Guest Post by Werner Brozek (Edited By Just The Facts)
GISS and other sets are poised to set new records in 2014, even without an El Nino. The present GISS record is a two way tie for first place with 2005 and 2010 both showing an average anomaly of 0.65. (By the way, in January of this year, it was stated that the 2010 anomaly was 0.67. I do not understand how 2010 lost 0.02 C over the last four months.) The present average over the first four months of 2014 is 0.64, so it is only 0.01 lower. However of greater significance is that the April anomaly was 0.73. If this anomaly were to continue for the rest of the year, the old GISS record would be shattered.
Below, I will provide the corresponding information for the other five data sets that I am following. All differences will be provided to the nearest 1/100 degree.
The current Hadsst3 average is 0.370, which is only 0.05 below its record of 0.416. And as is the case with GISS, the April anomaly was a huge 0.478, so if this anomaly were to continue for the rest of 2014, Hadsst3 would also set a new record.
The current Hadcrut3 average is 0.455, which is only 0.09 below its record of 0.548. And as is the case with GISS, the April anomaly was a huge 0.592, so if this anomaly were to continue for the rest of 2014, Hadcrut3 would virtually tie its record.
The current Hadcrut4 average is 0.500, which is only 0.05 below its record of 0.547. And as is the case with GISS, the April anomaly was a huge 0.641, so if this anomaly were to continue for the rest of 2014, Hadcrut4 would also set a new record.
The current RSS average is 0.222. This is 0.33 below the 1998 record of 0.550. This record seems safe for this year. Even the April anomaly of 0.251 would not challenge the record if it continued for the rest of the year.
The current UAH average is 0.171. This is 0.25 below the 1998 record of 0.419. This record seems safe for this year. Even the April anomaly of 0.184 would not challenge the record if it continued for the rest of the year. (Note: This applies to version 5.5.)
In the table, I have added a row 15 which I have labelled 15.dif and here I give the above differences between rows 4 and 13. Since no rank is first at this point, all numbers have the same sign indicating the present record is still higher than the present average in all cases.
In the parts below, as in the previous posts, we will present you with the latest facts. 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 statistically significant warming on several data sets.
The third section will show how 2014 to date compares with 2013 and the warmest years and months on record so far.
The appendix will illustrate sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.
Section 1
This analysis uses the latest month for which data is available on WoodForTrees.com (WFT). All of the data on WFT is also available at the specific sources as outlined below. We start with the present date and go to the furthest month in the past where the slope is a least slightly negative. So if the slope from September is 4 x 10^-4 but it is – 4 x 10^-4 from October, we give the time from October so no one can accuse us of being less than honest if we say the slope is flat from a certain month.
On all data sets below, the different times for a slope that is at least very slightly negative ranges from 9 years and 8 months to 17 years and 9 months
1. For GISS, the slope is flat since November 2001 or 12 years, 6 months. (goes to April)
2. For Hadcrut3, the slope is flat since August 2000 or 13 years, 9 months. (goes to April) The latest spike caused the time to start after the 1998 El Nino.
3. For a combination of GISS, Hadcrut3, UAH and RSS, the slope is flat since December 2000 or 13 years, 5 months. (goes to April)
4. For Hadcrut4, the slope is flat since January 2001 or 13 years, 4 months. (goes to April)
5. For Hadsst3, the slope is flat since December 2000 or 13 years, 5 months. (goes to April)
6. For UAH, the slope is flat since September 2004 or 9 years, 8 months. (goes to April using version 5.5)
7. For RSS, the slope is flat since August 1996 or 17 years, 9 months (goes to April).
The next graph shows just the lines to illustrate the above. Think of it as a sideways bar graph where the lengths of the lines indicate the relative times where the slope is 0. In addition, the upward sloping blue line indicates that CO2 has steadily increased over this period.
When two things are plotted as I have done, the left only shows a temperature anomaly.
The actual numbers are meaningless since all slopes are essentially zero. As well, I have offset them so they are evenly spaced. No numbers are given for CO2. Some have asked that the log of the concentration of CO2 be plotted. However WFT does not give this option. The upward sloping CO2 line only shows that while CO2 has been going up over the last 17 years, the temperatures have been flat for varying periods on various data sets.
The next graph shows the above, but this time, the actual plotted points are shown along with the slope lines and the CO2 is omitted.
Section 2
For this analysis, data was retrieved from Nick Stokes’ Trendviewer page. This analysis indicates for how long there has not been statistically significant warming according to Nick’s criteria. Data go to their latest update for each set. In every case, note that the lower error bar is negative so a slope of 0 cannot be ruled out from the month indicated.
On several different data sets, there has been no statistically significant warming for between 16 and 21 years.
The details for several sets are below.
For UAH: Since February 1996: CI from -0.043 to 2.349
For RSS: Since November 1992: CI from -0.022 to 1.867
For Hadcrut4: Since October 1996: CI from -0.033 to 1.192
For Hadsst3: Since January 1993: CI from -0.016 to 1.813
For GISS: Since August 1997: CI from -0.008 to 1.233
Section 3
This section shows data about 2014 and other information in the form of a table. The table shows the six data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, Hadcrut3, Hadsst3, and GISS.
Down the column, are the following:
1. 13ra: This is the final ranking for 2013 on each data set.
2. 13a: Here I give the average anomaly for 2013.
3. year: This indicates the warmest year on record so far for that particular data set. Note that two of the data sets have 2010 as the warmest year and four have 1998 as the warmest year.
4. ano: This is the average of the monthly anomalies of the warmest year just above.
5.mon: This is the month where that particular data set showed the highest anomaly. The months are identified by the first three letters of the month and the last two numbers of the year.
6. ano: This is the anomaly of the month just above.
7. y/m: This is the longest period of time where the slope is not positive given in years/months. So 16/2 means that for 16 years and 2 months the slope is essentially 0.
8. sig: This the first month for which warming is not statistically significant according to Nick’s criteria. The first three letters of the month are followed by the last two numbers of the year.
9. Jan: This is the January 2014 anomaly for that particular data set.
10.Feb: This is the February 2014 anomaly for that particular data set, etc.
13.ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months. However if the data set itself gives that average, I may use their number. Sometimes the number in the third decimal place differs slightly, presumably due to all months not having the same number of days.
14.rnk: This is the rank that each particular data set would have if the anomaly above were to remain that way for the rest of the year. It will not, but think of it as an update 15 minutes into a game. Due to different base periods, the rank is more meaningful than the average anomaly.
15.dif: This is row 4 minus row 13. A number of less than 0.10 at this point in time means that a record is possible for 2014 for four of the data sets. Both of the satellite data would need a miracle to set a record this year in my opinion.
| Source | UAH | RSS | Had4 | Had3 | Sst3 | GISS |
|---|---|---|---|---|---|---|
| 1. 13ra | 7th | 10th | 8th | 6th | 6th | 7th |
| 2. 13a | 0.197 | 0.218 | 0.486 | 0.459 | 0.376 | 0.59 |
| 3. year | 1998 | 1998 | 2010 | 1998 | 1998 | 2010 |
| 4. ano | 0.419 | 0.55 | 0.547 | 0.548 | 0.416 | 0.65 |
| 5.mon | Apr98 | Apr98 | Jan07 | Feb98 | Jul98 | Jan07 |
| 6. ano | 0.662 | 0.857 | 0.829 | 0.756 | 0.526 | 0.92 |
| 7. y/m | 9/8 | 17/9 | 13/4 | 13/9 | 13/5 | 12/6 |
| 8. sig | Feb96 | Nov92 | Oct96 | Jan93 | Aug97 | |
| Source | UAH | RSS | Had4 | Had3 | Sst3 | GISS |
| 9.Jan | 0.236 | 0.262 | 0.507 | 0.472 | 0.342 | 0.68 |
| 10.Feb | 0.127 | 0.161 | 0.304 | 0.264 | 0.314 | 0.44 |
| 11.Mar | 0.137 | 0.214 | 0.544 | 0.491 | 0.347 | 0.70 |
| 12.Apr | 0.184 | 0.251 | 0.641 | 0.592 | 0.478 | 0.73 |
| Source | UAH | RSS | Had4 | Had3 | Sst3 | GISS |
| 13.ave | 0.171 | 0.222 | 0.500 | 0.455 | 0.370 | 0.64 |
| 14.rnk | 10th | 9th | 5th | 7th | 7th | 3rd |
| 15.dif | 0.25 | 0.33 | 0.05 | 0.09 | 0.05 | 0.01 |
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 5.5 was used since that is what WFT used.
http://vortex.nsstc.uah.edu/public/msu/t2lt/tltglhmam_5.5.txt
For RSS, see: ftp://ftp.ssmi.com/msu/monthly_time_series/rss_monthly_msu_amsu_channel_tlt_anomalies_land_and_ocean_v03_3.txt
For Hadcrut4, see: http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.4.2.0.0.monthly_ns_avg.txt For Hadcrut3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadCRUT3-gl.dat
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
To see all points since January 2013 in the form of a graph, see the WFT graph below.
As you can see, all lines have been offset so they all start at the same place in January 2013. This makes it easy to compare January 2013 with the latest anomaly.
Appendix
In this part, we are summarizing data for each set separately.
RSS
The slope is flat since August 1996 or 17 years, 9 months. (goes to April)
For RSS: There is no statistically significant warming since November 1992: CI from -0.022 to 1.867.
The RSS average anomaly so far for 2014 is 0.222. This would rank it as 9th place 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 2013 was 0.218 and it is ranked 10th.
UAH
The slope is flat since September 2004 or 9 years, 8 months. (goes to April using version 5.5 according to WFT)
For UAH: There is no statistically significant warming since February 1996: CI from -0.043 to 2.349. (This is using version 5.6 according to Nick’s program.)
The UAH average anomaly so far for 2014 is 0.171. This would rank it as 10th place if it stayed this way. 1998 was the warmest at 0.419. The highest ever monthly anomaly was in April of 1998 when it reached 0.662. The anomaly in 2013 was 0.197 and it is ranked 7th.
Hadcrut4
The slope is flat since January 2001 or 13 years, 4 months. (goes to April)
For Hadcrut4: There is no statistically significant warming since October 1996: CI from -0.033 to 1.192.
The Hadcrut4 average anomaly so far for 2014 is 0.500. This would rank it as 5th place if it stayed this way. 2010 was the warmest at 0.547. The highest ever monthly anomaly was in January of 2007 when it reached 0.829. The anomaly in 2013 was 0.486 and it is ranked 8th.
Hadcrut3
The slope is flat since August 2000 or 13 years, 9 months. (goes to April)
The Hadcrut3 average anomaly so far for 2014 is 0.455. This would rank it as 7th place if it stayed this way. 1998 was the warmest at 0.548. The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to go back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2013 was 0.459 and it is ranked 6th.
Hadsst3
For Hadsst3, the slope is flat since December 2000 or 13 years and 5 months. (goes to April).
For Hadsst3: There is no statistically significant warming since January 1993: CI from -0.016 to 1.813.
The Hadsst3 average anomaly so far for 2014 is 0.370. This would rank it as 7th place if it stayed this way. 1998 was the warmest at 0.416. The highest ever monthly anomaly was in July of 1998 when it reached 0.526. The anomaly in 2013 was 0.376 and it is ranked 6th.
GISS
The slope is flat since November 2001 or 12 years, 6 months. (goes to April)
For GISS: There is no statistically significant warming since August 1997: CI from -0.008 to 1.233.
The GISS average anomaly so far for 2014 is 0.64. This would rank it as 3rd place if it stayed this way. 2010 and 2005 were the warmest at 0.65. The highest ever monthly anomaly was in January of 2007 when it reached 0.92. The anomaly in 2013 was 0.59 and it is ranked 7th.
Conclusion
Even without an El Nino, it appears likely that some records will be set on at least some surface data sets, however not on the satellite data sets.
@ur momisugly john Robertson
“I am all out of patience with these anomalies of 0.001 accuracy.
Pure fiction.
In audio this noise is called what it is, noise.”
NO, in audio , this is called SILENCE.
“First: “If we average a thousand readings that are only accurate to the nearest degree, we can easily get an average to the nearest 1/1000 degree.””
ONLY if those measurements are made under exactly the same circumstances of exactly the same item.
Its like measuring the length 1000 random pieces of wood to the nearest mm, and saying the average is to the nearest 1/000mm
IT ISN’T !!!
Dr Burns says:
May 25, 2014 at 10:50 pm
If it were true that greater accuracy could be achieved by simply more readings, we could get the Earth’s population to hold their fingers in the air to estimate temperature, then calculate an average to a high accuracy.
Of course it would really help if all people were spread evenly throughout the earth without having 15 million readings from Mexico city and 15 from Antarctica.
Jim says:
May 26, 2014 at 2:20 am
That was the objective of this year, to break the record come hook or crook.
And here I thought that a super El Nino was somehow expected to prove that man-made CO2 was responsible. I must confess that I thought the spikes over the last two months in Hadcrut3 and 4 were very surprising, especially since the expected El Nino has not even started yet.
thegriss says:
May 26, 2014 at 3:49 am
Its like measuring the length 1000 random pieces of wood to the nearest mm, and saying the average is to the nearest 1/000mm
IT ISN’T !!!
Of course you are correct. Let me rephrase that. Suppose that we wish to compare two soccer teams and we find that one team has scored 554 goals in 1000 games and the other has scored 1449 goals in 1000 games. The average for the first team was 0.554 goals a game and the average for the next was 1.449 goals a game. So even though one team was about three times better than the other, it would not have been apparent if we simply rounded both 0.554 and 1.449 to the nearest whole number which would have been 1 since you cannot have 1/10 or 1/100 or 1/1000 of a goal.
Of course measurements have inherent uncertainties so we have this added complexity to deal with. However that does not mean that the information is completely useless if given to an extra decimal place than the individual measurements warranted. You just have to keep the limitations in the back of your mind.
I saw NikfromNYC’s lovely 9:40 PM rant @ur momisugly the Bish’s and commented: Never have I missed paragraphs less. Bravo, Nik.
======================
Werner Brozek says:
May 25, 2014 at 6:59 pm
I never understood this reasoning. You would have to take 1,000 readings in the same location at the same time with the same instrumentation. Then this only improves the precision of the reading and not its accuracy. When you average many readings over different areas taken at different times with different measuring systems the average error goes up and not down.
You actually reported most of them to the nearest 1/1000 degree which is fairly silly. It would serve everyone (and the truth) better if you would report them to the proper number of sig. figures and include the error bars. By this I don’t mean just the error bars from averaging together a bunch of numbers, but the real errors carried through in a proper error analysis. If this was hammered home continuously, it would soon be obvious to most that saying one year is “hotter” than another when they differ by a few hundreths of a degree was nonsense.
Steve from Rockwood says:
May 26, 2014 at 5:13 am
When you average many readings over different areas taken at different times with different measuring systems the average error goes up and not down.
If you wanted to get the best value of the average temperature on Earth for a given day, you would ideally have many instruments that take 24 hour readings throughout the day. Then you would combine the temperature readings with the length of time at the various readings to get an average for the day at each spot. If you did this with 100 equally spaced spots on Earth, you would get a certain number. But if you did this with a million equally spaced spots on Earth, you would get a certain number that would be more accurate than the first.
Of course GISS, etc., can set new record highs in 2014. They must and they will.
Bill_W says:
May 26, 2014 at 5:44 am
You actually reported most of them to the nearest 1/1000 degree which is fairly silly.
My numbers are right from their sites such as:
http://www.cru.uea.ac.uk/cru/data/temperature/HadCRUT3-gl.dat
If you feel they are silly with all numbers to the nearest 1/1000 degree, you need to take it up with them. For me, my purpose is not to tell Hadcrut3 how to report things, but merely to show how long the pause in warming is with their own numbers as they are given.
So if you can convince Hadcrut3 to report things to the nearest 1/10 degree, I will do likewise.
Why can’t the NCDC issue the temperature record for the US Climate Reference Network (USCRN) in a format like that posted by Dr. Roy Spencer. The information goes all the way back to 2008. It would be the mot accurate data for the US and is surely warranted given all the manipulation of the USHCN data. Plus it was paid for out of the public purse.
Werner Brozek says:
If you wanted to get the best value of the average temperature on Earth for a given day, you would ideally have many instruments that take 24 hour readings throughout the day. Then you would combine the temperature readings with the length of time at the various readings to get an average for the day at each spot. If you did this with 100 equally spaced spots on Earth, you would get a certain number. But if you did this with a million equally spaced spots on Earth, you would get a certain number that would be more accurate than the first.
If the average temp of 100 equally spaced spots on earth returned a valid or useful value, then yes, 1000 spots could return a more precise value.
Whether the returned value has an understandable physical meaning is some what in doubt!
How we could evaluate for non-sinusoidal temperature variations I do not know.
Werner Brozek says:
May 26, 2014 at 5:46 am
Let’s say you started with 100 equally spaced dots (temperature measurements stations) on the Earth. Then, for convenience, you created 1 million dots placed mainly in urban areas, to make the recording as easy as possible. Which set returns the greater accuracy?
Let”s also say the 100 dots were measured continuously from which the daily min and max plus mean were taken. Compare that to the million dots where people take the measurements at their convenience but note the time or occasionally miss the readings because they have other things to do (like landing planes etc).
Consider that some scientists decide that not all the 1 million dots are of the same quality and eliminate 2/3 of them after having used all of them for several years. This of course requires an adjustment, which they calculate and make. Now what can we say about the accuracy of the 333,333 dots?
Some scientists further decide that previous measurements had systematic errors that require adjustment over time. It becomes quite a task to accurately adjust 333,333 dots so different teams tackle different data sets. Now what is the accuracy of this average?
And finally, compare the average value of all those dots to a single record that has been meticulously recorded for hundreds of years but without adjustment and with a precision of +/- 0.5. How does that one record compare (in an accuracy sense) to the average of the hundreds of thousands of dots – each one with its own set of problems.
In my experience accuracy is affected by systematic errors while precision is affected by random errors. You can always increase precision but accuracy is very difficult to improve unless you treat each systematic error properly for each data set. Anyone who thinks the worldwide temperature record has an accuracy of +/0.01 degrees C just because of the high number of readings has missed a very important point IMHO.
Kim:
Earlier I made a cathartic scrapbook version of trying to pull climate deception together, as a zoomable graphic:
http://k.min.us/iby6xe.gif
I called it The Green Bank Authority. I found myself rather confused by the sheer myriad enormity of the jungle of claims out there, so I tamed the thicket a bit.
Nick Stokes says:
May 25, 2014 at 10:00 pm
It was the topic of this very recent post. But the divergence between UAH and the surface indices is a lot less than the divergence between UAH and RSS.
No, UAH and RSS are converging. All you need to do is look at the data.
http://www.woodfortrees.org/plot/rss-land/to/plot/rss/to:2000/trend/plot/uah/to/plot/uah/to:2000/trend/plot/rss/from:2000/to/trend/plot/uah/from:2000/trend
They diverged in the 20th century.
I haven’t seen anyone state the obvious….
By adjusting past temps down…..they can claim any present year as the hottest
They are going to try and claim this year as the hottest….by some 100th or 10th of a degree…
…next year, if they adjust this years temp down……it not only means they were wrong by claiming that this year was the hottest…..it means the next year that’s the hottest doesn’t even have to be a higher temp
Steve from Rockwood says:
May 26, 2014 at 6:46 am
Anyone who thinks the worldwide temperature record has an accuracy of +/0.01 degrees C just because of the high number of readings has missed a very important point IMHO.
I do not believe any one is suggesting this. But if they are, then the fact that GISS went up by 0.03 from March to April versus 0.10 for Hadcrut3 disproves that.
Richard M says:
May 26, 2014 at 6:48 am
No, UAH and RSS are converging. All you need to do is look at the data.
Actually they are diverging since 1998. You cannot compare RSS land with UAH global. See the graphs where they were offset to start at the same place in 1998:
http://www.woodfortrees.org/plot/rss/from:1998/plot/rss/from:1998/trend/plot/uah/from:1998/offset:0.156/plot/uah/from:1998/trend/offset:0.156
Slope lines going in opposite directions is not converging.
Richard Mallett says:
May 26, 2014 at 8:08 am
So if none of the data sets can be trusted, how do we know that the pause is real ?
We know the pause is real because despite all adjustments that make the present warmer and the past cooler, they just cannot adjust too much without looking too suspicious in light of the satellite data. That is the way it appears anyway. They desperately do not want the pause to be there.
@thegriss 3:46am,
You are correct, this so-called temperature information would be silence in an audio circuit.
This is the charade of anomalies, much ado about no change.
Satellites show no warming for 16+ yrs, while GISS is setting records????
‘Nuff said.
@Werner:
“I do not believe any one is suggesting this. But if they are, then the fact that GISS went up by 0.03 +/- 0.25 from March to April versus 0.10 +/- 0.25 for Hadcrut3 disproves that.”
Fixed it for you.
Werner,
Excellent analysis as usual. One quibble: We are not in a “pause”. Global warming has stopped.
If GW begins again, then we can correctly call this a pause. Warming may commence again. But it might not. At this point we do not know. The only thing we know is that global warming stopped many years ago.
I am also bothered by the tiny tenth and hundreth of a degree claims. I have calibrated many thermometers. Only the very best, most expensive instruments can resolve a 0.1º C change. With a good thermometer you are lucky to be within ±1º.
In a rational world, we would use whole degrees.
Mi Cro
“If you want to see what the anomaly is, based solely on station measurements (no interpolation for places not actually measured, no other adjustments) follow the link in my name.”
Thanks I did very interesting and well worth the visit.