelion is about 2.3oC lower than it is at aphelion, despite the fact that it is receiving immensely more insolation. ”
Thanks, I’d never seen a figure expressed like that. Useful.
The thing is that SH hemisphere has greater heat capacity due to more water , so less temperature swing. So when you add everything together it’s larger temp swing of the NH that dominates the annual cycle.
NH is in winter at perihelion so global average is at a low.
This should also tell us something about ocean out-gassing and global CO2 variations which also peaks in SH winter. The January peak can be seen in MLO data: which is basically a 12mo and a larger 6 mo cycle added together.
http://climategrog.wordpress.com/?attachment_id=721
(Yeah, the orthodoxy has some hand-waving estimations about leaf rot in NH, mostly garbage IMO 😉 )
Willis, if you’re still reading comments, here’s a test to see under what circumstances, it’s possible to see a high frequency driving signal in a chaotic system. Try the Logistics equation x sub n+1 = r * ( 1 – x sub n), where r is a fixed consant. See the wikiepdia article for a lot of info on this equation. It produces various types of chaos for values of r somewhat less than 4. The equation produces a data sequence which we might consider an analog of global temperatures. The average value of x should not depend much on the initial condition, provided you are not very lucky and start with a reasonable value (try 0.5 or see the wikipedia article) and average over enough x sub n and call the average x-bar. Now it is possible to choose values of r that will exhibit no periodicity.
And changing r will change x-bar as is easy to verify. And so the natural math experiment is to change r periodically. For example, change r to be the high value for 6 samples and then low for 6 samples. Do you see the periodicity in the sample series? Or does the effect only happen in the average? And is the average changed at all?
The equation is deterministic and that means it’s going to do some crazy things. In particular, the series is truly chaotic only over a space of measure zero (assuming I recall this stuff correctly from 30 years ago). To avoid this, I’d be inclined to add a random number to each sample, say between +0.01 and -0.01. That might help avoid periodicity problems. And it should be done for a bunch of different pairs of r or ranges of r to see what kind of stuff is lurking out there.
Greg says,,,”The thing is that SH hemisphere has greater heat capacity due to more water , so less temperature swing.”
==============================
Yes, true, but understand the SH is not permanently losing that energy to the atmosphere. Energy cannot be destroyed. Said energy is for a time lost to the atmosphere as it enters below the surface of the ocean. This is why Konrad said the ocean should not be treated as a near blackbody as it is a three dimensional surface. The question I have asked, and thus far not had answered is ..”Is the earth gaining or losing energy during the SH summer? (I think, despite the higher albedo, it is gaining.)
Heat capacity of two different objects under equal radiation is a function of the residence time of the energies involved. The greater the residence time, the greater the heat capacity. Up to 1% of solar insolation penetrates up to 800′ into the dysphotic zone. (Which actually can extend to 3000′ deep). Each disparate WL of insolation has a different residence time. Most Oceans are 8 deg C at 600 m, 6 deg C at 800 m. The shorter insolation WL penetrate the deepest. Thus if you dive with a red object it quickly loses its color. The shorter WLs of insolation vary the most over the duration of solar cycles. However their residence time is the longest, in some cases centuries.
This is why it may well take several successive solar cycles unusually weak or strong, to manifest as a GAT in the atmosphere. This is also why the oceans may have continued to heat even after the very high solar insolation values ended in the 80s, as the following cycles were still well higher then the little ice age cycles, and the large heat capacity oceans had not yet reached equilibrium with these values.
“Only two things can affect the energy content of a system in a radiative balance; either a change of input, or a change of the residence time of some aspect of the energies within the system”
(Forgive me, but this is David’s law) To look for a very small change in solar insolation, which is mostly absorbed in the deep oceans, to manifest in ONE 11 year solar cycle, is, well let me say I am not surprised it is difficult to detect, as it is competing against many other climate factors.
However, have the earth undergo seven or eight successive strong or weak solar cycles, and this input differential will certainly manifest within the atmosphere.
Keep in mind this is not even considering the solar influence at the top of the atmosphere and potential jet stream changes and cloud cover flux. Those factors within the much reduced heat capacity of the atmosphere are likely to manifest in shorter time periods.
Willis,
I haven’t had time to read through all the comments to see if someone actually found a temperature dataset that shows an 11 year cycle. But I finally got in front of my computer and used the woodfortrees application to attempt to look for a cycle. I am not sure about the value of the frequency axis on their fourier analysis section so I made an overlay of Sunspot, Pmod and RSS and I think I have them sampled properly so I clealry see a bump on the RSS that lines up with the large spike on the PMOD and SSN. That is the 11 year cycle, it should be very weak, because of the one year cycle of earths elleptical orbit causing a 130 watt square meter variance each year, but that is about what I would expect to see.
http://www.woodfortrees.org/plot/pmod/from:1979/fourier/magnitude/from:1/to:50/normalise/plot/sidc-ssn/from:1979/fourier/magnitude/from:1/to:50/normalise/plot/rss/from:1979/fourier/magnitude/from:1/to:50/normalise
It is ths SUN
Willis,
I have had a thought about your periodicity analysis with regards to looking for the near 11-year signal in other climate data. I’ve tried finding this in the above comments, but with no luck (I did mostly skim and do control-f, though, so if this is a repeat, I apologize).
My thought is, based on other people’s works and comments, that we shouldn’t be looking at raw sunspot numbers as a proxy for energy, but rather as a proxy for the energy rate into the earth. The net energy is then the integral of the sunspot number. This was shown to provide good fits to temperature data in this post on HockeySchtick. I quote from that article:
If you take the integral of sunspot number (while subtracting an appropriate baseline value) and run the periodicity analysis, you don’t find the 11-month signal any more. I have an imgur album of images that shows this result. You can see my method for getting the baseline sunspot number in this album (which is just a re-hash of the hockey schtick post).
It is my belief that this is an avenue for further exploration. It allows for the sun’s influence to still be of interest, while explaining the lack of clear 11-year cycles in temperature and other data. If sunspot number is a proxy for energy input, then any temperature or other impact isn’t the result of the instantaneous energy input, but is more a function of current and past energy inputs (a simmering pot is hot not just due to the current low setting of a burner).
The integral of sunspot number helps us autoregress, in a way, against the past amount of energy being input to the system. It’s that net energy in the system that is more important, in my view, than the instantaneous energy flux that sunspots may be a proxy for. When that view is taken of sunspots, and the integral shows no 11 year periodicity for a given baseline, then it seems reasonable to me to conclude that we have an explanation for how the sun impacts the earth without showing an 11 year signal in the various climate/weather signals.
I have done cross-correlation of SLP, SST and MAT (marine air temp) against SSN
http://climategrog.wordpress.com/?attachment_id=952
They all show some correlation to the 11y solar cycle. What is surprising is that SST shows both negative and positive lag correlation, whereas MAT and pressure show simple causal responses.
I’m not certain about this interpretation but I think it may suggest a resonance in SST to the 11y cycle.
James says:
May 27, 2014 at 6:52 am
That Hockey Stick model is interesting. I’d tried that sort of thing my self but never got as good a match as that. Though from memory the neutral value was about the same.
Integrating in that way does make sense since the Earth is integrating the incoming power.
It will not totally remove the 11y cycle but will severely attenuate it. That seems to agree with the correlation results I’ve found. There is a correlated signal but it’s fairly small.
James. What’s the “periodicity analysis” you do here? http://imgur.com/a/7kf8a#lq9RHQY
It’s interesting that the 21y region shows that same pattern as 11y. I’ve never seen that before. BTW there is still a rise around 11 in the integral version but it’s getting drowned by the oscillation. Not sure about your “periodicity analysis” .
Pamela Gray says:
May 26, 2014 at 8:39 pm
IMO the ENSO does affect the PDO. Warm (El Niño) water spreading north along the coast of the Americas would support the so-called positive phase of the PDO, which allows warmer water to enter the Arctic as well. But IMO the PDO also influences the ENSO, as in its positive phase there is cool water in the western Pacific, which could flow (slosh?) into equatorial waters, affecting the ENSO.
But IMO the main engine of the ENSO is the sun shining upon the tropical Pacific with intensities which vary over time, while also modulating cosmic ray flux, thereby affecting cloudiness.
Pamela Gray says:
May 26, 2014 at 7:35 pm
“ENSO is short term only? Really. So the Pacific Decadal Oscillation, which is derived from ENSO data, and was first suggested by ship logs, is just a figment of my imagination, as well as that of ocean fisherman, Rocky Mountain fish and wildlife experts, and many agriculture scientists.”
Please take a look at the link I provided previously as it will spare you *lots* of confusion. That link talks about changes in the ITCZ vs. solar over *thousands* of years. In that context, of course the PDO is short term.
It seems both Hadcrut3 and HadCrut4 Southern Hemisphere show the 11 year cycle as well
http://www.woodfortrees.org/plot/pmod/from:1979/fourier/magnitude/from:1/to:50/normalise/plot/sidc-ssn/from:1979/fourier/magnitude/from:1/to:50/normalise/plot/hadcrut4sh/from:1979/fourier/magnitude/from:1/to:50/normalise
Shawnhet says:
May 27, 2014 at 8:14 am
IMO the climate of our water planet is largely controlled by ocean currents. Consider how & when the current Icehouse climate began (now about 38 million years old). Antarctica started developing ice sheets at the Eocene/Oligocene boundary, when that continent was finally isolated from South America & Australia by deep ocean channels.
During the Miocene, tropical & subtropical seaways still spanned the globe, which is why there was a Caribbean monk seal (now extinct) along with a Hawaiian monk seal & Mediterranean monk seal. (During the Pliocene the Med dried up thanks to plate collision at Gibraltar, but the monk seal’s ancestors survived in surrounding oceans.) This allowed warm currents to circle the planet, so Icehouse conditions were largely restricted to Antarctica. The Miocene was warmer than now, but less so than the Eocene & Paleocene Hothouse.
Even after the Tethys Sea closed in the Pliocene, warm currents flowed through the Caribbean from the Pacific to the Atlantic. The Arctic Ocean was still ringed by trees. Then about three million years ago, North & South America joined at the Isthmus of Panama, setting up glaciation in the northern hemisphere to match that on Antarctica.
Greg,
The periodicity analysis is based on this work. You can find the original paper there. I made python code that was just their modified matlab code. The periodicity power comes from their code in using the ‘projectp’ function, then getting the power of that projection from their ‘periodnorm’ function. The method will give high powers to periods that are multiples of lower periods with high powers. This makes sense in terms of periods. If there is a strong 11-year period, you can take a 22 year period (which is just two repeated 11 years) and stack that over the data, and it will look like a good fit.
I came across that method from a WUWT post, but for the life of me I can’t find it. I ran the M-best (corrected for larger periods) and put those images in the same album. Here’s the link for convenience (the new images are at the bottom). When the algorithm corrects for repeating periods, a 22-year period doesn’t show up. In the integral, the lowest period that shows up is at 12.5, so that might be some of that 11-year period coming through.
That imgur album is a bit rough, I just wanted to show the general process so people didn’t think I was completely pulling things out of thin air. The R-squareds are for the smoothed data, not the raw data, too. I have some other images not uploaded that only shows about .85 after fitting to raw data all the way through (sunspot integral + sinusoidal function with a period of ~70 years). I didn’t see any significant changes in the coefficients, which was enough to satisfy my curiosity at the time.
I hope this addressed your questions well enough.
Hi Milo,
I see the climate as influenced by a wide variety of things including ocean currents so I don’t really disagree. I am not sure I see how ocean currents could act independently, though. I would assume that the causation works something like the following – over time a sufficient of X(ie hot, cold, salty etc..) type of water builds up in Y location which causes Z ocean current patterns to develop.
In any case, allowing this does not prevent other patterns that affect climate to be taking place such as the connection between ITCZ location and solar activity I mentioned earlier.
Cheers, 🙂
I repeat changes in solar activity are quickly visible in the stratosphere. We shall soon see.
http://www.cpc.ncep.noaa.gov/products/intraseasonal/temp50anim.gif
Shawnhet says:
May 27, 2014 at 9:41 am
IMO ocean currents are driven by solar activity, among other factors, obviously, such as volcanic activity, plate tectonics, on various time scales. Climate’s control knob is not CO2.
carlbrannen says:
May 27, 2014 at 4:01 am
I tried that equation and it didn’t do anything like what you said. I looked at the wiki article, no help, might not be the right article. An hour wasted. Folks, please provide links to your claims. Just copy and paste the link in, WordPress takes care of the rest. Also, one worked example is worth ten thousand words. You try the dang equation and show us the actual results, I’m done wasting my time on your claim.
w.
Greg says:
May 27, 2014 at 2:36 am
The CERES data gives a figure very close to that, that we are 3.4°C cooler when we are nearest the sun. However, again I repeat, the total amount of energy the earth receives is independent of the distance from the sun. Yes, the TSI goes up and down as we approach and recede from the sun.
But the planet moves faster when it is nearer the sun, and slower farther away. So it spends less time in the hot zone, more time in the cold zone, and the two exactly cancel each other out!!
As a result, for example, the southern hemisphere faces the sun when we’re nearest the sun, which would make you think that over the year, the SH would receive more W/m2 on average than the northern hemisphere … but not so. They both receive exactly the same amount.
As others have commented, the difference lies both in the thermal mass and the relative areas of the ocean and the land. Only the skin of the land is warmed, while the ocean warms and cools deeply. As a result, while overall the planet is 3.4°C warmer in July (aphehelion, furthest from the sun) than in January (perihelion), the ocean is only 0.08°C warmer … but the land on average is a full ten degrees warmer in July, because so much of it is getting heated in the northern hemisphere. It is not widely recognized that disregarding Antarctica, there is about 3X as much land in the northern as in the southern hemisphere. In addition, the oceans are partitioned 40% / 60% north and south.
Here’s another oddity … disregarding clouds and assuming clear skies everywhere, which spot on the earth do you think would get the most hours of sunlight each year?
Regards to all,
w.