(Image Credit: WoodForTrees.com)
By Werner Brozek, edited and with introduction by WUWT regular “Just The Facts”
Your help is needed in building a regular temperature trend analysis for WUWT. With much attention being focused on how much warming, or lack thereof, has occurred in Earth’s recent past (1, 2, 3, 4) it seems worthwhile to establish a regular update that provided a consummate summary of the key temperature records and their associated trends. Fortunately, WUWT regular Werner Brozek has been compiling just such an update and posting it in comments on WUWT and Roy Spencer’s website. As such, we would like to present an expanded version of Werner’s analysis for your input and scrutiny, before finalizing the content and form of these regular updates. As such, please review the following and lets us know, if it appears to be factually accurate, what you think of the layout, what you think of the content, if you think certain links should be images or images should instead be links, any additional improvements that can be made. There are few additional specific questions included in Werner’s analysis below. Thank you for your input. JTF
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Temperature Trend Analysis
By Werner Brozek
This analysis has three section covering 6 data sets, including GISS, Hadcrut3, Hadsst2, Hadcrut4, RSS and UAH:
Section 1, provides the furthest date in the past where the slope is a least slightly negative.
Section 2, provides the longest time for which the warming is NOT significant at the 95% level.
Section 3, provides rankings of various data sets assuming the present ranking stays that way for the rest of the year.
Section 1
This analysis uses the latest date that data is available on WoodForTrees.com (WFT) to the furthest date 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, I give the time from October so no one can accuse me of being less than honest if I say the slope is flat from a certain month.
On all data sets, the different times for a slope that is at least very slightly negative ranges from 8 years and 3 months to an even 16 years.
1. UAH Troposphere Temperature: since October 2004 or 8 years, 3 months (goes to December)
2. NASA GISS Surface Temperature: since May 2001 or 11 years, 7 months (goes to November)
3. Wood For Trees Temperature Index: since December 2000 or 11 years, 9 months (goes to August)
4. Hadley Center (HadCrut3) Surface Temperature: since May 1997 or 15 years, 7 months (goes to November)
5. Hadley Center (HADSST2) Sea Surface Temperatures: since March 1997 or 15 years, 8 months (goes to October)
6. RSS Troposphere Temperature: since January 1997 or 16 years (goes to December) RSS is 192/204 or 94% of the way to Ben Santer’s 17 years.
7. Hadley Center (Hadcrut4) Surface Temperature: since December 2000 or an even 12 years (goes to November.)
Here they are illustrated graphically;
you can recreate the graph directly here.
Here is an alternate graphical illustration;
you can recreate the graph directly here.
(Which of these illustrations do you prefer? Are they too cluttered to include in one graph? If so, how can we make this more user friendly?)
Section 2
For this analysis, data was retrieved from SkepticalScience.com. This analysis indicates for how long there has not been significant warming at the 95% level on various data sets.
For RSS the warming is NOT significant for 23 years.
For RSS: +0.130 +/-0.136 C/decade at the two sigma level from 1990
For UAH, the warming is NOT significant for 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 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 18 years.
For Hadcrut4: 0.098 +/- 0.111 C/decade at the two sigma level from 1995
For GISS, the warming is NOT significant for 17 years.
For GISS: 0.113 +/- 0.122 C/decade at the two sigma level from 1996
(Note that we have concerns with using data from SkepticalScience.com, however we have not identified another source for this data. Does anyone know of a reliable alternative source where these data points can be readily accessed?)
Section 3
This section provides the latest monthly anomalies in order from January on. The bolded one is the highest for the year so far. I am treating all months equally and adding all anomalies and then dividing by the total number of months. This should not make a difference to the relative ranking at the end of the year unless there is a virtual tie between two years. After I give the average anomaly so far, I say where the year would rank if the anomaly were to stay that way for the rest of the year. I also show the warmest year on each data set along with the warmest month ever recorded on each data set. Then I show the previous year’s anomaly and rank.
The 2011 rankings for GISS, Hadcrut3, Hadsst2, and Hadcrut4 can be deduced through each linked source.
The latest rankings for UAH can be found here.
The rankings for RSS to the end of 2011 can be found here. (Others may also be found here)
With the UAH anomaly for December at 0.202, the average for the twelve months of the year is (-0.134 -0.135 + 0.051 + 0.232 + 0.179 + 0.235 + 0.130 + 0.208 + 0.339 + 0.333 + 0.282 + 0.202)/12 = 0.16. 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.
With the GISS anomaly for November at 0.68, the average for the first eleven months of the year is (0.32 + 0.37 + 0.45 + 0.54 + 0.67 + 0.56 + 0.46 + 0.58 + 0.62 + 0.68 + 0.68)/11 = 0.54. This would rank 9th 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 0.89. The anomaly in 2011 was 0.514 and it will come in 10th assuming 2012 comes in 9th or warmer.
With the Hadcrut3 anomaly for November at 0.480, the average for the first eleven months of the year is (0.217 + 0.194 + 0.305 + 0.481 + 0.473 + 0.477 + 0.445 + 0.512+ 0.514 + 0.491 + 0.480)/11 = 0.417. This would rank 9th 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. The anomaly in 2011 was 0.340 and it will come in 13th.
With the Hadsst2 anomaly for October at 0.428, the average for the first ten months of the year is (0.203 + 0.230 + 0.241 + 0.292 + 0.339 + 0.351 + 0.385 + 0.440 + 0.449 + 0.428)/10 = 0.336. This would rank 9th 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 2011 was 0.273 and it will come in 13th.
With the RSS anomaly for November at 0.195, the average for the first eleven months of the year is (-0.060 -0.123 + 0.071 + 0.330 + 0.231 + 0.337 + 0.290 + 0.255 + 0.383 + 0.294 + 0.195)/11 = 0.200. This would rank 11th 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 2011 was 0.147 and it will come in 13th.
With the Hadcrut4 anomaly for November at 0.512, the average for the first eleven months of the year is (0.288 + 0.208 + 0.339 + 0.525 + 0.531 + 0.506 + 0.470 + 0.532 + 0.515 + 0.524 + 0.512)/11 = 0.45. This would rank 9th if it stayed this way. 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.
Here are the above month to month changes illustrated graphically;
you can recreate the graph directly here.
Appendix
In addition to the layout above, we also considered providing a summary for each temperature record, as is illustrated below for RSS. Please let us know if you find this format to be adventurous/preferred as compared to the category breakout above, and also please let us know if there are any additional analyses that might be valuable to incorporate.
RSS
1. With the RSS anomaly for November at 0.195, the average for the first eleven months of the year is (-0.060 -0.123 + 0.071 + 0.330 + 0.231 + 0.337 + 0.290 + 0.255 + 0.383 + 0.294 + 0.195)/11 = 0.200. This would rank 11th 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 2011 was 0.147 and it will come in 13th.
The rankings for RSS to the end of 2011 can be found here.
2. RSS has a flat slope since January 1997 or 16 years (goes to December). See:
Recreate graph here.
3. For RSS the warming is NOT significant for 23 years.
For RSS: +0.130 +/-0.136 C/decade at the two sigma level from 1990
See here.
Put in 1990 for the start date; put in 2013 for the end date; click the RSS button; then calculate.
About the Author: Werner Brozek was working on his metallurgical engineering degree using a slide rule when the first men landed on the moon. Now he enjoys playing with new toys such as the WFT graphs. Werner retired in 2011 after teaching high school physics and chemistry for 39 years.
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Please let us know your thoughts and recommendations in comments below. Thanks Werner & Just The Facts
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Thank you for all your work “justthefacts”!
A minor omission occurred with the UAH information. It should read:
With the UAH anomaly for December at 0.202, the average for the twelve months of the year is (-0.134 -0.135 + 0.051 + 0.232 + 0.179 + 0.235 + 0.130 + 0.208 + 0.339 + 0.333 + 0.282 + 0.202)/12 = 0.16. 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.
Anthony, Happy New Year.
I am just a layman who reads your blog quite frequently. I don’t even profess to understand a lot of what is posted. But I think I understand the basics. If I purchased a weather station, here in Cheshire in the UK, would the data I collected be of use to you?
This is a good initiative but in the compilation showing all data sets (woodfortrees) I would use the equivalent past of one normal solar cycle i.e. is that 11 or 12 years?
Werner Brozek says: January 6, 2013 at 1:29 pm
Thank you for all your work “justthefacts”!
No problem, you did all of the heavy lifting. Thank you for your contribution to climate science.
A minor omission occurred with the UAH information. It should read:
With the UAH anomaly for December at 0.202, the average for the twelve months of the year is (-0.134 -0.135 + 0.051 + 0.232 + 0.179 + 0.235 + 0.130 + 0.208 + 0.339 + 0.333 + 0.282 + 0.202)/12 = 0.16. 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.
Corrected.
Big subject, large area, lots of data. I have broken down my involvement to those that have responsibility within the UK, the MO. So I produce the following:-
http://i49.tinypic.com/b3oifn.jpg
I use the 30 year WMO “Standard” to be compliant, the 15 year as a logical split and 10 years as an here and now indication.
The trend is your friend! The 30 year trend will continue in its reducing direction until the 10 and 15 year trends break up and through their longer friend.
I have to credit Henry (?) for the original chart idea.
Question: Why is CRN not included? I have long been interested in trends shown by the Climate Reference Network and how that network (which requires no adjustments) matches up with the other networks that require various adjustments.
Henry@crosspatch
can you give a link for CRN?
crosspatch says:
January 6, 2013 at 1:58 pm
Question: Why is CRN not included?
I have worked with things that WFT has provided. And neither CRN (nor NOAA) is on there. Perhaps this is something that the creator of WFT and justthefacts can discuss.
Your help is needed in building a regular temperature trend analysis for WUWT.
The simple truth is that the – all – measured ‘global’ temperature data sources exhibits the same temperature function over time and because there is only one Earth it seems that the differences in the zero lines are from different defined time ranges.
The question what the best temperature trend analysis is is not a question of science, but from politics to tell the crowd up and down nonsense.
Scientific analysis on the temperature data is possible and can discriminate the terrestrial oscillations like ONI from the solar tide oscillations because of the different frequency bands. And this leads to the low frequency temperature frequencies known as periods of litte ice ages or warm ages as now.
http://volker-doormann.org/images/rss_uah_december_2012.gif
One can clean the global temperature from the ONI function to make the solar tide oscillations visible.
http://volker-doormann.org/images/oni_cleaned_rrs_temps.gif
This holds also for longer time ranges and can show the character of the natural oscillation frequencies without ‘trends’.
http://volker-doormann.org/images/ghi6_plus_temps.gif
V.
@HenryP there are some links in this article from 2012 here at WUWT:
http://wattsupwiththat.com/2012/08/08/an-incovenient-result-july-2012-not-a-record-breaker-according-to-the-new-noaancdc-national-climate-reference-network/
Try this old article here:
http://wattsupwiththat.com/2012/08/08/an-incovenient-result-july-2012-not-a-record-breaker-according-to-the-new-noaancdc-national-climate-reference-network/
Werner Brozek says: January 6, 2013 at 2:15 pm
I have worked with things that WFT has provided. And neither CRN (nor NOAA) is on there. Perhaps this is something that the creator of WFT and justthefacts can discuss.
The best way for us to get his attention and consideration is probably to fill his charity tip jar a bit, and leave a note asking if he’d consider including CRN and NOAA data, and correcting the WoodForTrees Temperature Index (WTI);
http://www.woodfortrees.org/notes#wti
which, as you had pointed elsewhere, has not been updated since August:
http://www.woodfortrees.org/plot/wti/last:12/plot/gistemp/last:12/offset:-0.35/plot/hadcrut3vgl/last:12/offset:-0.26/plot/rss/last:12/offset:-0.10/plot/uah/last:12
WoodForTrees.com “is a self-funded personal project by Paul Clark, a British software developer and practically-oriented environmentalist and conservationist.”
http://www.woodfortrees.org/
This is his charity tip jar;
http://www.justgiving.com/WFT
In it he writes that, “I think it’s quite important it is clearly seen to be independent of any funding.”
“What would make me very happy, however, is if people wanted to make a donation to Charity to recognise any value they have received from using woodfortrees.org. Aptly enough, given both the name and my own interests, my selected Charity is the UK Woodland Trust. The Woodland Trust manages many woodlands across the UK and supports planting of new ones. I am a member and I do occasional volunteer photography for them.”
Seems like a worthy cause to me.
Having all the data in one place is good, but we still have the problem of everyone using different averaging periods.
Your chart (the “alternate graphical illustration”) shows just how much of a variation there is – seven different sources, seven different trends. If they all have the same “zero”, we’re currently anywhere between .2 and .6 above “zero” (which, again is based on locations, averaging period, type of measurement, addition of “extrapolations”, etc) .
It’s charts like that the “climate scientists” are having a hard time trying to explain – which of the seven sources do they consider the most accurate, and why?
Naturally, they’ll defend the one with the highest CURRENT anomaly – makes it look much worse.
I don’t know why, but I never thought of putting all the data sets on one graph. Seeing it above “Does Anybody Really Know What Time It Is?” popped in my head except temperature replaced time. LOL, I recommend keeping both graphics. Wonderful IMHO.
JTF/WB
Excellent, WFT is a marvelous, marvelous resource but graphic presentation is not it’s strong point!
I prepared this graph from data extracted from WFT, it presents decadal trends in temperature anomaly increases/decreases since 1987 along with that of CO2, I thought the graph made the relationship between CO2 forcing and temperature change starkly obvious…
I’d be prepared to assist in coding automated graphs should you feel it would help. Should he feel it appropriate, JTF could perhaps integrate the graph in the comment rather than leave it as a link.
One suggestion: add the ability to include a non-linear trend, such as a sinusoidal curve.
The reason I suggest this is the apparent 60-65 year oscillation in many climate datasets. This is only rarely put online, not least because it requires a commercial stats package (Excel can’t do it) and also it drives CAGW people nuts for the good reason that it appears to explain about 1/3rd of the temperature ‘rise’ last century due to endpoint selection.
Ray Spencer for some time playfully added a polynomial fit to the UAH data, but unfortunately this opened a door to strawman criticism, as polynomials can only simulate oscillations for so long before they go off scale.
Reblogged this on sainsfilteknologi and commented:
Trend Analysis
There is no need to feel uncomfortable about the data from Skeptical Science. The trend calculation is just normal least squares, and the standard error is corrected as in the appendix of F&R. I have checked the results from the trend calculator in several occasions, and my results agree. Eg. for GISTEMP since 1996 the SKS trend calculator gives:
Trend: 0.113 ± 0.122 °C/decade (2σ)
My result is:
Trend: 0.116 ± 0.119 °C/decade (2σ)
The difference is most likely caused by a difference in the year range used for the autocorrelation calculation or to slightly different versions of the GISTEMP dataset.
Gras Albert says: January 6, 2013 at 3:08 pm
I prepared this graph from data extracted from WFT, it presents decadal trends in temperature anomaly increases/decreases since 1987 along with that of CO2, I thought the graph made the relationship between CO2 forcing and temperature change starkly obvious…
… Should he feel it appropriate, JTF could perhaps integrate the graph in the comment rather than leave it as a link.
Sure. It is an interesting graphic, but the time-frame seems arbitrary. What does it look like with data through present?
I’d be prepared to assist in coding automated graphs should you feel it would help.
Most appreciated, we may take you up on this if the need arises.
I challenge that any temp series is accurate to a 1/10th of a degree, I would also point out that bad data in, makes for bad data out.
I should add that I don’t mean to be harsh, but if you put the same data on a chart with +5/-5 degrees off of the zero line, what you see is a little wiggle that doesn’t even hit a degree. These charts, they look impressive but quite a few folks do not realize the scale is just a little over 1 degree. Even with the “massive warming era” if you put it on a chart that gives it a value most people understand and can relate to, it becomes a non issue because honestly can you tell its .2 degrees warmer or colder? Neither can they.
Interesting ensemble … that supports the view that the CO2 increase follows temperature increase.
Maybe section 2 would be clearer with a table. Having many lists of these:
> For RSS the warming is NOT significant for 23 years.
> For RSS: +0.130 +/-0.136 C/decade at the two sigma level from 1990
makes it somewhat hard to read because of the repeated information.
Something like (but with better formatting):
DatasetYears With No Significant WarmingRateStart Year
RSS 23 +0.130 ±0.136°C 1990
UAH 19 +0.143 ±0.173°C 1994
Werner Brozek
Thanks Werner for your helpful work.
1) Show highest and lowest +/- 95% significant trend limits.
You already have the +/- trend limits at the +/- 95% extreme points at the beginning and end of the period.
I recommend adding dashed lines the +/- significant trend limits.
2) Red noise adjusted trends.
See Lucia’s trend adjustments for red noise, then ARIMA.
See the analyses by Lucia Lilijgren at The Blackboard under Data Comparisons.
@crosspatch, Henry C., etc.
Re the CRN network, a link is provided in my guest post of August 30:
http://wattsupwiththat.com/2012/08/30/errors-in-estimating-temperatures-using-the-average-of-tmax-and-tmin-analysis-of-the-uscrn-temperature-stations/
The CRN is excellent for providing data from well-administered sites meeting all NOAA/WMO criteria. It will be useful in coming decades for establishing trends. However, at present the full network of 114 or so stations has only been operating for four years, so will not be useful in my opinion for trend analysis until a number more years have gone by.