(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
—
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.
—
Please let us know your thoughts and recommendations in comments below. Thanks Werner & Just The Facts
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.
Werner,
I had a go a summarizing your section 1 and 2 into a graph. I only did it for HADCRUT4 as an example. It essential shows what you show in those sections. The trend in HADCRUT4 goes negative in 2001 (blur line crosses zero) and stops being statistically different from zero in 1995 (red line crosses zero).. But I think it also adds a bit more info, it shows how as the time interval gets shorter for the the data series the confidence levels get much larger, I didn’t plot the data after 2006 because they were so large they were making things look wonky. But they do highlight the caution required in trying to make any sort of call based on short time series.
I did also had a go at plotting the expected temperature trends from the CMIP5 model mean on the same graph. That produced an interesting result in that the trend in the model mean is outside the confidence range for the HADCRUT4 dataset for most of the time period (i.e the black dotted line is above the green line). I only calculated the trends in the model mean from linear trends in the annual data, maybe there is a better way of doing it but this might be other way of showing the models are running hot compared with the observations at the moment.
Here’s the example graph I produced.
http://i49.tinypic.com/1t50gh.png
This is a great idea, looking forward to seeing what comes out of it. Some thoughts:
o perhaps a bar graph for each index showing the number of month/years of no statistical warming? I’d prefer that to the spaghetti graphs
o would it be possible to depict the model performance vs actual? tough to do because you have to pick en ensemble mean otherwise the spaghetti gets even worse
o would be nice to see an easy way to compare to co2 concentration over the same time period as well, maybe even something depicting theoretical forcing based on ippc guestimates, show it rising commensurate with actual values while the temps wander off to nowhere
jJTF//WB AND WERNNER BROZEK
Great ideas and graphs . I personally found the decadal or 11 year moving average that
CLIMATE 4YOU uses in their SUN section very informative . You should also track decadal sunspot number [derived version as Lief proposes] Showing the HADSETT2, HADCRUT 3 and DERIVED SOLAR SUNSPOT NUMBER on the same plot going back 1830 tells an interesting story. We currently have the global SST global surface temperatures and solar sunspot number graphs all going down like they did 1870-1910 . The threshold for cooling appears to be approximately the derived decadal solar sunspot number of about 48-50. Some time the global sst cycle and sunspot numbers cycle are not in sync like the 1950’s when the solar cycle was peaking but the ocean cycle was cooling and again the 1980-1990’s, when the oceans were still warming but the sun spot number curve was declining. The sunspot cycle seems to have started to decline after the 1980’s
Would it be possible to note the zero(assumed mean temperature) in degrees C with error range on these anomaly graphs, for the ignoramus such as myself?
I have difficulty discerning which mean is used on which anomaly graph.Hence remain unclear as to the magnitude of the change of temperature.
Nice job Werner,
IMO, Section 3 would be more easily compared if in the form of a table. Each data set could be represented by a row. Column headings could be Rank, Warmest Year, Warmest Year Anomaly Value, Highest Monthly Anomaly month/year, HMA Value, 2011 Anomaly, 2011 Rank.
This is another example of how to show temp Vs Co2 http://woodfortrees.org/plot/rss/from:1980/to:2013/scale:50/plot/esrl-co2/from:1980/to:2013/offset:-350/plot/rss/from:1998/to:2013/scale:50/trend/plot/esrl-co2/from:1998/to:2013/offset:-350/trend/plot/uah/from:1998/to:2013/scale:50/plot/uah/from:1998/to:2013/scale:50/trend
Why not use data from KNMI see here http://climexp.knmi.nl/start.cgi?someone@somewhere. Please note that KNMI are the official repository of daily data for all European countries.
Where the data is raw ie European at least they do not manipulate it like others.
Certainly nothing from SkepticalScience is acceptable (it is an CAGW biased blog and it is known to select data and manipulate it)
Lance Wallace says:
January 6, 2013 at 5:20 pm (Edit)
@crosspatch, Henry C., etc.
Hmmmn.
No answers allowed on that post anymore, but I strongly recommend you run the analysis again looking for the main-max relationships not against latitude – which was present but only moderately strong – but against humidity or elevation. West TX and NM and AX and mid California and the other “red dots” are over 3000 feet elevation. Humidity, night radiation, night radiation, air clarity, etc … All could affect the night and day readings differently than the low level east, northeast, and Midwest. Chicago is what – only 250 feet elevation? Upstate and lakeside MN, WI, IL, etc are not much higher. Upstate NY and PA and OH are all about the elevation of Lake Eire – 220 feet.
Mountains sure – PA is NOT flat – but where are the sensors?
cementafriend,
KNMI may indeed be a reliable source of data, but I am not (yet) familiar enough with it’s background to trust it. I have found both sceptics and warmists to be OK with the lack of obvious bias on the WoodForTrees site. Applause.
(As a slight political aside, which I generally try to avoid, I was not sure whether KNMI was dependent on EU funding. I am pained to admit that my view of the EU has taken quite a reverse since the start of this millenium.)
Back on topic, and probably more important though, is the simple format of WFT. I go there for data and simple graphs, nothing else. My understanding is that Anthony Watts was receiving funding to set up a similar resource at the time of the Gleick/Heartland events, using data sourced and funded by the US. I still hope to see that (I can’t see why a reasonable person would object to it).
I would like to thank you for your comments so far. Justthefacts and I will go through them and decide what to do. There are many good ideas. I just wish I had the expertise to implement some of them such as HR and others! We may well need to get another person involved to do things like graphs and tables via computer. I would just like make some general responses from my perspective so far in no particular order. Justthefacts may also decide which other correlations that have been mentioned could be looked at beyond what my focus has been.
I agree that sine waves are more accurate, however the statements by NOAA and Santer seem to imply that things are wrong if the linear trend is 0 for 15 or 17 years. If these are their goal posts, we have to use linear trends to show that Earth has scored a goal or is close it. How could one even define a goal in terms of a sine wave?
As far as bar graphs are concerned, at least the graph with the 7 lines can be viewed as a sideways bar graph to see for how long various data sets show no trend. Mind you, the bars are as thin as lines. But for other bar graphs. I would need someone with good computer expertise.
As far as the “0” is concerned, that is a big problem. Just to illustrate, suppose a data set said the anomaly is 0.2. What would this mean? For GISS, it is lower than 25th; for UAH, it is in 7th place; for Hadcrut3, it is in 19th place, etc. So to put things into perspective for the present year, I give the ranking if a certain anomaly were to continue for the rest of the year. So to just put all numbers into a bar graph, some bars would be very high but would mean little due to the baseline that was used.
I can do what WFT allows me to do, although there may be some tricks I have not figured out yet. I agree that the graph with 14 different things is not useful. Would it work if I made 7 graphs, one for each data set? And for each data set, I would start the year from the point where the warming is not significant and draw a trend line from that point. Then on the same graph, I would draw a line for the longest line where the slope is 0. For RSS, it would look as follows:
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1997/trend
I’ve been running something similar at home, but I didn’t realize there was such a big demand for it. I download the Hadcrut3, GISS, UAH, RSS, and NOAA monthly anomalies and graph them in a big spreadsheet chart on my 1920×1080 24″ LCD monitor. I run on linux, and use the “gnumeric” spreadsheet, saving in native gnumeric XML format. I can save to various Excel formats if anybody’s interested.
UAH seems to be a bit of an outlier in how short the zero/negative-trend period is. I also plot the 12-month running mean. The UAH 12-month running mean is always lower than the RSS 12-month running mean. Last December, that rule was broken for the first time in the history of those 2 data sets. An interim corrected version of UAH was released. The UAH 12-month running mean is now slightly below that of RSS, but there does seem to be a change approximately June 2011. Anything significant happen then?
Werner Brozek;
As far as bar graphs are concerned, at least the graph with the 7 lines can be viewed as a sideways bar graph to see for how long various data sets show no trend. Mind you, the bars are as thin as lines. But for other bar graphs. I would need someone with good computer expertise.
>>>>>>>>>>>>>>>
Werner, in section 1 you’ve already got the values calculated, all you need to do is type them into a spreadsheet and draw the graph. About 5 minutes if you are already familiar with Excel or similar. Also, if you look under the WFT graph, there’s a clickable link to raw data. You can copy and paste that into a text document and then import it into Excel. A bit more complicated to learn, but once you know how it is done, pretty straight forward.
I can send you a couple of examples you can use as templates if you’d like to get you going. Just contact me by email, the mods have my email address (I’d rather not post it).
Walter Dnes says:
January 6, 2013 at 7:51 pm
>>>>>>>>
Werner, I’m OK with Excel, better than most, but this guy sounds like a heavy hitter!
I just thought of an addition to my earlier email. I added two lines to the graphic that I put up before to show the +/- parts of the 95% uncertainty. Does this look better:
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1990/detrend:0.3128/trend/plot/rss/from:1990/detrend:-0.3128/trend/plot/rss/from:1997/trend
P.S. Thank you David and Walter. Let us see what JTF says. Please check back in 24 hours as neither of us may be available for a little while.
Henry@Werner
remember that I predict from my own data set that temps. will drop by -0.3K in the next 8 years or so.
It appears that the average length of one solar cycle is 10.66 years.
So I would plot my graph accordingly,, i.e. 11 years (from 2002) and every month you dump one month at the beginning and you add one month at the end. This will show the increase in cooling that we can expect.
You need to decide which data sets to reject. But be careful, it’s the data sets that John West rejects, that make John West the best. (sorry, had to do it)
But seriously, this is good work. my appreciation to werner and ‘facts’.
This may have the unintended consequence of alarming the alarmists as the months go by.
JTW
Sure. It is an interesting graphic, but the time-frame seems arbitrary. What does it look like with data through present?
Hmmmm, perhaps the graph is not as clear as I thought, 🙂
It’s a plot of ‘ten year’ trends, i.e. the oldest decadal trend starts in 1987 and finishes in 1996, the most recent starts in 2003 and finishes in 2012, it is current through 2012. The graph shows that the rate of warming per decade peaked in 1992 and has decreased every decade since with all but UAH now showing decadal cooling…
Streetcred says:
January 6, 2013 at 4:41 pm
Interesting ensemble … that supports the view that the CO2 increase follows temperature increase.
There is an alternative view that supports the view that the CO2 decrease follows temperature:
http://www.volker-doormann.org/images/down3.gif
V.
Bruce of Newcastle says:
January 6, 2013 at 3:22 pm
One suggestion: add the ability to include a non-linear trend, such as a sinusoidal curve…
A great idea, Other simple non linear functions simple polynomial or exponential functions would also be very useful useful.
There is currently a discussion in another section (AGW Bombshell? A new paper shows statistical tests for global warming fails to find statistically significantly anthropogenic forcing
Posted on January 3, 2013 by Anthony Watts) centering on the claim by the authors of the paper that “informal” inspection of the temperature data from 1880 to 2007 shown in panel c of figure 1 is more stable than the curves for the grenhouse gas emmissions.
I contend that this is merely a matter of difference in the y-scaling of the data sets. The temperature data is taken from NASA GISS global temperature (meteorological stations) presented here with a less compressed y scaling, where informal examination shows an increase in the rate of warming over the period.
http://data.giss.nasa.gov/gistemp/graphs_v3/
The impression is confirmed by a simple nonlinear fit to a data set comprised of an average of 10 data sets, including the GISS data:
http://www.skepticalscience.com/pics/AMTI.png
Although the data sets are effectively the same, some have objected to the “provenance” of the nonlinear data fit, prefering individual wood for trees data sets with less well fitting linear plots. The capacity to fit plots with different functions and giving R2 correlation coefficients would be most useful.
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….
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>…
My Husband look at your graph and said you forgot to apply the ‘Mann’ Tiljander flip to turn the temperature chart upside down.
Baa Humbug says:
“it’s the data sets that John West rejects, that make John West the best. “
LOL!
— just in case people aren’t following, it’s a John West Salmon slogan except with fish instead of data, of course.
I know it is necessary to do this! But, all of the models are broken, since none of them incorporate the effects of the Sun. Some might use TSI data, but what about the known effects caused by the “unknown mechanism {stated by Leif}”.
We could use this information as a base line of “previously implemented Theories”. How do we move on to get “better models”?
Folks,
OK, I consider myself chivvied 🙂
First up, WTI has now been updated to use UAH 5.5 (that’s why it was stuck in August, because 5.4 stops then).
For adding CRN / NOAA and anything else, I need:
– URL to data source file in moderately sane text format (I’m used to reading most format horrors now, but basically it needs monthly anomaly data)
– Credit information as in the current credits page
If people can find these details and either post here or mail me it makes it much easier to add rather than a vague wishlist.
Best wishes
Paul
As for new fit functions, trend significance etc. – yes, it would all be nice, but above both my stats skills and available time! If anyone would like to help, the core code is in the ‘analyse’ source package on the site; everything else is just URL munging and gnuplot plumbing. To add a new function you simply need to add a new command line option to ‘analyse’ – hopefully the code is trivial enough to make this obvious.
… and therein lies the rub. I want to keep ‘analyse’ easy to build, understand and verify, which means using only primitive ISO C++ maths, not fancy external stats libraries that I don’t understand and would make it hard for others to build it. But if anyone wants to try just download the source, play with it and send me a patch (or complete update). It’s all in ‘git’ this end so be brave… Indeed if multiple people want to play I’ll put it up on github as well.
Cheers
Paul
If Werner Brozek would like to contact me via WUWT I should very much like to discuss this project with him. It is a first-class idea, and badly needed. But it needs to be well executed. It is particularly important to provide a single, bold, accurate, visually-clear image that will reproduce well on TV and in the news media. That image should include the following elements:
A short headline stating the main point discernible from the graph (e.g. “No global warming for 18 years 7 months”).
Temperature on the y axis, years on the x axis. The period should be the longest period for which the combined mean of the RSS and UAH monthly global mean lower-troposphere temperature anomalies exhibits a trend that is no greater than statistically-indistinguishable from zero to 95% confidence (i.e., the warming, if any, should not exceed 0.05 K over the period).
A substrate showing the predicted global warming interval and central estimate out to 2015 according to as many of the IPCC reports 1-5 as we can accommodate without confusion.
The actual monthly anomalies, taken as the mean of the anomalies on the UAH and RSS satellite-temperature datasets.
The least-squares linear-regression trend line on the anomalies.
A short description of how the graph was compiled, the data sources, and a brief description of the statistical technique used.
This single graph will do more to wake up the world to the failure of climate extremism than anything else. I can provide camera-ready artwork automatically generated by PowerBasic, which has a powerful graphics interface and can easily process the data to make the graph look good.
Monckton of Brenchley says:
January 7, 2013 at 9:00 am
Yes, but that first graph needs to be followed immediately by a second showing the 350 year slow rise of temperatures from 1650 through 2012!
Followed by a simple but clear verbal statement
There was a routing to scrape CRN data via the web posted back in 2007 on Climate Audit:
http://climateaudit.org/2007/08/07/scraping-uscrn-data/
There was also an article that list the various sources of data here:
http://climateaudit.org/station-data/
The script here is old, might work but might need some tweaking if the website has changed since then,
http://www.climateaudit.info/scripts/station/read.uscrn.txt
if you want CRN data I wrote a package to do that back in 2011
Paul, if you want help with CRN and you know R the data can be pulled down and formatted rather easily. The difficult part is creating a us average from this data. Simply averaging the series will give you poor result , for that I have a few standard methods, but it takes a bit more skill
Thanks both, but it’s that level of skill / determination / time that I’m short of, and why I haven’t already done it. Basically to add a dataset I need a single publicly available file with monthly globally averaged data in it (actually for NSIDC I fetch monthly files and grep/sort them to make one). Steve McIntyre’s script is only one station at a time, and whole PhD’s have been written on how to combine multi-station data into a global/regional average!
Of course, someone else could do the scraping and republish it, then I could pull it from them!
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…
It makes it obvious to me there is no relationship!
Well, CRN is probably easier to than others because there are no UHI or any other “adjustments” required which is why I am a fan of the network. But what I am trying to understand is why there doesn’t seem to be a problem producing a monthly average using a much more difficult network like USHCN where there is a lot of fiddling for station/equipment changes and UHI but the network that requires no such fiddling seems to be *more* difficult to produce a monthly average as nobody has done it yet.
Slightly off topic but as good a place a any to raise this issue.
It is a real problem for me (red green color blind) to determine the colors of the traces on the graphs posted on woodfortrees. It would be a huge help to me and others who are colorblind (about 10% of your viewers) if you could either increase the line width on the chart traces by 2x – 3x or provide a check box where the user could choose a line width for the chart.
Beyond that, I think this is a great idea and visual representations can be very effective and powerful ways to quickly communicate data relationships.
Larry
pkatt says:
January 6, 2013 at 4:17 pm
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.
————————
Try putting it on a graph that starts at 0°K and see what kind of line you get!
Showing the data at different scales is a good way to show how trivial the issue is. If displayed on several different scales it is easy to see that most of the alarm is manufactured. This has already been done over at junk science as I recall, he showed how changing the range and scaling of the y axis changes the “apparent severity of the issue”
I can’t find it right now, but the same data was graphed with various vertical scales and ranges on the Y axis.
Larry
Monckton of Benchley says:
“Today’s high CO2 levels – the 97% natural and the 3% human-released”
This may lead people to conclude that human activities have added only 3% to atmospheric CO2. In the interests of clarity, Monckton should point out that the 97% natural contribution refers to CO2 being recycled through the biosphere, whereas the 3% is that added to the atmosphere by the burning of fossil fuels which has seen the CO2 concentration rise from 280 ppm at the beginning of the industrial revolution to 390 ppm today This is a rise of 39%.
I am also unclear about what time period the 3% covers. According to the following sources, the rise in atmospheric carbon was only 2.0 ppm in the decade 2000-2009, which is only a 0.52% rise over that period.
Tans, Pieter. “Trends in Carbon Dioxide”. NOAA/ESRL. http://www.esrl.noaa.gov/gmd/ccgg/trends/.
Carbon Budget 2009 Highlights, globalcarbonproject.org, http://www.globalcarbonproject.org/carbonbudget/09/hl-full.htm,
Someone’s had some cherry-picking fun with that graph, haven’t they? 🙂
http://www.woodfortrees.org/plot/gistemp/from:1966/plot/gistemp/from:2001.95/trend/plot/gistemp/from:1996.8/to:2001.95/trend/plot/gistemp/from:1987/to:1996.8/trend/plot/gistemp/from:1977/to:1987/trend/plot/gistemp/from:1966/to:1977/trend/plot/gistemp/from:1966/trend
I’d like to see “Data Visualization” gurus such as Stephen Few or Edward Tufte (or comparable disciples) take a hand cleaning the imagery up.
The bits where the lines run over the titles/legends is particularly distracting.
Mr Shehan attributes to me a statement that I did not make. Some 40 per cent of the CO2 in the air is anthropogenic, not the 3 per cent that Mr Shehan attributes to me.
woodfortrees (Paul Clark) says:
January 7, 2013 at 8:42 am
> For adding CRN / NOAA and anything else, I need:
> URL to data source file in moderately sane text format (I’m used to reading
> most format horrors now, but basically it needs monthly anomaly data)
Here’s a core dump of what I have available for monthly data
GISS (needs to be reformatted)
http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
Hadley 3 (needs to be reformatted)
http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt
Hadley 3 early monthly data (same data set as above, but in a nice columnar format, and also comes out a week or so earlier than the above version)
http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/monthly
Hadley 4 monthly data
http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.4.1.1.0.monthly_ns_avg.txt
NOAA monthly data (Seems to be refreshed/updated every day or 2)
Note that even though it’s a text file, it gets mime-type “bin”, and web browsers have problems displaying it. Downloading it directly is better.
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_ocean.90S.90N.df_1901-2000mean.dat
various CET monthly data main page (actual data, not anomalies)
http://www.metoffice.gov.uk/hadobs/hadcet/data/download.html
Monthly sunspot numbers
http://solarscience.msfc.nasa.gov/greenwch/spot_num.txt
Very good Werner, Just The Facts,
This highlights what an excellent resource WoodForTrees is. Thanks Paul!
woodfortrees (Paul Clark) says:
January 7, 2013 at 8:42 am
First up, WTI has now been updated to use UAH 5.5
Thank you very much!
Earlier I had said
3. Combination of 4 global temperatures: since December 2000 or 11 years, 9 months (goes to August)
With the update, it would now be since December 2000 or 12 years (goes to November)
See:
http://www.woodfortrees.org/plot/wti/from:2000.9/plot/wti/from:2000.9/trend
Monckton of Brenchley says:
January 7, 2013 at 9:00 am
The period should be the longest period for which the combined mean of the RSS and UAH monthly global mean lower-troposphere temperature anomalies exhibits a trend that is no greater than statistically-indistinguishable from zero to 95% confidence (i.e., the warming, if any, should not exceed 0.05 K over the period).
In light of this, my question for Paul Clark is if this can be easily done. Thanks!
Werner Brozek says: January 6, 2013 at 7:49 pm
I would just like make some general responses from my perspective so far in no particular order. Justthefacts may also decide which other correlations that have been mentioned could be looked at beyond what my focus has been.
I think there may be two articles coming out of this exercise. One that will be similar to the current one, with a few additions and tweaks, the second is more in vein of what Monckton of Brenchley has suggested. The first article is intended for a more targeted audience and provide an in-depth and multifaceted analysis of the temperature trends. The second article is intended to isolate the most salient points and package them for a broad audience. I think we should focus on polishing up the first article and then we can begin work with on the second.
I agree that sine waves are more accurate, however the statements by NOAA and Santer seem to imply that things are wrong if the linear trend is 0 for 15 or 17 years. If these are their goal posts, we have to use linear trends to show that Earth has scored a goal or is close it. How could one even define a goal in terms of a sine wave?
I agree, the goal here is to document how long there hasn’t been warming, a linear trend does that best.
As far as bar graphs are concerned, at least the graph with the 7 lines can be viewed as a sideways bar graph to see for how long various data sets show no trend. Mind you, the bars are as thin as lines. But for other bar graphs. I would need someone with good computer expertise.
I think we are ok with lines versus bars. I would prefer to use WFT for charts, versus making them ourselves, in order to maintain calculatory independence. Additionally, I’d prefer to keep the production of the content of this article completely in your hands, so that you can readily reproduce it, and aren’t dependent on others to complete it.
(As far as the “0” is concerned, that is a big problem. Just to illustrate, suppose a data set said the anomaly is 0.2. What would this mean? For GISS, it is lower than 25th; for UAH, it is in 7th place; for Hadcrut3, it is in 19th place, etc. So to put things into perspective for the present year, I give the ranking if a certain anomaly were to continue for the rest of the year. So to just put all numbers into a bar graph, some bars would be very high but would mean little due to the baseline that was used.
Baselines are a mess, as John Christy pointed out a while back, even the RSS and UAH anomalies are not comparable because they use different base periods, i.e., “RSS only uses 1979-1998 (20 years) while UAH uses the WMO standard of 1981-2010.” There’s nothing that we can do about this.
I can do what WFT allows me to do, although there may be some tricks I have not figured out yet. I agree that the graph with 14 different things is not useful.
I don’t know if it’s not useful. It’s definitely messy, and isn’t suitable for mass audience, but it does paint a picture.
Would it work if I made 7 graphs, one for each data set? And for each data set, I would start the year from the point where the warming is not significant and draw a trend line from that point. Then on the same graph, I would draw a line for the longest line where the slope is 0. For RSS, it would look as follows:
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1997/trend
I think we may want to create a section at the bottom of the article with an analysis for each data set, as you did already for RSS, such that it’s readers can view the data however they prefer.
Werner Brozek says: January 7, 2013 at 4:53 pm
An aside here, 28 hours, 4,080 views, 69 comments, and no one seems to have identified any flaws in your analysis. Good job. Maybe the Warmists are just going to concede that it’s not getting warmer…
Monckton of Brenchley says:
January 7, 2013 at 9:00 am
The period should be the longest period for which the combined mean of the RSS and UAH monthly global mean lower-troposphere temperature anomalies exhibits a trend that is no greater than statistically-indistinguishable from zero to 95% confidence (i.e., the warming, if any, should not exceed 0.05 K over the period).
If I could just address this one point for now, I can do one or the other, but not both. See the graph below that shows RSS with a slope of 0 for 16 years and the other slope from 1990 with the error bars for the 95% confidence. The slope of the middle line is 0.0128/year and since it goes for 23 years, the total rise is 0.0128 x 23 = 0.29 C. To have an increase of no more than 0.05 K, the time would be somewhere between 16 years and 23 years for RSS.
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1990/detrend:0.3128/trend/plot/rss/from:1990/detrend:-0.3128/trend/plot/rss/from:1997/trend
RACookPE1978 says:
January 7, 2013 at 9:20 am
> “No one denies the world is warming. It has been naturally warming for 350
> years, and that continuous slow natural warming is feeding the hungry, clothing
> the naked, and saving the sick, and heating the cold.
Make that 18,000 years. Another graphic we need is the retreat of ice since the peak of the last ice age. At the peak of that ice age, most of Canada and the northern tier US was covered by ice sheets 1 or 2 *MILES* thick, For the past 18,000 years, the arctic ice cap has been in a general retreat with a few speed bumps along the way (e.g. Younger Dryas and Little Ice Age). Why are the warmists freaking out over the last 30 years? It’s merely continuing the pattern of the last 18,000.
Another embarressing fact is that 18,000 years, when the ice sheets began retreating, there were less than a million human beings on the planet, mostly living in caves unless they were in the tropics. So even if humanity were to have a massive holocaust, and the few survivors went back to being hunter-gatherers living in animal skins, the arctic ice would still continue retreating.
Gras Albert says: January 7, 2013 at 12:42 am
Hmmmm, perhaps the graph is not as clear as I thought, 🙂
It’s a plot of ‘ten year’ trends, i.e. the oldest decadal trend starts in 1987 and finishes in 1996, the most recent starts in 2003 and finishes in 2012, it is current through 2012. The graph shows that the rate of warming per decade peaked in 1992 and has decreased every decade since with all but UAH now showing decadal cooling…
Got it. I think it would need a bunch of explanation and background to support it, as the knee-jerk reaction, which was admittedly mine, is that the data is cherrypicked. Perhaps if you did it as a family of graphs showing the full trend and decadal trend for each record, (or perhaps one for the satellite records and one for the surface records), which then builds up to your final graph, it would be clearer. Also, you would need to copiously document the process and data sources used, ideally mirroring the results using a publicly available resource, as your graph is bound to garner howls and intense scrutiny from those who disagree with what it illustrates. If you are interested and open to investing the time, I would be happy to help you develop it into an article, once we complete this article and a few others in the works.
Werner Brozek says: January 6, 2013 at 9:45 pm
I just thought of an addition to my earlier email. I added two lines to the graphic that I put up before to show the +/- parts of the 95% uncertainty. Does this look better:
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1990/detrend:0.3128/trend/plot/rss/from:1990/detrend:-0.3128/trend/plot/rss/from:1997/trend
I’d be inclined to put all three versions in as links and use this one;
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1997/trend
as the image.
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…
CoRev says: January 6, 2013 at 6:17 pm
This is another example of how to show temp Vs Co2 http://woodfortrees.org/plot/rss/from:1980/to:2013/scale:50/plot/esrl-co2/from:1980/to:2013/offset:-350/plot/rss/from:1998/to:2013/scale:50/trend/plot/esrl-co2/from:1998/to:2013/offset:-350/trend/plot/uah/from:1998/to:2013/scale:50/plot/uah/from:1998/to:2013/scale:50/trend
I like the inclusion of CO2 in at least one of the header graphics.
Werner, what do you think about creating a introductory and/or concluding chart that includes CO2, along with the key temp trends? We could draft a paragraph or two in support, which discusses what it illustrates in dry and academic terms.
Lance Wallace said (January 6, 2013 at 5:20 pm)
“…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…”
The length of time for trend analysis may not be there, but it might be useful as a “control” – that is, which of the seven listed sources is the closest match to sites that are “well-administered sites meeting all NOAA/WMO criteria”.
woodfortrees (Paul Clark) says: January 7, 2013 at 8:42 am
OK, I consider myself chivvied 🙂
We prefer pursued with diligence and rigor… 🙂 BTW, brilliant website. Thank you for your contributions to the advancement of human knowledge.
First up, WTI has now been updated to use UAH 5.5 (that’s why it was stuck in August, because 5.4 stops then).
Most appreciated.
For adding CRN / NOAA and anything else, I need:
– URL to data source file in moderately sane text format (I’m used to reading most format horrors now, but basically it needs monthly anomaly data)
– Credit information as in the current credits page
If people can find these details and either post here or mail me it makes it much easier to add rather than a vague wishlist.
Is what Walter Dnes provided for NOAA:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_ocean.90S.90N.df_1901-2000mean.dat
along with this credit page;
http://www.ncdc.noaa.gov/cmb-faq/anomalies.php
sufficient for your purposes? The Monthly Global (land and ocean combined into an anomaly) Index can be found towards the bottom of the above page, more easily linked to from here:
http://www.ncdc.noaa.gov/cmb-faq/anomalies.php#anomalies
Also here’s GHCN-M version 3.2.0 Technical Report on their newest version:
http://www1.ncdc.noaa.gov/pub/data/ghcn/v3/techreports/Technical%20Report%20NCDC%20No12-02-3.2.0-29Aug12.pdf
We’ll keep working on CRN to see if we can find it or put it in a “moderately sane text format”. If there’s anything we can help you with, now or in the future, please let us know, and we’ll be happy to help.
Walter Dnes says: January 7, 2013 at 5:16 pm
Click the pic to view at source[/caption]
Click the pic to view at source[/caption]
Make that 18,000 years. Another graphic we need is the retreat of ice since the peak of the last ice age.
The best I’ve got is 140,000 Years Antarctic/Vostok;
[caption id="" align="alignnone" width="578"]
carried into 11,000 years GISP2 Temperature Since 10700 BP with CO2 from EPICA DomeC:
[caption id="" align="alignnone" width="578"]
both of which will be included in the forthcoming WUWT Paleoclimate Reference Page.
Monckton of Brenchley says:
January 7, 2013 at 9:00 am
It is particularly important to provide a single, bold, accurate, visually-clear image that will reproduce well on TV and in the news media.
justthefactswuwt says:
January 7, 2013 at 5:43 pm
I like the inclusion of CO2 in at least one of the header graphics.
Can we build on what I have reproduced below?
I do not know if UAH and RSS can be easily combined, however if they can, then the period from December, 1997 to the present would be extremely close to no change. The positive slope for UAH is 0.00495983 per year but the negative slope for RSS is -0.00464267 per year. The difference is about 0.0003 per year. This would be flat for all intents and purposes. If this straight line is then superimposed on the CO2 change as shown, it would look dramatic. We could then show the graph with a bold headline:
SATELLITE DATA SHOWS NO CHANGE FOR 15 YEARS AS CO2 CLIMBS
This would be followed by the following, perhaps:
http://www.woodfortrees.org/plot/rss/from:1997.9/plot/rss/from:1997.9/trend/plot/uah/from:1997.9/plot/uah/from:1997.9/trend/plot/esrl-co2/from:1997.9/normalise/offset:0.25/plot/esrl-co2/from:1997.9/normalise/offset:0.25/trend
Henry@werner
current data on UAH simply still is wrong as it (completely) differs from all other datasets (going in the opposite direction) and might give the wrong impression that there is a possibility of warming. However, there is no warming. I checked this with my own sample of 47 stations.
Why not work out the average deltaT anomalies coming from all data sets, satellite or not,
and same presentation as at the end of your last post?
I think that would be neat.
Walter / JTF: Thanks for the NOAA/NCDC links, that’s exactly what I need and should be easy to add.
Larry: Noted your concerns about colour blindness, and interesting that line width would help – I’ll add a line width selector to the wishlist.
To answer Werner’s / Monckton’s question about averaging UAH & RSS it isn’t possible yet on WFT itself, although I did have in mind adding some tricks allowing combination of series with a simple stack-based system (think RPN, Forth, Postscript or JVM according to age, applied to entire series).
In the meantime, however, would it not be better to use WTI, which includes HADCRUT3 (currently, I’m wondering if I should shift to 4) and GISTEMP as well as RSS + UAH – so two land and two satellite datasets…
OK, that all said, maybe it’s time to cash in some reputation points here: I’m a little worried about where this analysis is leading and the conclusions that may be drawn from it by others… OK, maybe we can demonstrate a lack of statistically significant warming in global surface/LT temperatures for N years, and maybe N is getting surprisingly large. It would be quite another thing to derive from this that “global warming has stopped” (there may be other heat reservoirs, and there certainly are longer term cyclical processes at work *), let alone any stronger political statements about the value of energy efficiency measures etc. I know people haven’t been doing this in this thread, but just tread carefully, please.
(*: actually the many layers of cycles is where my real interest lies, and the reason I built WoodForTrees in the first place)
Here is a style of plot that I think may be more suited to your needs. It is a color map of all possible trends you could create over a period of time, and uses fading out to show the limits of significance. The axes are start point (y) and end point(x). To look at all trends ending at the present, you just follow down the right axis. But it puts it in the context of other periods too.
You can choose different datasets and time periods – I’ve shown Hadcrut 1989-2010 here. You can also show the plots without shading, and plots of the CI’s.
Paul Clark (wood for trees) says
….where this analysis is leading…
*: actually the many layers of cycles is where my real interest lies, and the reason I built WoodForTrees in the first place)
Henry says
The measurements with the correct science will show the truth?
I agree with you that there could be a number of cycles playing, but I found that one of the main cycles is that of the 88 year Gleisberg cycle which duly causes the ca. 90-100 year weather cycle as identified even in ancient history.
I don’t know if you figured out our current position within that cycle?
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
Note that the energy-in over the whole of that cycle is basically zero but we have now entered the cooling part which I expect to be rather spectacular, i.e. showing global cooling rather than global warming, (although some places on earth run opposite the wave due to increased clouds and precipitation.)
Perhaps you should extend the time line back so that the data covered would be statistically significant.
Lower up:
At January 8, 2013 at 3:55 am you say
I say, perhaps you, Lower up, should learn from the well-deserved trouncing you received on the thread at
http://wattsupwiththat.com/2013/01/04/the-dr-david-viner-moment-weve-all-been-waiting-for-a-new-snow-record/
and learn to think before making a post.
Richard
woodfortrees (Paul Clark) says: January 8, 2013 at 1:53 am
OK, that all said, maybe it’s time to cash in some reputation points here: I’m a little worried about where this analysis is leading and the conclusions that may be drawn from it by others… OK, maybe we can demonstrate a lack of statistically significant warming in global surface/LT temperatures for N years, and maybe N is getting surprisingly large. It would be quite another thing to derive from this that “global warming has stopped” (there may be other heat reservoirs, and there certainly are longer term cyclical processes at work *), let alone any stronger political statements about the value of energy efficiency measures etc. I know people haven’t been doing this in this thread, but just tread carefully, please.
No worries, the output from this exercise will be judiciously factual, and we’ll keep our eyes on the big picture. If fact, part of the reason for this exercise is to develop additional content for the next update of our Big Picture Look At “Earth’s Temperature”:
http://wattsupwiththat.com/2012/11/10/a-big-picture-look-at-earths-temperature-extreme-weather-update/
(*: actually the many layers of cycles is where my real interest lies, and the reason I built WoodForTrees in the first place)
There are so many layers of cycles. We’ve tried to capture as many as we could in the WUWT Potential Climatic Variables Reference Page;
http://wattsupwiththat.com/reference-pages/research-pages/potential-climatic-variables/
but there are decades, if not centuries, of research ahead of us before our understanding of Earth’s climate system moves beyond rudimentary.
woodfortrees (Paul Clark) says:
January 8, 2013 at 1:53 am
In the meantime, however, would it not be better to use WTI, which includes HADCRUT3 (currently, I’m wondering if I should shift to 4) and GISTEMP as well as RSS + UAH – so two land and two satellite datasets…
Thank you for your reply. When I use WTI, the slope for the last 15 years is 0.0018. (As per NOAA’s criteria). However the slope is flat for 12 years.
http://www.woodfortrees.org/plot/wti/from:1997.9/plot/wti/from:1997.9/trend/plot/wti/from:2000.9/trend
This slope of 0.0018 is an order of magnitude greater than the 0.0003 that I calculated for just the two satellite data, even though we are awaiting a more accurate version6 from UAH. It may be tempting to accuse us of using the data sets that suit our biases. However, despite issues with the latest UAH version, the land data sets have UHI issues, thermometer placement issues, time of day issues and perhaps questionable adjustment issues, etc.
If we were to have a temperature slope line going up at 20 degrees, and a CO2 line going up at 40 degrees, it may look like the CO2 is going up twice as fast and we may be accused of misrepresenting things due to the scale we use. That is one reason why I like a slope of 0.
Another reason I like a slope of 0 is that we do not have to explain something to the general public that may confuse the issue even more. When Phil Jones had his interview in February, 2010, he said the 0.12 C/decade warming was not significant at the 95% level over 15 years, and many papers made no attempt to explain the 95% significance and simply said “No warming for 15 years”. I talked to a person who believed in CAGW and he was very upset over the dishonesty of the reporters for this sort of headline. Ideally, I would like a headline that is short and true and to the point with no explanation required where “No warming for 15 years” means exactly that.
Very, very tempting. In fact I’m afraid you may have just handed people who want to shoot this down a missile launcher and a couple of cases of heat seekers. 🙂
henry says
http://www.woodfortrees.org/plot/wti/from:2002/plot/wti/from:2002/trend
increasing the “no warming” trend as global cooling sets in, clearly, in the end, will eventually lead to a misrepresentation of science; people will stop worrying about global warming forgetting that global cooling also needs attention,
i.e.
As the farmers in Anchorage have noted,
http://www.adn.com/2012/07/13/2541345/its-the-coldest-july-on-record.html
the cooling is so bad there that they do not get much of any harvests.
And it seems NOBODY is telling them there that it is not going to get any better. The cooling will last until 2030-2040. See here:
http://wattsupwiththat.com/2012/11/19/cooling-in-the-near-future/
The sad story is, that as we enter 2013, and where the world should prepare itself for climate change due to (natural) global cooling,
for example, by initiating more agricultural schemes at lower latitudes (FOOD!),
and providing more protection against more precipitation at certain places (FLOODS!),
the media and the powers-that-be are twiddling with their thumbs, not listening to the real scientists,
e.g. those not making any money and nice journeys out of the gravy train that “global warming” has become.
Therefore: be careful of being apologetic: in the end the truth will suffer
always depict the results as they are.
If you use the 11 or 12 year trend, explaining it shows all positive and negative coming from the sun, in one solar cycle, it would show the real trend, as I see it coming;
for 2013 I predict that as you throw off one month each time at the beginning, and add the new month at the end, the (visible) negative trend during one solar cycle time period will increase.
You want to bet?
It helps in two ways. In some cases if the color sample is large enough I can figure out the color by eye with careful examination (red green color blind are not truly “color blind” we just see some colors with much lower intensity than those with normal color vision. That means colors who differ by slight differences are very difficult assign a color name too). In other cases I use a colorblind assist tool like “whatcolor4” which uses a color picker to select a sample of something and then I can compare that reading with a color sample from the key and work out which color is which. Color dithering makes this more difficult on thin lines, and thicker lines it is much easier to get a 3×3 pixel or 5×5 pixel sample which will give a true color sample.
http://www.visibone.com/colorblind/
http://safecolours.rigdenage.com/
Larry
woodfortrees (Paul Clark) says:
January 8, 2013 at 9:54 am
Very, very tempting. In fact I’m afraid you may have just handed people who want to shoot this down a missile launcher and a couple of cases of heat seekers. 🙂
Sometimes you just cannot win! A few months ago I was challenged to prove the slope was 0 for 15 years. I did so. But I was accused of cherry picking since the 15 years was before the big El Nino. Another person used less than 15 years and was accused of using less than 15 years!
By the way, RSS for December just came out and it dropped even more than UAH from November. It went to 0.101 from 0.195, or a drop of 0.094 versus a drop of 0.080 for UAH.
With the RSS anomaly for December at 0.101, the average for the twelve months of the year is (-0.060 -0.123 + 0.071 + 0.330 + 0.231 + 0.337 + 0.290 + 0.254 + 0.383 + 0.294 + 0.195 + 0.101)/12 = 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.
Earlier I had said RSS had a slope of 0 for 16 years. In about 7 hours I will know whether I have to add 1 or 2 months to this. I really appreciate that I can rely on the WFT update right on time. In contrast, the Hadsst2 for November is still not out!
Richards didn’t get a trouncing several posters agreed that the mechanism off AGW has feasible based on the fact the CO2 was a greenhouse gas, CO2 concentration is increasing in the atmospher, and the greenhouse effect increases as the concentration increases. Finally no one could dispute that humans were contributing to the CO2 in the atmosphere due to (among other thing) the combustion of fossil fuels.
NO ONE could show those facts were incorrect, even after lengthy discussion.
Lower up says:
“…and the greenhouse effect increases as the concentration increases.”
Wrong. Wrong! As I and others have repeatedly explained to you. That is simply an incorrect “fact”, which would falsify your conclusion if it wasn’t already deconstructed.
In reality, the ‘greenhouse effect’ decreases as the concentration of CO2 increases. Currently, a large rise in CO2 makes no measurable difference in global warming — which has stalled for the past decade and a half, while CO2 continues to rise. The link above shows exactly why this is.
DBoehm, with all due respect, you provided a graph that showed the greenhouse effect increased as the concentration of CO2 increased. As you pointed out the effect deminished at higher concentrations of CO2, but it still increased.
The reason I suggested extending the time line so that the data is statistically significant because it can be legitimately said that there has been no statistical cooling over that period. In fact it makes no sense to display incomplete day where you cannot draw a conclusion. If you do as I suggest, you could not be accused of misleading the readers.
DBoehm, I see how you have miss read your own graph, you are looking at the ppm on the x axis and the read the increase in temperature from the y axis. This is wrong wrong wrong as you say. You don’t honestly believe that the increase in temperature at 580 ppm raise the temperature by 0.02 degrees, whereas a concentration of 20ppm will give a increase of 1.7 degrees.
Each increase along the x axis is CUMULATIVE. The effect of each concentration should be added together. This is a simple process using calculus to calculate the area under the line (so showing it as a bar graph is misleading and probably caused your problem).
To Lord Monckton and others interested in combining RSS and UAH:
In an earlier post I said:
“I do not know if UAH and RSS can be easily combined, however if they can, then the period from December, 1997 to the present would be extremely close to no change. The positive slope for UAH is 0.00495983 per year but the negative slope for RSS is -0.00464267 per year. The difference is about 0.0003 per year. This would be flat for all intents and purposes.”
However RSS for December just came out and to update this:
The negative slope for RSS is -0.0049078 per year. The difference now is 5.2 x 10^-5. For all intents and purposes, this is 0. By the way, the December UAH is not yet in the form to be used by WFT. However that will have no effect since the December point is right on the slope line. 0.0049078 x 15 is 0.0735, so if I plot RSS from December, 1997; get the trend line; and then detrend it by -0.0735, I get a straight line.
It is not as good as automatically combining UAH and RSS since each has to be plotted separately, but the straight line with 0 slope can clearly be shown. See below for what this looks like.
http://www.woodfortrees.org/plot/rss/from:1997.9/plot/uah/from:1997.9/to:2013/plot/rss/from:1997.9/to:2013/detrend:-0.0735/trend
Would this be acceptable to you? Is there anything else you would like me to try out?
Lower up:
In this thread at January 8, 2013 at 4:05 am I advised you to learn from “the well-deserved trouncing you received” on another thread.
Your subsequent posts in this thread demonstrate that you are unwilling (unable?) to accept that advice. So, it seems you are another ‘Greg House’.
I strongly commend everybody to ignore your posts unless – as in the previous thread – they are so fallacious that they warrant rebuttal to avoid your errors misleading onlookers.
Richard
RichardCourtney, your explanation of the decrease in the greenhouse effect using light and increasing numbers of glass panes was very good, but it completely escaped DBoehm comprehension. He appears to think the greenhouse effect DECREASES as the concentration of carbon dioxide increases. Oh dear, when discussing the mechanism behind AGW, I assumed a little bit of understanding. I would have expected the more learned posters such as yourself and Davidmhoffer to have picked it up and corrected DBoehm’s fundamental error.
Richard, you are both mistaken in your critercism and advice. I have pointed out how DBoehm has misread his graph and come to the incorrect conclusion. You did not pick this up or if you did decided to remain mute in the matter. I understand why you have advised people to ignore me, it is embarrassing to you.
My point that the mechanism for AGW has merit. Namely:
Carbon dioxide is a greenhouse gas
Carbon dioxide concentration is increasing in the atmosphere
The increase in Carbon Dioxide concentration is increasing the greenhouse effect
Humans are increasing the amount of Carbon dioxide in the atmosphere
Repeatedly I have asked anyone to point out which of those four facts are incorrect and NO ONE has. This means the mechanism for AGW is valid.
Trying to hide this from the other poster is unfair to them. You should be advising them to read my posts so they can make up their own informed opinion of whether AGW is actually happening.
Lower up says: ” This means the mechanism for AGW is valid.” With the use of “the” you assume that it Is the primary/only source for warming. In light of the various graphs shown in this article and the comments, how do you explain the obvious divergence?
If you believe it is one of several possible sources for warming, then give us some rankings and actual empirical evidence of each of their numeric impacts.
Friends:
I pointed out that ‘Lower up’ was soundly trounced in the thread at
http://wattsupwiththat.com/2013/01/04/the-dr-david-viner-moment-weve-all-been-waiting-for-a-new-snow-record/
and, therefore, his repetition of the same refuted points should be ignored as a disruption of this thread.
‘Lower up’ says he was not trounced and his assertions were not refuted.
He was and they were.
To avoid repetition of the discussion of that thread in this thread, and to save people needing to refer back to that thread, I copy here a summarising post I provided on that thread.
Richard
==============
richardscourtney says:
January 6, 2013 at 6:48 am
D Böehm :
At January 6, 2013 at 5:44 am you say
Yes. You, I and David M Hoffer have repeatedly said that.
I provide an analogy in case there are any who fail to understand the matter.
A stone thrown into the ocean displaces some water and, therefore, raises sea level. Children throw stones into the sea every day, so children are raising sea level. But the effect of those stones on sea level is too small to be discernible. The effect of the stones is trivially small because it is insignificant against the natural variations in sea level (caused by surface waves, tides, seismic variations, ocean spreading, etc.). Hence, for all practical purposes children throwing stones into the sea can be said to not raise sea level although theoretically it does. Indeed, no sane person would stop children throwing stones into the ocean for fear of the resulting sea level change.
But ‘Lower up’ says (first at January 4, 2013 at 11:40 pm) that he will not accept there is no AGW unless it is shown that his “four facts” are incorrect; viz.
Thereafter, he pretends that we accept AGW is a real and present effect because we don’t dispute his so-called facts but point out that any such AGW is trivially small and indiscernible against natural variations.
His pretence is daft.
It has equal merit to his being asked if he disputes that children throwing stones in the sea causes sea level rise, and when he replies it is trivially small and indiscernible against natural variations, his being told he admits child-induced sea level rise is a real and present effect.
Richard
richardcourtney,
Yes, ‘Lower up’ cannot see his error. He states that “the greenhouse effect increases as the concentration increases.”
That is wrong, of course. The effect clearly decreases with added CO2. But some people are so captive to their belief system that they cannot see reality.
DBoehm, you are not telling the truth for the simple fact that the temperature does not go below the x axis in your graph as the concentration of carbon dioxide increases.
You have simply miss understood your own graph and you persist in repeating your incorrect conclusion. Why?
Richard, your acceptance of a mechanism for AGW is a relief.
You then state it is trivial and use an apology of a child throwing stones into the sea. I am interested in understanding your logic in how you come to this conclusion? Could you provide your evidence please?
Corev, please show me where I have said it is the only CO2 is the only source of temperature change. Stop making things up.
My thoughts on matter are that it is a complex system, that is why each day and each year doesn’t have the same weather.
That is why you have to look at trends in change and to look at that meaningfully you use stats.
In light of the graphs, I will answer your question when you show me what has happened over a significantly significant period of time. The graphs don’t extend long enough to say what the trend in temperature is.
Lower up says
Oh dear, when discussing the mechanism behind AGW,
Henry says
on the off chance that you are not in fact trying to hi jack this thread, I show you here that nobody has in fact proven – in the correct dimensions – that the net effect of more CO2 in the atmosphere is that of warming rather than that of cooling.
I challenge you to answer the questions at the end of this blog post,
http://blogs.24.com/henryp/2011/08/11/the-greenhouse-effect-and-the-principle-of-re-radiation-11-aug-2011/
namely
From all of this, you should have figured out by now that any study implying that the net effect of more CO2 in the atmosphere is that of warming, must exhibit a balance sheet in the right dimensions showing us exactly how much radiative warming and how much radiative cooling is caused by an increase of 0.01% of CO2 that occurred in the past 50 years in the atmosphere. It must also tell us the amount of cooling caused by the increase in photosynthesis that has occurred during the past 50 years.
There are no such results in any study, let alone in the right dimensions.
Lower up says:
January 9, 2013 at 12:43 pm [ … ]
It is clear that ‘Lower up’ is borderline insane. Against all empirical evidence, ‘Lower up’ wrongly asserts that the greenhouse effect INCREASES as the concentration of carbon dioxide increases. That is flatly contradicted by the facts. In reality, as CO2 rises, it’s warming effect diminishes at a logarithmic rate.
So as everyone except ‘Lower up’ can clearly see: as CO2 concentration increases, it’s effect DECREASES — exactly the opposite of what ‘Lower up’ claims.
Once in a while we run into a lunatic like ‘Lower up’, who cannot grasp simple scientific facts. ‘Lower up’ has no common sense, so he cannot understand that simple chart, which proves conclusively that ‘Lower up’ is wrong. His mental state is such that he cannot admit that the effect of CO2 decreases as the concentration rises; each CO2 molecule has less effect than the preceding one. If ‘Lower up’ admitted the truth, his CO2=CAGW conjecture would be falsified. So he misrepresents the science.
richardscourtney says:
January 5, 2013 at 4:17 am
Lower up:
It is a new dawn and a new day so I have returned.
At January 4, 2013 at 4:56 pm you asked me
At January 4, 2013 at 5:21 pm I replied saying
And at January 4, 2013 at 11:40 pm you replied to that answer by saying to me
“Sort of”!?
Pray tell, what more clear and all-embracing answer could I have given than “ANY”?
I think you need to question your motivations because it seems you are not capable of accepting undeniable truths which do not fit your belief.
Having answered your question I reciprocated by listing some of the evidence that refutes there is any discernible AGW and I asked you
You claim to have answered my question but you have not: instead, you demonstrate that your belief in AGW is not related to evidence but is pure superstition.
You say
I address each of your “facts” in turn.
Your fact 1.
Carbon dioxide is a greenhouse gas, but so what?
Your fact 2.
The atmospheric CO2 concentration is increasing, but so what? This is good for the biosphere.
Your fact 3.
At present levels of atmospheric CO2 concentration any increase to atmospheric CO2 concentration will have trivial increase to the greenhouse effect: the effect on global temperature is so small as to be indiscernible.
Clearly, you are not aware that each additional unit of CO2 added to the air has less effect than its predecessor. This reducing effect is logarithmic. Think of it this way.
Light enters a room through a window. A layer of paint over the window pane reduces the light entering the room. A second layer of paint also reduces the light entering the room but the reduction is less than for the first layer. A third layer has even less effect.
IR from the Earth’s surface is entering space via the atmosphere. CO2 is a greenhouse gas (GHGs) and in the atmosphere it absorbs IR in two narrow wave bands (at 25 micron and 4 micron) with almost all that absorbtion being in the 15 micron band. There is much CO2 in the atmosphere so adding more CO2 has negligible effect on the atmosphere.
Additional atmospheric CO2 has as trivial an effect as adding a seventh layer of paint on the window: see
http://c3headlines.typepad.com/.a/6a010536b58035970c0115707ce438970b-pi
and
http://wattsupwiththat.files.wordpress.com/2010/03/heating_effect_of_co2.png
Your fact 4.
I don’t know what has caused the recent increase to atmospheric CO2 concentration, but I want to know. And anybody who thinks they know is mistaken because available data permits either an anthropogenic or any of several natural causes to be attributed.
(ref. Rorsch A, Courtney RS & Thoenes D, ‘The Interaction of Climate Change and the Carbon Dioxide Cycle’ E&E v16no2 (2005) ).
Hint: you may want to notice the second author in the reference.
Anyway, nature emits 34 molecules of CO2 into the air for each molecule of CO2 emitted by human activities. And CO2 is essential for life on Earth. It is a very strange assertion that a tiny increase will convert the ‘stuff of life’ into the ‘destroyer of worlds’ especially when life flourished on Earth when atmospheric CO2 was much higher than now. Perhaps you would consider how that strange assertion can be justified?
In summation:
1.
I listed some of the evidence which refutes the existence of discernible AGW and I asked you,
“How much more evidence do you need before you reject the AGW-scare?”
2.
You have not mentioned any potential evidence that would cause you to reject the scare.
3.
You have stated ‘facts’ which are not pertinent to the existence of discernible AGW but which you say need to be refuted for you to recant your belief in discernible AGW.
4.
Your “facts” are clearly the foundation of your superstitious belief in discernible AGW which has no supporting evidence and which is denied by much empirical evidence.
You then try to claim that a list of organisations which endorse the AGW-scare somehow indicates the majority of scientists accept AGW. NO! It does not.
Firstly, the number of scientists who accept or reject is a political – not a scientific – point. As Einstein famously said when told that 100 scientists had rejected his “Jewish science”,
“It would only require one of them to provide one piece of evidence if I were wrong.”
Secondly, that organisations endorse AGW is the logical fallacy of ‘Appeal to Authority’. It says nothing about the truth of a matter. Indeed, the great benefit of the Enlightenment was the replacement of statements from Authority with acceptance of empirical evidence.
Thirdly, the organisations represent the ‘interests’ of their members. Governments support AGW so provide funding for AGW research. Few Executive Committees of organisations will make statements which amount to, “Stop funding our members”.
Fourthly, the organisations’ statements are not an indication of what the members of the organisations think. No polls of the members have been taken and when given the opportunity tens of thousands of them have rejected AGW; e.g the Oregon Petition.
And you have been misled about the Oregon Petition. Signatories had to print a response from their computer, personally sign it, then post it by snail-mail at their own expense. Each signatory was then checked individually before being added to the list. Also, those 30,000+ signatories consisted solely of Americans and, therefore, are ‘the tip of the iceberg’.
Fifthly, the Executives of science organisations have been usurped by activists. Richard Lindzen details this – and names names – in a fascinating and shocking paper that can be read at
http://www.lavoisier.com.au/articles/climate-policy/science-and-policy/LindzenClimatescience2008.pdf
Lower up, you really need to learn about the AGW-scare because it seems you have been duped by propagandists.
Richard
I must say I am not impressed by how this thread has been hijacked.
However
D Boehm Stealey says:
January 9, 2013 at 1:19 pm
each CO2 molecule has less effect than the preceding one
Lower up says:
January 8, 2013 at 6:26 pm
As you pointed out the effect diminished at higher concentrations of CO2, but it still increased.
In the above, you are both saying the same thing and you are both right!
Let me put it this way. Suppose the CO2 went up from 280 to 300 and this resulted in the temperature to go up by 0.02 degrees C. Then suppose the CO2 went up from 380 to 400 and this may cause the temperature to go up by only 0.01 C.
Apparently you would both agree with a decrease, whatever its magnitude might be. Right? It is just that D calls 0.01 a decrease from 0.02 and L calls 0.01 an increase over 0.000.
But the bottom line is: Who cares if the earth warms by 0.1 C if CO2 is doubled? Now whether or not the 0.1 for a doubling is correct or not is a matter of debate.
Friends:
My post which is here in this thread at January 9, 2013 at 1:55 pm is a copy of a post I provided to ‘Lower up’ in the thread at
http://wattsupwiththat.com/2013/01/04/the-dr-david-viner-moment-weve-all-been-waiting-for-a-new-snow-record/
It is one of several posts from several people which explained matters to him in that thread but which – at January 9, 2013 at 12:47 pm – in this thread he claims not to know.
He is either an idiot or a troll. In either case, he disrupted the other thread, and seems to want to disrupt this one.
Richard
Werner Brozek says:
“…you are both saying the same thing and you are both right!”
Does that mean we both get a prize?☺
Anyway, I suppose that means I didn’t make myself clear, so I’ll try again:
Each subsequent CO2 molecule emitted has a smaller warming effect than previous CO2 molecules. It’s the analogy of repeatedly painting a window: each coat of paint lets in less light than the previous coat. Eventually, another coat of paint makes no measurable difference. Thus, the effect of CO2 diminishes as the atmospheric concentration of CO2 rises. Is that better?
[Sorry about the O/T. That eventually happens in most threads as they age.]
DBoehm, much better and a good analogy.
Monckton of Brenchley says:
January 7, 2013 at 3:29 pm
Mr Shehan attributes to me a statement that I did not make. Some 40 per cent of the CO2 in the air is anthropogenic, not the 3 per cent that Mr Shehan attributes to me.
Thank you for the reply. The only sense in which I attributed the 3% to you was in that I found that this sentence was confusing in that it seemed to suggest this and asked for a clarification:
‘Philip Shehan says:
January 7, 2013 at 12:56 pm
Monckton of Benchley says:
“Today’s high CO2 levels – the 97% natural and the 3% human-released”
This may lead people to conclude that human activities have added only 3% to atmospheric CO2. In the interests of clarity, Monckton should point out that the 97% natural contribution refers to CO2 being recycled through the biosphere, whereas the 3% is that added to the atmosphere by the burning of fossil fuels which has seen the CO2 concentration rise from 280 ppm at the beginning of the industrial revolution to 390 ppm today This is a rise of 39%.’
We are afte rall in agrement that the anthropogenic CO2 content is 40%. As the 97% vs 3% figure is frequently given, and I am sure many other than myself misinterpret this statement, can you explain to me what you understand is meant by it. Can you also suggest an expalnation the other difficulty I had with this:
“I am also unclear about what time period the 3% covers. According to the following sources, the rise in atmospheric carbon was only 2.0 ppm in the decade 2000-2009, which is only a 0.52% rise over that period.”
Thank you again and hoping you can help
Phil, I have been discussing the mechanism behind AGW with several other posters. Two posters (DBoehm and RcihardCourtney) presented the idea that humans contributed a negligible amount CO2 into the atmosphere.
According to the good lord they are incorrect. So another of the four facts underpinning the mechanism for AGW is confirmed.
Lower up:
Your post at January 9, 2013 at 7:49 pm says in total
That explanation and analogy has been presented to you repeatedly on WUWT.
It was first put to you personally by me in another thread days ago. And I copied that post to this thread where it can be seen above at January 9, 2013 at 1:55 pm. The analogy is provided in that post in the answer to your “Your fact 3”.
You are an egregious troll who is deliberately disrupting several WUWT threads by repeatedly posting the same fallacious points and pretending they have not been answered.
GO AWAY!
Richard
Lower up:
Your post at January 10, 2013 at 3:01 am is another example of your posting a fallacious point which has repeatedly been rebutted for you on WUWT.
Stop your egregious disruption of WUWT threads with your nonsense. GO AWAY!
Richard
REPLY: Richard, this is my blog not yours. You are out of line to make that call. The choice is mine, not yours. – Anthony
Anthony:
At January 10, 2013 at 3:36 am you say to me
Of course you are right. I stand corrected and I apologise.
Also, prior to seeing your admonition to me, on another thread I made the same objection to Lower up. I anticipate it being snipped and take no offence in the light of your admonition.
As explanation, my making that call is frustration at Lower Up persistently pretending that points I and others had answered for him had not been made. I need more tolerance of trolls.
Richard
Werner, per my email, the potential changes/additions to this article that you might want to consider include tto:
– Write Title e.g. Monthly Atmospheric Temperature Trend Update – Pause in RSS Satellite Temperature Trend Reaches 16 years.
– Write a brief/paragraph introduction that helps to introduce, explain and summarize what your article shows
– Write a brief/paragraph conclusion that helps to conclude, explain and summarize what your article shows.
– Make the name of each data sources 1 – 7 in Section 1 links to the associate source chart for each data source.
– Adding in a entry for the WFT Index into Section 1
– Using data from KNMI Climate Explorer http://climexp.knmi.nl/selectannualindex.cgi?id=someone@somewhere for Section 2, rather than Skeptical Science, if feasible, per
cementafriend says: January 6, 2013 at 6:20 pm .
– Making Section 3 into a table format per Ockham says:January 6, 2013 at 6:03 pm
– Adding in a graph that shows CO2 versus each or some combination of the temperature data, e.g.CoRev says: January 6, 2013 at 6:17 pm;
http://woodfortrees.org/plot/rss/from:1980/to:2013/scale:50/plot/esrl-co2/from:1980/to:2013/offset:-350/plot/rss/from:1998/to:2013/scale:50/trend/plot/esrl-co2/from:1998/to:2013/offset:-350/trend/plot/uah/from:1998/to:2013/scale:50/plot/uah/from:1998/to:2013/scale:50/trend
Possibly display the entire satellite record, but only the temp trend for the period that it’s been flat.
– Build out the Appendix with a succinct analysis for each data set, similar to what you already did already for RSS, such that it’s readers can view the data however they prefer. Include links to these charts
– http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1997/trend
– http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1990/detrend:0.3128/trend/plot/rss/from:1990/detrend:-0.3128/trend/plot/rss/from:1997/trend
You might want to exclude the monthly figures in order to make the Appendix cleaner and less burdensome to keep up.
Please let me know if you have any questions or would like help in implementing any of the potential changes/additions.
Werner
Also, in Section 1, we might want to add a little more description to each item, e.g.
UAH: [Has been flat or Has no slope or Has paused or etc.] since October 2004 or 8 years, 3 months (goes to December)
Werner
Below I’ve drafted and updated Section 1 that add links to each source, expand the naming convention to make it easier for readers to evaluate the source of each data set and adds the phrase “has paused” as this seems to be the budding meme to refer to it, i.e. in the Guardian Jan 9th“has the rise in temperatures ‘paused’?” and Daily Mail Jan 12th “on Tuesday, news finally broke of a revised Met Office ‘decadal forecast’, which not only acknowledges the pause, but predicts it will continue at least until 2017.” Please let me know your thoughts on the suggested changes below. I think I am going to include your Section 1 in the introduction to the forthcoming Big Picture update, e.g.:
1. University of Alabama in Huntsville (UAH) Troposphere Temperature has paused since October 2004 or 8 years, 3 months (goes to December)
2. Remote Sensing Systems (RSS) Troposphere Temperature has paused since January 1997 or 16 years (goes to December) RSS is 192/204 or 94% of the way to Ben Santer’s 17 years.
3. NASA Goddard Institute for Space Studies (GISS) Surface Temperature has paused since May 2001 or 11 years, 7 months (goes to November)
4. Hadley Center (HADCRUT3) Surface Temperature has paused since May 1997 or 15 years, 7 months (goes to November)
5. Hadley Center (HADCRUT4) Surface Temperature: has paused since December 2000 or an even 12 years (goes to November.)
6. Hadley Center (HADSST2) Sea Surface Temperatures has paused since March 1997 or 15 years, 8 months (goes to October)
7. Wood For Trees Temperature Index has paused since December 2000 or 11 years, 9 months (goes to August)
I understand the reasoning of justthefacts but eventually lengthening the period of the pause on and on will lead to giving the wrong impression that there is no global cooling. If you don’t like the idea of including one solar cycle (12 years) for the trendline then a longer period could be chosen, e.g. 17 years. As long as the time point where you draw the trendline stays constant.
I would also exclude UAH seeing that it does not correspond to any dataset.
Well JTF,
It is confession time for me! Do you remember Phil Jones saying he cannot work excel? I can’t either! Perhaps we should take advantage of others with much more expertise than me such as David Hoffer or Walter Dnes. It has been a long time since I made any table and I am not even sure if my home computer can even do it.
“Ockham says:
January 6, 2013 at 6:03 pm
Nice job Werner,
IMO, Section 3 would be more easily compared if in the form of a table. Each data set could be represented by a row. Column headings could be Rank, Warmest Year, Warmest Year Anomaly Value, Highest Monthly Anomaly month/year, HMA Value, 2011 Anomaly, 2011 Rank.”
You liked his idea and I do too. If any one wants to make a table, here are the latest data. If other data becomes available over the next few days, I will post it here as soon as I can.
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 December at 0.342, the average for the twelve months of the year is (0.203 + 0.230 + 0.241 + 0.292 + 0.339 + 0.351 + 0.385 + 0.440 + 0.449 + 0.432 + 0.399 + 0.342)/12 = 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.
With the RSS anomaly for December at 0.101, the average for the twelve months of the year is (-0.060 -0.123 + 0.071 + 0.330 + 0.231 + 0.337 + 0.290 + 0.254 + 0.383 + 0.294 + 0.195 + 0.101)/12 = 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.
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.
As for the SkS site, I have not been able to get KNMI to work in order to get the maximum number of years of no significant warming. Even climate4you did not help.
“SRJ says:
January 6, 2013 at 3:40 pm
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.”
Could we ask this person for help? Or should we ignore this part or should we use SkS again?
Other than these items, I should be OK with everything else and I expect to post what I can by tomorrow night.
I would like to elaborate on combining RSS and UAH to see how far back the slope is 0. Since December, 1979 the slope for RSS is +0.00496208, and the slope for UAH is -0.00490787. The difference is 0.00005421. Assuming this difference gets divided between the two, the slope, if the two were combined, it would be 0.000027/year. SkS , giving things to the nearest 1/1000 per decade would round 0.00027 to 0.000. Also, UAH and RSS have been nosediving lately; but even if we assume the same rate in January as in December, the slope should be negative by now. At this point, while the slope is 0 for 15 years and 1 month, my inclination would be to not mention the extra month now, but to keep a close eye on it. If both continue to nosedive in January, then we could have a 0 slope for and additional 2 or 3 months, which, in my opinion, would be worth mentioning. See the graph below. Should all three slope lines be shown or just the middle straight one?
http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend/plot/uah/from:1997/plot/uah/from:1997.9/trend/plot/rss/from:1997.9/trend/detrend:-0.0735/offset:-0.080/plot/esrl-co2/from:1997.9/normalise/offset:0.68/plot/esrl-co2/from:1997.9/normalise/offset:0.68/trend
How is this for an eye catching title for the above:
SATELLITE DATA SHOWS NO CHANGE FOR 15 YEARS AS CO2 CLIMBS
Werner
It is confession time for me! Do you remember Phil Jones saying he cannot work excel? I can’t either!
No need for Excel, this is all in HTML, i.e.:
http://www.w3schools.com/html/html_tables.asp
I’ll email the code, it’s just a matter of adding more rows and columns.
As for the SkS site, I have not been able to get KNMI to work in order to get the maximum number of years of no significant warming. Even climate4you did not help.
I guess that we stick with SkS, keep a close eye out for abnormalities and possibly include a brief notation/warning about the source?
Should all three slope lines be shown or just the middle straight one?
http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend/plot/uah/from:1997/plot/uah/from:1997.9/trend/plot/rss/from:1997.9/trend/detrend:-0.0735/offset:-0.080/plot/esrl-co2/from:1997.9/normalise/offset:0.68/plot/esrl-co2/from:1997.9/normalise/offset:0.68/trend
I think it looks good as is.
How is this for an eye catching title for the above:
SATELLITE DATA SHOWS NO [Temperature]CHANGE FOR 15 YEARS AS CO2 CLIMB[ed][Rapidly]
Good title, I added a couple potential descriptors in brackets. Also, I’d avoid all caps, as it is perceived as YELLING by some 🙂
HenryP says: January 12, 2013 at 10:35 pm
I understand the reasoning of justthefacts but eventually lengthening the period of the pause on and on will lead to giving the wrong impression that there is no global cooling.
Baby steps, if we can change the conversation from “rapid global warming” to we are in a “pause”, we are at least closer to reality. Assuming that temperatures continue to decline, then in the future we can start to message that the “dip” or “decline” has been occurring for X years, e.g.:
http://www.woodfortrees.org/plot/rss/from:2002/plot/rss/from:2002/trend/plot/uah/from:2002/plot/uah/from:2002/trend/plot/rss/from:2002/trend/detrend:-0.0735/offset:-0.080/plot/esrl-co2/from:2002/normalise/offset:0.68/plot/esrl-co2/from:2002/normalise/offset:0.68/trend
If you don’t like the idea of including one solar cycle (12 years) for the trendline then a longer period could be chosen, e.g. 17 years. As long as the time point where you draw the trendline stays constant.
Aside from the issue you raise above, which we’ll address when the time comes, I don’t see the advantage of a fixed period versus the data set specific periods the Werner is using. Are there any other advantages to the approach you propose?
I would also exclude UAH seeing that it does not correspond to any dataset.
We’ve been using UAH for years, we can’t just abandon it because it now appears discordant with the other datasets. Spencer and Christy are aware of the differences, i.e.;
http://www.drroyspencer.com/2012/11/uah-v5-5-global-temp-update-for-october-2012-0-33-deg-c/
and seem to think it is justified/accurate, thus I see no basis to exclude UAH.
Testing table format
Data Source
Jan
Feb
Mar
UAH
-0.134
-0.135
0.051
RSS
-0.060
-0.123
0.071
Had4
0.288
0.208
0.339
justthefactswuwt says:
January 13, 2013 at 6:07 pm
No need for Excel, this is all in HTML, i.e.:
http://www.w3schools.com/html/html_tables.asp
I got it to work, but it looks like the only way I can get it to you is by email.
By the way, the GISS site is back up, but instead of having the data for December, they even deleted the November data and published last month’s values.
.justthefacts wuwt says
…..if we can change the conversation from “rapid global warming” to we are in a “pause”, we are at least closer to reality. Assuming that temperatures continue to decline, then in the future we can start to message that the “dip” ……
the problem with that is that we are not helping those that are suffering…e.g.
http://www.tutiempo.net/clima/Anchorage_Elmendorf_Air_Force_Base/702720.htm
these data show severe cooling in Anchorage that has affected farming in Anchorage
(tomatoes etc.)
and nobody is telling those poor farmers that it is not going to get better…
Hello JTF,
The link for the RSS from Lubos is brand new from last time as he has now incorporated 2012. GISS, Hadcrut3, Hadcrut4 and of course WTI are not in for December. As soon as anything comes, I will let you know. Or if it comes Saturday, I can always post an update as a comment. Right after this, I will post my total entry. Please let me know if I missed anything and do not hesitate to improve any wording as that is not a big strength of mine. :- )
Has Global Warming Stalled?
Satellite Data Shows No Temperature Change for 15 Years as CO2 Climbed Rapidly
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 at:
http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2008-lo-rez.pdf
In this parts below, we will present you with just the facts and then you can decide 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 date that data is available on WoodForTrees.com (WFT). 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 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, 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 a 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 December 2000 or an even 12 years. (goes to November.)
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 December 1996 or 16 years and 1 month. (goes to December) RSS is 193/204 or 94.6% of the way to Ben Santer’s 17 years.
8. For a combination of the satellite data, namely RSS and UAH, the slope is flat since December 1997 or 15 years and 1 month. (goes to December)
The next link shows just the lines to illustrate #1 through #7 above. Think of it as a sideways bar graph where the lengths of the lines indicates the relative times where the slope is 0.
http://www.woodfortrees.org/plot/hadcrut3gl/from:1997.33/trend/plot/gistemp/from:2001.33/trend/plot/rss/from:1996.9/trend/plot/wti/from:2000.9/trend/plot/hadsst2gl/from:1997.1/trend/plot/hadcrut4gl/from:2000.9/trend/plot/uah/from:2004.75/trend
The next link shows #1 through #5 above, but this time, the actual plotted points are shown along with the slope lines.
http://www.woodfortrees.org/plot/hadcrut3gl/from:1997.33/trend/plot/gistemp/from:2001.33/trend/plot/wti/from:2000.9/trend/plot/hadsst2gl/from:1997.1/trend/plot/hadcrut4gl/from:2000.9/trend/plot/hadcrut3gl/from:1997.33/plot/gistemp/from:2001.33/plot/wti/from:2000.9/plot/hadsst2gl/from:1997.1/plot/hadcrut4gl/from:2000.9
The next link illustrates #8. Up to the present time, UAH has a positive slope from December 1997, however RSS has a virtually identical negative slope over the same time. So if we were to combine both satellite data sets, they would show virtually no slope since December, 1997 or for the last 15 years and 1 month. At the same time, CO2 levels have been climbing steadily since that time.
http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend/plot/uah/from:1997/plot/uah/from:1997.9/trend/plot/rss/from:1997.9/trend/detrend:-0.0735/offset:-0.080/plot/esrl-co2/from:1997.9/normalise/offset:0.68/plot/esrl-co2/from:1997.9/normalise/offset:0.68/trend
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. The first number in each case was taken from WFT. However the second +/- number was taken from the site mentioned above. As far as I was able to tell, these numbers can only be obtained for whole calendar years. So on the average, you can add half a year to the given time period. The larger the magnitude of the second number relative to the first, the closer the period of no significance is to the next higher number. In every case, note that the magnitude of the higher number is larger than the first number. This means that we cannot be 95% certain that there has been any warming over the period indicated.
For RSS the warming is NOT significant for 23 years.
For RSS: +0.126 +/-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: 0.116 +/- 0.122 C/decade at the two sigma level from 1996
Section 3
This section shows data about 2012 in the form of two 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. If there is a * behind the ranking, it means that we only have 11 months worth of data and the December anomaly could change the final ranking.
2. Anom. Here I give the average anomaly for 2012 so far, and this will change slightly for those with a *.
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. 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. (With GISS, two months were tied for highest, namely January 2007 and March of 2002 at o.89.)
6. Anom. This is the anomaly of the month immediately to the left.
7. 11ano. This is the average anomaly for the year 2011.
8. rank. This is the new ranking for 2011. In all cases, 2012 was slightly warmer than 2011 and therefore pushed the 2011 ranking up by a unit.
Please insert table.
If you wish to verify all rankings, go to the following:
For UAH, see: http://wattsupwiththat.com/2013/01/03/uah-global-temperature-report-2012-was-9th-warmest/
For RSS, see: http://motls.blogspot.ca/2013/01/rss-amsu-2012-was-11th-warmest-year.html#more
For Hadcrut4, see: http://wattsupwiththat.com/2013/01/03/uah-global-temperature-report-2012-was-9th-warmest/
Note the number opposite the 2012 at the bottom. Then going up to 1998, you will find that there are 8 numbers above this number. That confirms that 2012 is in 9th place.
For Hadcrut3, see: http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt
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: http://www.cru.uea.ac.uk/cru/data/temperature/hadsst2gl.txt
Verify 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: For Hadsst2, see: http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
Once the December value is plotted, check the J-D (January to December) average and then check to see how often that number is beaten back to 1998.
For the next table, we again have the same six data sets, but this time the anomaly for each month is shown up to the latest that we have. The last column has the average of all points to the left. But this could change slightly in those cases where December is blank.
To see the above in the form of a graph, see the WFT graph below.
http://www.woodfortrees.org/plot/wti/from:2012/plot/gistemp/from:2012/plot/uah/from:2012/plot/rss/from:2012/plot/hadsst2gl/from:2012/plot/hadcrut4gl/from:2012/plot/hadcrut3gl/from:2012
Appendix
In this part, we are summarizing data for each set separately.
RSS
The slope is flat since December 1996 or 16 years and 1 month. (goes to December) RSS is 193/204 or 94.6% of the way to Ben Santer’s 17 years.
For RSS the warming is NOT significant for 23 years.
For RSS: +0.126 +/-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.
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1996.9/trend
http://www.woodfortrees.org/plot/rss/from:1990/plot/rss/from:1990/trend/plot/rss/from:1990/detrend:0.3128/trend/plot/rss/from:1990/detrend:-0.3128/trend/plot/rss/from:1996.9/trend
UAH
The slope is flat since October 2004 or 8 years, 3 months. (goes to December)
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 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.
http://www.woodfortrees.org/plot/uah/from:1994/plot/uah/from:1994/trend/plot/uah/from:2004.75/trend
http://www.woodfortrees.org/plot/uah/from:1994/plot/uah/from:1994/trend/plot/uah/from:2004.75/trend/plot/uah/from:1994/detrend:%200.3287/trend/plot/uah/from:1994/detrend:-0.3287/trend
Hadcrut4
The slope is flat since December 2000 or an even 12 years. (goes to November.)
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
With Hadcrut4, the anomaly for the first eleven months of the year is 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.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut4.
http://www.woodfortrees.org/plot/hadcrut4gl/from:1995/plot/hadcrut4gl/from:1995/trend/plot/hadcrut4gl/from:2000.9/trend
http://www.woodfortrees.org/plot/hadcrut4gl/from:1995/plot/hadcrut4gl/from:1995/trend/plot/hadcrut4gl/from:2000.9/trend/plot/hadcrut4gl/from:1995/detrend:0.1998/trend/plot/hadcrut4gl/from:1995/detrend:-0.1998/trend
Hadcrut3
The slope is flat since May 1997 or 15 years, 7 months (goes to November)
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
With the Hadcrut3 anomaly for the first eleven months of the year is 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.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut3.
http://www.woodfortrees.org/plot/hadcrut3gl/from:1994/plot/hadcrut3gl/from:1997.33/trend/plot/hadcrut3gl/from:1994/trend
http://www.woodfortrees.org/plot/hadcrut3gl/from:1994/plot/hadcrut3gl/from:1997.33/trend/plot/hadcrut3gl/from:1994/trend/plot/hadcrut3gl/from:1994/detrend:0.1862/trend/plot/hadcrut3gl/from:1994/detrend:-0.1862/trend
Hadsst2
The slope is flat since March 1997 or 15 years, 10 months. (goes to December)
The Hadsst2 anomaly for 2012 at 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 the following
http://www.woodfortrees.org/plot/hadsst2gl/from:1997.1/plot/hadsst2gl/from:1997.1/trend
GISS
The slope is flat since May 2001 or 11 years, 7 months. (goes to November)
For GISS, the warming is NOT significant for 17 years.
For GISS: 0.116 +/- 0.122 C/decade at the two sigma level from 1996
With the GISS anomaly for the first eleven months of the year is 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.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to GISS.
http://www.woodfortrees.org/plot/gistemp/from:1996/plot/gistemp/from:1996/trend/plot/gistemp/from:2001.33/trend
http://www.woodfortrees.org/plot/gistemp/from:1996/plot/gistemp/from:1996/detrend:0.2074/trend/plot/gistemp/from:1996/detrend:-0.2074/trend/plot/gistemp/from:1996/trend/plot/gistemp/from:2001.33/trend
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 that 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?
http://www.woodfortrees.org/plot/hadcrut4gl/from:1990/mean:12/offset:-0.16
Table codes will come by email.
Werner Brozek says: January 14, 2013 at 7:47 pm
Table codes will come by email.
Included in your comment above and at the end of the article above for reference. Problem, tables are too big. A few options. 1, you could remove one column for the first table and split the second table into two parts/half years. 2, we could try to add some html that would shrink the text, e.g. http://www.tizag.com/htmlT/font.php but I’m not sure if this would help. 3, we could figure out some html to shrink the wasted space between the cell entries, i.e. cellpadding or cellspacing:
http://www.w3schools.com/tags/tag_table.asp
When would you like to publish this? If Fri, I won’t have much time to play, if Sat, Sun or beyond, I should be able to help figure out a more artful solution.
Guys, I eagerly await the expanded article.