Guest Post by Willis Eschenbach
Whenever I find myself growing grim about the mouth; whenever it is a damp, drizzly November in my soul; whenever I find myself involuntarily pausing before coffin warehouses, and bringing up the rear of every funeral I meet; and especially whenever my hypos get such an upper hand of me, that it requires a strong moral principle to prevent me from deliberately stepping into the street, and methodically knocking people’s hats off—then, I account it high time to get to sea as soon as I can.
Ishmael, in Moby Dick.
Yeah, that pretty well describes it. I’d been spending too much time writing about the weather and the climate, and not enough time outdoors experiencing the weather and the climate. So following Ishmael’s excellent advice, I have been kayaking and walking the coast and generally spending time on and around the ocean. During this time I have been considering what I want to write about next. Being on the water again, after the last few years of being boatless, has been most invigorating.
I have chosen to write about my on-and-off investigation of the relationship between changes in surface temperature and corresponding changes in top-of-atmosphere (TOA) radiative balance. I wrote about this previously in a post entitled A Demonstration of Negative Climate Sensitivity. This is an interim report, no code, little analysis, just some thoughts and some graphics, as I am in the (infinitely) slow process of assembling code, data, and results for publication in a journal. Unlike my previous post which used 5°x5° data, in this post I am using 1°x1° data.
Let me start with an interesting question. Under the current paradigm, the assumption is made that surface temperature is a linear function of the TOA imbalance (forcing). But is it true? In particular, is it true all over the world? To answer this, I looked at the monthly TOA radiation imbalance (all downwelling radiation minus all upwelling radiation) versus the change in temperature.
Figure 1. Maximum of the R^2 value, temperature vs TOA imbalance. This is the maximum of the individual R^2 for each 1°x1°gridcell, calculated at lags of 0, 1, 2, and 3 months. An R^2 of 0 means there is no relation between the two datasets, and an R^2 of 1 means that they move in lockstep with each other. In the red areas, when the TOA radiation balance changes, the temperature changes in a similar fashion. In the blue areas, changes in temperature and TOA imbalance are not related to each other.
Figure 1 has some interesting aspects.
Figure 1 was created by displaying, for each gridcell, the largest of the four R^2’s, one from each of the four lag periods (0, 1, 2, and 3 months). One interesting result to me was that while the temperature of a large part of the earth slavishly follows the variations in the local TOA balance (red areas), this is not true at all, at any lag, for the area of the inter-tropical convergence zone (ITCZ, blue, green, and yellow areas). This is evidence in support of my tropical thunderstorm thermostat hypothesis, which I discuss in The Thermostat Hypothesis and It’s Not About Feedback. For that hypothesis to be correct, the surface temperature in the ITCZ must be decoupled from the TOA forcing … and it is obvious from Figure 1 that the ITCZ temperature has little to do with forcing.
Next, I wanted to look at the climate sensitivity. In a general sense, this is the amount of change in the surface temperature for a 1-unit change in the TOA radiation imbalance. There are a variety of sensitivities, from instantaneous to equilibrium. Because I have monthly data, I’m looking at an intermediate sensitivity.
Figure 2 shows the temperature change due to a 3.7 watt per metre squared (W/m2) at various time lags. When the TOA radiation changes, the surface (land or ocean) does not respond immediately. By examining the response at different time lags, we can see the characteristic lag times of the land and the ocean.
Figure 2. Climate sensitivity (temperature change from a 3.7 W/m2 TOA imbalance) for the earth. Sensitivity is determined as the slope of the linear regression line regarding TOA variations and surface temperature for each gridcell, over the period of record. Click on upper or lower image for larger version.
Consider first the land. For most of the land, the strongest response (orange and red) occurs after a 1-month lag. The maximum sensitivity is in the areas of Siberia and the Sahara Desert, at around 0.8° per doubling of CO2. Extratropical land areas are more sensitive to TOA variations than are tropical land areas. The highest sensitivity in the Southern Hemisphere is about 0.3°C per doubling of CO2
Curiously, tropical Africa shows a lagged negative sensitivity. This becomes evident at a 2-month lag, and increases with the 3-month lag.
The ocean, as we would expect, is nowhere near as sensitive to TOA variations as is the land, with a maximum sensitivity of about 0.4°C per doubling, The sensitivity over most of the ocean is on the order of 0.1°Ç per doubling.
Finally, Figure 3 shows the relationship between the climate sensitivity and the temperature. Because of the large difference between the land and the ocean, I have shown them separately.
Figure 3. The relationship between climate sensitivity and temperature. Each point represents one gridcell on the surface of the earth. For each gridcell, I have used the time lag which gives the greatest response. Colors show the latitude of the gridcells.
Here, let me point out that I have long maintained that climate sensitivity is inversely related to temperature. This is clearly true for the land.
As I said, not much analysis, just some thoughts and graphics.
Best to all,
w.
DATA
Sea Temps: NOAA ERSST
Surface Temps: CRU 3.1 1°x1° KNMI
TOA Radiation: CERES data
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tty says:
December 10, 2012 at 5:22 am
The lagged negative response in the Sahel (and to a smaller extent in India and northern South America) is presumably a monsoonal effect, warmer temperatures causes the air over land to rise more, which pulls the ITCZ further north with more rains that cools the climate. During previous warmer interglacials this effect caused the Sahara to more or less disappear.
One can describe the climate as a system that transports heat (enthalpy) from where it is gained to where it it is lost. And this process occurs both vertically and horizontally. IMO the monsoons are an underappreciated and little understood aspect of horizontal transport.
Willis, if you are an ocean kayaker you might add the Ningaloo Reef in Western Australia to your bucket list. One of the last pristine ocean shorelines left outside the polar regions. I kayaked most of its length 20 years ago and am still amazed at how abundant life is in the ocean when there are no people.
@Pochas:
I suspect that the negative sensitivity in the tropics is due to the water / thunderstorm “thermostat” process; while that at the pole(s?) is based on the winter lack of troposphere height. In the stratosphere, the CO2 effect is negative (more radiation of heat is caused). During the polar winter, the stratospheric height becomes nearly zero (especially on top of the S. Pole 11,000 foot plateau…) so any increased CO2 or increased energy to the stratosphere will show up as increased radiation…
https://en.wikipedia.org/wiki/Troposphere
Those polar stratospheric vortex winds can be a cold cold mistress… and the land radiates heat like crazy out the poles. (Most heat gain is at the equator and most heat loss is from the poles).
@Willis:
I’m once again missing my boat… Tacking around the bay can clarify the mind in ways nothing on land can do…
Maybe I need to buy a kayak… with a sail 😉
E.M.Smith says:
December 10, 2012 at 12:31 pm
Indeed, it is a flux.
Thanks, Chiefio.
Interesting thought, I haven’t pulled out polar summer vs. polar winter. So many analyses … so little time.
Thanks for the links. The processes do not go on at annual, monthly, or weekly scales. They go on minute by minute and hour by hour. In that regard, the records of the TAO buoys in the tropical Pacific are quite revealing.
Part of the problem with doing that is the shortness of the dataset. Going quarterly means dividing N by three, one third the data. In such a short dataset, that gets you out on shakier ground.
Indeed. Some of the TAO buoys have data at 10-minute intervals, I haven’t looked at those yet. So many musicians, so little time …
w.
Willis –
Big thank you for this, it really got me thinking, along the lines that this could be really important and deserves the courtesy of some serious critical review. Here are some thoughts:
TOA imbalance has to be wildly seasonal. If you correlate TOA imbalance with changing temperature, you are correlating two sine waves sampled (if monthly data) 12 times a period. In that case, the climate sensitivity you have measured is the ratio of the average monthly change in temperature to the average monthly change in insolation. But the average change in insolation is huge. For example, at latitude 22.5 degrees north, the TSI/4 average insolation varies by 176 watts, from 285 to 461. In round numbers about 30 watts per month (six months in each direction). So a sensitivity of 1 degree per doubling 3.7 watts is a change of about 8 degrees per month – which is a lot! it isn’t surprising that the sensitivities you measure are low.
This also explains why the sensitivity over the ocean is lower – the ocean changes temperature slower than the land.
Next notice the range in the south is higher, because perihelion is in the southern summer. The range at latitude 22.5 degrees south is 233 watts, from 261 to 494 watts. For the same temperature differences, the sensitivities you will measure will be lower in the south, which corresponds to what you see.
Next, in equatorial regions, there are two peaks in the annual insolation cycle, not one. By the time you are looking at monthly measurements with lags, the cycles can be completely out of synch. I think that’s why you see minimal correlation at the equator.
Broadly, I think you need to ‘seasonally adjust’ the data somehow, perhaps by looking at annual variations in each item.
Hope this is some use,
RERT
RERT says:
December 10, 2012 at 2:38 pm
Much appreciated.
If this were the cause of the low correlation, we would see it quite evenly across the tropics near the equator.
We do not see the low correlation in the part of the tropics with two peaks in the annual solar cycle (which only extends from about 3°S to about 6°N or so). Instead, we see the lack of correlation only the part of the tropics occupied by the ITCZ.
w.
Willis Eschenbach: However, in fact what is happening is not zero. It is a series of strong but opposite control inputs which balance out over time, and that is very different from a condition called “no feedback”.
I agree. You have shown that the effect of increased radiation, whether called “a” feedback or not, depends on the region of the earth surface, and its state.. I erred in not saying that I was referring specifically to the graph of the land relationships. However, I would also conjecture that, at each region of the earth surface, the relationship of radiation change to temperature change is not even constant across seasons, even within temperature ranges.
One of the desirable consequences of good analyses is that the next questions become obvious.
Thanks, Willis. Super-interesting post.
It shows the vacation time! 🙂
View from the Solent says:
December 10, 2012 at 7:31 am
Not just physical objects. That’s the principal of least action http://www.principlesofnature.net/principle_of_least_action.htm
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reminds me of quantum mechanics. like stepping into a maze and always knowing in advance which turn to take to reach the exit with the least number of steps. how does nature know how the way? We can describe the path, but what is the underlying mechanism? Perhaps we are a resonance of all possibilities, with “now” being the most likely. Is the big bang and the universal background radiation we see in fact a black hole seen from the inside? is the acceleration due to dark energy a result of our parent universe? are there an exponentially increasing number of universes as black holes reproduce new universes with each generation? Does this give rise to the resonance, a multi-verse of universes. what gave rise to the very first?
John Doe says:
December 10, 2012 at 4:20 am
You obviously know what ‘boat’ stands for … Break Out Another Thou$and. 🙂
Carrick says:
December 10, 2012 at 6:51 am
Actually they don’t assume sensitivity is a constant. That’s a common assumption by people try to arrive at estimates of climate sensitivity, but it is neither an assumption, nor does it even hold true in the models. see e.g. http://www.gfdl.noaa.gov/blog/isaac-held/2011/03/19/time-dependent-climate-sensitivity/
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Interesting result, it shows similar to what Willis has shown. That warm regions of the earth are able to get rid of energy more easily than cold regions. That the effect of GHG is to act as a thermostat. That run-away warming is near to impossible as a result.
joelshore says:
“You seem to understand neither what the conventional scientific understanding is nor what Willis has shown here. Not surprisingly, your misunderstandings are in the direction of causing you to believe what you want to believe.”
Yet joelshore says he isn’t in agreement with Willis. From my view then, joelshore is the one who doesn’t understand. Regarding what I “believe”, that is just more projection. I look at empirical evidence above all, and Willis’ article is a gem of empirical evidence. If the evidence showed that CO2 had a significant, measurable effect on global temperature, then I would accept that, because I “believe” testable, empirical scientific evidence and verifiable observations.
But joelshore does not. He believes in catastrophic AGW caused by the rise in CO2. But the planet is in alignment with Willis Eschenbach’s view — while the planet is deconstructing joelshore’s model-based belief. Which one is correct? Planet Earth, which has not been warming for a decade and a half despite a hefty rise in CO2? Or the IPCC’s models that joelshore cites as his authority? I prefer to listen to what Planet Earth is telling us.
Interesting ‘natural experiment’ in my home town last week: warm westerly winds blew in some high temperatures up to 39C during the clear sunny days … at night with the clear skies the temperatures dropped up to 17C lower than the daily highs. I’m pretty much certain that CO2 concentration was around about constant ; So how come the CO2 didn’t re-radiate the energy back down to keep the temperatures warmer during the night ? /sarc
Very interesting post. I had several questions similar to old engineer. Thank you for the clarifications. Christopher Game at Dr Spencer’s blog has described “compensations” to CO2 flux changes that are similar or identical to your assertion,
“It is a series of strong but opposite control inputs which balance out over time, and that is very different from a condition called “no feedback”.”
Everyone notices here that the northern continents respond most quickly to a forcing change, so it is very indicative when those are the same areas that are warming fastest in the last few decades. We are in a long-term period of a steady forcing change that now is leaving a distinctive fingerprint on the warming pattern. Not really surprising, but a good way to confirm it.
@Willis:
Looking at theTao posting (that I’d somehow missed the first go round, dang it…) the comments are closed. So two points here:
1) That evening ‘shoulder’… check for dew point. IIRC that’s about the time in the evening that things get ‘sticky’ in the tropics as relative humidity gets high… Some enthalpy change instead of temperature change, perhaps?
2) Why the same start time for the cumulus: Look for solar / water angle of incidence. Up to some hour, light will mostly reflect, then at a critical angle (time of day) it will start to enter / absorb and warm the surface layer.
Don’t know if those are correct / causal, just what comes to mind to me.
Also, per what I noticed in Florida on land, the early afternoon warmth comes just about the time the morning moisture has gotten high in the sky, to form rain and give a very cooling mid-afternoon shower. So a time coefficient to travel, condense, rain. ( i.e. not just ‘size of rain’ but time lag to rain). Thus the slight drop after formation of cumulus time. (The moisture heat engine has run a while prior to the delivery of the cool rain cargo 😉 that then overshoots to cooler just a little. Modulo the big hurricanes and any major all night long storms 😉
FWIW, after a hurricane (sorry, don’t remember which one) passed off shore, Orlando was significantly cooler in the wake. All the hot air was sucked in, lofted and cooled (rained out) then spread out from the top and descended cooler. If I had to guess I’d guess about 5 F? cooler? Enough that it was more comfortable than the days before the storm passed. Couple of hundred mile radius of effect… A whole lot of heat sucked out of all of land, sea, and air. (Takes a lot of energy to run a cyclone 😉
Strange thing was seeing low clouds spiraling in toward the core and high clouds spiraling out at the same time. Rushing toward the eye to rise, then being spread out and disposed once done. Interesting opposite handedness to the spirals motion (speeding up going in, slowing down coming out). At any rate, if you get a chance to watch a hurricane from just outside the storm area, it’s well worth it.
E.M.Smith says:
December 10, 2012 at 8:14 pm
Thus the slight drop after formation of cumulus time. (The moisture heat engine has run a while prior to the delivery of the cool rain cargo 😉 that then overshoots to cooler just a little.
Ditto the monsoon in the horizontal plane.
“During the winter there is nearly NO “downwelling” anything. (Heck, the hight of the stratosphere become ‘indistinct’ then and there; as the ‘troposphere’ essentially goes way).”
Indeed. There has been serious proposals to put an (remote controlled) IR observatory on top of Dome C in Antarctica rather than on a satellite. In winter there is essentially no water vapour to absorb infrared and CO2 absorption alone does not amount to very much, so it is practically the equivalent of being in orbit.
Philip Bradley says:
December 10, 2012 at 12:44 pm
The most striking thing about Figure 1 is the way it highlights places where heat is moved horizontally from one place to another. The most prominent locations for mismatch between TOA imbalance and temperature are the locations of: ENSO, the Indian Ocean Dipole, and the Atlantic Equatorial Mode, then, less prominently, the Gulf Stream, the North Pacific and Alaska currents, perhaps including upwelling effects. The subtropical convergence zone to the South shows higher correlation, no doubt because of the slow motion of the water, rather than the 100 million tons of trash reputed to be stuck there. There may be a signature of the Antarctic cirumpolar current, but that’s hard to tell.
On the land, we can see lack of correlation in equatorial South America and Africa. Monsoon effects are strongly suggested in Thailand and India, with the latter showing a beautiful cutoff at the Himalayas, and at the mountainous border between Pakistan and Afghanistan. We’d expect such heat transfer reduce correlation between TOA imbalance and temperature. The Gulf stream will bring massive amounts of heat to England regardless of whether or not it’s cloudy there. For a lot of the world, this heat transfer signal looks strongly imprinted on the data, so that it would be more of a challenge to find anything there about thunderstorms, or other processes that take place within one gridcell.
For the equatorial land and oceansareas, in the ITCZ, the convection that drives the Hadley cells (and eventually, the world’s weather as we know it) will carry off a tremendous amounts of heat. Since the convection is driven by solar heating, it will increase or decrease with available sunlight, and damp the temperature effects of varying cloud cover. This will also work to reduce correlation in the ITCZ.
In the maps that show correlation, or anticorrelation, for various time lags, there is a strong anticorrelation at two and three months in Africa, just North of the equator. These areas have distinct wet and dry seasons, and when you correlate wet-season weather today with dry-season sunshine three months ago, or vice versa, you’ll get a mismatch. With a 3-month lag they’ll be out of phase for a lot of the time. But if that were the only reason, you’d expect to see it show up in other places too. So, perhaps those anomalies have somthing to do with the convection “hot spots” shown here.
http://upload.wikimedia.org/wikipedia/commons/6/6b/Omega-500-july-era40-1979.png
Negative numbers (blue/purple) show rising air; positive ones (pink–yellow) show descending air. It’s not easy to see Africa, hidden under air masses, but three strong convecion areas are prominent. It’s only one month (July 1979) so those hot spots might move around, but the correspondence with the 2- and 3-month lag maps is interesting.
It’s an interesting post. It’s hard to see how much one can say about thunderstorms until the effects of horizontal heat transfer are accounted for. As for the the Increased cloud formation with heat available is obvious, though nailing down the details could be formidable. A study like this might have something interesting to say in its own right about heat transfer around the globe.
The ENSO fluctuations have been going on for many thousands of years, probably since the isthmus of Panama closed. In all that time there is no evidence that they are the cause of warming or cooling beyond the typical timescale of a few years that the ENSO changes occupy. Certainly no credible evidence exists that they have caused a cooling or warming trend in global temperatures in the past.
Bob Tisdale now asserts that for the last few decades the extra energy transferred from the oceans to the atmosphere and land by an El Nino event has not been completely lost during any following La Nina so that energy is accumulating. The question then becomes why this change in behaviour and what is causing the reduced loss of energy during a El Nino event.
Bob Tisdale dates the change to around the start of the satellite record.
I would suggest that the change dates to the start of the rise in atmospheric CO2 levels which also provides a clear physical process that explains this reduction in energy loss.
Izen says……..
Bob Tisdale has data showing what happens. He does not assert any “theory”, rather he just shows what the data shows.
You on the other hand have a “theory” and no data to support it.
Bob talks facts. I prefer his facts over your assertions.
Willis,
Your observations are similar to mine from a statistical analysis of regional data. I included water vapor and rain in my regressions. http://www.kidswincom.net/CO2OLR.pdf. I would like for you to consider these factors as you continue your work.
@- Ed_B says:
“Bob Tisdale has data showing what happens. He does not assert any “theory”, rather he just shows what the data shows.”
Correct.
He provides a description of what has happened without attempting an explanation.
Very interesting. I am trying to get a grasp of what is meant by TOA forcing here. The term ‘forcing’ comes, as far as I know (and I’d very much appreciate any correction here) from computer modellers who found a tractable way to include atmospheric composition changes in their models by the simple device of converting them to instantaneous ‘forcings’ at the model TOA. They then watch while the model re-equilibrates and their new forcings drop to zero.
In the real world, of course, this does not happen. Atmospheric composition does not change instantaneously, but rather evolves over both time and space. The difference in incoming and outgoing radiation at the real ‘TOA’ has long been established as being net positive inwards in equatorial regions and net positive outwards at polar ones, an effect, not a cause, of poleward transfers of heat and of the spherical shape of the earth (reduced insolation per unit area with latitude).
Now CO2 largely emerges at the surface, and largely from vegetation in the tropical and subtropical land regions. The CO2 is also transferred polewards in the same tropospheric movements that carry heat. There is a great deal of spatial and temporal variability involved which, again as far as I know, is not taken into account by the ‘forcing’ device. I can appreciate the merit of such a device for making coding problems tractable, but I am struggling to see it as a close analogue of any physical process actually taking place in the system.
Hello Mr. Eschenbach
Trying to reproduce your results i hit one problem: How did you account for heat exchange between the northern and southern hemisphere, when calculating the sensitivities? One would need the amount of energy “blown” in and out of each parcel.
The heat exchange between the hemispheres is most significant near the equator, because of the proximity. However it is also warmest near the equator. The inverse relationship between temperature and sensitivity may be an artifact of miscalculating the heat exchange.
M.B
John Shade says:
The models can be run either with an instantaneous change in atmospheric composition or a continuous change in atmospheric composition. I kind of doubt the models take the spatial variation of CO2 concentration into account because that spatial variation is frankly very small. They do take spatial variation into account for aerosols and other constituents where the spatial variation in concentration is significant and important.