A Longer Look at Climate Sensitivity

Guest Post by Willis Eschenbach

After I published my previous post, “An Observational Estimate of Climate Sensitivity“, a number of people objected that I was just looking at the average annual cycle. On a time scale of decades, they said, things are very different, and the climate sensitivity is much larger. So I decided to repeat my analysis without using the annual averages that I used in my last post. Figure 1 shows that result for the Northern Hemisphere (NH) and the Southern Hemisphere (SH):

Figure 1. Temperatures calculated using solely the variations in solar input (net solar energy after albedo reflections). The observations are so well matched by the calculations that you cannot see the lines showing the observations, because they are hidden by the lines showing the calculations. The two hemispheres have different time constants (tau) and climate sensitivities (lambda). For the NH, the time constant is 1.9 months, and the climate sensitivity is 0.30°C for a doubling of CO2. The corresponding figures for the SH are 2.4 months and 0.14°C for a doubling of CO2.

I did this using the same lagged model as in my previous post, but applied to the actual data rather than the averages. Please see that post and the associated spreadsheet for the calculation details. Now, there are a number of interesting things about this graph.

First, despite the nay-sayers, the climate sensitivities I used in my previous post do an excellent job of calculating the temperature changes over a decade and a half. Over the period of record the NH temperature rose by 0.4°C, and the model calculated that quite exactly. In the SH, there was almost no rise at all, and the model calculated that very accurately as well.

Second, the sun plus the albedo were all that were necessary to make these calculations. I did not use aerosols, volcanic forcing, methane, CO2, black carbon, aerosol indirect effect, land use, snow and ice albedo, or any of the other things that the modelers claim to rule the temperature. Sunlight and albedo seem to be necessary and sufficient variables to explain the temperature changes over that time period.

Third, the greenhouse gases are generally considered to be “well-mixed”, so a variety of explanations have been put forward to explain the differences in hemispherical temperature trends … when in fact, the albedo and the sun explain the different trends very well.

Fourth, there is no statistically significant trend in the residuals (calculated minus observations) for either the NH or the SH.

Fifth, I have been saying for many years now that the climate responds to disturbances and changes in the forcing by counteracting them. For example, I have held that the effect of volcanoes on the climate is wildly overestimated in the climate models, because the albedo changes to balance things back out.

We are fortunate in that this dataset encompasses one of the largest volcanic eruptions in modern times, that of Pinatubo … can you pick it out in the record shown in Figure 1? I can’t, and I say that the reason is that the clouds respond immediately to such a disturbance in a thermostatic fashion.

Sixth, if there were actually a longer time constant (tau), or a larger climate sensitivity (lambda) over decade-long periods, then it would show up in the NH residuals but not the SH residuals. This is because there is a trend in the NH and basically no trend in the SH. But the calculations using the given time constants and sensitivities were able to capture both hemispheres very accurately. The RMS error of the residuals is only a couple tenths of a degree.

OK, folks, there it is, tear it apart … but please remember that this is science, and that the game is to attack the science, not the person doing the science.

Also, note that it is meaningless to say my results are a “joke” or are “nonsense”. The results fit the observations extremely well. If you don’t like that, well, you need to find, identify, and point out the errors in my data, my logic, or my mathematics.

All the best,

w.

PS—I’ve been told many times, as though it settled the argument, that nobody has ever produced a model that explains the temperature rise without including anthropogenic contributions from CO2 and the like … well, the model above explains a 0.5°C/decade rise in the ’80s and ’90s, the very rise people are worried about, without any anthropogenic contribution at all.

[UPDATE: My thanks to Stephen Rasey who alertly noted below that my calculation of the trend was being thrown off slightly by end-point effects. I have corrected the graphic and related references to the trend. It makes no difference to the calculations or my conclusions. -w.]

[UPDATE: My thanks to Paul_K, who pointed out that my formula was slightly wrong.  I was using

∆T(k) = λ ∆F(k)/τ + ∆T(k-1) * exp(-1 / τ)

when I should have been using

∆T(k) = λ ∆F(k)(1 – exp(-1/ τ)) + ∆T(k-1) * exp(-1 / τ)

The result of the error is that I have underestimated the sensitivity slightly, while everything else remains the same. Instead of the sensitivities for the SH and the NH being 0.04°C per W/m2 and 0.08°C per W/m2 respectively, the correct sensitivities should have been 0.05°C per W/m2 and 0.10°C per W/m2.

-w.]

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Kev-in-Uk
May 31, 2012 5:25 pm

Hah!
Now all you have to do is add a couple of adjustments, one -ve (but small), lets call it adjustment X – and one +ve (but larger than the other one) and call it adjustment CO2 – and hey presto, you will have a model that demonstrates AGW quite well!
If you bury the adjustments as several ‘forcings’ (all estimated of course, and probably calculated from other variables in direct and indirectly proportional manners) you can make these fudge factors extremely difficult to find. Bingo, you now have the next model for the next round of IPCC projections…….

MaineIdea
May 31, 2012 5:29 pm

The gauntlet has been thrown. I for one, will not pick it.

Richard M
May 31, 2012 5:32 pm

I’ve mentioned before that GHGs may work as little thermostats. They have both a warming and cooling effect. The thing that determines the “setting” of the thermostat is the amount of energy entering the system. That is, the sun and clouds.

May 31, 2012 5:37 pm

Peter Taylor pointed out in his 2009 book ‘Chill’ that the combined effects of decreased albedo [e.g. earthshine data from Palle et al & satellite data] and solar activity could account for 4 times the forcing alleged to result from anthropogenic GHGs.
http://hockeyschtick.blogspot.com/2012/05/environmental-scientist-explains-why.html

Physics Major
May 31, 2012 5:41 pm

Touché, Willis. Well played.

tchannon
May 31, 2012 5:55 pm

Any have a working link to NASA servers Willis cites in the other post?
`

Joachim Seifert
May 31, 2012 6:01 pm

Willis, wait only a few more months – your PS is BS, skim over my
booklet: Climate IS explained and calculated with examples from over
50,000 years of paleoclimate…..
My new paper will outline and calculate 4 different climate forcing
mechanisms over the past 10,000 years – this as announcement
to you…..
I can say: all climate mechanisms have to be proven over LONG
time spans, over a minimum of several 1,000 years……
All engaging in short term curve fitting of less than this time span is
just curve twisting….or call it meteorology but not climate science…
See my new paper coming out towards the end of this year …..
BTW: your volcano part is very good, it coincides with my findings
Regards meanwhile
JS

kuhnkat
May 31, 2012 6:06 pm

Willis,
you are not a Climate Scientist. That means they will not listen to your nonconsensus view. Heck, MoshPup might stop talking to you cause it shows that RT isn’t the be all and end all of climate!!
HAHAHAHAHAHAHAHAHAHAHAHAHAHAHA
Nice.

RobW
May 31, 2012 6:11 pm

“but applied to the actual data…”
We don’t need no stinkin” data (need to wear a sombrero while saying) {sarc}

Truthseeker
May 31, 2012 6:26 pm

“Second, the sun plus the albedo were all that were necessary to make these calculations.” and “… when in fact, the albedo and the sun explain the different trends very well.” seem to be an elegant (if limited) confirmation of Nikolov and Zeller’s theories of climate and temperature.
Just sayin …

Michael D Smith
May 31, 2012 6:46 pm

nobody has ever produced a model that explains the temperature rise without including anthropogenic contributions from CO2 and the like
I don’t believe I’ve ever seen one that explains the temperature WITH including them either.

May 31, 2012 6:46 pm

I have this nagging question about phase of the data in regards to the analysis window. It looks like it starts in Jan and ends in December. Would you get the same slope if you went from Jan to Jan? Or Feb to Jan? Or July to June?
My guess is that you will not get the same slope with these different windows, but how much of a difference is it?

May 31, 2012 7:02 pm

Reason for selection of start & end dates?
My apologies if I missed it if stated before.
I’ve been studying hot year 1998 and it has some peculiar properties, so I’m keen to see what follows. There was a reason for the hot year and the explanation is either in your parameters, or a different forcing. It appears to have a NH vs. SH difference.

gnomish
May 31, 2012 7:14 pm

bravo Willis.
your thinker runs smooth and cool.

May 31, 2012 7:19 pm

Thank you for this post. I’m very glad to see the albedo being given the attention it deserves. When it comes to wondering how the albedo would respond to a doubling of CO2, it’s not so difficult to build a simulation of the evaporation cycle, in which a slight warming of the Earth causes more evaporation, which leads inevitably to more clouds, and therefore less sunlight reaching the Earth’s surface. Some collaborators and I did this, and produced a straightforward result: without clouds, a CO2 doubling would indeed result in 2 or 3 C warming of the surface, but with the effect of clouds, the warming drops to around 0.5 C. You will find more details here.
To get such a simulation to work, you need to model the formation of rain and clouds, but there’s nothing particularly difficult about it. Perhaps you and your collaborators could do something similar, and see if you come up with the same answers. It appears to us that the positive feedback in the IPCC models arises from the correct assumption that water vapor will increase with CO2 doubling, thus increasing the CO2-induced warming, but at the same time failing to allow for the inevitable increase in cloud cover that results from increased water vapor. The increased cloud cover is a much more powerful effect, because even 3 mm of water as cloud droplets will reflect of order half the incoming sunlight, while the same amount of water in vapor form effects the outgoing radiation by only a few percent.
Or so it seems to us, it would be nice to have someone else apply themselves to the problem.

Joachim Seifert
Reply to  Willis Eschenbach
May 31, 2012 7:46 pm

Willis, you can laugh as want… but I repeat: The climate forcing
analysis without CO2-forcing already exists, AGAINST your wrong
claims that it does not exist +
and I gave you the ISSN number various times….. nothing new to you….
To short term – long term analysis: Everybody in the climate field
agrees (consensus?) that the longer the time frame, the higher the
accuracy, therefore
…we have to stay on the millenial time level to produce meaningful
climate forcing calculations……..
Rahmstorf recently had an analysis over a 30-year time span, trying to
prove Warmist forcings….
If you do analysis on a shorter than 1 millenium time frame, you will
see in a few months, that all short term forcing jiggling is nothing but
for the Katz….
Dont get mad, I know you will scrutinize my coming paper and I do not
want to put you in a negative mood (if you are not already)…..
JS

Camburn
May 31, 2012 7:38 pm

W:
I am tired, and did a quick read of your post. AT 1st glance, it looks pretty good.
I have to be missing something tho as this does not support the AGW theme and the consensus developed.
Or…….could it be the consensus is similiar to Alfred Wegener days? He was right, but highly ostrasized.

BarryW
May 31, 2012 7:50 pm

So given the time frame of your calculation, the temperature rise and the .3 deg C per doubling for the NH, how much of the temperature rise is “attributable” to CO2?

May 31, 2012 7:56 pm

Second, the sun plus the albedo were all that were necessary to make these calculations. I did not use aerosols, volcanic forcing, methane, CO2, black carbon, aerosol indirect effect, land use, snow and ice albedo, or any of the other things that the modelers claim to rule the temperature.
Surely, if you measure albedo from top of atmosphere, it comprises the net of aerosols, BC, aerosol indirect effect (clouds), land use, snow and ice, plus some other things.
Although perhaps that’s implicit in what you wrote.
BTW, you have a typo in the graphic – Observerver.

Maus
May 31, 2012 7:58 pm

Willis, I’m going to assume that the spell-checkers here will catch any flaws in your model and I’ll run on the assumption that your model is sound. What I’m curious about is how this compares to the other climate models running around out there and there fit on back-casting.
That is, does your model fit as well as other models? Does it fit better? Or does it fit worse?
‘Model’ being the oft-equivocated word that means ‘theory’ and I’m interested in whether or not yours is preferable on parsimony for an equal fit (Occam), better fit, or whether it doesn’t make as good a match as the competing theories.
I’m not here talking about the physical or philosophical underpinnings of any specific model. Just correlation and the buzzword notion of science preferring the closer over the farther, and thereafter the simple over the epicycle. Thanks in advance for any time spent in reply. And a great many thanks for the time spent huddling over spreadsheets already.

Lance Wallace
May 31, 2012 8:01 pm

Geoff Sherrington says:
May 31, 2012 at 7:02 pm
Reason for selection of start & end dates?
My apologies if I missed it if stated before.
I’ve been studying hot year 1998 and it has some peculiar properties, so I’m keen to see what follows. There was a reason for the hot year and the explanation is either in your parameters, or a different forcing. It appears to have a NH vs. SH difference.
The Hatzianastassiou reference refers to the years 1984-1997 whereas Willis uses the phrase 1984-1998. Both are correct I suppose, since the period appears from Hatzianastassiou’s graphs to end about December 1997, but there is an ambiguity. Anyway, it is too bad that the “hot” year of 1998 just missed being included.

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