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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The two best days in a boat owner’s life are the day he buys his boat and the day he sells it.
The days come in pairs but there may be more than one pair.
Welcome back Willis! I, for one, have seriously missed your contributions here.
as usual, your analysis has excellent graphics supporting your exploration. I’m looking forward to the full paper.
Wow,
Real data about how the real climate operates. I think you got it here.
This all fits with what we have seen and know about – some polar amplification, flat equatorial Ocean temps going back 140 years, temperature not rising anywhere near the rate predicted in the theory, Land warming in certain places (mainly high latitudes) with very little in the Oceans, very limited feedbacks operating, much more consistent with paleoclimate data, 1000 times higher spatial resolution than anything that has been done with CERES before.
You might have rewritten the book here.
Your analysis is always so visual and that’s a good thing for me. The gray of Antarctica leaped out at me when I went to compare the north pole with the south (or the south with all the rest of the world). Looking at the data for the southern region indicates sparse and short term data. I am guessing that is the reason for the the gray southern region. What a pity that we lack data for such an important part of the world if this is the case.
Bernie
Consistent with phase changes of water that can produce large heat fluxes while simultaneously registering minimal temperature changes.
Great to have you back, Willis! I really hope you take care of yourself as you are a hero of mine.
Greatings from a snowy and unsually cold Copenhagen.
The observation that there is a significant difference between ocean and land is further evidence that atmospheric CO2 is not a major controlling factor (concentrations are the same over land and sea at the same latitude). The water cycle is the big controlling factor(evaporation/condensation – freeze/thaw).
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.
Welcome back Willis, missed your posts.
Good, succint post as usual.
Figure 1, showing blue at the north pole and equator is interesting. It would be interesting to see what is happening at the south pole. The green at the antarctic peninsula hints that the south pole may also be blue.
The blue region at the north pole indicates that the melting of sea ice at the north pole is not an indication of atmospheric forcings. This has significant implications for climate science on its own, as it has long been publicized that the melting of arctic sea ice was an indication.
A paper showing that there is little of no correlation between arctic temperatures and climate forcings would perhaps be very significant.
Always good to have you thinking about a new perspective on the climate data, Willis.
If you hadn’t noticed, Bejan and colleagues have done some more work on applying Constructal Theory to climate with this paper” http://www.constructal.org/en/art/Climate_change_%20in_the_framework_of_the_Constructal_Law.pdf. Any comments on that?
The scatter plots are interesting. They show that one of the most basic of climate assumptions is wrong. The climate models that temperature is a linear function of forcings – that sensitivity is a constant.
However, what the scatter plot shows is that sensitivity is not a constant. Sensitivity is a function of temperature as well as forcings. That as temperature increases, sensitivity decreases, until it becomes negative at about 30C.
This suggests that runaway temperature increase is impossible. That the earth has a mechanism in place that operates around 30C to prevent any further temperature increase.
These scatter plots are very significant because the show that the underlying assumption of constant climate sensitivity is wrong. This would help explain why temperatures have not increased significantly in 16 years. Runaway warming is impossible because as temperatures increase sensitivity turns negative, preventing further increase.
This has huge implications in climate science and would explain why we have not seen runaway warming in the paleo records, even when CO2 levels were much higher.
Reblogged this on gottadobetterthanthis and commented:
Thanks Willis.
Gary says:
December 10, 2012 at 5:56 am
If you hadn’t noticed, Bejan and colleagues have done some more work on applying Constructal Theory to climate with this paper”
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Constructal theory is an interesting idea. Boat owners (mono-hulls) curse it every time they anchor and the wind drops. The boats immediately turn broadside to the swell to minimize the energy used to move with the swell, and in the process roll the guts out of everyone aboard.
Sailboats hang a “flopper stopper” out over the side on a spinnaker pole to prevent this. This changes the energy needed to roll the boat and the hull will quickly turn to face the waves as it now takes less energy to pitch than roll.
What this means is the physical objects seek the minimum energy level required to accomplish the work. Water seeks the easiest path as it were. Not only water, but boat hulls and now it seems climate as well.
Great paper. If I read the charts right it means that the tropics has found its temperature, and any amount of CO2 is totally swamped by the effect of water vapor in the tropics. This seems to validate the thermostat hypothesis, and all climate models will have to take into account the effect of clouds and thunderstorms and their strong negative feedback
Willis
It seems from your plots that the relationship between surface temperature and TOA, that you’re using as a proxy for sensitivity (right?), is a dependent on latitude over land and not over ocean. Therefore, it seems likely that you’re measuring the dampening effects of atmospheric water vapour? In short, you get the greatest response over drier and colder parts of the planet. Was this not a prediction of the original GCMs?
If so how do your results compare to their predicted (projections) for high latitude warming?
Yes, Welcome back, Willis! Always a thought-provoking exercise–I think you’re onto something big here.
So as the hydrologic cycle is the vast heat radiator and temperature knob for the earth, can we expect current encroachment of the Sahel upon the Sahara to continue until the sand is overtaken with vegetation? Do we know if this has happened with any/each of the past three temperature maxima that have appeared at regular 1,000-yr intervals, as this current one would suggest? When grapes were grown in England and Vikings farmed Greenland, did goat herds thrive across the Sahara?
Good news! It looks like the IPCC is going to back away from global warming hysteria. Slashdot has the following story:
That story links to an ABC News story: http://abcnews.go.com/International/science-hone-climate-change-warnings/story?id=17906408#.UMVJntHQQSk
I wasn’t surprised to see oceans max out at ~30 degrees; however, I was surprised to see land max out at about 30 degrees also. The oceans benefit from rapid evaporation at that high temperature–is that also the mechanism that operates on land? Or is it merely a function of the granularity of the sample size, with space for relatively few outliers?
Wow, this is really, really interesting stuff. Like Fred Berple, I was especially intrigued by the scatter plots. I’ve long suspected that sensitivity isn’t linear at all – your scatter plots shows it. So much for “runaway warming” – for all we know, we may be close to the upper limit to how warm the earth can become in the current phase of the Milankovitch cycles and with the current continent configuration!
Figure 3 is absolutely stunning. The most amazing effect is the swing into negative climate sensitivity at around 30 C. This occurs over oceans even though higher temperatures should cause higher absolute water vapor concentrations and *increase* the climate sensitivity immediately.
ferd bergle:
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. this
Re: CO2 sensitivity
So it is not necessary to go to an over-elaborate analysis to
plot a graph to show that the CO2 saved N. Hemisphere
or even the world from onset of the new LIA in 1960s.
or to calculate theCO2 feedback sensitivity at 3 degrees C
for doubling of the CO2 concentration.
http://www.vukcevic.talktalk.net/00f.htm
(acrostichis web page)
Once again, nice work Willis. I also wonder about those areas of negative sensitivity. Is it related to the fact that those are areas of intense precipitation?
ferd berple says:
December 10, 2012 at 6:20 am
….
What this means is the physical objects seek the minimum energy level required to accomplish the work. Water seeks the easiest path as it were. Not only water, but boat hulls and now it seems climate as well.
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Not just physical objects. That’s the principal of least action http://www.principlesofnature.net/principle_of_least_action.htm