UAH Global Temperature Update for Dec. 2011: +0.13 deg. C
By Dr. Roy Spencer
The global average lower tropospheric temperature anomaly for December, 2011 remained about the same November, +0.13 deg. C (click on the image for the full-size version):
The 3rd order polynomial fit to the data (courtesy of Excel) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever.
Here are the monthly stats for 2010 and 2011:
YR MON GLOBAL NH SH TROPICS
2010 1 +0.542 +0.675 +0.410 +0.635
2010 2 +0.510 +0.553 +0.466 +0.759
2010 3 +0.554 +0.665 +0.443 +0.721
2010 4 +0.400 +0.606 +0.193 +0.633
2010 5 +0.454 +0.642 +0.265 +0.706
2010 6 +0.385 +0.482 +0.287 +0.485
2010 7 +0.419 +0.558 +0.280 +0.370
2010 8 +0.441 +0.579 +0.304 +0.321
2010 9 +0.477 +0.410 +0.545 +0.237
2010 10 +0.306 +0.257 +0.356 +0.106
2010 11 +0.273 +0.372 +0.173 -0.117
2010 12 +0.181 +0.217 +0.145 -0.222
2011 1 -0.010 -0.055 +0.036 -0.372
2011 2 -0.020 -0.042 +0.002 -0.348
2011 3 -0.101 -0.073 -0.128 -0.342
2011 4 +0.117 +0.195 +0.039 -0.229
2011 5 +0.133 +0.145 +0.121 -0.043
2011 6 +0.315 +0.379 +0.250 +0.233
2011 7 +0.374 +0.344 +0.404 +0.204
2011 8 +0.327 +0.321 +0.332 +0.155
2011 9 +0.289 +0.304 +0.274 +0.178
2011 10 +0.116 +0.169 +0.062 -0.054
2011 11 +0.123 +0.075 +0.170 +0.024
2011 12 +0.127 +0.197 +0.057 +0.043
I’m making very good progress on the Version 6 of the global temperature dataset, and it looks like the new diurnal drift correction method is working for AMSU. Next is to apply the new AMSU-based corrections to the older (pre-August 1998) MSU data.
[Reminder: Since AMSR-E failed in early October, there will be no more sea surface temperature updates from that instrument.]
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RE: 3rd Order Polynomials.
Just for “entertainment value”, I fit third order polynomials to the data, starting at the beginning (1979) and going to various points. I seem to have lost the file, but I remember the basic results:
Stop in 1998 (right after the big peak): the current predicted anomaly would be +3.6 K
Stop in 2000 (after the big dip): the current predicted anomaly would be -0.1 K
In fact, if you stop after pretty much any major dip or bump, the trend-line changes noticeably. Even fairly recent cubic fits (2008+) result in very noticeable changes in the predictions now (and even more so into the future).
Over-fitting noisy data like this with a high order polynomial is indeed nothing but “entertainment value”.
sky says:
January 3, 2012 at 3:03 pm
It’s curious that, despite a double-dip La Nina and upwardly revised monthly ‘norms,” the global average anomaly stubbornly refuses to dip significantly below zero.
It is curious that, despite claims of “accelerating warming” and “tipping points of no return from certain doom”, the global average anomaly stubbornly refuses to rise
significantlyany at all above where it was nearly fifteen years ago.The average temperature record is a sine wave for every day, and every year.
Should I be surprised to see longer sign waves in the average, for longer temperature records?
When science was more about observation, and less about “generating an emotional respose to get grant money”, the common wisdom was, there was a cyclical nature to the physical world. There is not much money, in common wisdom, and maybe that is why it is correct so often.
The 3rd order polynomial fit to the data (courtesy of Excel) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever.
Whoa, you know Excel? I know a certain climate scientist that needs a few lessons!
Tim Folkerts says:
January 4, 2012 at 7:51 am
“RE: 3rd Order Polynomials.
Over-fitting noisy data like this with a high order polynomial is indeed nothing but entertainment value”.
And nevertheless, the pattern-recognision system in my brain did react……but, alas, probably just an evolutionary thing….
Uh, when a third order polynomial peak “flattens”, it is approaching an inflection point, and the trend is about to head the other way.
____
Nope…it only might be headed “the other way”. It is a fit to the data, not a prediction that the trend is about to do anything. It could just as well deflect higher as lower. It has no predictive value, but is a fit to the data after the fact. As Dr. Spencer points out…”entertainment” only…so apparently he is given to entertaining us. Seems to be a common theme among scientists these days….
„The 3rd order polynomial fit to the data (courtesy of Excel) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever.”
I agree.
Let me say this. One thing is the measurement. An other thing is the interpretation.
It is obvious – not only from the data from 2009 – that a main frequency is phase coherent in NH and SH. This main frequency can be interpreted with the solar synodic tide function of the couple Mercury/Earth which is superimposed by three or more other solar synodic tide functions, as a simple comparison with astronomical data shows:
http://volker-doormann.org/images/uah_temp_4_r.gif
Because of the well known ocean and atmosphere oscillations on the globe the temp data are superimposed by these frequencies (Chandler, QBO, ENSO [4:2:1]). This both leads to the complicated temperature function of the data.
That this interpretation is valid one can see fitting the solar synodic tide function strength of 11 couples in our solar system in comparison with the hadcrut data:
http://volker-doormann.org/images/ghi_had_1960_3.gif
A third validity is the phase coherence of the frequency, which is superimposed to the sea level data from Colorado University if one subtract the increasing linear function from the data:
http://volker-doormann.org/images/sealevel_vs_abcd.gif
The general different point is, after fitting the strength of the tide functions the astronomical data can be well used for the prediction of global climate for the next 1000 years, because the NASA ephemrides are precise for that days.
But very Yes, without the high resolution temperature satellite data from Dr. R. Spencer there wouldn’t precise climate simulation possible. Great Thanks.
V.
The 3 month lag with respect to the ENSO means that UAH Temperatures in December (+0.127C) are responding to the mild -0.74C Nino 3.4 index of September.
The last time the Nino 3.4 was in this range was June 2010 when it was -0.65C. The 3 month lag means the comparable UAH Temperature number is September 2010 when it was +0.477C.
The Nino 3.4 index will reach its low point around late-January at about -1.25C so we will have further cooling over the next four months at least.
Other issues developing is that the AMO has gone negative now and the Atlantic Nino (the Atlantic’s version of the ENSO) has gone strongly negative and this usually leads to further declines in the AMO. So the paused downspike will resume in short order (but then I said that last month as well).
Volker Doorman’s post is particularly interesting and in line with Scafetta’s analysis of correlations between climate and planetary orbits. The correlation between the total tidal gravitational force of the planets and both temperatures and sea levels appears strong. We can test sea levels against the predictions of falls until March 2012, then rises to a plateau between May and November, followed by falls from December this year.
R. Gates. Professors Knox and Douglass would disagree with you about rising OHC. See http://www.pas.rochester.edu/~douglass/papers/KD_InPress_final.pdf
I provided a link for the data I quoted, though I acknowledge it was Pacific tropical only.
I’ll be away now till Tuesday, so unable to respond promptly.
“Uh, when a third order polynomial peak “flattens”, it is approaching an inflection point,”
No, the point of inflection of the given curve is around 1996, (where it changes from positive curvature to negative curvature)
The terminology you are looking for is “stationary point”. The maximum point, where the slope of the line is zero, about 2010.
If you go further to the right, the 3rd order curve will start to dip rapidly, which hopefully will not be the case. !
Just a thought from a dedicated skeptic. For a decade now the CAGW clique have been frustrated by the fact that the actual temp data doesn’t fit the projections of their ‘climate models’ in which the place their religious belief. They are certain they ‘understand’the physics of CO2 and thus they are confident their models will predict future temps. Some skeptics are also certain they understand smaller climate phenomenon, the ENSO, AO, SSTs, La Nina cycles, etc and based on that knowledge they are certain of being able to make seasonal predictions. I tend to believe in much of this– Joe Bastardi is paid fees by comodities traders for weather pattern predictions for futures trading. There was a consensus in this group that the Upper Midwest USA and central canada would see a brutally cold December and the mid atlantic to maritme Canada would see average temps and very stormy conditions. Hasn’t happened; the Greenland block never developed and NA has had a placid, dry and mild december/early January. Is the “climate” a chaotic system that can’t be predicted with anyone’s model?
NK says:
January 5, 2012 at 5:57 am
… They are certain they ‘understand’ the physics of CO2 and thus they are confident their models will predict future temps. … Some skeptics are also certain they understand smaller climate phenomenon, the ENSO, AO, SSTs, La Nina cycles, etc and based on that knowledge they are certain of being able to make seasonal predictions. … Is the “climate” a chaotic system that can’t be predicted with anyone’s model?”
I only can speak for myself (I have done big finite element method {FEM} heat current models with fast streaming fluids) . I think, it is not possible to mix the world of climate politics with the world of physics. In my point of view the cycles you have mentioned are mostly not elements of physics but social defined conventions; SSTs as an exception can be used in a physical model. A physical model of thermodynamics is using a heat current, a heat source, a heat resistance and heat impedances like oceans or the atmosphere. If this would be done well, an average global temperature as a function of time must fit with the reconstructed or measured temperature spectra. After this one can make local printouts depending on the locals seasons. It can be imagined that such model must be supplied with a time function of the heat power load. And this needs knowledge of the physics of the heat source (What is the heat source?). If we take the well known reconstructed global temperature spectra for real, we have to find out physical processes, which result in the global temperatures from the heat current floating from warm to cold. To my knowledge today there is no known varying physical process that leads to the known reconstructed global temperatures. If there would be knowledge it would be possible to simulate the reconstructed global temperatures. The term chaotic means that the scientist is not able to simulate a physical process, but it doesn’t mean that the nature of climate is chaotic. There are serious hints that the global temperature function of the Earth has a connection to the motion of the planets, and because the motion of the planets is precisely known for about 1000 years ahead, it is not out of the question of physics that it is possible in general to calculate the global temperatures for those days.
A word to politics. Politics can ask climate science whether they do understand the nature of climate as a physical process, or whether they do not understand the nature of climate. If climate science claims understanding, then the have it to show by physics laws simulations of the real complex reconstructed global temperature spectra. Otherwise they have to say, sorry we don’t know. To my knowledge there is no published paper available yet in that one can find such a simulation of physical processes for the last 2000 years.
V.
Volker, read my book: Das Ende der globalen Ewaermung, Berechnung des Klimawandels …all transparently for everyone calculated…all your questions answered….about literature and climate system changes…. only 12,90 E , bei Amazon.de … JS
“”””” tim in vermont says:
January 3, 2012 at 2:38 pm
I should add that I smoothed the input data for the forumla above. “””””
So you admit that you fudged the data before coming up with a theoretical model for it ??
I thought the problem was to come up with an equation that could predict what will happen in the future.
So just what is your prediction; excuse me, that is projection for the future climate of the planet.
“”””” kwik says:
January 4, 2012 at 11:45 am
Tim Folkerts says:
January 4, 2012 at 7:51 am
“RE: 3rd Order Polynomials.
Over-fitting noisy data like this with a high order polynomial is indeed nothing but entertainment value”. “””””
Well faced with real data as “noisy” as this, nobody would call a third order polynomial a “high order polynomial”. Maybe a 12th order polynomial would be “high order”.
By the way; that ISN’T noise; it is REAL data., the third order polynomial IS noise.
“”””” Mike McMillan says:
January 3, 2012 at 9:57 pm
kramer says:
… (I’m curious as to where he gets his temperature data from since there aren’t a whole lot of temp sensors in the Arctic).
1. Gather available data
2. Homogenize
3. Adjust for proper slope
4. Extrapolate
GSW says:
… You can’t get a sine wave from a third order polynomial and you should not ‘anticipate’ a cyclical temperature signal from the ‘fit’ shown.
Still looks like a 3rd order polynomial sine wave with a 60 year period. “””””
Well a sine wave is certainly not a third order polynomial
“”””” n Statham says:
January 3, 2012 at 4:58 pm
Itsaying such a thing only shows what low standards of “science” are maintained here. “””””
Well just in case you think that YOUR favorite text book from which you got all YOUR wisdom, is Biblical truth and beyond reproach; be forewarned; it ain’t necessarily so.
I have in my hand a Text book on thermodynamics.
” An Introduction to Thermal Physics.” by C.J. Adkins
This is not just any text book and adkins is not just any author.
Published by Cambridge University Press, as in the UK Cambridge, and the author is a lecturer in Physics, and a fellow ofJesus College, Cambridge; well he was in 1976.
This copy is from the Hewlett Packard Research Labs Library (and headed back there).
It is actually a fairly reasonable book and as it says, an Introduction. but turn to page 97 where it so happens the section on the Stefan-Boltzmann law starts.
the immediately preceding section is actually about GREENHOUSES and figure 6.14 shows a cross section picture of a greenhouse.
Short wavelength sunligh charges right through the glass roof on the right of the drawing, and impinges on the plants on the tables inside the greenhouse.
Long wavelength IR emitted from the plants, and other things inside heads towards the glass roof on the left, where it is largely stopped, and mostly reflected, with a small transmitted component..
As they say, the long wavelength is instercepted by the glass.
Now everybody above 4-H club knows that green houses simply DO NOT work that way.
well actually they do. The sunlight does enter, largely unhindered except for its long IR tail, and even that gets through; and the internally emitted LWIR does get intercepted by the roof glass, just as Lecturer author Adkins shows; EXCEPT, it doesn’t reflect, it gets absorbed, and heats the glass, just as the incoming solar IR does, and then the glass inturn radiates LWIR both inside and outside, so about half of the internal IR probably leaks out maybe more.
As we all know, except for C.J. Adkins, it is the inability of the heated internal air to escape through the roof by convection, that causes the Temperature to rise as far inside the enclosure.
Well you could make the green house out of opaque material like fiberglass or steel, and it would still get hot inside, even though sunlight could no longer penetrate, to be down converted to LWIR.
So don’t take for granted, that your favorite text book is above reproach; it surely was well known by 1976 that green houses don’t actually work via the “greenhouse effect” although we know that atmospheric warming surely does to some extent. As to what else is warmed; well that is another matter.
Joachim Seifert says:
January 7, 2012 at 1:57 pm
…
Joachim,
i have written to this thread because it can be shown, that global climate can be calculated -3000 AD +3000 AD from the real motion of ten planets in high resolution. The time resolution seems to be limited to month because of the solar tide frequency of the fastest synodic couple Mercury/Earth. I have shown this in this graph here, in comparison to the hadcrut 3 data. But it holds also for the whole time span of 6000 yeas (s. graph) .
You are dealing with one (?) cycle of 790 years. In a comparison with the reconstructed temperatures from A. Moberg et al. and/or E. Zorita et al., you can see that a sinusoidal cycle of 790 years with a maximum in these decades does not fit with the spectra in the pass, solar tide functions does.
History tells us that there were cold years some 1500 years ago. I think it is understandable that the real motion of ten bodies can tell more details in global climate then one cycle of 790 years.
The climate code is solved. The global climate can easy be calculated now in high resolution for the next 1000 years similar terrestrial tides.
V.
I wonder why the monthly widget is not updated
(to show the December results)
I also wonder if the widget is changed automatically every month at the sites where it has been introduced?
HenryP says:
January 8, 2012 at 9:05 am
I wonder why the monthly widget is not updated
(to show the December results)
http://www.volker-doormann.org/images/uah_temp_4_dec.gif
V.