By Dr. Roy Spencer
(See the graph an summary comparison below to RSS. – Anthony)
Our Version 5.5 global average lower tropospheric temperature (LT) anomaly for October, 2012 is +0.33 deg. C (click for large version):
The hemispheric and tropical LT anomalies from the 30-year (1981-2010) average for 2012 are:
YR MON GLOBAL NH SH TROPICS
2012 1 -0.134 -0.065 -0.203 -0.256
2012 2 -0.135 +0.018 -0.289 -0.320
2012 3 +0.051 +0.119 -0.017 -0.238
2012 4 +0.232 +0.351 +0.114 -0.242
2012 5 +0.179 +0.337 +0.021 -0.098
2012 6 +0.235 +0.370 +0.101 -0.019
2012 7 +0.130 +0.256 +0.003 +0.142
2012 8 +0.208 +0.214 +0.202 +0.062
2012 9 +0.339 +0.350 +0.327 +0.153
2012 10 +0.331 +0.302 +0.361 +0.106
Differences with RSS over the Last 2 Years
Many people don’t realize that the LT product produced by Carl Mears and Frank Wentz at Remote Sensing Systems has anomalies computed from a different base period for the average annual cycle (1978-1998) than we use (1981-2010). They should not be compared unless they are computed about the same annual cycle.
If the anomalies for both datasets are computed using the same base period (1981-2010), the comparison between UAH and RSS over the last couple of years looks like this:
Note that the UAH anomalies have been running, on average, a little warmer than the RSS anomalies for the last couple of years.
Source: UAH v5.5 Global Temp Update for October 2012: +0.33 deg. C
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UAH wrong again. It has been cooling significantly. I wonder why you are not picking
it up? errors….first… look at calibration/reference?
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
“Note that the UAH anomalies have been running, on average, a little warmer than the RSS anomalies for the last couple of years.”
Does that make them “deniers” now? Don’t tell M. Mann.
I have to ask: where is the “for entertainment purposes only” curve courtesy of Excel!!! Yes, I miss it!
Bring back the entertainment!
I would like to see a Fourier analysis of the UAH raw data specifically to try to identify the high-frequency components (period <10 years). My experienced eye says that there is a component or two in there with a pseudo-periodicity of several months and amplitudes ~0.1 degree.
2012 in Perspective so far on Six Data Sets
Note the bolded numbers for each data set where the lower bolded number is the highest anomaly recorded so far in 2012 and the higher one is the all time record so far. There is no comparison.
With the UAH anomaly for October at 0.33, the average for the first ten months of the year is (-0.13 -0.13 + 0.05 + 0.23 + 0.18 + 0.24 + 0.13 + 0.20 + 0.34 + 0.33)/10 = 0.144. If the average stayed this way for the rest of the year, its ranking would be 9th. 1998 was the warmest at 0.42. The highest ever monthly anomaly was in April of 1998 when it reached 0.66. With the adjustments, the 2010 value is 0.026 lower than 1998 instead of 0.014 as was the case before.
With the GISS anomaly for September at 0.60, the average for the first nine months of the year is (0.32 + 0.36 + 0.45 + 0.55 + 0.67 + 0.55 + 0.46 + 0.57 + 0.60)/9 = 0.503. This would rank 10th if it stayed this way. 2010 was the warmest at 0.63. The highest ever monthly anomalies were in March of 2002 and January of 2007 when it reached 0.88.
With the Hadcrut3 anomaly for September at 0.520, the average for the first nine months of the year is (0.217 + 0.194 + 0.305 + 0.481 + 0.475 + 0.477 + 0.446 + 0.512+ 0.520 )/9 = 0.403. This would rank 10th if it stayed this way. 1998 was the warmest at 0.548. The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less.
With the sea surface anomaly for September at 0.453, the average for the first nine months of the year is (0.203 + 0.230 + 0.241 + 0.292 + 0.339 + 0.352 + 0.385 + 0.440 + 0.453)/9 = 0.326. This would rank 10th if it stayed this way. 1998 was the warmest at 0.451. The highest ever monthly anomaly was in August of 1998 when it reached 0.555.
With the RSS anomaly for October at 0.294, the average for the first ten months of the year is (-0.059 -0.122 + 0.072 + 0.331 + 0.232 + 0.338 + 0.291 + 0.255 + 0.383 + 0.294)/10 = 0.202. If the average stayed this way for the rest of the year, its ranking would be 11th. 1998 was the warmest at 0.55. The highest ever monthly anomaly was in April of 1998 when it reached 0.857.
With the Hadcrut4 anomaly for September at 0.524, the average for the first nine months of the year is (0.288 + 0.209 + 0.339 + 0.514 + 0.516 + 0.501 + 0.469 + 0.529 + 0.524)/9 = 0.432. If the average stayed this way for the rest of the year, its ranking would be virtually tied for 10th. 2010 was the warmest at 0.54. The highest ever monthly anomaly was in January of 2007 when it reached 0.818. The 2011 anomaly at 0.399 puts 2011 in 12th place and the 2008 anomaly of 0.383 puts 2008 in 14th place.
On all six of the above data sets, a record is out of reach.
On all data sets, the different times for a slope that is at least very slightly negative ranges from 11 years and 3 months to 15 years and 10 months.
1. UAH: The new update is not on woodfortrees yet, but according to Walter Dnes, it is since July 2001 to September 2012, which would be 11 years and 3 months.
2. GISS: since January 2001 or 11 years, 9 months (goes to September)
3. Combination of 4 global temperatures: since November 2000 or 11 years, 10 months (goes to August)
4. HadCrut3: since April 1997 or 15 years, 6 months (goes to September)
5. Sea surface temperatures: since February 1997 or 15 years, 8 months (goes to September)
6. RSS: since January 1997 or 15 years, 10 months (goes to October)
RSS is 190/204 or 93.1% of the way to Santer’s 17 years.
7. Hadcrut4: since December 2000 or 11 years, 10 months (goes to September.)
See the graph below to show it all.
http://www.woodfortrees.org/plot/hadcrut3gl/from:1997.25/trend/plot/gistemp/from:2001.0/trend/plot/rss/from:1997.0/trend/plot/wti/from:2000.8/trend/plot/hadsst2gl/from:1997.08/trend/plot/hadcrut4gl/from:2000.9/trend
Yesterday, I posted the full sea surface temperature update for October 2012:
http://bobtisdale.wordpress.com/2012/11/05/october-2012-sea-surface-temperature-sst-anomaly-update/
Regards
BBC Worldl Service with Justin Rowlatt last night – listen to first minute for introduction. program will be about (POLITICAL BUZZWORD “TRANSFORMATIVE”? CAGW COWBOYS NEED INCENTIVES?) :
“the transformative power of incentives, how legalising bribery is the best way to tackle corruption”
“plus we will be discovering why america can expect more natural disasters, there is a storm coming”
BBC Business Daily: The power of incentives
Availability:over a year left to play
It is extraordinary what you can achieve if the incentives are right. People will – for example – do a surprising amount just for a free cup of tea. Take bribery – it is usually assumed that once a culture of bribery has taken root it is almost impossible to erradicate. Not so, says our regular commentator Stever Fritzinger. It is – he says – all a question of incentives…
Plus we speak to a reinsurance giant which is predicting more storms for America
http://www.bbc.co.uk/programmes/p0104hwl
so Reinsurers are able to predict exceptional weather, just for the US.
Thank you.
http://www.volker-doormann.org/images/uah_rss_ghi11_r_oct.gif
Fits well.
V.
The “entertainment” curve: That curve is/was not even entertaining. It was meaningless, use a different order polynomial on the same data and you end up with a very different impression. Best not to use it because it is robs the data of its real significance. People won’t look beyond that curve. Some will take it at face value. Others, knowing what is going on, will see it as an attempt to deceive and thus completely devaluing the content.
An Off Topic side note if I may, here in the USA it’s election day. If you vote on an electonic touch screen like I did, a little window in the lower left will scroll your votes on paper as you make them. (I assume in case a recount is needed.) Check the scroll to be sure your vote was recorded correctly. If not, call a poll worker right away.
No increase even with all the adjustments?
From Philip Peake on November 6, 2012 at 2:00 pm:
Would it have hurt you to actually read the post and notice the 4th-order polynomial fit wasn’t there before launching into the pontification about its inherent evilness?
Philip Peake says:
The “entertainment” curve: That curve is/was not even entertaining. It was meaningless, use a different order polynomial on the same data and you end up with a very different impression. Best not to use it because it is robs the data of its real significance.
Nonsense. Fitting trends to data is a basic statistical technique. It has meaning, and can reveal the significance of the data. That is why it is done. Everywhere. People only complained about it when Roy did it, because the results didn’t confirm their bias. The same people love throwing a linear trend on the same data, because it does confirm their bias. That’s how bias works.
Volker Doormann says:
http://www.volker-doormann.org/images/uah_rss_ghi11_r_oct.gif
Do you have an explanation of that ghi thing in English ? Looks interesting
I’m sorry about that. I’ve been trying to breathe out as much CO2 as I can, but it clearly wasn’t enough. I’ll have to get a cat to help me.
I actually agree with Philip.
ALL trend lines should be left off these graphs.
ANY trend like is based on assumption, and is meaningless unless those assumptions can be proven.
The only trends that might apply are cyclical ones, but we don’t know enough about them yet either.
As for linear trends in climate……. roflmao !!!
If people want to use them, they should state “short term linear trend with zero predictive value”
like Poy use to do with his polynomial curve.
like ROY used to do with his polynomial curve … typo.. doh !!
We need to send the process and control engineers into space to develop these satellites in orbit, it would be less expensive than trial and error. lol
Reblogged this on The GOLDEN RULE and commented:
Still a flat trend since 1998 – no correlation to increasing CO2!
Where does the “0” line come from?
A “Little” warmer than RSS? It affects the entire trend.
[i] P. Solar says:November 6, 2012 at 3:46 pm
Volker Doormann says:
http://www.volker-doormann.org/images/uah_rss_ghi11_r_oct.gif
Do you have an explanation of that ghi thing in English ? Looks interesting [/i]
I have written some basic explanations about the GHI (Geometric Harmonic Index) on a page on Tallbloke’s Talkshop:
http://tallbloke.wordpress.com/2012/08/28/volker-doormann-graph-links-and/#comment-32220
a page asking ‘Is the cliamate code solved?’
http://www.volker-doormann.org/climate_code_s.htm
and a paper ‘SOLAR SYSTEM GEOMETRIES AND TERRESTRIAL CLIMATE’ from August 2010:
http://www.volker-doormann.org/ghi_solar_s.pdf
I think it is the most meaning discovery in astronomy since J. Kepler’s discovery of the third law.
http://www.volker-doormann.org/images/ghi_had_1960_3.gif
http://www.volker-doormann.org/images/ghi_6_lockwood_1.gif
However. It is not in common with the geocentric climate worldview and therefore an anathema and banished.from the authorities.
V.
A nice steadily warming channel with noise. No sign of any cooling whatsoever.
It’s worth remembering when making comparisons with RSS that UAH go down to 85S, whereas RSS only go to 70S.
As the Antarctic seems to have been on a cooilng trend in recent years, this should mean that RSS shows more warming than UAH. However the reverse seems to be the case.