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 there has to be a lack of “significant” 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 here
Below, we will present you with just the facts and then you can decide whether or not global warming has stalled in a statistically significant manner.
The information will be presented in three sections and an appendix. Section 1 will show for how long there has been no warming on several data sets. Section 2 will show for how long there has been no significant warming on several data sets. Section 3 will show how January 2013 compares with 2012 and the warmest years and months on record so far. The Appendix will illustrate Sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.
Section 1
This analysis uses the latest month for which data is available on WoodForTrees.com (WFT). However WFT has not been updated for GISS, Hadcrut3 and WTI past November so I had to use the SkS site for GISS and Hadcrut3. 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 4 years and 7 months to 16 years and 1 month.
1. For GISS, the slope is flat since May 2001 or 11 years, 9 months. (goes to January)
2. For Hadcrut3, the slope is flat since March 1997 or 15 years, 11 months. (goes to January)
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, 3 months. (goes to January)
5. For Hadsst2, the slope is flat since March 1997 or 15 years, 11 months. (goes to January)
6. For UAH, the slope is flat since July 2008 or 4 years, 7 months. (goes to January)
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 next graph 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.
When two things are plotted as I have done, the left only shows a temperature anomaly. It goes from 0.1 to 0.6 C. A change of 0.5 C over 16 years is about 3.0 C over 100 years. And 3.0 C is about the average of what the IPCC says may be the temperature increase by 2100.
So for this to be the case, the slope for all of the data sets would have to be as steep as the CO2 slope. Hopefully the graphs show that this is totally untenable.
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.
Section 2
For this analysis, data was retrieved from SkepticalScience.com. This analysis indicates for how long there has not been significant warming according to their criteria. The numbers below start from January of the year indicated. Data have now been updated either to the end of December 2012 or January 2013. In every case, note that the magnitude of the second number is larger than the first number so a slope of 0 cannot be ruled out. (To the best of my knowledge, SkS uses the same criteria that Phil Jones uses to determine significance.)
For RSS the warming is not significant for over 23 years.
For RSS: +0.127 +/-0.134 C/decade at the two sigma level from 1990
For UAH the warming is not significant for over 19 years.
For UAH: 0.146 +/- 0.170 C/decade at the two sigma level from 1994
For Hadcrut3 the warming is not significant for over 19 years.
For Hadcrut3: 0.095 +/- 0.115 C/decade at the two sigma level from 1994
For Hadcrut4 the warming is not significant for over 18 years.
For Hadcrut4: 0.095 +/- 0.110 C/decade at the two sigma level from 1995
For GISS the warming is not significant for over 17 years.
For GISS: 0.111 +/- 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 June 1993; Hadcrut3 since August 1993; Hadcrut4 since July 1994; GISS since August 1995 and NOAA since June 1994.
Section 3
This section shows data about 2013 and other information in the form of a table. Each table shows the six data sources along the top, namely UAH, RSS, Hadcrut4, Hadcrut3, Hadsst2, and GISS. Down the column, are the following:
1. 2012 rank: This is the final ranking for 2012 on each data set.
2. 2012 anomaly: Here I give the average anomaly for 2012.
3. warmest year: 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. anomaly of above: This is the average of the monthly anomalies of the warmest year just above.
5. warmest 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. anomaly of above: This is the anomaly of the month just above.
7. year/month no warm: This is the longest period of time where the slope is not positive. So 15/11 means that for 15 years and 11 months the slope is 0 or slightly negative.
8. This is the January, 2013, anomaly for that particular data set.
20. This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months. (Of course, for this time, it would simply be the January anomaly.)
21. This is the rank that each particular data set would have if the anomaly above were to remain that way for the rest of the year. Of course it won’t, but think of it as an update 5 minutes into a game. Expect wild swings from month to month at the start of the year. As well, expect huge variations between data sets at the start. For UAH, the 0.506 was ranked first. That is because 0.506 is above the highest yearly average of 0.419 in 1998. It is not the hottest month ever. That happens to be April of 1998 when the anomaly was 0.66.
| Source | UAH | RSS | Had4 | Had3 | HADSST2 | GISS |
|---|---|---|---|---|---|---|
1. 2012 Rank |
9th | 11th | 10th | 10th | 8th | 9th |
| 2. 2012 Anomaly | 0.161 | 0.192 | 0.433 | 0.406 | 0.342 | 0.56 |
| 3. Warmest Year | 1998 | 1998 | 2010 | 1998 | 1998 | 2010 |
| 4. Anomaly Of Above | 0.419 | 0.55 | 0.540 | 0.548 | 0.451 | 0.66 |
| 5. warmest month | Ap98 | Ap98 | Ja07 | Fe98 | Au98 | Ja07 |
| 6. Anomaly Of Above | 0.66 | 0.857 | 0.818 | 0.756 | 0.555 | 0.93 |
| 7. Years / Months With No Warming | 4/7 | 16/1 | 12/3 | 15/11 | 15/11 | 11/9 |
| 8. Jan. 2013 Anomaly | 0.506 | 0.442 | 0.433 | 0.388 | 0.283 | 0.61 |
| 20. 2013 Average So Far | 0.506 | 0.442 | 0.433 | 0.388 | 0.283 | 0.61 |
| 21. 2013 Rank So Far | 1st | 3rd | 10th | 12th | 12th | 4th |
If you wish to verify all 2012 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.
For Hadcrut3, see here. Here you have to do something similar to Hadcrut4, but look at the numbers at the far right. One has to go 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.
To see all points since January 2012 in the form of a graph, see the WFT graph below:
Relative to December, the January anomalies have changed as follows: UAH up 0.30, RSS up 0.34, Hadcrut4 up 0.17, Hadcrut3 up 0.13, Hadsst2 down 0.06, and GISS up 0.17.
Dr. Spencer explains why the satellite anomalies are up but the sea surface anomaly is down here.
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 +/-0.134 C/decade at the two sigma level from 1990.
The RSS average anomaly so far for 2013 is 0.442. This would rank 3rd if it stayed this way. 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 2012 was 0.192 and it came in 11th.
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 according to the SkS site criteria. 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 using the SkS site criteria. Note that the lower line is almost horizontal but slopes slightly downward. This indicates that there is a slight chance that cooling has occurred since 1990 according to RSS per graph 1 and graph 2.
UAH
The slope is flat since July 2008 or 4 years, 7 months. (goes to January)
For UAH, the warming is not significant for over 19 years.
For UAH: 0.146 +/- 0.170 C/decade at the two sigma level from 1994
The UAH average anomaly so far for 2013 is 0.506. This would rank 1st if it stayed this way. 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 2012 was 0.161 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to UAH.
Hadcrut4
The slope is flat since November 2000 or 12 years, 3 months. (goes to January.)
For Hadcrut4, the warming is not significant for over 18 years.
For Hadcrut4: 0.095 +/- 0.110 C/decade at the two sigma level from 1995
The Hadcrut4 average anomaly so far for 2013 is 0.433. This would rank 10th if it stayed this way. 2010 was the warmest at 0.540. The highest ever monthly anomaly was in January of 2007 when it reached 0.818. The anomaly in 2012 was 0.433 and it came in 10th.
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 March 1997 or 15 years, 11 months (goes to January)
For Hadcrut3, the warming is not significant for over 19 years.
For Hadcrut3: 0.095 +/- 0.115 C/decade at the two sigma level from 1994
The Hadcrut3 average anomaly so far for 2013 is 0.388. This would rank 12th 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 go back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2012 was 0.406 and it came in 10th.
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, 11 months. (goes to January)
The Hadsst2 average anomaly so far for 2013 is 0.283. This would rank 12th 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. The anomaly in 2012 was 0.342 and it came in 8th.
Sorry! The only graph available for Hadsst2 is the following this.
GISS
The slope is flat since May 2001 or 11 years, 9 months. (goes to January)
For GISS, the warming is not significant for over 17 years.
For GISS: 0.111 +/- 0.122 C/decade at the two sigma level from 1996
The GISS average anomaly so far for 2013 is 0.61. This would rank 4th if it stayed this way and would tie it with 1998. 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 2012 was 0.56 and it came in 9th.
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 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 feel that we should spend billions to prevent catastrophic warming? Or do you feel 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?
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
We are cooling, folks; for how long even kim doesn’t know.
===============
The problem I have is that this is an adjusted data set and I have no faith in the adjustments. Furthermore, adjustments to many of these data sets seem to be continuously and retroactively so the adjustment of information from the past can change in the future. I have no confidence in the data so whether or not it “breaks” 1998 or not seems rather a silly question. I guess my answer is “yes, if they want it to break 1998, no if they don’t want it to”.
JTF, I just have a concern about the size of the graphs. When you click on them, they are good, but when viewed as they are, they are twice as big as they should be and just the left half appears. This applies to 4 out of the 5. Can this be fixed? Thanks!
I am 100% positive that I remember Gavin stating in a post at Realclimate that if there was no warming for 10 years, that would indicate the models were wrong.
“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?”
No one can tell. It might wiggle a bit upwards again like a rising zig-zag, and yet it might not. If it does wiggle upwards again, it is unlikely to be much of an increase compared to 1998…..but noone knows. And noone can know. Bob Tisdale is the one to ask. He seems to be one of the few that has some understanding on how the small variance’s is induced via ENSO. Because they are small, look at the y-axis.
Excellent work. This piece needs to be kept close to hand for ready accessibility.
Werner, you write “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?”
This is not quite a complete picture of what happened. Using 2004 data Smith et al from the Met. Office, published their decadal forecast in the August 2007 edition of Science. This forecast that, following 2009, half the years would have temperatures in excess of 1998. When this was obviously not happening, the Met. Office quietly altered their forecast; on Christmas Eve 2012. The change was not noted until early in Jan. 2013. We have not yet been given the details of the science behind the new forecast, or the reasons why the Met. Office has abandoned Smith et al.
So I dont think anyone is in a position to answer the questrion as to whether we agree or not. Surely the Met.Office needs to give us the sort of detail that we were given in Smith et al, BEFORE this question can be answered.
I’m not a mathematician but it looks more like a wave than a rise up a hill. The data set does seem too small to make a prediction of any kind though, I don’t know how they’re getting “in-coming heat wave” from that data.
Well, based on the record so far I’d say no.
And here’s something they prepared earlier.
Further reading:
“Met Office Climate Forecasts: Always Wrong But Never In Doubt“
Lol. Maybe time for another derivative, such as “The rate of change of climate-change remains the same”?
The models still have no predictive skill, however frequently the hind-casts are changed to keep up (or down).
Imagine for a moment that the American Clean Energy and Security Act of 2009 had passed and we had a Cap ‘n Trade system for the last three years. Then imagine for a moment how loud the climate alarmistists would proclaiming the effectiveness of their efforts. It would be a case of the rooster crowing and then taking credit for the sunrise.
– – – – – – – – –
Werner Brozek,
I think your statement is too prescriptive to be true.
Surely a person is entitled to present what they consider facts for others to ‘fact check’.
Surely people are entitled to ‘fact check’ all things presented as facts . . . . even when the facts are presented by GISS, HadCRU, RSS and UAH.
That is my only criticism of your very useful post about the temp time series of the past several decades. Thank you for your efforts to bring this to WUWT.
John
Oh no he didn’t! Taking SkepticalScience tools to show no warming is going to make some people very upset. Note that that definitely non-skeptic website likes to edit posts and comments without notice, so look for the tool to change in a substantial way after this post.
As I understand, the adjusted data is because of the time that the temperatures readings were taken. They were in the mornings I believe and now later in the day. But I have some problems with this.
Once adjusted, the temperatures seem still subject to more adjustments as time goes by. Also the baseline temperature is adjusted.
And one more worry, if the adjustments are made to adjustments then what happens to .6 + .6. Does this become 1 + 1 = 2 or (.6 + .6) = 1.2 = 1?
After so many adjustments just thinking about it makes my head hurt.
It would be helpful if both of the separate y-axes were labeled. The CO2 line is obviously not measured in degrees – and putting a second y-axis on the -right- for ppm would make this a fairly common method of plotting two disparate things on one chart.
The problem has never been warming. Warming such as the Roman Optimum and the MWP have been kinder to humanity than times such as the LIA. The problem is likely to be cooling, and a time of troubles.
Should those troubles come, those who like to work behind the scenes will simply say, “Never let a good crisis go to waste,” and will attempt to continue to leech off the ignorant. However those who enjoyed the spotlight will be marked men (and women,) stained by a blot that will not wash away.
The important issue is NOT whether global temperatures have been “warming” or “stalled”, since they have been warming since the Little Ice Age with oscillations on top of that trend.
The critical issue is whether there is MAJOR anthropogenic global warming as advocated by the IPCC, rather than minor anthropogenic global warming or statistically unquantifiable global warming.
The scientific challenge is to quantitatively distinguish between three major models:
A) Damaging Anthropogenic Global Warming: > 50% of warming due to humans, OR
B) Minor Anthropogenic Global Warming: 5% to 50% of warming due to humans, OR
C) Null Hypothesis: Natural Global Warming: < 5% or unknown due to humans.
Lack of statistically significant global warming for extended periods at least shows the IPCC’s models are wrong, and probably that there is NOT dangerous anthropogenic global warming. The IPCC sea temperature model trends are now running 3 times too hot since 1998.
To find out which model is better, the challenge is to statistically quantify the difference between models for both major and minor anthropogenic global warming over the null hypothesis of natural global warming with natural fluctuations since the Little Ice Age.
Compare models by:
the Global Warming Prediction Project
Nicola Scafetta
and
Syun-Ichi Akasofu, On the recovery from the Little Ice Age, Natural Science, Vol.2, No.11, 1211-1224 (2010), doi:10.4236/ns.2010.211149 http://www.scirp.org/journal/NS/
The far greater climate challenge is:
Can we prevent descent into the next glaciation in some 1500 years?
I am very angry about the NOAA quote above. I feel very let down by those who have excerpted it from the report. I had trusted it to be correct, and nearly repeated the quote myself. I had a narrow escape, because, deliberately or otherwise, It misrepresents what the authors were saying.
The discussion at ‘the blackboard’ led me to read the full context. The quote is talking about 15 years of absence of warming from ENSO- adjusted data sets, not 15 years of absence of warming from raw temperature measurements. The second is what I took it to mean, and how most skeptical users of the quote have presented it as meaning. But that just plain wrong.
The website drroyspencer.com demonstrates that there clearly has been warming in the ENSO-adjusted data set.
Rightly, he points out that the actual measurement is significantly below the forecast measurement- but that does not justify us taking the quote out ofvthe context of ENSO adjusted data sets and applying it to raw temperature measurements.
For shame, people.
– – – – – – – – – –
Werner Brozek,
Responses to your two questions are:
To your first question => No waiting for me, it is a waste of my precious life, just live with a reasonable eye on only the plausible potentials and then determine individualistic priorities.
To your second question => I do not know what the average GST anomaly will be in 2017 and neither does the MET. However, I think in the decadal timescale there will be overall moderate cooling based on my understanding of several physical phenomena.
John
Hey fellas! Instead of relying on a very unreliable source. Why not just go to the source for the temp data…. Here’s GISS http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
For some fun, about the temp abatement, I would submit that there’s not been any significant warming…. evuh!!!!
I’ve plotted the GISS temps as they would appear on an alcohol thermometer, and I’ll be darned if I can see any significant warming. Even embiggified!!!!
It’s dead, Jim.
This is the closest I found: [my bold]
If 1998 is not exceeded this year then Gavin Schmidt agrees that he would be worried about state of understanding. Just under 10 months to go then before Warmists called him a ‘denier’ / sarc.
no data should be presented past 2005. did you not receive the memo?
Leo,
Did James Hansen wait for an ENSO adjusted 15 year temperature rise before he made his presentation to Congress in 1988? (I really don’t know the answer to that).
Leo Morgan says:
March 5, 2013 at 10:15 am
The quote is talking about 15 years of absence of warming from ENSO- adjusted data sets, not 15 years of absence of warming from raw temperature measurements. The second is what I took it to mean, and how most skeptical users of the quote have presented it as meaning. But that just plain wrong.
—————————————-
Your comprehension is somewhat adrift because the quote does not relate to ENSO adjusted data. In essence the quote means that if the ‘predicted’ (i.e. the simulation) trend of warming is not supported by the observed data then the models are wrong.
To reiterate:
”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.”