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.
Thank you Steve and dbstealey and all others for your comments so far.
As far as global warming resuming, it will be a very long time before the slope of RSS is not negative for over 17 years. But even if that should happen, it will be much longer before the warming is significant at the 95% level for 15 years.
However depending on where things are, changes could happen very quickly. For example, Hadcrut3 went from 16 years and 10 months to 13 years and 9 months from March to April. Exactly the same thing could happen with GISS with regards to the 95% and 15 years. Take a look at the following where GISS has no warming at the 95% level. A high May anomaly just could push it over the edge. But GISS would be all by itself then because none of the other data sets are close to losing their 15 years at 95% statistical significance.
http://www.woodfortrees.org/plot/gistemp/from:1997.55/plot/gistemp/from:1997.55/trend
As the correlation between co2 and temperature breaks down we have a new correlation! From the BBC.Maybe the BBC is being given a hint by the statistician and owner of the website ‘Spurious Correlations’.
The amazing thing is that in historical times, with very little added human CO2 and human population only a fraction of what it is now, atmospheric temperatures were recorded that appear to approach those values recorded in the present.
Enjoyed your post Werner 😉
What happen to Hawaii land temperature data? Giss has no data after February 2013. Did I miss the news of a massive eruption destroying the islands? Temperature had been dropping there for a few years. Maybe it has continued to be inconvenient for setting a record.
Bob Koss says:
May 26, 2014 at 4:17 pm
Sorry! I only work with global data or Hadsst3 as I am more interested in the global aspect of global warming. Hopefully another reader can help you out.
Bob Koss says: May 26, 2014 at 4:17 pm
“What happen to Hawaii land temperature data? Giss has no data after February 2013.”
GHCN has up to date data on all four major islands. GISS has up to date Hilo and Kahului, but for some reason lags with Honolulu and Lihue.
(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.). Here again Steve Goddard has the answers, this is just plain old fashioned Fraud, not even scientific fraud.
http://stevengoddard.wordpress.com/2014/01/15/almost-23-of-giss-warming-is-fake/
One of these days they’ll forego adjusting data to meet their politcal desires and just create a program to make up “data” out of the whole cloth.
Nick,
If the stations aren’t listed in the Giss homogenized database they don’t get used. Giss isn’t using the stations you mentioned. Using the Giss maps tool to plot land data trends you will see Hawaii shows a negative trend since 2001 of about 0.35c. In effect they have now wiped the whole state off the earth.
Here are the only stations listed as being used. Only two of them have data as recent as February 2013. Next most recent stations ended in 2003.
http://data.giss.nasa.gov/cgi-bin/gistemp/find_station.cgi?lat=21.3&lon=-158.1&dt=1&ds=14
Nick,
Here is the Giss trend map for land data.
http://data.giss.nasa.gov/cgi-bin/gistemp/nmaps.cgi?sat=4&sst=0&type=trends&mean_gen=0112&year1=2001&year2=2012&base1=1951&base2=1980&radius=1200&pol=reg
Bob Koss says: May 26, 2014 at 5:45 pm
“If the stations aren’t listed in the Giss homogenized database they don’t get used. Giss isn’t using the stations you mentioned.”
They have the data for Kahului and Hilo, and list it pre-homogenization. It seems they can’t homogenize it because of recent gaps.
I’ve plotted recent unadjusted GHCN station trends here. I can’t see anything downward at Honolulu. I get 1.59°/century since 1997, or 1.29°C since 1977. Much in line with nearby SST.
Got a lot of millions of square kilometers of arctic up there past 72 and 80 north that are colored red and orange that HAVE NO THERMOMETERS ON THEM.
See, the DMI has measured the daily air temperatures at 80 north latitude since 1959. There has been 0.0 increase in summertime temperatures up there at 80 north since 1959. (Winter temp’s have gone up, but there is no sunlight p there in winter for the CO2 to interact with. )
RACookPE1978 says: May 26, 2014 at 6:03 pm
“Got a lot of millions of square kilometers of arctic up there past 72 and 80 north that are colored red and orange that HAVE NO THERMOMETERS ON THEM.”
As stated, it shades colors on a triangle mesh between stations. You can see the stations, and the mesh too, if you want.
“Winter temp’s have gone up, but there is no sunlight up there in winter for the CO2 to interact with…”
Sunlight does not interact with CO2. It obstructs IR.
Kid to his mother upon being caught fibbing:
“But Maa, It’s not a lie. It’s the truth, but I homogenized it”
Anyone remember this letter from GISS? I didn’t save the link, but it’s out there.
http://i.imgur.com/McgXE3y.png
Nick,
Hilo, Honolulu, and Lihue were all being homogenized and used by Giss as recently as 2011 in ver. 2. All show a negative trend of several degrees/century since 2001. After February 2013 Giss uses no temperature data for Hawaii. Makes me wonder what is going on.
I noticed Hawaii annual temperatures were down around the time of the 1998 super el nino(close to the 1951-80 average). That may be the reason for your positive trend for Honolulu starting with 1997. Around 2010 I believe we had another el nino when annual temperature also dropped in Hawaii. Could it be el nino has the effect of reducing land temperatures around Hawaii? If that were true, I imagine it would be easier to set a new temperature record without Hawaii data. That area covers around 1.5 million sq km they way they spread temperature data around.
In reply to:
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 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.)
William:
There is the first observational evidence of cooling. The UAH data set shows the Southern Hemisphere temperature has dropped to the 30 year average.
http://www.ospo.noaa.gov/data/sst/anomaly/2014/anomnight.5.26.2014.gif
The mechanism that was inhibiting GCR (GCR is an abbreviation for galactic cosmic rays and is also called cosmic ray flux CRF, there are no rays the first discovers thought they had discovered a new type of radiation and the idiotic scientific community never bothered to correct, GCR/CRF are mostly high speed protons which are modulated by the strength and extent of the solar heliosphere) and solar wind modulation of planetary clouds for the last 7 year to 10 years is now starting to abate.
This chart shows neutron counts at a high latitude location. Neutron counts are proportion to the amount of GCR that are striking the earth’s atmosphere.
http://cosmicrays.oulu.fi/webform/query.cgi?startday=27&startmonth=03&startyear=1975&starttime=00%3A00&endday=27&endmonth=04&endyear=2014&endtime=00%3A00&resolution=Automatic+choice&picture=on
if I understand the mechanisms and based on cycles of similar warming and cooling that correlate with solar magnetic cycle changes roughly 90% of the warming (90% of 0.8C which is 0.7C) in the last 150 years was due to solar magnetic cycle modulation of planetary cloud cover.
The UAH data is not contaminated by the urban heat effect and is not contaminated by climategate type of manipulation. The UAH satellite measured temperature for the planet, average long term temperature anomaly is roughly 0.3C. Cooling of 0.8C will result in a UAH average (new typical base) of -0.5C.
Werner Brozek says:
May 26, 2014 at 7:55 am
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.
I didn’t compare UAH global to RSS land. I used both the global trend lines. Of course, if you offset them start at the same point it looks like they are diverging, but that is fooling with the graphs and is not an accurate representation of the data. If you look at the entire time period, they diverged in the 20th century and are now converging. (I assumed they are both based on the same base period).
Richard M says:
May 27, 2014 at 6:56 am
(I assumed they are both based on the same base period).
See: http://www.drroyspencer.com/2012/11/
“Differences with RSS over the Last 2 Years
Many people don’t realize that the LT product produced by Carl Mears and Frank Wentz at Remote Sensing Systems has anomalies computed from a different base period for the average annual cycle (1978-1998) than we use (1981-2010). They should not be compared unless they are computed about the same annual cycle.”
Walter,
Thank you for that – very illuminating.
I downloaded all the datasets a couple of years ago, and imported them into a spreadsheet so that I could do my own analyses on them. Then each month I just type in the most recent figure, rather than downloading the whole thing again.
How naive of me! The GISS figures change all the time, and even the most recent couple of months have already been revised. I must be careful to load the latest version in full every month. Are the other datasets as volatile? The occasional correction I can understand, but continual changes to the same month several years back suggests that none of the figures is particularly accurate, and will change repeatedly in the future.
Richar Barraclough says:
May 27, 2014 at 9:52 am
Are the other datasets as volatile?
Just in case Walter does not respond with a more complete answer, my experience has been that the most recent month may have an adjustment of a few thousandths of a degree and occasionally, the second last month may also have a slight change. So if you check the previous two months, you should be OK 99% of the time on all but GISS.
Werner Brozek says:
May 27, 2014 at 7:32 am
See: http://www.drroyspencer.com/2012/11/
“Differences with RSS over the Last 2 Years
Many people don’t realize that the LT product produced by Carl Mears and Frank Wentz at Remote Sensing Systems has anomalies computed from a different base period for the average annual cycle (1978-1998) than we use (1981-2010). They should not be compared unless they are computed about the same annual cycle.”
Do you know what the difference comes out to? That would be the proper amount to offset the graphs. For example, using -.05 for RSS it shows a divergence followed by convergence and then divergence in the opposite direction.
http://www.woodfortrees.org/plot/rss/to/plot/rss/to:2000/trend/offset:-.05/plot/uah/to/plot/uah/to:2000/trend/plot/rss/from:2000/to/trend/offset:-.05/plot/uah/from:2000/trend
The implicit implication here is that if a record is indeed set, the reason for that record will be human CO2. While we dither with hundredths of a degree it is well to remember the one degree drop and recovery from the MWP to the present.
Pick your trend.
What source(s) are you using for the difference between the MWP / LIA and the present ?
I was just using my eyechrometer on this:
http://wp.me/a1uHC3-jd
Hollowscene optimum to LIA nearly one degree. Maybe only 3/4 degree from MWP. Still a lot more than a few hundredths.
Also this IPCC 1990
http://geosciencebigpicture.com/?attachment_id=1195
http://wattsupwiththat.com/2014/05/25/can-giss-and-other-data-sets-set-records-in-2014-now-includes-april-data/#comment-1656450
Thanks, I often exchange emails with Tony Brown.
Richard M says:
May 27, 2014 at 10:22 am
Do you know what the difference comes out to?
I cannot give a complete answer since there are so many variables and I do not know all. Then there is the point that WFT only has version 5.5 and not version 5.6. Version 5.6 is even further apart from RSS. However what WFT shows is that the average for all RSS values is 0.09774 and the average for all UAH values is 0.00878. So taking the difference of 0.08896 and adding it to UAH, we get the following graph. It shows that UAH started cooler and is getting warmer whereas RSS started warmer and is getting cooler.
http://www.woodfortrees.org/plot/uah/from:1978/offset:0.08896/plot/rss/from:1978/plot/uah/from:1978/trend/offset:0.08896/plot/rss/from:1978/trend