Has Global Warming Stalled?

Guest Post By Werner Brozek, Edited By Just The Facts

In order to answer the question in the title, we need to know what time period is a reasonable period to take into consideration. As well, we need to know exactly what we mean by “stalled”. For example, do we mean that the slope of the temperature-time graph must be 0 in order to be able to claim that global warming has stalled? Or do we mean that we have to be at least 95% certain that there indeed has been warming over a given period?

With regards to what a suitable time period is, NOAA says the following:

”The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.”

To verify this for yourself, see page 23 of this NOAA Climate Assessment.

Below we present you with just the facts and then you can assess whether or not global warming has stalled in a significant manner. The information will be presented in three sections and an appendix. The first section will show for how long there has been no warming on several data sets. The second section will show for how long there has been no significant warming on several data sets. The third section will show how 2012 ended up in comparison to other years. The appendix will illustrate sections 1 and 2 in a different way. Graphs and tables will be used to illustrate the data.

Section 1

This analysis uses the latest month for which data is available on WoodForTrees.org (WFT). (If any data is updated after this report is sent off, I will do so in the comments for this post.) All of the data on WFT is also available at the specific sources as outlined below. We start with the present date and go to the furthest month in the past where the slope is a least slightly negative. So if the slope from September is 4 x 10^-4 but it is – 4 x 10^-4 from October, we give the time from October so no one can accuse us of being less than honest if we say the slope is flat from a certain month.

On all data sets below, the different times for a slope that is at least very slightly negative ranges from 8 years and 3 months to 16 years and 1 month:

1. For GISS, the slope is flat since May 2001 or 11 years, 7 months. (goes to November)

2. For Hadcrut3, the slope is flat since May 1997 or 15 years, 7 months. (goes to November)

3. For a combination of GISS, Hadcrut3, UAH and RSS, the slope is flat since December 2000 or an even 12 years. (goes to November)

4. For Hadcrut4, the slope is flat since November 2000 or 12 years, 2 months. (goes to December.)

5. For Hadsst2, the slope is flat since March 1997 or 15 years, 10 months. (goes to December)

6. For UAH, the slope is flat since October 2004 or 8 years, 3 months. (goes to December)

7. For RSS, the slope is flat since January 1997 or 16 years and 1 month. (goes to January) RSS is 193/204 or 94.6% of the way to Ben Santer’s 17 years.

The following graph, also used as the header for this article, shows just the lines to illustrate the above. Think of it as a sideways bar graph where the lengths of the lines indicate the relative times where the slope is 0. In addition, the sloped wiggly line shows how CO2 has increased over this period:

The next graph shows the above, but this time, the actual plotted points are shown along with the slope lines and the CO2 is omitted:

WoodForTrees.org – Paul Clark – Click the pic to view at source

Section 2

For this analysis, data was retrieved from WoodForTrees.org and the ironically named SkepticalScience.com. This analysis indicates how long there has not been significant warming at the 95% level on various data sets. The first number in each case was sourced from WFT. However the second +/- number was taken from SkepticalScience.com

For RSS the warming is not significant for over 23 years.

For RSS: +0.127 +/-0.136 C/decade at the two sigma level from 1990

For UAH, the warming is not significant for over 19 years.

For UAH: 0.143 +/- 0.173 C/decade at the two sigma level from 1994

For Hacrut3, the warming is not significant for over 19 years.

For Hadcrut3: 0.098 +/- 0.113 C/decade at the two sigma level from 1994

For Hacrut4, the warming is not significant for over 18 years.

For Hadcrut4: 0.095 +/- 0.111 C/decade at the two sigma level from 1995

For GISS, the warming is not significant for over 17 years.

For GISS: 0.116 +/- 0.122 C/decade at the two sigma level from 1996

If you want to know the times to the nearest month that the warming is not significant for each set, they are as follows: RSS since September 1989; UAH since April 1993; Hadcrut3 since September 1993; Hadcrut4 since August 1994; GISS since October 1995 and NOAA since June 1994.

Section 3

This section shows data about 2012 in the form of tables. Each table shows the six data sources along the left, namely UAH, RSS, Hadcrut4, Hadcrut3, Hadsst2, and GISS. Along the top, are the following:

1. 2012. Below this, I indicate the present rank for 2012 on each data set.

2. Anom 1. Here I give the average anomaly for 2012.

3. Warm. This indicates the warmest year on record so far for that particular data set. Note that two of the data sets have 2010 as the warmest year and four have 1998 as the warmest year.

4. Anom 2. This is the average anomaly of the warmest year just to its left.

5. Month. This is the month where that particular data set showed the highest anomaly. The months are identified by the first two letters of the month and the last two numbers of the year.

6. Anom 3. This is the anomaly of the month immediately to the left.

7. 11ano. This is the average anomaly for the year 2011. (GISS and UAH were 10th warmest in 2011. All others were 13th warmest for 2011.)

Anomalies for different years:

Source 2012 anom warm anom month anom 11ano
UAH 9th 0.161 1998 0.419 Ap98 0.66 0.130
RSS 11th 0.192 1998 0.55 Ap98 0.857 0.147
Had4 10th 0.436 2010 0.54 Ja07 0.818 0.399
Had3 10th 0.403 1998 0.548 Fe98 0.756 0.340
sst2 8th 0.342 1998 0.451 Au98 0.555 0.273
GISS 9th 0.56 2010 0.66 Ja07 0.93 0.54

If you wish to verify all rankings, go to the following:

For UAH, see here, for RSS see here and for Hadcrut4, see here. Note the number opposite the 2012 at the bottom. Then going up to 1998, you will find that there are 9 numbers above this number. That confirms that 2012 is in 10th place. (By the way, 2001 came in at 0.433 or only 0.001 less than 0.434 for 2012, so statistically, you could say these two years are tied.)

For Hadcrut3, see here. You have to do something similar to Hadcrut4, but look at the numbers at the far right. One has to back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less.

For Hadsst2, see here. View as for Hadcrut3. It came in 8th place with an average anomaly of 0.342, narrowly beating 2006 by 2/1000 of a degree as that came in at 0.340. In my ranking, I did not consider error bars, however 2006 and 2012 would statistically be a tie for all intents and purposes.

For GISS, see here. Check the J-D (January to December) average and then check to see how often that number is exceeded back to 1998.

For the next two tables, we again have the same six data sets, but this time the anomaly for each month is shown. [The table is split in half to fit, if you know how to compress it to fit the year, please let us know in comments The last column has the average of all points to the left.]

Source Jan Feb Mar Apr May Jun
UAH -0.134 -0.135 0.051 0.232 0.179 0.235
RSS -0.060 -0.123 0.071 0.330 0.231 0.337
Had4 0.288 0.208 0.339 0.525 0.531 0.506
Had3 0.206 0.186 0.290 0.499 0.483 0.482
sst2 0.203 0.230 0.241 0.292 0.339 0.352
GISS 0.36 0.39 0.49 0.60 0.70 0.59
Source Jul Aug Sep Oct Nov Dec Avg
UAH 0.130 0.208 0.339 0.333 0.282 0.202 0.161
RSS 0.290 0.254 0.383 0.294 0.195 0.101 0.192
Had4 0.470 0.532 0.515 0.527 0.518 0.269 0.434
Had3 0.445 0.513 0.514 0.499 0.482 0.233 0.403
sst2 0.385 0.440 0.449 0.432 0.399 0.342 0.342
GISS 0.51 0.57 0.66 0.70 0.68 0.44 0.56

To see the above in the form of a graph, see the WFT graph below.:

Appendix

In this part, we are summarizing data for each set separately.

RSS

The slope is flat since January 1997 or 16 years and 1 month. (goes to January) RSS is 193/204 or 94.6% of the way to Ben Santer’s 17 years.

For RSS the warming is not significant for over 23 years.

For RSS: +0.127 +/-0.136 C/decade at the two sigma level from 1990.

For RSS, the average anomaly for 2012 is 0.192. This would rank 11th. 1998 was the warmest at 0.55. The highest ever monthly anomaly was in April of 1998 when it reached 0.857. The anomaly in 2011 was 0.147 and it will come in 13th.

Following are two graphs via WFT. Both show all plotted points for RSS since 1990. Then two lines are shown on the first graph. The first upward sloping line is the line from where warming is not significant at the 95% confidence level. The second straight line shows the point from where the slope is flat.

The second graph shows the above, but in addition, there are two extra lines. These show the upper and lower lines for the 95% confidence limits. Note that the lower line is almost horizontal but slopes slightly downward. This indicates that there is a slightly larger than a 5% chance that cooling has occurred since 1990 according to RSS per graph 1 and graph 2.

UAH

The slope is flat since October 2004 or 8 years, 3 months. (goes to December)

For UAH, the warming is not significant for over 19 years.

For UAH: 0.143 +/- 0.173 C/decade at the two sigma level from 1994

For UAH the average anomaly for 2012 is 0.161. This would rank 9th. 1998 was the warmest at 0.419. The highest ever monthly anomaly was in April of 1998 when it reached 0.66. The anomaly in 2011 was 0.130 and it will come in 10th.

Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to UAH. Graph 1 and graph 2.

Hadcrut4

The slope is flat since November 2000 or 12 years, 2 months. (goes to December.)

For Hacrut4, the warming is not significant for over 18 years.

For Hadcrut4: 0.095 +/- 0.111 C/decade at the two sigma level from 1995

With Hadcrut4, the anomaly for 2012 is 0.436. This would rank 10th. 2010 was the warmest at 0.54. The highest ever monthly anomaly was in January of 2007 when it reached 0.818. The anomaly in 2011 was 0.399 and it will come in 13th.

Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut4. Graph 1 and graph 2.

Hadcrut3

The slope is flat since May 1997 or 15 years, 7 months (goes to November)

For Hacrut3, the warming is not significant for over 19 years.

For Hadcrut3: 0.098 +/- 0.113 C/decade at the two sigma level from 1994

With Hadcrut3, the anomaly for 2012 is 0.403. This would rank 10th. 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. The anomaly in 2011 was 0.340 and it will come in 13th.

Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut3. Graph 1 and graph 2.

Hadsst2

The slope is flat since March 1997 or 15 years, 10 months. (goes to December)

The Hadsst2 anomaly for 2012 is 0.342. This would rank in 8th. 1998 was the warmest at 0.451. The highest ever monthly anomaly was in August of 1998 when it reached 0.555. The anomaly in 2011 was 0.273 and it will come in 13th.

Sorry! The only graph available for Hadsst2 is this.

GISS

The slope is flat since May 2001 or 11 years, 7 months. (goes to November)

For GISS, the warming is not significant for over 17 years.

For GISS: 0.116 +/- 0.122 C/decade at the two sigma level from 1996

The GISS anomaly for 2012 is 0.56. This would rank 9th. 2010 was the warmest at 0.66. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2011 was 0.54 and it will come in 10th.

Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to GISS. Graph 1 and graph 2.

Conclusion

Above, various facts have been presented along with sources from where all facts were obtained. Keep in mind that no one is entitled to their own facts. It is only in the interpretation of the facts for which legitimate discussions can take place. After looking at the above facts, do you think that we should spend billions to prevent catastrophic warming? Or do you think that we should take a “wait and see” attitude for a few years to be sure that future warming will be as catastrophic as some claim it will be? Keep in mind that even the MET office felt the need to revise its forecasts. Look at the following and keep in mind that the MET office believes that the 1998 mark will be beaten by 2017. Do you agree?

WoodForTrees.org – Paul Clark – Click the pic to view at source
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185 Comments
Philip Shehan
February 15, 2013 5:07 pm

PPS Very peripherally involved. Not taking any credit.

Philip Shehan
February 15, 2013 5:24 pm

Gawd it was a heavy night. It’s only Saturday. On to my second coffee.

D.B. Stealey
February 15, 2013 6:30 pm

Graham W says:
“So climate sensitivity to CO2 must be at the lower end of the spectrum. Exactly how low is hard to say…”
Sensitivity to CO2 is very low — really, it is non-existent for all practical purposes at current CO2 concentrations.
The reason for this is clear: At current concentrations, adding more CO2 makes no measurable difference. That is why the UN/IPCC’s predictions are so wildly off-base.

February 15, 2013 11:13 pm

Henry
depending on what you want to do research on, your sampling technique is very important. First and foremost, it has to be random. In the case of global temperature: I have explained things here.
http://wattsupwiththat.com/2013/02/10/has-global-warming-stalled/#comment-1223942
Each place on earth is on its own sine wave of temp. change with wavelength of ca. 88 years, but height of temp. change being dependent on the ozone & others above.
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/

CoRev
February 16, 2013 6:58 am

Philip Shehan, what a mess you wrote. 😉 You start off with: “Corey. I am not defelecting from the data, I am subjecting it to statistical analysis. ” and follow with an appeal to your own authority on the subject, the, you go completely off the rails. This was I hope a typo? “You have to look at 30 decades to come up with a sufficiaently small error range to decide whether temperatures are rising or falling with atrend that can be considered as having some accuracy.” If not, if you actually believe this, then your whole position re: GW validity is undermined.
Anyway, I hope your day is going better now.

D.B. Stealey
February 16, 2013 2:56 pm

Yes, global warming has stalled. The facts are clear. It may resume, or not, or global cooling may follow. Whatever happens, most of us will follow the empirical evidence, rather than engaging in wishful thinking.
Dr Irving Langmuir explained scientific wishful thinking in a series of lectures titled Pathological Science. Dr Langmuir would use the term today to describe the belief in AGW. Langmuir explained the symptoms:

Characteristic Symptoms of Pathological Science
The characteristics of this Davis-Barnes experiment and the N-rays and the mitogenetic rays have things in common. These are cases where there is no dishonesty involved but where people are tricked into false results by a lack of understanding about what human beings can do to themselves in the way of being led astray by subjective effects, wishful thinking or threshold interactions. These are examples of pathological science. These are things that attracted a great deal of attention. Usually hundreds of papers have been published upon them. Sometimes they have lasted for fifteen or twenty years and then they gradually die away.
Now, the characteristic rules are these (see Table I}
TABLE I
Symptoms of Pathological Science:
The maximum effect that is observed is produced by a causative agent of barely detectable intensity [think: AGW], and the magnitude of the effect is substantially independent of the intensity of the cause.
The effect is of a magnitude that remains close to the limit of detectability; or, many measurements are necessary because of the very low statistical significance of the results.
Claims of great accuracy.
Fantastic theories contrary to experience.
Criticisms are met by ad hoc excuses thought up on the spur of the moment.
Ratio of supporters to critics rises up to somewhere near 50% and then falls gradually to oblivion.
The maximum effect that is observed is produced by a causative agent of barely detectable intensity. For example, you might think that if one onion root would affect another due to ultraviolet light, you’d think that by putting on an ultraviolet source of light you could get it to work better. Oh no! OH NO! It had to be just the amount of intensity that’s given off by an onion root. Ten onion roots wouldn’t do any better than one and it doesn’t make any difference about the distance of the source. It doesn’t follow any inverse square law or anything as simple as that, and so on. In other words, the effect is independent of the intensity of the cause. That was true in the mitogenetic rays, and it was true in the N-rays. Ten bricks didn’t have any more effect than one. It had to be of low intensity. We know why it had to be of low intensity: so that you could fool yourself so easily. Otherwise, it wouldn’t work. Davis-Barnes worked just as well when the filament was turned off. They counted scintillations.
Another characteristic thing about them all is that, these observations are near the threshold of visibility of the eyes. Any other sense, I suppose, would work as well. Or many measurements are necessary, many measurements because of very low statistical significance of the results.
In the mitogenetic rays particularly it started out by seeing something that was bent. Later on, they would take a hundred onion roots and expose them to something and they would get the average position of all of them to see whether the average had been affected a little bit by an appreciable amount. Or statistical measurements of a very small effect which by taking large numbers were thought to be significant. Now the trouble with that is this. There is a habit with most people, that when measurements of low signifcance are taken they find means of rejecting data. They are right at the threshold value and there are many reasons why you can discard data. Davis and Barnes were doing that right along. If things were doubtful at all why they would discard them or not discard them depending on whether or not they fit the theory. They didn’t know that, but that’s the way it worked out.
There are claims of great accuracy. Barnes was going to get the Rydberg constant more accurately than the spectroscopists could. Great sensitivity or great specificity, we’ll come across that particularly in the Allison effect.
Fantastic theories contrary to experience. In the Bohr theory, the whole idea of an electron being captured by an alpha particle when the alpha particles aren’t there just because the waves are there doesn’t make a very sensible theory.
Criticisms are met by ad hoc excuses thought up on the spur of the moment. They always had an answer — always.
The ratio of the supporters to the critics rises up somewhere near 50% and then falls gradually to oblivion. The critics can’t reproduce the effects. Only the supporters could do that. In the end, nothing was salvaged. Why should there be? There isn’t anything there. There never was. That’s (p.7) characteristic of the effect. Well, I’ll go quickly on to some of the other things…[source]

AGW fits this template exactly. There is no measurable, empirical evidence of AGW. It is a conjecture. As atmospheric CO2 continues to rise steadily, the Null Hypothesis remains un-falsified: there are still no measurable effects that can be directly attributed to AGW. That may well be simply because there isn’t anything there.

Werner Brozek
February 16, 2013 8:11 pm

I will do the three tables in a vertical format for next time.
The last article had all the statistics from 2012 so it necessitated 3 tables. However next time, I will just have the January, 2013 data to deal with. As well, with the new vertical format, I will not run out of room at the side, so a single table works very well for now. (I will send it to you as an email with only UAH and RSS updated for January.) I see no reason not to use the single table all year. It will just get longer vertically.
I’ve copied this article in full back to our staging area, an played with the title, which you’ll want to do to avoid the titles getting mixed from an indexing perspective and to keep it fresh.
If we just have the following for next time:
“Has Global Warming Stalled? January Update” and so on, would that be O.K.? I know it is not very creative, but on the other hand, people know what the article is about and every title will be different.
It is your call in terms of timing, but given the positive response that this article has received, I’d be inclined to keep beating the drum until the message is clearly heard. Given that WUWT readership tends to have a reasonable split between weekdays and weekends, you might want to publish the next one midweek so that audience will also get exposed. Also to prevent the article from getting stale, you might want to tweak the intro and conclusion, tie in new findings and occurrences, introduce/test new components/graphs, etc.
I was not aware of the split in readership, but with that being the case, it would be a good idea to change the times from one month to the next so the weekenders get an update every two months, just like the others. Then we can see how the responses are. As far as staleness is concerned, there have been many good responses and comments and questions this time so I will end up tweaking quite a bit for next time automatically.
Let me know a week before you want to publish the article again and I will try to reach out to Paul to see if we can get the data as current as possible.
That would be nice. But if it is not updated, I will use SkS to make the best guess that I can.
Will do, I envisage several of your graphs and summaries being added to the next Big Picture update and, if you are open to it, I’d appreciate your help in reviewing and editing that article when I get around to drafting it.
No problem!

D.B. Stealey
February 16, 2013 8:22 pm

Werner and JTFWUWT,
In line with other WUWT series’ [eg: ‘Sea Ice #4’, etc.], may I suggest the simple and unambiguous: “Has Global Warming Stalled #2”? [Then #3, #4, etc.]
It would make an archive search very easy for our readers.

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