Guest essay by Stan Robertson
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In a recent post entitled “Changes in Total Solar Irradiance” (http://wattsupwiththat.com/2014/10/25/changes-in-total-solar-irradiance/ ), Willis Eschenbach showed a plot of the solar irradiance that impinges at the top of the earth’s atmosphere. I have borrowed that from his post and repeat it here for convenience:
Fig. 1 Variations of TSI
Willis asked a profound question about these results:
“If the tiny eleven-year changes in TSI of a quarter of a W/m2 cause an observable change in the temperature, then where is the effect of the ~ 22 W/m2 annual variation in the amount of sun hitting the earth? That annual change is a hundred times the size of the eleven-year TSI change. Where is the effect of that 22 W/m2 change?”
This is a great question, but it is really two questions. First, why don’t we see some significant annual cyclic variation of global mean temperature? This is a truly profound question! It ought to keep climate modelers awake all night, every night. Second, if 22 W/m2 variations peak to trough don’t produce noticeable temperature variations, why should the 0.25 W/m2 variations of TSI associated with solar cycles produce any measurable temperature variations?
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Let’s take the first question first. TSI reaches a peak on January 3 when we are nearest the sun and drops to a minimum six months later. Now 22 W/m2 is comparable to the change of TSI at 60 degrees north or south latitudes between ice ages and interglacial times. On this basis, one might expect to see a fairly substantial annual cyclic variation in global mean temperature. I failed to recall any in the many plots of global temperature anomalies that I have seen, but thought perhaps that single years wouldn’t stand out clearly in long, noisy records. So I grabbed a quick ten year data plot that I happened to have on hand to see if it showed annual cycles. None were obvious, but just to be sure, I took another look at the (also-quickly-available) periodogram for sea surface temperatures that I had made for a previous WUWT article (http://wattsupwiththat.com/2014/07/26/solar-cycle-driven-ocean-temperature-variations.) Not only is there no significant temperature variation with a one year period, there IS a small amplitude oscillation (0.13 oC peak to trough, 2X amplitude) at the 11 year solar cycle period with oscillation peaks that are nicely in phase with the sunspot peaks.
Fig. 2. Amplitude Periodogram of sea surface temperature anomalies 1954 – 2014
One of the first suggested explanations for the lack of annual cycles that I recall was that the variations might occur too fast for the earth mean temperature to respond. Considering that temperatures of either the northern or southern hemispheres of earth respond dramatically on a seasonal time scale to changes of solar flux at the surface, this seemed unlikely to me. Nevertheless, I dusted off my old computer program for calculating ocean surface temperature changes for changes of impinging solar flux. Previous calculation results have been reported here: (http://wattsupwiththat.com/2013/10/10/the-sun-does-it-now-go-figure-out-how) and here: http://wattsupwiththat.com/2014/07/26/solar-cycle-driven-ocean-temperature-variations
In the first of these, I found that a thermal diffusivity of 1 cm2/s for upper ocean waters was needed to account for the ocean surface temperatures (HadSST3gl) and ocean heat content measurements since 1965. If there were no changes of cloud cover or evaporation, 70% of that 22 W/m2 or 15 W/m2 would enter the atmosphere. If it impinged on oceans, it would drive annual temperature variation of 0.45 oC peak to trough. The temperature oscillations would, indeed, be larger if the solar flux variations occurred over a longer time. With a ten year period, they would produce temperature oscillations of 2.25 oC. In either case, most of the variations of the peak heat flux would be taken into the oceans and eventually returned later. Nevertheless, annual oscillations of 0.45 oC ought to stick out like a sore thumb in Fig. 2. So why don’t they occur? The only plausible explanation is that increases of cloud cover prevent most of that 22 W/m2 variation from ever reaching the surface. If absorbed by atmosphere, land or ocean, large temperature changes would necessarily follow. The minimum temperature increases would be those of the oceans, due to their transparency and large heat capacity. But they don’t show!
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We can make this a little more quantitative to show that there is reason to believe that most of the TSI variations are negated by changes of cloud cover. The variations of cloud cover should correspond to variations of the atmospheric water column, as shown here in this plot from http://www.climate4you.com .
Fig 3. Atmospheric water vapor column (thickness if subjected to 1 atm pressure)
The total water column varies annually by about 0.45 cm peak to trough, for about 19% annual variation. Taken as a sinusoidal oscillation, its peak to trough variation would be 0.45 cm and its rate of change would have a peak to trough variation of (2 π 0.45 cm/yr). This rate of change would need to be provided by the solar flux that evaporates water at the earth’s surface. It takes about 2260 joules per gram to evaporate water. Then neglecting the minor amount of energy needed to lift the water vapor up into the atmosphere, the peak to trough rate of energy change needed for evaporation at the earth surface would then be:
(2 π 0.45 cm/yr) x (1 gm/cm3 x ( 2260 j / gm) x (1 yr / (365 x 86400 s)) x 104 cm2/m2 = 2 W/m2
This shows that very little of the available TSI variation is needed to produce the annual changes of atmospheric water column and, presumably, the variation of cloud cover. But if earth albedo changes in proportion to the variation of the atmospheric water column, then reflected solar radiation would vary by 19% of the mean 101 W/m2, or 19 W/m2. That would leave only about 3 W/m2 of the 22 W/m2 of TSI variation available to heat the earth surface. Since about 2 W/m2 is needed to produce evaporation, that leaves only about 1 W/m2 to be absorbed and warm the surface. Using the same computer program that I mentioned previously, I calculated that 1.0 W/m2 annual variations at the ocean surfaces would produce surface temperature oscillations of about 0.037 oC peak to trough. This is too little to be reliably extracted from noisy sea surface temperature data, but this is about what is shown in Figure 2.
A careful examination of Fig. 3 shows that the water column peaks seem to occur about late October rather than Jan. 3. The early peak is thought to be due to the end of the vegetation growth season in the northern hemisphere. The larger land mass of the northern hemisphere allows it to contribute more to evaporation during its growth season than does the southern hemisphere. This puts the annual TSI variation and cloud cover variation slightly out of phase but that really doesn’t matter much as long as there is enough extra cloud in January to negate the peak TSI. Another point worth noting about Fig. 3 is the step change downward after the 1998 El Nino. Prior to that, the water column was increasing, presumably because of surface warming and increasing evaporation. The smaller water column since 1998 is consistent with some cooling and the flat global temperatures of this century.
The most significant result of the preceding analysis is that it is clear that evaporation of water vapor into the atmosphere and cloud formation must provide a very strong negative feedback to radiative forcing in the UV/Vis bands that deliver most of the solar energy to earth. Starting from the present near-equilibrium conditions, a decrease of albedo would let more solar radiation reach the surface of the earth. That should be able to evaporate more water, produce more clouds and raise the albedo. If the albedo were to increase a bit beyond equilibrium, the surface would receive less insolation, the upper oceans would cool and cloud cover would decrease until balance was restored. Considering that downwelling infrared radiation is absorbed essentially at the ocean surfaces, the only thing that it can do is produce evaporation. We have just seen that a radiative forcing of 22 W/m2 apparently produces only a few hundredths of a degree of ocean surface temperature change. It seems a bit absurd to think that the 3.7 W/m2 of IR forcing that is expected to accompany a doubling of the atmospheric concentration of CO2 might do more. CO2 is simply not the control knob for the earth’s temperature.
Since cloud cover is so exquisitely regulated that it maintains a steady mean temperature, it would appear to be necessary for climate models to handle clouds well. In fact, however, that is one of their weaknesses. In general, the models used by the IPCC do a miserable job of modeling rainfall. It is highly likely that they are doing an equally poor job of cloud cover and albedo. Until this situation is dramatically improved, the climate models will remain essentially useless for anything but scare tactics.
Moving on to Willis’ implied question: If 22 W/m2 produces no significant temperature variations, why should the 0.25 W/m2 associated with the approximately 11 year solar cycles have the larger effect shown in Fig. 2? Only about half of this small amount would even reach ground level anyway. So how is it that we see 11 year solar cycle period temperature variability in the 60 year sea surface temperature record of Fig. 2? There are several possible explanations here. Some folks claim that the solar cycle temperature oscillations are spurious, but that seems unlikely to me for several reasons. First, the temperature peaks match the sunspot peaks. Second, I showed that Willis’ slow Fourier transform technique is quite capable of pulling this small signal out of the noisy data. Additionally, Roy Spencer, Nir Shaviv and others have found temperature variations of similar magnitude using different methods and data sets. Leif Svalgaard thinks that ~ 0.1oC temperature variations are real; however, he mistakenly persists in thinking that TSI variations of order 0.1 W/m2 at the earth surface can cause such temperature changes in several tens of meters of upper oceans. (Bear in mind that the first 25 meters of ocean has about 10X the heat capacity of the entire atmosphere.) Others claim that the temperature variations are spurious due to significant volcanic eruptions having occurred with approximate solar cycle timing. I think this to be very unlikely on a 60 year data set.
So, let’s take the question and the result of Fig. 2 seriously for a moment. The TSI variations associated with the solar cycle are only about 0.25 W/m 2, averaged over the earth surface and daily cycles. About 70%, or 0.175 W/m2 enters the troposphere. About (160/340)x0.25W/m2 = 0.117 W/m2 reaches the surface at wavelengths below 2 micron. About half the difference between the 0.175 and 0.117 W/m2 reaches the surface at longer wavelengths and after scattering in the atmosphere. This gives a peak to trough variation of about 0.15 W/m2 that would reach the surface. This is only about 15% of the 1.0 W/m2 that would be needed to drive surface temperature oscillations of 0.13 oC. So without even considering the possibility that changes of albedo might prevent most of the solar flux variation from even reaching the earth, it is apparent that TSI variations associated with the solar cycle do not provide enough energy to produce the temperature oscillations shown in Fig. 2.
To make it even more certain that the TSI variations are not the direct cause of the surface temperature oscillations, recall that albedo variations of about 19% were sufficient to negate the 22 W/m2 annual TSI variation and that this required only about 2 W/m2 to evaporate the water. One would therefore expect that about one could negate 0.25 W/m2 variations with about (0.25/22)x2 = 0.023W/m2. This is only about 15% of the 0.15 W/m2, 11 year, TSI variation that would occur at ground level if there were no albedo change. So even though the TSI variations would be too small to produce the observed surface temperature changes, they should easily evaporate enough water for a nullifying negative feedback. So the tiny variations of TSI associated with the solar cycle should be just as effectively negated as the 22 W/m2 of the annual cycle. This leaves a very stark question: If the temperature oscillations of Fig. 2 at the 11 year period are real and if they are produced by the sun, then how could the sun do it?
To answer this we need to consider another point made by Willis Eschenbach here: http://wattsupwiththat.com/2013/12/28/the-thermostatic-throttle/ . He showed that the evaporative feedback that regulates Earth’s albedo and temperature functions most strongly near the equator. Oceans areas near the poles show the reverse behavior. Tropical albedo changes cool the tropics, but near the poles the albedo decreases with increasing temperatures. This has the effect of making the equatorial zone cooler than it would be otherwise, while making the poles warmer. There seems to be less of either positive or negative feedback in mid-latitudes. This is what allows volcanic eruptions and other atmospheric disturbances outside the equatorial regions to affect surface temperatures. If the sun contributes something other than the dinky TSI changes over solar cycles, and outside the equatorial zone, then it might be able to produce the oscillations shown in Fig. 2.
It is well known that large volcanic eruptions can cool the earth. Volcanic ash shades the earth and produces short term cooling, but the most significant and longer lasting effects occur due to aerosols. The USGS (http://volcanoes.usgs.gov/hazards/gas/climate.php) says: The most significant climate impacts from volcanic injections into the stratosphere come from the conversion of sulfur dioxide to sulfuric acid, which condenses rapidly in the stratosphere to form fine sulfate aerosols. [Cloud droplets grown on] the aerosols increase the reflection of radiation from the Sun back into space, cooling the Earth’s lower atmosphere or troposphere. Several eruptions during the past century have caused a decline in the average temperature at the Earth’s surface of up to half a degree (Fahrenheit scale) for periods of one to three years. The climactic eruption of Mount Pinatubo on June 15, 1991, was one of the largest eruptions of the twentieth century and injected a 20-million ton (metric scale) sulfur dioxide cloud into the stratosphere at an altitude of more than 20 miles. The Pinatubo cloud was the largest sulfur dioxide cloud ever observed in the stratosphere since the beginning of such observations by satellites in 1978. It caused what is believed to be the largest aerosol disturbance of the stratosphere in the twentieth century, though probably smaller than the disturbances from eruptions of Krakatau in 1883 and Tambora in 1815. Consequently, it was a standout in its climate impact and cooled the Earth’s surface for three years following the eruption, by as much as 1.3 degrees at the height of the impact. Sulfur dioxide from the large 1783-1784 Laki fissure eruption in Iceland caused regional cooling of Europe and North America by similar amounts for similar periods of time.
These comments show that naturally occurring variations of aerosols are capable of producing surface insolation changes that are NOT entirely killed by negative feedback.
As long-time WUWT readers are aware, the Danish researcher, Henrik Svensmark, in 1996 proposed that cosmic rays that enter the atmosphere can produce aerosol condensation nuclei. The flux of cosmic rays is modulated by the strength of the sun’s magnetic field that reaches the earth and this varies with the nominal 11 year solar cycle. Fewer cosmic rays reach earth at the solar cycle peaks than at minima. This has been confirmed by direct measurements of cosmic ray flux over several solar cycles. Recent studies also seem to confirm that condensation nuclei can be produced by cosmic rays. See, e.g., http://www.youtube.com/watch?v=sDo7saKaEys .
What remains to be seen is whether the amounts of cosmic ray produced condensation nuclei and their variations are capable of significantly modulating the amount and reflectivity of cloud cover. This should be settled by measurements within the next decade or two. It would take very little change of cloud cover to produce the 0.13 oC peak to trough temperature oscillations at the 11 year period shown in Fig. 2. In the WUWT article in which I first used Fig. 2, I showed that it would take peak to trough variation of solar flux of about 1 W/m2, averaged over the sea surfaces to produce this temperature oscillation. This solar magnetic field effect would presumably occur over all latitudes from poles to equator. It would need to produce an average of about 1% change of cloud reflectivity, which presently reflects about 100 W/m2 of the average TSI at the earth.
Conclusions: The feedback that negates the effect of 22 W/m2 should be of huge concern to climate modelers. The amounts, types, both vertical and horizontal distributions and albedo of clouds need to be accurately modeled in order to determine the patterns of surface temperature on the earth. In these regards, I think that the present models used by the IPCC are inadequate, misleading and lacking in any ability to predict global mean temperatures for the future.
Whatever one might think to be the cause of the temperature oscillations shown in Fig. 2 at the nominal 11 year solar cycle period, it should be very clear that the TSI variations over a solar cycle are completely incapable of producing them. If the sun really is responsible for producing those small temperature changes, then Svensmark’s cosmic ray modulation theory would seem to be our best hope for understanding how it does it. Think of the cosmic ray modulation as a small amount of jiggling of the earth’s cloud thermostat. About one percent modulation of cloud albedo over a nominal 11 year solar cycle is all that is required.
Or maybe I should just say:
I’ve looked at clouds from both sides now
From up and down and still somehow
It’s cloud’s illusions I recall
I really don’t know clouds at all
Biographical Note: Stan Robertson, Ph.D, P.E., is a physicist, retired from Southwestern Oklahoma State University.
Presuming Roberson is right or even that Svalgaard is right then both imply Earth’s temperatures should be close to steady state. What, then, tips the Earth into glaciation for hundreds of years and then reverses it?
A question that has exercised me since I first started to look more closely at climate science about ten years ago!
I have two working hypotheses – one favoured by my colleague analysing the ice-core and marine sediment cores; and one evolving from my largely intuitive disbelief of his conclusions. Almost all of the science literature finds that orbital variations in insolation – particularly at 65 North, prime the steady state system of ‘ice-ages’ for a sudden threshold response. There also appears to be a roughly 10kyr cycle, most readily seen in the Greenland ice-data for 50-30 kyr BP, so after a number of these cycles, the system becomes sensitive enough to flip by 10-15 C degrees at the poles and 3-5 degrees at the equator. The roughly 100 kyr cycle is then held to be a combination of inclination, eccentricity and precessional cycles – and the explanation as to why some peaks in-between do not produce deglaciation may lie in the sensitivity of the system which somehow increases as the glacial period nears its end-time. We know, for example, that the glacial planet is much drier and dustier, and probably has less cloud; it also has a more zonal pattern of jetstreams with more southerly tracks of cyclones. CO2 is reduced to 180 ppm. My colleague thinks that this system is then a lot more sensitive to small upward changes in CO2 – and at first thought that these could trigger deglaciation, once the orbital parameters had primed the system. The standard view is that although orbital changes in annual wattage are small, the changes in summer insolation at 65N are quite large enough to melt snow cover on land and decrease albedo, reduce sea-ice, increase freshwater input to the North Atlantic, and perhaps affect the oceanic system of currents and overturning circulation – a system of positive feedbacks amplified by release of CO2 from the warming and upwelling oceans.
The problem I have with the standard view – and my colleague’s closer look at it as a damped oscillator, is that assumptions are made about past system responses which ‘fit’ the known changes , whereas there is very little direct evidence for these mechanisms. Furthermore, the rise in regional mean temperature that precedes the global warming of the oceans is very sudden – of the order of 1 degree C/year in the northern hemisphere (damped around the equator by a factor of five). The polar ice-cap changes precede the equatorial and oceanic changes by several hundred years. Only a major shift in wind patterns can do this – from zonal to meridional.
So what else, other than this threshold idea, can trigger such abrupt shifts in wind patterns?
I am not convinced by the posited internal mechanisms and look to the Sun as a potential source of ‘abrupt’ change. This would not likely be insolation changes, rather magnetic flux and farUV effects…which have been implicated in shifting the jetstream equatorward (Drew Shindell’s work at NASA in 2001-2003). Recent jetstream dynamics during sudden and unexpected low magnetic status (since 2006) show more meridional patterns. Certainly these changes in wind patterns would affect cloudiness, albedo, and surface insolation and quite abruptly. If I am right, then proxies for the magnetic status of the Sun should show low magnetic status as the ‘norm’ over the 100 kyr cycle, with 10 kyr pulses of higher activity and perhaps a major period of activity for the final deglaciating cycle. The problem at the moment is that the proxy for magnetic status (also therefore the proxy for far-UV) is also affected by wind changes (via rates of snow accumulation). And although there has been a major reduction in magnetic status – there has not been a significant change in cloud patterns or surface temperatures (other than the failure of temperature to go on rising after the drop in cloud cover during the high solar status period of the late 20th century; and a slight recovery in cloud cover after 2001, when solar magnetic status was high.
So – for me, the mystery endures, but for many it was solved some time ago.
The biggest problem with the Milankovich cycle explanation of glacials is that like almost all other studies of natural phenomena, it limits the time span to a period of clear patterns and then correlates a known phenomenon with the pattern. If you consider global climate in geological spans of time, the available evidence indicates that the climate changes in a manner that no current theory explains.
Shaviv and Veizer make a serious attempt, but they reach outside the solar system to find an answer. If they are right, then no internal explanation will ever suffice. There have been some serious efforts to defend CO2’s influence on climate over the Phanerozoic (e,g. http://www.atmosedu.com/Geol390/articles/RoyeretalCO2GSAToday%2704PhanerozoicClimate.pdf) and these do address Shaviv and Veizer, but they only correlate CO2-levels to glacial epochs. While no one disputes that there is clear indication that very low CO2 levels and very low temperatures correlate (we can even see this over the comparatively short Pleistocene span), there is no evidence at all that very high levels of CO2 correlate with very high planetary temperatures. Worse, since there have only been two very cold/very low CO2 episodes in the last 500 My: the Permian/Triassic transition and the Pleistocene-Holocene, even that huge span may not offer a sufficiently long data span to extract climate regularities. There may well be none to extract.
Duster,
The only interval comparable to the ongoing Cenozoic Ice House is the Late Carboniferous/Early Permian Ice House, which stayed cold enough long enough for CO2 levels to fall perhaps as low as they do during Pleistocene glacial phases.
The prior Ice House occurred during the relatively brief but intense glaciation (Ice Age) at the Ordovician/Silurian Period boundary, under CO2 levels ten to 20 times higher than now.
Cosmoclimatology at least offers an explanation for the periodicity of Ice Houses (~every 150 million years), although the Mesozoic one (at the Jurassic/Cretaceous boundary) was too warm & the continents too far from the poles for a full-blown Ice Age to happen then.
Milankovitch Cycles of course happen continuously, but other factors need to be in place for them to produce the periodic glacial & interglacial phases observed in the current & previous Ice Ages.
Anthony, I fear you need to vet these submissions a bit more closely. An entire complicated analysis about a lack of seasonal variation that uses a data set from which seasonal variation has been removed? Come on.
Yes, not the first time in that last week or two either. 🙁
Indeed, This is not the first time in the last week or so either. 🙁
Indeed, not the first time in the last week or so either. 🙁
Sounds sort of curious. In the anual tropics cycle, the lag in the warming peak is more than double the lag in the cooling peak.
plazaeme, I suggest you read my posts above, Firstly you seem to have your sun-earth distance wrongly aligned in time. See above.
Also if you fit a 6mo and 12mo cosine to d/dt(SST) in the tropics it all ties up quite closely with max over head sun at the equinox and perihelion in January.
Nothing odd at all.
What is your red line? Distance to the sun (solar insolation) peaks 5 January, and is at its yearly minimum mid-July year.
He was using “monthly” data based on 21st of each month. 🙁
Dr. Robertson,
Well said. It is even more interesting that actual temperatures go against the 22w/m2. If you and Willis are right then it makes sense that the greater exposure in the southern hemisphere of ocean water would have an impact on temperatures.
P.S. your figure 2 is missing!
v/r,
David Riser
The figures do not appear here as they are in the Word doc that I emailed away, but it doesn’t matter. This whole submission is wrong in several respects. As several have noted, the seasonal variations are removed from anomaly plots and I should have caught that. Please read Greg Goodman’s comments above to see what I should have found.
DR. Robertson,
I am aware of the error, but my point is that the error is not really a problem to the greater question. I say this because the temperature reacts differently in each hemisphere in the opposite direction of the forcing. Your thoughts on this would work based on the idea that the southern ocean has much more water surface area which would lead to more cloud formation from excess energy. The Northern hemisphere has a great deal more land surface in the critical 0-23 degrees of lat which reduces the moderating effect of cloud creation from ocean water evaporation. just my two cents.
v/r,
David Riser
I think the 22 Wm-2 is wrong. The trough to peak variation is more like 100 Watt per square metre. Eccentricity of 0.0167 will give you 94 on a base of 1365, or check the “TSI True Earth” on the SORCE website, which cycles from the low 1300s to the low 1400s. R.
The TSI intercepted by the Earth varies indeed by nearly 100 W/m2, but has to be distributed over the whole surface [a sphere], whose area is 4 times as large as the area of the intercepting flux [a flat disk], hence 22 ≈ 92/4
Shouldn’t the fact that the earth spends less time near the sun than it does in the far part of the orbit, be taken into account? So northern winters are shorter than southern ones.
Indeed, damn that factor of 4….!
What’s more it provides an answer to Willis’ “very good question” : how much does this affect global temps.
Well, at least I derived an answer for the tropics which have the strongest neg. feedbacks:
http://wattsupwiththat.com/2014/11/11/cloud-feedback/#comment-1786422
… and the follow-on comments.
“… if that 0.4 degrees results from 22W/m2 annual variation then 3.7 W/m2 of AGW would lead to 0.06 deg C rise in tropics.”
That would seem to be what the author set out to do. So a bit of peer reviewed worked a treat.
Probably a little more for extra tropics which have less forceful negative feedbacks.
Actually, that does not necessarily follow since the AGW is all longwave IR whereas the 22W/m2 is “broadband” solar. It’s probably the short vis and UV components that are doing the warming.
I think that Svensmark’s cosmic ray theory is probably the best explanation for climate changes. Readers should watch the following video that explains so much about the issue:
Thank you Stan Robertson for this informative post. Heavy reading for me as well as looking up various links. Be happy to fork out a couple of quid or so for a kindle version of the whole story. 🙂
I see we’re now in an agreement with China to save the world from AGW.
What could possibly go wrong.
No. Obama wants to save , the Chinese want to buy the world.
They have agreed to mutually work to jerk off the population of the West.
Anomalies are relative to the mean for that particular month. For example, the February anomaly is relative to the average of all Februaries, August’s anomaly refers to the average of all Augusts etc. So, you should not expect to see any cyclic variation by looking at anomalies. To do this, it is necessary to look at the absolute temperatures for those months. Edim has posted a graph that does this and shows a marked cyclic variation throughout the year.
The warmest month (globally) is July and the coldest is January (although January is the month when the Earth is closest to the Sun). This occurs because most of the land mass is in the Northern Hemisphere(NH) and land warms and cools more quickly in response to changes in TSI. This means that the globe warms in the NH summer and cools in the NH winter and the magnitude of this change overwhelms the 22W/m2 change in TSI.
Which proves the total futility of averaging two incompatible measurements.
The average of an apple and an orange is a fruit salad.
Not very helpful.
However, if you look at d/dt(SST) in the tropics it all makes a lot more sense 😉
http://wattsupwiththat.com/2014/11/11/cloud-feedback/#comment-1786442
Using Leif’s figure of 1.4 W/m2 for solar cycle variation in TSI:
0.4deg C / 22 * 1.4 = 0.025 deg C in tropics, expect more outside tropics where feedbacks are less strong. It remains very small and compatible with his suggested figure of 0.1 deg C.
Greg, thanks for correcting my errors and doing what I should have done. I have enjoyed the resulting discussion, but with a lot of egg on my face. But I still regard Leif’s calculation as inapplicable. Most of the outgoing IR at the top of the atmosphere originates from cloud tops rather than the earth surface. The temperature there is closer to 255 K than to 288 K. One cannot just look at the top of the atmosphere and assume that the radiation arises from a blackbody surface below the clouds.
Yes, I thought the dT/T=dS/S idea makes some huge unspoken assumptions. I did not bother commenting since there’s no chance of correcting someone who knows it all already and with an ego bigger than his telescope. Always a waste of huff and puff in my experience.
Thanks for the positive comment. It was interesting to find direct signal of earth-sun distance. It would be interesting to do it with actual ephemeris data rather than a cosine approximation. There’s phase mismatch of about 12 and 15 days in the two cases that I’d like to explain. ( I log that monthly means at mid month, so it’s not that.)
Also the neg. f/b should give a phase lag in the other sense I think but as a first stab it’s interesting.
Solar EUV causes the Ozone layer to warm and expand the upper atmosphere. The EUV has such a strong effect that NASA monitors it and issues alerts to satellite operators. Strong EUV can expand the atmosphere so much that the increased drag will change the satellites orbits.
A thickened atmosphere keeps in heat [infrared]. The “Ozone holes” allow heat to escape [infrared].
Why is this smoking gun ignored??
Perhaps because it’s wrong?
For example EUV is absorbed in the thermosphere not the ozone layer. A thicker thermosphere doesn’t ‘keep in heat’.
You are incorrect. You need to study and learn the facts. The Ozone layer is thickened by the Solar EUV!!
EUV is the spectrum below ~124nm and is absorbed above ~130km, the Ozone layer lies between ~20 and 30km.
what’s going on with Artic Sea Ice. Trend is down!
The price of corn is down too ! OT much?
Greg, you never learned that if you dont have something nice to say, don’t say anything at all. Don’t worry, you are forgiven.
Climate models do a very poor job with clouds, and a poor job with precipitation. From which it can be inferred that they don’t get specific humidity right either. Documented in essays Cloudy Clouds and Humidity is still Wet.
The reason is intrinsic. Smallest computable grid cells are at least one order of magnitude larger than what is needed to physically convection cells responsible for humidity transport into the troposphere, cloud condensation with release of latent heat, and precipitation washing out humidity. Explained and illustrated in essay Models all the way Down. Since time steps must increase as grid cells shrink, the computational gap is rule of thumb two orders of magnitude and unlikelymtombe solved by any supercomputer forseeable in the next few decades.
Tangible evidence of both above statements is the physical absence of the CMIP5 modeled tropical troposphere hotspot. Evidence presented by Dr. Christy to Dr. Koonin’s APS climate statement review committee. All covered in Blowing Smoke, essays on energy and climate.
“A careful examination of Fig. 3 shows that the water column peaks seem to occur about late October rather than Jan. 3. The early peak is thought to be due to the end of the vegetation growth season in the northern hemisphere. The larger land mass of the northern hemisphere allows it to contribute more to evaporation during its growth season than does the southern hemisphere.”
The fertilization effect on plants has contributed greatly to the increased vegetative health, planet wide. This in turn, has increased plant transpiration significantly. This is especially true in the Northern Hemisphere.
That contribution to low level moisture and precipitable water vapor in the lower levels, has reduced lifting condensation levels, which has resulted in more lower level(cumulus) clouds, that develop earlier in the day and block more SW radiation. This has also contributed to rain events with a positive feedback going on there.
With regards to global warming, the increase in vegetation acts as a negative feedback, not only via albedo changes from more low clouds but also from changes in the surface albedo from the increase in vegetation.
An additional factor is related to increased rainfall and in some locations a positive feedback in the water cycle as the additional transpiration leads to increases in rainfall, which continue to be used by plants that transpire back into the atmosphere.
We are also seeing clear evidence that diurnal temperature departures are less. Minimums are higher, while maximums are not. Much of the global warming contribution has come from higher min’s(warmer nights). This is consistent with the above.
Stan wrote:
“The most significant result of the preceding analysis is that it is clear that evaporation of water vapor into the atmosphere and cloud formation must provide a very strong negative feedback to radiative forcing in the UV/Vis bands that deliver most of the solar energy to earth.”
Around half of solar heating is in the near infra-red, where there are several absorption bands for water vapour.
“Then neglecting the minor amount of energy needed to lift the water vapor up into the atmosphere..”
Does it rise simply due to its low density?
“This leaves a very stark question: If the temperature oscillations of Fig. 2 at the 11 year period are real and if they are produced by the sun, then how could the sun do it?”
I would discard the periodicity analysis, and study the chronology of discrete events to see if they aligned better with the solar wind peaks and troughs better than the sunspot cycle. That could also help explain the other large peaks in fig 2.
Distribution of water vapour is also a critical factor:
http://www.fourmilab.ch/cgi-bin/Earth/action?opt=-p&img=vapour.bmp
(check “no night” and then click “update”.)
Sadly this seems like a hit and run article. I would have thought the author would have wanted to follow reaction and correct some of the bloopers.
Maybe he’s rewriting it now …
It’s a little disappointing from someone with his credentials.
Agreed
The author comments as “bones”.
Senility is a curse. I should have known intuitively that anomaly plots suppressed seasonal effects. It seems that my ocean heat program nailed the 0.45 C variations, but that is small consolation. If not for some other pressing time demands, I would be fixing some problems here. The effect of CO2 forcing still should be small, say (3.7/22)x0.45 = 0.075 C. That point and the small amount of heat required to change the atmosphere water column might be worth salvaging someday.
Stan Robertson
Thanks, Dr. Robertson.
“there is reason to believe that most of the TSI variations are negated by changes of cloud cover.”
I think yes, this are changes driven by the Eschenbach convection thermostat and the Svensmark nucleation from cosmic rays.
clouds do not affect TSI in any way. What you maybe meant was the effects of TSI variations on climate.
Those were “negated” by the author choosing an anomaly dataset. Try reading some of the above discussion.
The amplitude of the annual component of just 0.4 deg C pk-pk that I found in tropics confirms strong negative feedbacks are present. Also note that Reynold SST has a small non significant negative trend over the full record. beginning in 1980. Not a sniff of warming going on.
Climate by definition is a Coupled Non-Linear Chaotic System.
Thus we would not expect to see small cyclical changes in [one of many] inputs as cyclical changes in [one of many] outputs — certainly not when there are untold metrics and myriad ways of looking at climate “output”.
Recommended reading ==> Gleik’s “Chaos – Making of a new Science” and/or Ian Stewart’s “Does God Play Dice?”
For more advanced readers ==> “Chaos and Fractals: New Frontiers of Science” by Heinz-Otto Peitgen, Hartmut Jürgens, Dietmar Saupe
It is only given that definition by people that do not understand it.
It’s all “stochastic” except the bit they want to keep. That’s 95% certain, dangerous, toxic worse than ebola and ISIL all rolled together. We MUST act NOW ( before the penny drops ).
1975 to 1995 was not at all stochastic, it has been proven to be caused by humans, however, it’s been getting a lot most stochastic for the last 18 years and 1 month. 1945 to 1975 was a pretty stochastic bit too.
Reply to Ulric ==> Edward Norton Lorenz discovered this during the 1950s. “Lorenz became skeptical of the appropriateness of the linear statistical models in meteorology, as most atmospheric phenomena involved in weather forecasting are non-linear.[2] His work on the topic culminated in the publication of his 1963 paper Deterministic Nonperiodic Flow in Journal of the Atmospheric Sciences, and with it, the foundation of chaos theory._ — Wiki
Dr. Brown, at Duke, goes into this quite a bit in his recent post in the comments particularly.
The IPCC says “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. ” TAR – Working Group I: The Scientific Basis
It is those who do not acknowledge this fact and its implications that run into trouble.
Kip, it’s not a fact at all, it’s just a label to make it appear like they know what they are talking about, that’s the price of being an official expert, you can’t just say nothing. Their whole approach is backwards anyway, they attempt to forecast likely future regional weather states by modelling the climate change. While the only way to forecast climate with any certainty whatever, is to forecast what the short term solar effects on atmospheric teleconnections will be doing, and then their effects on oceanic modes over varying time scales. That way you start with short term deterministic regional weather forecasts, from which climatic forecasts can then be extrapolated. For example, I can give you a deterministic forecast for a very negative AO/NAO and very cold Arctic outbreaks in the northern mid latitudes from Jan through March 2017. Given that will take the SOI negative, and warm the AMO/North Pacific, that then provides the beginnings of a climate signal, and also the likely SST anomaly pattern for applying to the subsequent shorter term regional weather forecasts. Repeating that builds a climate forecast step by step. The key to it is forecasting the short term solar signal, without that, there’s basically nothing to go on.
Reply to Ulric Lyons ==> It is not that forecasts can’t be made — of course they can.
As a professional, I’m sure you are aware of Lorenz and his work. I’m fairly sure that you must know that the Earth’s climate is a non-linear dynamic system — name your desired name — but that won’t change the physics and mathematics of it.
Short term predictions based on known conditions, observed cycles, historic record of repeating patterns are all good. This is what farmers use to decide on predicting when and what to plant.
If you think that correctly naming the climate as a “Coupled Non-Linear Chaotic System” or “Coupled Non-Linear Dynamical System” means one can’t do short-term predictions, you should take advantage of the reading list above — as it means no such thing.
I have a little trouble understanding who the “they” is you are speaking of when you say:
Dr. R G Brown? Me? Edward Lorenz? James Gleick? Ian Stewart? Heinz-Otto Peitgen, Hartmut Jürgens and Dietmar Saupe? The IPCC? (well, there, I agree that they miss the mark in general — but they finally admitted the non-linear dynamics.)
You might want to look at Dr. Judith Curry’s “Stadium Wave” idea ==> “Role for Eurasian Arctic shelf sea ice in a secularly varying hemispheric climate signal during the 20th century” by Marcia Glaze Wyatt and Judith A. Curry. It has nothing particular to do with non-linear dynamics, but it uses recognizable repeating climate features to predict future conditions.
What climate being a non-linear dynamic system does mean is that
Kip said:
“I’m fairly sure that you must know that the Earth’s climate is a non-linear dynamic system..”
I’m sure that the major oceanic modes of ENSO and the AMO are negative feedbacks (with large overshoot) to solar variations at less than weekly scales. We should find that solar plasma variability has a direct effect on polar air pressure and the NAO/AO at down to daily scales. Meaning that none of what is assumed to be internal to the climate system, is really internal at all.
It is the antithesis of chaotic, and can be predicted, from forecasting the solar signal, at great range, at very small scales. Like the forecast I have given you for early 2017. This cold hit into the US currently is a highly similar solar signal to the cold that came in from the second week of March 2013. I forecast this one to start from around 10/11th Nov 2014. Given what I know, and what forecast experience I have, I’m thoroughly satisfied that the idea that the Earths climate of being a Coupled Non-Linear Chaotic System, is a techno waffle expert syndrome sound bite, a hypnotic mantra that only serves to extinguish scientific curiosity. and confound any proper understanding of climate.
I look forward to your papers and books that set the rest of the scientific community to rights, then. Should be an interesting read.
The link to Stewarts book should be : http://www.goodreads.com/book/show/445129.Does_God_Play_Dice_?
If you don’t want a whole book, just read Dr. Robert G. Brown’s recent WUWT essay (and his subsequent replies in the comments section) at: Real Science Debates Are Not Rare .
“What remains to be seen is whether the amounts of cosmic ray produced condensation nuclei and their variations are capable of significantly modulating the amount and reflectivity of cloud cover. This should be settled by measurements within the next decade or two. ”
You can settle it now by looking at historical data.
There is NO measureable, consistent, relationship between GCRs and cloud cover at any pressure level.
None. zip. nada.
There is however good correlation between GCRs (10Be and temperatures.) See the Steinhilber data in Fig 10 at http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
See also the 10Be ice core flux data from Berggren Fig 11
Re sun climate connection the post says
“NOTE!! The connection between solar “activity” and climate is poorly understood and highly controversial. Solar “activity” encompasses changes in solar magnetic field strength, IMF, CRF, TSI, EUV, solar wind density and velocity, CMEs, proton events etc. The idea of using the neutron count and the 10Be record as the most useful proxy for changing solar activity and temperature forecasting is agnostic as to the physical mechanisms involved.”
Having said that, however, it is reasonable to suggest that the three main solar activity related climate drivers are:
a) the changing GCR flux – via the changes in cloud cover and natural aerosols (optical depth)
b) the changing EUV radiation – top down effects via the Ozone layer
c) the changing TSI – especially on millennial and centennial scales.
The effect on climate of the combination of these solar drivers will vary non-linearly depending on the particular phases of the eccentricity, obliquity and precession orbital cycles at any particular time.
Of particular interest is whether the perihelion of the precession falls in the northern or southern summer at times of higher or lower obliquity.”
There is a huge variation on average global surface temperature summer to winter caused by most of the land mass being in the northern hemisphere. Not sure what this article is claiming isn’t there.
This discussion illustrates the danger of using anomalies. Unfortunately, anomalies are a rule rather than an exception in climatology. As opposed to measured data, an anomaly depends on a lot of other influences, e.g.
– what is the base period for an anomaly computation?
– is the base data raw data or adjusted data?
– if it is adjusted data (where the history changes routinely), what version of data was used?
– has any smoothing been used for the base?
– is the anomaly defined as a difference from a monthly average or a yearly average?
(spelling corrected)
His whole essay is based on this premise which is demonstrably false. As stated several times in the comments, there IS a “significant annual cyclic variation of global mean temperature” so the arguments he puts forward that the global temperature is almost completely insensitive to TSI because of this so called “fact” collapses and his conclusion immediately loses about 90% of its support.
The residual question remains of how sensitive the global temperature is to TSI, but that is a much more finely balanced equation and probably needs a lot more time and effort to tease out than has been put into this effort. All of this has been thoroughly researched before, of course, as it is fundamental to the whole of meteorology and climate. Maybe a bit of reading of the existing literature before posting is called for?
Sadly I think we have to dismiss this whole essay and ask Dr Robertson to go back and start again – if he can be bothered after such a catastrophic blooper.
In the absence of peer review it might be worth running these sorts of essays past somebody with existing knowledge in the field, particularly if you think you have stumbled on an effect that appears to totally debunk all climate models at a stroke! The models have all sorts of problems, an inability to predict anything useful being the main one, but the modellers all have a much better grounding in climate science than Stan so one needs to be really up to speed on our current understanding before telling them how they have got it all wrong.
Having said all that, I am glad WUWT is around and is prepared to post this sort of stuff – it is entertaining and we can all learn by other people’s mistakes!
http://spot.colorado.edu/~koppg/TSI/TSI.jpg
The problem which can not be better illustrated .
Nevertheless there is much historical to show galactic cosmic ray increase/decline in global temperatures.
What has to be kept in mind is it is not just the sun which controls the amounts of galactic cosmic rays coming into our atmosphere, one has to take into the account the strength of the earth’s magnetic field and the concentration of galactic cosmic rays out in space in the vicinity of earth.
An interesting graph. Where does it come from, please?
Among other sources, it is available at the Solar Reference page here at WUWT, which duplicates the original through a live link.
See the reference links across the top of the http://www.wattsupwiththat.com Home page.
Direct link is: http://spot.colorado.edu/~koppg/TSI/TSI.jpg
Now, what I find interesting is that it shows the solar input is measured as significantly reducing since th earliest measurements 1975 at 1372 watts/m^2 down to today’s 1360 watts.m^2.
Leif, however, strongly disagrees, and maintains firmly that solar output has NOT changed over time, but that instruments THEN were measuring TODAY’S TOA values incorrectly, and that solar output has remained unchanged over time.
However, if that were true, then EVERY calculation made between 1975 and 2014 (today) using ANY solar power TOA value other than today’s 1362 watts/m^2 is WRONG and needs to be re-calculated with the correct solar radiation level.
Here is the story of TSI:
http://www.leif.org/EOS/2010GL045777.pdf
“TIM’s lower solar irradiance value is not a change in the Sun’s output”
Thanks Leif for that paper on the TSI radiometry. I certainly agree with the improved collection optics. Once you let excess radiation enter the instrument, you have a devil of a time making sure that the surplus doesn’t cause any havoc. So I assume that the first input aperture has to be highly broad band reflective on the outside to keep it from reaching a Temperature that can then re-radiate inside the system ??
The various calibration degradation mechanisms is interesting. I guess you can’t really depend on anything staying put, once you put it in outer space. I’m amazed they can even quantify some of those effects.
G
I want to add.
The position of the two earth magnetic poles also playing a part as to where galactic cosmic rays may be directed. The lower the latitude galactic cosmic rays would be directed to via the configuration of the earth’s magnetic field the more moisture they would have to work with the more effective cloud formation potential.
In addition ,volcanic activity putting up aerosols also has a role in cloud formation and I think to some degree can probably moderate the effectiveness of galactic cosmic rays in cloud formation potential.
Stan Robertson: This shows that very little of the available TSI variation is needed to produce the annual changes of atmospheric water column and, presumably, the variation of cloud cover. But if earth albedo changes in proportion to the variation of the atmospheric water column, then reflected solar radiation would vary by 19% of the mean 101 W/m2, or 19 W/m2. That would leave only about 3 W/m2 of the 22 W/m2 of TSI variation available to heat the earth surface. Since about 2 W/m2 is needed to produce evaporation, that leaves only about 1 W/m2 to be absorbed and warm the surface. Using the same computer program that I mentioned previously, I calculated that 1.0 W/m2 annual variations at the ocean surfaces would produce surface temperature oscillations of about 0.037 oC peak to trough. This is too little to be reliably extracted from noisy sea surface temperature data, but this is about what is shown in Figure 2.
Have you been able to find calculations such as those in the published literature?
Good post. Thank you.