UAH Global Temperature Update for February 2012: -0.12 deg. C
By Dr. Roy Spencer
The global average lower tropospheric temperature anomaly cooled a little more in February, 2012, again not unexpected for the current La Nina conditions in the tropical Pacific Ocean (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:
YR MON GLOBAL NH SH TROPICS
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 +0.126 +0.197 +0.055 +0.041
2012 01 -0.090 -0.057 -0.123 -0.138
2012 02 -0.116 -0.014 -0.217 -0.281
Progress continues on Version 6 of our global temperature dataset, which will have a better adjustment for drift of the satellites through the diurnal cycle, and an improved calibration procedure for the older MSU instruments (pre-1998).
If not for the big jump early in the month the number would have been much lower. Electroscavenging? It fits the data as the upward movement started immediately after a major CME.
All the evidence is pointing towards GHGs working as tiny little thermostats and the real difference in temperatures is driven by changes in albedo. Since several factors appear to affect albedo it makes it difficult to sort them all out. GCRs, CMEs, variations in magnetism, etc., etc.
Of course, the models do little to help us out.
They are so found of saying the 2000’s are the “warmest decade EVA” but I suspect they won’t be fond of this new decade when all is said and done.
Dr. Roy: For updating and easier understanding: Could we write El Nino 2010 above
the 2010 temp spike? This would help explain to NEW viewers….. Thanks…..
I have a computer model that says your experimental data is wrong.
“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.”
Then take it off. It implies a pattern.
I’m sure the warming alarmist will once again declare that lower temperatures are a sure sign of man-made global warming. Why let the facts cloud a good old fashioned scare-mongering good time! Heck, the good intentions of those who want to spend trillions of dollars (from others of course) to make us live like stone age serfs should be all that is required for the masses to bow to their great intellect.
TallDave says:
March 2, 2012 at 8:57 am
I have a computer model that says your experimental data is wrong.
“Brevity is the soul of wit”
Oscar Wilde (?)
This temperature decline is *completely consistent* with CAGW theory! 🙂
Did anyone else notice that the ENSO meter moved to neutral a couple days ago?
Dino:
When you create a satellite derived global and regional temperature reconstruction, feel free to take off (or leave on) whatever items you choose.
In the meantime, Dr. Spencer can put whatever graphic he chooses on his graph. And Anthony can give guest posts to whomever he wants.
I did. And then I went on the ENSO page and noticed two things. First, the first graph, the NINO 3.4 index, had a HUGE spike up. Then I went down to the NOAA SST anomaly graphic and noticed a big spot of yellow off the coast of South America that wasn’t there last month. It appears to me that the oceans have really warmed over the past month, so I suspect the UAH temperature anomaly with creep up next month.
Dinostratus says: March 2, 2012 at 9:14 am
“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.”
Then take it off. It implies a pattern.
_____________________
It implies a third degree polynomial fit of ACTUAL DATA.
I say leave it in.
If you want to argue this point Dino, you should argue with those who choose to extrapolate a linear relationship into the future, when it is most likely the ~30-year warming half of a ~60 year warming and cooling cycle.
This cycle is apparent in some much data, from Western Canada river flows to salmon runs to global surface temperatures. I expect it is apparent all over the world. It may be a global manifestation of the PDO.
I predicted imminent global cooling in an article published in 2003.
My guess is the polynomial, while having no predictive value, is pointing in the right direction.
To date, the IPCC’s climate models have over-predicted global warming and have been scaled downward again and again. To my knowledge, none of the IPCC’s published model results have predicted global cooling.
Anyone else is welcome to do their own research and come up with their own predictions.
You are all likely to do better than the IPCC.
Ladies and gentlemen, faites vos jeux!
To put the combined January and February numbers into perspective, 2012 for these two months is the 26th warmest out of the 33 years of UAH data. Of course this will change before the year is out, but you are not going to set a new record this way.
Dr. Spencer proves the thesis, IPCC projections under estimated natural cycles and thus over estimate AGW. Its fairly obvious from AR4 but to what conclusion?
Mildly interesting that the averages for January and February 2012 are both lower than their respective averages last year. (Does anyone have 2010 handy? How many years back, if any, does that go?)
“The circular fit of observational data (courtesy of Ptolemy’s equants) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Copernicus, 1539, De Revolutionibus Orbium Coelestium
“The circular fit of observational data for Copernian helio-centric circles for all other planets except the earth and moon (courtesy of sextants, quadrants, and armillary spheres) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Tycho Brahe, 1588, “De Mundi Aetherei Recentioribus Phaenomenis”
“The octahedron, icosahedron, dodecahedron, tetrahedron, and cubic fit of observational data for all planets (courtesy of observational data confirming the size of each planet’s orb to the length of its orbital period for a ratio of increase in orbital period at twice the difference in orb radius) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Johann Kepler, 1595, “Mysterium Cosmographicum”
“The elliptical fit of Tycho’s observational data for Mars (courtesy of my assumption that planets move in ellipses, with the sun at one focus while sweeping out equal areas in equal times) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Johann Kepler, 1609, “Astronomia nova”
“The Jovian-circular fit of Galileo’s observational data for its moons (courtesy of his telescope) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Johann Kepler, 1610, “Dissertatio cum Nuncio Sidereo” discussing Galileo’s recent Sidereus Nuncius
“The heliocentric fit of observational data for all planets and their moons (courtesy of new observational data from my telescope) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Galileo Galilei, 1632, “Dialogo sopra i due massimi sistemi del mondo”
“The elliptical fit of observational data for orbits of the Jovian moons (courtesy of Kepler’s Third Law) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth.” Godefroy Wendelin, 1643, “Loxias seu de obliquitate solis” *8<)
"The inverse squared fit of observational data for all masses under the theoretical influence of the Law of Gravity (courtesy of observational data from an apple) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever for future planetary positions with respect to the earth." Issac Newton, 1686, "Philosophiæ Naturalis Principia Mathematica"
RACookPE1978 says:
March 2, 2012 at 10:59 am
===========
Newton and Descartes — rescued Science from the “Church of Rome” and ushered generations into freedom of thought?
I don’t see it in any other way.
Do You and if so please explain!!!
@TallDave says:
“Brevity is the soul of wit” – Oscar Wilde (?)
Obviously you missed class when they were doing Hamlet….
@Dinostratus
…Then take it off. It implies a pattern…”
It seems obvious to me that the Earth’s climate is constrained between quite narrow bands by various negative feedbacks, otherwise it would have swung to a limit before now. If this is true, then I would expect to see a repetitive pattern in the temperature – oscillation is so common in these kind of situations. So leave it in – we are looking for a pattern, not trying to ignore one….
So the Earth’s temperature has now returned to where it was back in 1980 when A Flock of Seagulls had the hit song “And I Ran”. How can this be?? There is clearly more CO2 in the air! How CAN this be?
The Talking Heads said it best:
“Same as it ever was…”
There is a sting in the tail of Excel trend lines. It seems that the curve drawn is ok on the graph but if you display the equation to the trend line, an option provided by Excel, the equation is only accurate when the chart selected to display the data is an X Y plot.
http://support.microsoft.com/kb/211967
I realise no one has got that far yet on this thread but. . . . . .
ENSO is headed straight up at the moment, and recently crossed into “neutral” territory. There is some months of lag in these things, typically, before they start impacting the global anomaly significantly.
The ensemble average of predictions suggests we might be flirting with a moderate El Nino by this fall, but that’s subject to change as well.
And, as I usually write about this time each month, for those interested, I’ve posted the preliminary February 2012 sea surface temperature anomaly data here:
http://bobtisdale.wordpress.com/2012/02/28/preliminary-february-2012-sst-anomaly-update/
The full update will be available on Monday March 5th.
Certain people really seem to be annoyed by that polynomial…
So leave it in!
Dinostratus says:
March 2, 2012 at 9:14 am
“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.”
Then take it off. It implies a pattern
And
Allan MacRae says:
March 2, 2012 at 10:00 am
“It implies a third degree polynomial fit of ACTUAL DATA.
I say leave it in.”
I say the good doctor puts it in there as bait for people like Dino. Allan – just relax and enjoy the show when they bite!
John from CA says:
March 2, 2012 at 11:12 am (commenting on)
RACookPE1978 says:
March 2, 2012 at 10:59 am
===========
Newton and Descartes — rescued Science from the “Church of Rome” and ushered generations into freedom of thought?
I don’t see it in any other way.
Do You and if so please explain!!!
The positions of either with respect to the discussion at hand is irrelevant.
You missed the entire point of my comment: it is a light-hearted comment about an earth-shattering – but totally wrong! presentation of incomplete and somewhat inaccurate observational data using the wrong theory … by (abusing) the good doctor’s own Excel apology.
But each observation was defiantly earth-shattering … despite being definitely wrong at the same time.
Further, each observation had no theoretical justification by any known physics or mathematics theory at the time it was made … but every observation was physically correct to visible facts at the time it was made.
Newton’s and Descartes supposed “heroic fight” against the church’s view can be mostly derived from today’s back-asswards teaching about Galileo and his trials. At the time of Copernicus, Tycho Brahe, and Kepler the “new” equations and predictions of planetary motion were no better than the original Ptolemy theory of equants and geo-centrism. In fact, the geo-centric theory of orbits and spheres WAS ACCURATE. It had been accurate for over a thousand years with almost no contradictory evidence.
Let me reverse the aim of your comment: Reinhold’s, Rheticus’, Newton’s, Copernicus’, Brahe’s and Kepler’s known and deliberate use of astrological predictions for their monied sponsors; their sponsor-beneficat dedications and praises in the dedications and signature pages of their books can be very explicitly compared to today’s CAGW “scientists” paying off their governmental agencies for grant money and influence over the world’s political future.
Ptolemy’s Geo-centric theory with equants was more accurate than Columbus’ prediction of a sea route to the Indies – because the established authorities KNEW the earth was circular, but that the real sphere was far larger than Columbus’ deliberate but totally wrong assumption about a small radius, and thus a safe journey sailing west!
Wade says:
March 2, 2012 at 9:57 am
Frizzy says:
March 2, 2012 at 9:41 am
Did anyone else notice that the ENSO meter moved to neutral a couple days ago?
I did. And then I went on the ENSO page and noticed two things. First, the first graph, the NINO 3.4 index, had a HUGE spike up. Then I went down to the NOAA SST anomaly graphic and noticed a big spot of yellow off the coast of South America that wasn’t there last month. It appears to me that the oceans have really warmed over the past month, so I suspect the UAH temperature anomaly with creep up next month.
But the Indonesian warm pool that normally recharges the El Nino is absent. A very strange pattern of temperatures at the moment. With these extensive cold temperature anomalies outside the constraints of the ENSO box perhaps the metering may not be so predictive. Have to wait for Bob Tisdale to comment.
And, by the way, Columbus’ critics preceded any thought or conception of helio-centric theory’s.
His voyage (and fund-raising) in 1492 HAD to use accurate and repeatable Ptolemaic geo-centric star-charts to plot his path to and from the West Indian islands. Magellan’s fleet circled the globe in 1522-1523 using Ptolemy’s geo-centric star charts before Copernicus published his helio-circular – but wrong – theory in 1543.
Brahe and Copernicus and Ptolemy correctly predict the position of the planets with respect to the earth with considerable accuracy. Magellan and hundred’s of other Europeans used Ptolemy’s geo-centric star charts 80 years before Kepler first published his – totally wrong – first religious-based theories about why the sun held an attraction for its planets.
Hint. Read: Owen Gingrich’s “The Book No One Read” about the publishing, editing and numerous edits and revisions to Copernicus’ De Revolutionibus before you go further.
It’s worse than we thought!
Someone had to say it.
What’s happened to January’s Hadcrut ?
DirkH says:
March 2, 2012 at 11:50 am
“Certain people really seem to be annoyed by that polynomial…
So leave it in!”
Yes, consider it to be the “Anti-Hockeystick”.
Re Dino and the polynomial, which I agree with Seth and others is a bit of a tease: You can be sure that if the right end of the curve pointed up, the AGW crowd would be touting it as “settled science.”
TallDave says: March 2, 2012 at 8:57 am
“I have a computer model that says your experimental data is wrong.”
Well I have an experimental computer model that says observations are wrong.
Why is it that you big oil funded denialists have such a problem understanding the new consensus based science? As CO2 emissions cause the planet to heat up it has the effect of cooling the planet down, simple cause and effect isnt it? Simple physics dictates that heating something makes it cooler. And as the planet gets hotter and hotter which the the computer models have conclusively proved the planet in turn gets cooler as the observed data proves. What could be simpler to understand? And yet the big oil funded denier industry constantly attempts to confuse the issues and refuses to enter a rational dialogue in the simple form of an abject grovelling apology and conversion to the universal consensus. We simply must continue to drastically slash CO2 emissions whatever the cost, its the only way to stop the global warming that leads to the planet cooling leading to utterly disastrous warming/cooling/droughts/floods/too much snow/not enough snow. In short CO2 causes everything to happen or not happen as the case may be. CO2, its not a trace gas, its an evil genius out to deceive and conquer us using big oil funded deniers as its agents.
Come and join the consensus, we are not a cult you know.
REPLY: Stephanie, this is a joke, right? You just forgot to add the /sarc tag right? – Anthony
The funniest thing about that 3rd-order polynomial fit is that historically, by chance, it does have predictive power.
If you delete the last 10 years of data and draw a 3rd order polynomial through the remainder, and then project that line forward 10 years (Excel will do that), you get an excellent prediction of actual temperature, and a line very similar to the current one.
As such, it has vastly greater predictive power than any climate model of ten years ago. Yes, this is just a statistical fluke, but it also tells you something about the the models. They can’t even get it right by chance.
“braddles says:
March 2, 2012 at 1:20 pm
….As such, it has vastly greater predictive power ….”
NO! A 3rd order polynomial has 1 maximum and 1 minimum. It is now heading down forever hence no predictive power at all just chance over the last 10 years.
I wonder how you have to draw the trend line to make the ridiculous claim it’s still warming? (Getting warmer.)
I know, just draw a line from the start point (1979) to the end point (2010) and just continue to infinity.
Ah, but what does an sinusoid curve predict?
Cassandra King says:
March 2, 2012 at 1:07 pm
WTF?
I hope to goodness Anthony’s reply is valid or else we really do have some completely deranged ‘faithful’ out there in la-la land!
“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.”
Neither do the climate models. Looks like a pretty sinusoidal function to me. Why would it be any less predictive than said models?
joshua says:
March 2, 2012 at 10:44 am
Mildly interesting that the averages for January and February 2012 are both lower than their respective averages last year. (Does anyone have 2010 handy? How many years back, if any, does that go?)
See
http://vortex.nsstc.uah.edu/data/msu/t2lt/uahncdc.lt
You may also want to see the following which ranks all 33 years on this set from hottest to coldest:
http://motls.blogspot.com/2012/01/uah-amsu-2011-was-4th-coldest-in-this.html
Dr Burns says:
March 2, 2012 at 12:17 pm
What’s happened to January’s Hadcrut ?
I was wondering that myself. The January 2012 value for HadCrut3 at about 0.22 certainly does not help THE CAUSE. At 0.22, it would rank 18th hottest. And UAH for February certainly will not help either.
http://www.climate4you.com/GlobalTemperatures.htm#HadCRUT3%20TempDiagram
Time and tide wait for no man. But we all wait for Hadcrut.
Jim G it is not a sine wave, as son of mulder says it can only go down now. Go to fooplot.com and enter y(x) = x – x^3 to get a more complete picture of what a third-order polynomial looks like.
I think Dinostratus’s point is a fair one and I am glad that Spencer always posts the disclaimer clearly.
Dinostratus says:
March 2, 2012 at 9:14 am
“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.”
Then take it off. It implies a pattern.
And a pattern is such a bizzare, forbidden idea? Oh – I forgot – nonequilibrium/nonlinear pattern formation is to current climate research what the periodic table of elements would have been to 13th century alchemists.
Cassandra King says:
March 2, 2012 at 1:07 pm
Come and join the consensus, we are not a cult you know.
Sarcasm has to be used sparingly on sites like these, go too deep into cover and folks lose the plot and get nervous.
Kev-in-UK says:
March 2, 2012 at 2:00 pm
Cassandra King says:
March 2, 2012 at 1:07 pm
WTF?
I hope to goodness Anthony’s reply is valid or else we really do have some completely deranged ‘faithful’ out there in la-la land!
Folks here should know Cassandra King better than that!
Bob Tisdale says:
March 2, 2012 at 11:45 am
And, as I usually write about this time each month, for those interested, I’ve posted the preliminary February 2012 sea surface temperature anomaly data here:
http://bobtisdale.wordpress.com/2012/02/28/preliminary-february-2012-sst-anomaly-update/
The full update will be available on Monday March 5th.
Thanks Bob. I guess the usual hue and cry for el Nino will go up. However such is the intensity and persistence of the south west Pacific surface warmth that it is interesting to speculate that, even in the (temporary) absence of Peruvian coast cold upwelling, an east-west equatorial temperature gradient will remain sufficient to cap off the growth of a strong el Nino (by sustaining the trades, preventing them from turning into doldrums) and keep renewed La Nina upwelling not too far away.
Dinostratus, it could be that the entertainment value lies in the responses to it such as yours. I agree on a scientific basis but its easy to ignore the poly curve if you try.
Dr Burns, I am not sure when HADCRUT are switching to version 4 of their model, the one that apparently makes 2010 hotter than 1998 by changing to CRUTEM4. Maybe it is imminent so updating HADCRUT3 might finish soon or at least be a low priority? Might explain the delays in releasing figures under the old model.
P.D. Jones, D.H. Lister, T.J. Osborn, C. Harpham, M. Salmon, and C.P. Morice, “Hemispheric and large-scale land surface air temperature variations: An extensive revision and an update to 2010”, Journal of Geophysical Research
joshua says @ March 2, 2012 at 10:44 am
> Mildly interesting that the averages for January and February 2012 are both
> lower than their respective averages last year. (Does anyone have 2010 handy?
> How many years back, if any, does that go?)
Click on the link http://vortex.nsstc.uah.edu/public/msu/t2lt/tltglhmam_5.4 to get UAH monthly data all the way back to December 1978.
Dinostratus says:
March 2, 2012 at 9:14 am
“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.”
Then take it off. It implies a pattern.
Only Dr Spencer can say for sure why he includes it, but I have always interpreted it as a sly dig at the climate models. Rather clever IMO. His trend is for entertainment purposes, while the climate models’ trend is the basis for changing the entire world economy.
I’m only lukewarm on AGW, but to say UAH shows cooling is jumping the gun. Here it is with a 2 yr avg. (I find 2 years gets rid of a lot of noise and makes it easier to see what’s going on.)
http://www.woodfortrees.org/plot/uah/mean:24
It’s going to take several years of cooling for the graph to look convincing.
Joshua,
Here’s the raw data back to 1978. It doesn’t have Feb in it yet:
http://www.woodfortrees.org/data/uah
“In the meantime, Dr. Spencer can put whatever graphic he chooses on his graph. And Anthony can give guest posts to whomever he wants.”
Bull. The impact of the data is lessened when random shapes are tossed across it.
“It implies a third degree polynomial fit of ACTUAL DATA.”
Any odd order polynomial will show it was cold before and hot later or hot before and colder later. It implies a trend. With the fit as it is now, the coefficient of the highest order term is negative, implying that in the future the zeroth law of thermodynamics will be violated and we will have a negative absolute temperature.
Let’s not limit our selection to a third order polynomial. Why not a zero, second or fourth order polynomial or any even polynomial? Why not a harmonic wave? Why not any function? I vote for the error function. I’ve always liked the name. Sort of a oxymoron. How about a Bessel function with imaginary arguments? That’s a good point. Why should we limit ourselves to arguments on the real plane?
I wonder why the Mt Pinatubo cooling label never gets questioned next to the 1985 low, or the lesser but evident 2000 and 2008 lows. Could it be that volcanic eruptions don’t cool the earth as much as we think?
Have a look at http://www.cru.uea.ac.uk/cru/info/warming/ (today updated to 2011) where the CRU is now clearly showing a slight global cooling since 2003.
Still HADCRUT3 data for January 2012 is not available.
There is something about Roy Spencer’s chart that I do not understand. It shows the February, 2012 anomaly as minus 0.12 deg. C. and the minimum reached back in 2008 as minus 0.4 deg. C. It is my understanding that he uses the Aqua satellite readings at 14,000 feet for the monthly chart.
When you go to the published daily readings of Aqua Channel # 5 (see link below) and chart all the years from 2002 to date, you will find no month recorded where temperature was as low as it appears on the ASMU-A chart for February, 2012. In view of this, how could a lower temperature have been reached previously as Roy’s chart shows (actually three time before)?
What am I missing here? I’d appreciate an explanation.
http://discover.itsc.uah.edu/amsutemps/
They are so found of saying the 2000′s are the “warmest decade EVA” but I suspect they won’t be fond of this new decade when all is said and done.
The argument that this decade is the “warmest ever” (on record) and that therefore global warming has not stopped (paused, whatever) contains a common fallacy of logic: They are conflating offset and trend.
I’ve seen it a zillion times and it needs a bit of explanation:
During the 1984 presidential campaign, Mondale pointed out (correctly) that the ‘average” inflation under Reagan’s first four years was worse than that of Jimmy Carter’s administration. Well, sure. Reagan had crashed inflation at a slightly lower rate than Carter had exploded it. So, yeah, sure, the “average” under Reagan was higher.
Reagan responded (correctly) with the following: “If the Carter administration was a book, you would have to read it from back to front to get a happy ending.”
Likewise, you would have to read the HadCRUt3 graph for the last decade from right to left to get a warming trend.
Claude – I was wondering the same thing. Based on the satellite plots, I was expecting a lower figure than that of 2008.
I don’t understand how claims are made that global warming is happening faster than expected. No data set shows any significant warming for this decade. How can it be faster than expected?
Sassandra – thanks for the physics lesson, I’ve just put a saucepan of water on the hot stove. Somewhere in the process of heating up, I expect the water to freeze.
You’re right. It seems that if it’s hot, it’s global warming. If it’s cold, it’s global warming. If it’s snowing, it’s global warming. If it’s not snowing it’s global warming. And the latest – if horses get smaller, it’s global warming (this one really broke me up).
Claude Harvey says:
March 2, 2012 at 6:22 pm
Yes. I’ve just done a little digging of my own, and something, on the face of it, looks odd.
I calculated the actual daily average temperature from the discover site here :
http://discover.itsc.uah.edu/amsutemps/data/amsu_daily_85N85S_ch05.r002.txt
Then compared them with the raw anomaly figures from the woodfortrees link, kindly provided by GregF above, here :
http://www.woodfortrees.org/data/uah
Subtract the anomaly from the average temperature, and you should get a consistent number which represents the long-term baseline. Agreed?
This is what I actually found for February 2003-2012
2003 : 252.50 average, +0.17 anomaly, 252.33 baseline
2004 : 252.42 average, +0.20 anomaly, 252.21 baseline
2005: 252.44 average, +0.17 anomaly, 252.26 baseline
2006 : 252.38 average, +0.22 anomaly, 252.17 baseline
2007 : 252.41 average, +0.22 anomaly, 252.19 baseline
2008 : 252.12 average, -0.26 anomaly, 252.37 baseline
2009 : 252.35 average, +0.15 anomaly, 252.19 baseline
2010 : 252.71 average, +0.51 anomaly, 252.20 baseline
2011 : 252.20 average, -0.02 anomaly, 252.22 baseline
2012 : 252.08 average, -0.12 anomaly, 252.20 baseline
What’s up with that?
I checked out the post at Dr. Spencer’s site. Has Roy temporarily given up on moderating and set the site for automatic posting? David Appell is holding court in the comments.
One:
Two:
Two-A:
The warming rate in One seems possible, but confirmation of greenhouse theory, with presumably something it has always said would happen? With that much ocean heat content gain in Two, especially since 2007 in Two-A given the global temperatures?
How much of that is true, from real true trustworthy actual measurements, and how much just warmist made-up figures and model-assisted extrapolations? Unless I haven’t been reading close enough here on WUWT, most of what Appell’s spewing doesn’t seem possible or plausible.
GregF,
You could try a 13 month mean: http://www.woodfortrees.org/plot/uah/mean:13
It shows a recent cooling trend after the El Niño warming of 2010.
So to see a downward trend 15 years in the making (1997 – 2012), I have to use a 13 month avg. so I can see the tail at the end. I’m afraid I don’t find that very convincing.
fyi: I do find the solar cycle correlations to temps very intriguing, but its 5 or 10 more years before we can truly confirm they pan out. That is, my opinion is a lot of the 1980-2010 warming was solar cycle driven, but as long as both the solar cycle forcing and the CO2 forcing are pushing temps up it is hard to distinguish which is which. Based on correlation analysis the solar cycle forcing should now be pushing towards cooler temps, but that just started and we need a few years to see what impact it truly has. Obviously my comment here is what makes me a lukewarmer.
R James says:
March 2, 2012 at 8:01 pm
“Cassandra – thanks for the physics lesson, I’ve just put a saucepan of water on the hot stove. Somewhere in the process of heating up, I expect the water to freeze.
You’re right. It seems that if it’s hot, it’s global warming. If it’s cold, it’s global warming. If it’s snowing, it’s global warming. If it’s not snowing it’s global warming. And the latest – if horses get smaller, it’s global warming (this one really broke me up).”
Deaf fish was my particular crack up point, that and the vision of crabs with no shells.
I feel that I must apologise to Anthony Watts for the lack of the (sarc) tag at the end. I was merely trying to get the alarmist position right in my head, it pays to know what the enemy are thinking.
GregF says:
March 2, 2012 at 4:27 pm
I’m only lukewarm on AGW, but to say UAH shows cooling is jumping the gun. Here it is with a 2 yr avg. (I find 2 years gets rid of a lot of noise and makes it easier to see what’s going on.)
What noise?
The ‘noise’ argument used by the AGWers is that natural variation is ‘noise’ in the AGW signal. Not that there is significant noise in the tropospheric sattelite temperature data.
The cooling on a monthly basis is almost certainly real.
By noise I meant things that don’t impact the trend. La Nina and El Nino qualify as noise from a trend analysis perspective. ie. That doesn’t mean the temps are in accurate, it just means the overall trend is easier to see if you get rid of the short term variability.
From Cassandra King on March 2, 2012 at 9:25 pm:
The fate of the world is at stake. You must immediately place all of your wealth and freedom at the disposal of We Who Are Smarter Than You if life on Earth* is to be saved.
*-saving of human lives besides our own shall be at our discretion
Now you know what they are thinking. Glad to be of help. 😉
Dinostratus says:
Bull. The impact of the data is lessened when random shapes are tossed across it.
It is not a random shape. It is a third order polynomial trend line, fit to the subject data in a manner that minimizes the residuals.
Any odd order polynomial will show it was cold before and hot later or hot before and colder later. It implies a trend.
It doesn’t imply a trend, it specifies one and demonstrates it.
With the fit as it is now, the coefficient of the highest order term is negative, implying that in the future the zeroth law of thermodynamics will be violated and we will have a negative absolute temperature.
Don’t be silly. It implies no such thing. Not even to you.
All over every climate related website site that you visit, there are hundreds of temperature graphs with linear (i.e. first order polynomial) trends fit to them. For some strange reason, we don’t see you demanding that all of those linear trends be removed from all of those graphs, despite the fact that (by your silly reasoning) every single one of them “implies” both a negative absolute temperature and an infinitely positive absolute temperature at some future/past point in time.
Let’s not limit our selection to a third order polynomial. Why not a zero, second or fourth order polynomial or any even polynomial?
Not a zero, because a zero order polynomial a horizontal line. Ya can’t really demonstrate a trend with one dimension. You can do a second order if you want. Roy chose to use a third order – it fits better.
For your education and edification, a fourth order polynomial trend fit to the current UAH data is effectively indistinguishable from the third order that Roy presents. Looks the same and shows the same fit. You seem to be laboring under the misconception that odd polynomial trend lines “imply” a downward trend with these data, and that even polynomial trend lines “imply” the opposite. Not so.
Why not a harmonic wave?
Simplicity. Excel quickly graphs low order polynomial and log/Exp trend lines. A more complex trend such a sinusodial trend line is a lot more work to produce, and over a dataset that is short relative to the fundamental period of oscillation, a simple sinus curve doesn’t produce results that are substantially different than the third (or fourth, if you prefer) order polynomial.
Why not any function?
Given that this question subsumes “Why not a third order polynomial?”, one wonders why you are asking it.
If you are interested in seeing what a four part sinus plus linear trend looks like, fit to a longer temp dataset with more fundamental and harmonic periods, see here:
http://wattsupwiththat.com/reference-pages/scafettas-solar-lunar-cycle-forecast-vs-global-temperature/
I’m betting you don’t like that one, either. Note that it’s author, unlike Spencer, does assert that this is one is useful as a forecast.
And although Spencer specifically states that he doesn’t endorse the third order polynomial trend as a forecast, it has done a pretty good job over the last seven years or so in that role, only slightly overestimating the realized trend.
If you fit a second order polynomial (viz. quadratic) you get a very different picture. 0.0 rate of increase in 1979, 0.36 C/year increase at present and a rate of temperature increase accelerating by 0.01 per year.
As, ur, “entertained” as i was by your brilliant third order polynonial fit, i still fail to see what the point in this post was in the first place? Sounds like a transparent legal disclaimer to me. So in the context of the graph, the fact that the temperature anomaly is negative means what exactly?
The cubic fit does indeed have entertainment value; the further downward it trends, the more entertaining it gets.
David says:
March 3, 2012 at 1:32 am
As, ur, “entertained” as i was by your brilliant third order polynonial fit, i still fail to see what the point in this post was in the first place? Sounds like a transparent legal disclaimer to me. So in the context of the graph, the fact that the temperature anomaly is negative means what exactly?
It means that the mean temperature for February 2012 was about -0.12 deg lower than the mean temperature for all Februarys over the 1981-2010 period. This is not unexpected as temperatures in the Lower Troposphere are currently responding to a fairly deep La Nina which developed during the latter part of 2011. La Nina (temperature troughs) an El Nino (temperature peaks) episodes can be seen clearly in Roy’s graph above. However, what is also evident is that, over time, recent temperature troughs are warmer than previous temperature troughs and, apart from 1998, recent
temperature peaks are warmer than previous temperature peaks. Transistion from La Nina to El Nino and vice versa can result in a change in temperature of up to half a deg. It’s perfectly reasonable, therefore, to expect short term cooling – even in a generally warming world.
Any talk of a cooling trend is exremely premature and probably wrong. When the Nino index returns to neutral we might have a better idea if anything significant is taking place.
I’ve been modeling the various temperature series for awhile based on the ENSO, the AMO and the Ln(CO2). I’ve recently added in the volcanic aerosols influence (the forcing that will be used in the upcoming IPCC AR5) and there were two significant volcanoes in the beginning of the UAH record which distorts the overall trendline over the period.
So, the model for UAH is pretty good (not perfect but representative at least).
http://img717.imageshack.us/img717/2716/uahmodelfeb12.png
And the left-over warming trend is only 0.042C per decade (versus about 0.202C per decade in the climate models over the period).
http://img845.imageshack.us/img845/3516/uahwarmingfeb12.png
Dr. Nicola Scafetta, at http://wattsupwiththat.com/2012/01/09/scaffeta-on-his-latest-paper-harmonic-climate-model-versus-the-ipcc-general-circulation-climate-models/ says:
“The results of this paper reinforce previous claims that the relevant physical mechanisms that explain the detected climatic cycles are still missing in the current GCMs and that climate variations at the multidecadal scales are astronomically induced and, in first approximation, can be forecast.”
The main thing, seems to me, is that Dr. Scafetta is putting his empirical theory up to a test.
I have published 3 articles on Dr. Scafetta at http://www.oarval.org/ClimateChangeBW.htm
“”””” Richard M says:
March 2, 2012 at 8:18 am
If not for the big jump early in the month the number would have been much lower. Electroscavenging? It fits the data as the upward movement started immediately after a major CME.
All the evidence is pointing towards GHGs working as tiny little thermostats and the real difference in temperatures is driven by changes in albedo. Since several factors appear to affect albedo it makes it difficult to sort them all out. GCRs, CMEs, variations in magnetism, etc., etc.
Of course, the models do little to help us out “””””
Several questions come to mind.
1/ Are you suggesting that the “big jump early in the month” was a fiction and did not really happen ? IF that “big jump early in the month” really happened then of course the “number” would NOT “have been much lower” ; it would have been exactly what it was. If so why did you even mention it ?
2/ so “all” the evidence “”””” is pointing towards GHGs working as tiny little thermostats “””””.
What evidence is that since you cite none. I don’t disagree that “albedo changes” can affect Temperatures; but to the extent that such albedo changes might be cloud and by inference water related; there is also a direct absorption of solar spectrum energy, that permanently reduces the total solar energy captured by earth. That might affect Temperatures also.
If your data disagrees with Dr Spencer’s, then let’s see it; otherwise, why wouldn’t we accept what Roy said it was ?
“It is not a random shape.”
Is too. Minimally acceptable asymptotic analysis requires at least a passing glance towards the grouping of terms and the type of expansion.
“”””” braddles says:
March 2, 2012 at 1:20 pm
The funniest thing about that 3rd-order polynomial fit is that historically, by chance, it does have predictive power. “””””
Well of course it does; if you run the time clock backwards from today, the cubic does a fairly good job of predicting the past events.
To those expecting a rebound into El Nino territory: That was what the models were predicting at this time last spring, but it didn’t happen. Then, last fall, some of the same models were predicting this La Nina would plunge to record levels, but that didn’t happen either. I tend to look at the Enso models “for entertainment purposes only,” and to feel they “should not be construed as having any predictive value whatsoever.”
For example, click onto the “ENSO/SST Page” tab at the right hand side of this site, and scroll down to the second graph, “CFS forecast Nino3.4 Forecast anomalies.” Compare the most recent model runs (blue lines) with the earliest model runs (red lines). The blue lines suggest that, after flirting with neutral, we sink back to the third dip of a triple dip La Nina. However the red lines suggest we warm up into El Nino territory. (This is in the graph updated Sat Mar 3 2012, involving “intial conditions: 21Feb2012 — 1Mar2012.”)
In other words, there is such variety in the model runs you can pretty much pick and chose one you prefer, if you squint hard enough into the spaghetti.
Then check back in a couple days. There will be a whole new batch of model runs to be dumbfounded by.
I’m adopting a wait-and-see policy. Triple-dip La Ninas are not that common, but I can spot at least three, looking back to 1950. The 1954-1957 one interests me, as that was at the start of a cool PDO cycle, I think. However the sun wasn’t as “quiet.”
In the end all I’m sure of is that an El Nino will warm things up, and a La Nina will cool things down. And I’m not 100% sure of even that!
Dinostratus says:
Is too.
Nope.
Minimally acceptable asymptotic analysis requires at least a passing glance towards the grouping of terms and the type of expansion.
Isn’t that, either. It is a perfectly acceptable third order polynomial trend line, fit to the subject data. You like even numbers? Use a fourth order. The shape and fit are the same.
As is the entertainment value, which is the designated purpose to which that curve is directed. Both third and fourth order polynomial fits cause guys like you to screw yourself into the ground, with little smoke plumes curly cuing from your ears. Then there’s the back flips you perform when you sooooooo desperately want to use a first order polynomial trend line, over your own goofily stated objections. Of course your desire for those is presently waning, as statistically significant timeframes are pointing those toward the state where – how did you put that again? Oh yeah – “…in the future the zeroth law of thermodynamics will be violated and we will have a negative absolute temperature.”
Who needs HD with 5 channel sound, when that is on tap?
George E. Smith; says:
March 3, 2012 at 10:11 am
Several questions come to mind.
1/ Are you suggesting that the “big jump early in the month” was a fiction and did not really happen ? IF that “big jump early in the month” really happened then of course the “number” would NOT “have been much lower” ; it would have been exactly what it was. If so why did you even mention it ?
2/ so “all” the evidence “”””” is pointing towards GHGs working as tiny little thermostats “””””.
What evidence is that since you cite none. I don’t disagree that “albedo changes” can affect Temperatures; but to the extent that such albedo changes might be cloud and by inference water related; there is also a direct absorption of solar spectrum energy, that permanently reduces the total solar energy captured by earth. That might affect Temperatures also.
If your data disagrees with Dr Spencer’s, then let’s see it; otherwise, why wouldn’t we accept what Roy said it was ?
1) No, I’m not saying it was a fiction. I’m saying the warming bump may have been due to a low probability event. Because of the timing of that event it hides the fact that February would have been cooler than what we ended up seeing. Electroscavening supposedly works to reduce cloud formation. Without the clouds the temperature increases until the effect wears off.
2) The evidence I’m looking at is the ERBE data shown in David Evans article last week. It supports a view of GHGs having two effects. The first is the GHE. The second gets no mention at all from the warmists. The GHGs radiate most of the energy the Earth receives back to space. If you add more GHGs to the atmosphere there are more parallel paths for that energy to take. The result is that GHGs may provide a cooling effect in addition to the GHE. The balance of these two effects may work like a thermostat. At low concentrations of GHGs the GHE dominates. As more GHGs enters the atmosphere the GHE starts to saturate and effect of the added radiation paths may just cancel out the warming at some point. If we’ve reached that point, I would expect to see a pattern in the ERBE data exactly as David Evans showed.
The data will need to be adjusted “faster than expected”.
“It is a perfectly acceptable third order polynomial trend line, fit to the subject data…..
You like even numbers? Use a fourth order……”
Again, the choice is arbitrary. Why throw an arbitrarily chosen shape across the data? Let the data stand by itself. It’s power is lessened by superimposing a shape that is for “entertainment value”.
Joshua, I would also direct you to http://discover.itsc.uah.edu/amsutemps/
Choose 14000 feet AQUA Ch 5 since this is the primary source of Lower Tropospheric temperature used for UAH.
It will give you an opportunity to compare the current collection data source by day since the current source started in 2002. Warning, although the label says 14000 feet, this channel is mislabeled. It is influenced by temperatures from other heights — including the stratospere. UAH uses a procedure to remove the influences of other heights before releasing its monthly estimate.
Dinostratus says:
Again, the choice is arbitrary.
Pay attention. The choice between a third order polynomial trend fit to these data (which you objected to) and a fourth oder polynomial fit to these data (which you suggested) is not arbitrary. It is irrelevant. They both produce the same shape, with the same fit statistics. You were all up on even order polynomial fits, when you very mistakenly thought that they would show something different – something more to your preconceived liking. Now you run away.
Why throw an arbitrarily chosen shape across the data? Let the data stand by itself.
If that is a genuine question, you will find a perfectly good answer in any high school mathematics program. Perhaps you should take one.
If that is a rhetorical question, then please, do publish your finding that the practice of fitting trend lines to data is wrong. It would seem that a Nobel prize awaits your revolutionary finding, Dr. Dino. Gvient the way the Nobel comittee hands those things out these days, you’re probably a shoe in.
It’s power is lessened by superimposing a shape that is for “entertainment value”.
He says, in glaring proof to the contrary. That simple trend line is the gift that keeps on giving.
A El Nino can only get so warm and so frequent enough to peak global temperatures. After that the only way is back down towards a less intense period or a period of negative PDO with more La Nina’s than El Nino’s. The previous decade will likely be the peak one until at least mid-century. Should be around May when global temperatures start responding from very recent changes in ENSO conditions towards neutral.
“The choice between a third order polynomial trend fit to these data (which you objected to) and a fourth oder polynomial fit to these data (which you suggested) is not arbitrary. It is irrelevant. They both produce the same shape, with the same fit statistics. You were all up on even order polynomial fits, when you very mistakenly thought that they would show something different – something more to your preconceived liking. Now you run away.”
No, a fourth order polynomial and a third order are not the same shape. That is a silly assertion.
However, you inadvertently make a good point, “something more to your preconceived liking”, is the reason why throwing a third order polynomial across the data is a bad idea. The third order polynomial is to Dr. Scencer’s liking and showing a liking across good hard data lessens the impact of the data. It is better for the data for it to stand alone. Embellishments distract from its truth..
Dinostratus says:
No, a fourth order polynomial and a third order are not the same shape. That is a silly assertion.
It is not a silly assertion. It is the simple truth. Fitted thru the UAH dataset, a third order polynomial trend line and a fourth order polynomial trend line are indistinguishable. You’ve been talking out of the wrong orifice since you started.
However, you inadvertently make a good point, “something more to your preconceived liking”, is the reason why throwing a third order polynomial across the data is a bad idea.
Yes, it is your desire to see a specific outcome “implied” that is the sole source of your objection. That is why you only object to a trend line fitted to these data and not all data, why you initially objected to a third order polynomial trend line while suggesting others, and why you run from those suggestions when they turn out to not behave they way you thought they would.
On the other hand, there are objective reasons why, of the readily available choices, a third order polynomial trend line is the best pick for these data, for purposes yet more rigorous than the stated entertainment value. And it is entertaining, watching the data bounce along a progression of very similar and better fitting third order polynomial curves month after month.
The third order polynomial is to Dr. Scencer’s liking and showing a liking across good hard data lessens the impact of the data.
Showing a trendline fitted to data does not lessen the impact of the data. That is why the whole wide world, not just Roy Spencer, uses trendlines in presentation of timeline data. Given that you think trendlines are an illegitimate distraction, why dont you take your one man crusade to rid the world of trendlines on the road? Once again, every field that trades on numeric data uses trend lines fitted to the data. You’ll make quite a name for yourself if you demonstrate that this practice is an incorrect “embellishment”.
“That is why the whole wide world, not just Roy Spencer, uses trendlines in presentation of timeline data.”
Congratulations on knowing all that is in the whole wide world but you must have skipped at least a part of it. Observing my small part of the whole wide world, I can say if someone put up a polynomial fit to data and said it was for entertainment value, they would be thrown out of the room. Now my small part of the whole wide world may be populated with black swans but if a physical reason for a third order fit is not given, the researcher would be told to get his GD fit line out of the way so the serious people could pay attention to the data without any distractions. The data is entrainment enough.