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).
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.