Guest Post By Werner Brozek, Edited by Just The Facts:

Note: Featured image and text below updated based upon input from rgbatduke. The graph shows HadSST3 Sea Surface Temperature Anomaly and RSS Lower Troposphere Temperature Anomaly since 1997, and is offset such that their means are at the same height. Note that the last two blue points for HadSST3 are higher than the highest point in 1998. The previous record anomaly was in July of 1998 at 0.526. June, 2014 had an anomaly of 0.563 and the anomaly for July of 2014 was 0.552. Furthermore, due to the high specific heat capacity of water, I would expect the August anomaly to also beat the previous record from July of 1998.
The average HadSST3 anomaly for the first seven months is 0.439 and 2014 would rank in 1st place if it stayed this way. An average of only 0.384 is needed for the next five months to set a new yearly record which looks extremely likely now. The period of a slightly negative slope for HadSST3 decreased significantly to 5 years and 5 months, which means it is negative from March 2009. The period without statistically significant warming decreased by 2 months to August 1994, or an even 20 years. (C.I. = -0.014 to 1.666)
However the record HadSST3 anomalies this year are not reflected in the RSS data set. RSS had a July, 2014 anomaly of 0.350, which was the fifth warmest July and significantly less than the prior record of 0.605 in July, 1998.
So why is there such a large divergence between HadSST3 and RSS in 2014? Bob Tisdale notes in his recent article that the north east of the Pacific ocean is quite warm at present, whereas during the 1998 El Nino, it was the tropics that were very warm. Would it make a difference to RSS if warm tropics water rose by 3 C rather than if an equal volume of a much cooler north Pacific rose by 3 C? Due to the law of conservation of energy, if more water evaporates, then more water vapor condenses in the lower troposphere. And it becomes warmer. However if a colder part of the ocean warms up, there should be less evaporation and condensation, which could explain some of the divergence between RSS and HadSST3. Also, Sea Surface Temperatures remained elevated for extended periods of time in 1997/1998 and 2009/2010, whereas the recent record HadSST3 anomalies appear to be the result of a brief spike, which could also explain some of the divergence.
Regardless, in the sections below, as in 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 5 years and 5 months to 17 years and 9 months.
1. For GISS, the slope is flat since September 2004 or 9 years, 11 months. (goes to July)
2. For Hadcrut4, the slope is flat since February 2001 or 13 years, 6 months. (goes to July)
3. For Hadsst3, the slope is flat since March 2009 or 5 years, 5 months. (goes to July)
4. For UAH, the slope is flat since June 2008 or 6 years, 2 months. (goes to July using version 5.5)
5. For RSS, the slope is flat since November 1996 or 17 years, 9 months (goes to July).
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 red 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 available on his website <a href=”http://moyhu.blogspot.com.au/p/temperature-trend-viewer.html”. 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 March 1996: CI from -0.001 to 2.341
For RSS: Since December 1992: CI from -0.015 to 1.821
For Hadcrut4: Since November 1996: CI from -0.003 to 1.184
For Hadsst3: Since August 1994: CI from -0.014 to 1.666
For GISS: Since October 1997: CI from -0.002 to 1.249
Section 3
This section shows data about 2014 and other information in the form of a table. The table shows the five data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, 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 three 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. Note that this does not yet include records set so far in 2014 such as Hadsst3 in June.
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.
16.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.
17.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 35 minutes into a game. Due to different base periods, the rank is more meaningful than the average anomaly.
| Source | UAH | RSS | Had4 | Sst3 | GISS |
|---|---|---|---|---|---|
| 1.13ra | 7th | 10th | 8th | 6th | 6th |
| 2.13a | 0.197 | 0.218 | 0.487 | 0.376 | 0.60 |
| 3.year | 1998 | 1998 | 2010 | 1998 | 2010 |
| 4.ano | 0.419 | 0.55 | 0.547 | 0.416 | 0.66 |
| 5.mon | Apr98 | Apr98 | Jan07 | Jul98 | Jan07 |
| 6.ano | 0.662 | 0.857 | 0.829 | 0.526 | 0.93 |
| 7.y/m | 6/2 | 17/9 | 13/6 | 5/5 | 9/11 |
| 8.sig | Mar96 | Dec92 | Nov96 | Aug94 | Oct97 |
| Source | UAH | RSS | Had4 | Sst3 | GISS |
| 9.Jan | 0.236 | 0.262 | 0.509 | 0.342 | 0.68 |
| 10.Feb | 0.127 | 0.162 | 0.304 | 0.314 | 0.45 |
| 11.Mar | 0.137 | 0.214 | 0.540 | 0.347 | 0.69 |
| 12.Apr | 0.184 | 0.251 | 0.643 | 0.478 | 0.73 |
| 13.May | 0.275 | 0.286 | 0.584 | 0.477 | 0.78 |
| 14.Jun | 0.279 | 0.345 | 0.620 | 0.563 | 0.62 |
| 15.Jul | 0.221 | 0.350 | 0.549 | 0.552 | 0.52 |
| Source | UAH | RSS | Had4 | Sst3 | GISS |
| 16.ave | 0.208 | 0.267 | 0.535 | 0.439 | 0.64 |
| 17.rnk | 6th | 6th | 3rd | 1st | 3rd |
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 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 2014 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 2014. This makes it easy to compare January 2014 with the latest anomaly.
Appendix
In this part, we are summarizing data for each set separately.
RSS
The slope is flat since November 1996 or 17 years, 9 months. (goes to July)
For RSS: There is no statistically significant warming since December 1992: CI from -0.015 to 1.821.
The RSS average anomaly so far for 2014 is 0.267. This would rank it as 6th 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 June 2008 or 6 years, 2 months. (goes to July using version 5.5 according to WFT)
For UAH: There is no statistically significant warming since March 1996: CI from -0.001 to 2.341. (This is using version 5.6 according to Nick’s program.)
The UAH average anomaly so far for 2014 is 0.208. This would rank it as 6th 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 February 2001 or 13 years, 6 months. (goes to July)
For Hadcrut4: There is no statistically significant warming since November 1996: CI from -0.003 to 1.184.
The Hadcrut4 average anomaly so far for 2014 is 0.535. This would rank it as 3rd 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 0.487 and it is ranked 8th.
Hadsst3
For Hadsst3, the slope is flat since March 2009 or 5 years and 5 months. (goes to July).
For Hadsst3: There is no statistically significant warming since August 1994: CI from -0.014 to 1.666.
The Hadsst3 average anomaly so far for 2014 is 0.439. This would rank it as 1st place if it stayed this way. 1998 was the warmest at 0.416 prior to 2014. The highest ever monthly anomaly was in July of 1998 when it reached 0.526. This is also prior to 2014. The anomaly in 2013 was 0.376 and it is ranked 6th.
GISS
The slope is flat since September 2004 or 9 years, 11 months. (goes to July)
For GISS: There is no statistically significant warming since October 1997: CI from -0.002 to 1.249.
The GISS average anomaly so far for 2014 is 0.64. This would rank it as third place if it stayed this way. 2010 was the warmest at 0.66. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2013 was 0.60 and it is ranked 6th.
Conclusion
There is a large divergence between HadSST3 and RSS in 2014. Why?
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It might also be that the UK met off are serial adjusters.
It would be worth finding out how much of this is adjustments. The net “corrections” are positive since about 1998-2000.
As Bob noted in his last post on this, almost all of the warming in SST is in N. Pacific.
To be more precise it is centred on Berring Sea area and also Labrador Str between Canada and Greenland.
This article mentions the effects of evaporation but it is the latent heat of fusion ( freezing/melting ) of water that may be more pertinent.
A quick back of envelope calculation using phycical properties of pure water rather than sea water shows that freesing 1kg of water releases enough heat to warm 100kg of water by 0.8K. That is about the current anomaly in those regions.
The SST shown has been climbing since 2012. That was the low point of arctic sea ice coverage. There was a recovery in ice volume of 50% in 2013. That implies an enormous transfer of energy, initally to surrounding water.
It looks like that may be the origin of the recent rise.
Maps shown in Bob’s post show most of the rest of the world is showing very neutral SST anomalies.
Most of this warming could be due to the Arctic ice recovery.
So the freezing could be causing the warming? Go figure……
Thanks Greg that is quite interesting.
To ossqss:
Remember it is anomalies. If -20c air flows over an ocean, then as long as it gains ice, the temperature would be kept just below freezing and not the -20c. The air takes up the heat released from the freezing.
Yes – good point!
Yours is an interesting idea to think about, however I think a lot of the heat released from the phase change from liquid water to solid ice goes up into the air blowing over the open water and freezing it. You notice this especially when a cold air mass from the tundra moves over the open water of Hudson Bay or the Laptev Sea. The air may be minus-forty over the land, but as it moves off shore it nearly immediately warms to a temperature near that of the water.
Not only is the heat sucked up by the air molecules, but evaporation occurs even at sub-zero temperatures (creating what is called “sea smoke”) and in evaporation the phase change is moving the opposite way, and latent heat is imprisoned rather than freed.
Nice comment Greg. I had not considered that the phase change of water to ice would transfer heat to the air and sea.
Interesting. This could also account for the high pressure ridge that has been stationary over the NE Pacific, causing not only the drought in the west/southwest US but the cold over the midwest/eastern US.
Greg,
I think we had a brief discussion on this in another post or maybe it was another Greg. There is no doubt that the physics of ice formation releases heat energy which either tends to warm the surrounding water or atmosphere or prevent it from cooling more.
What I am not certain about is how significant this is relative to other factors? Previously, I have not heard this this is a consideration. It seems as though when there is massive ice growth (or decline) it could be a factor. As I previously indicated some go wild over several hundredths of a degree change while ignoring the latent heat of ice formation.
I would like to hear Bob weigh in on this.
There is no doubt that the physics of ice formation releases heat energy which either tends to warm the surrounding water or atmosphere or prevent it from cooling more.
I think you hit the nail on the head here. As mentioned by others above, you are not going to get water that is at 5 C to form ice and then warm up to 8 C in the process. Rather, cold water at the freezing point of ice, and perhaps with colder air above it, may cause ice to form. And this newly formed ice emits a bit of heat which just reduces the rate at which further ice is formed. And this emitted heat may warm the air from – 20 C to -19 C, but it will not warm the water so the newly formed ice melts.
Evaporation cools the water surface and air near the surface. Condensation warms the upper air and causes rain. Cloud dynamics is controlling both the atmospheric temperature and atmospheric CO2 concentrations.
Where does HadSST3 get it’s Raw Data from and what “Quality Control Adjustments” do they make?
I bet HADSST3 shows higher current temps and cooler past temps than HADSST2 and HADSST do/did
You’d bet? Best go and look. Comments like that are not worth much. Since you don’ t even know what the source data is, it’s worth nothing.
HadSST2 had a stupid 0.5 degree step adjustment in 1946.
HadSST3 evens it out a bit but finds another logic to arrive a similar results. Neither have been properly validated IMO.
The source data is ICOADS SST. In this case there is a similar rise over the last couple of years, though I have not plotted the difference.
Where does HadSST3 get it’s Raw Data from
Bob Tisdale – bobtisdale.wordpress.com – Click the pic to view at source[/caption]
HadSST3 :SST data are taken from version 2.5 of the International Comprehensive Ocean-Atmosphere Data Set, http://icoads.noaa.gov/”
http://www.metoffice.gov.uk/hadobs/hadsst3/
what “Quality Control Adjustments” do they make?
HadSST3 makes copious adjustments to the ICOADS prior to 1945;
[caption id="" align="alignnone" width="850"]
primarily due to the Bucket Model;
http://wattsupwiththat.com/2013/05/25/historical-sea-surface-temperature-adjustmentscorrections-aka-the-bucket-model/
however, more recently, HadSST3 has trended only slightly above ICOADS.V2.5.
You would also expect the Lower Trop temps to reflect any surface increase as the Water warms the Atmosphere.
Do they even match Area wise?
The “upward sloping blue line” for CO2 is red.
Corrected, thank you.
Ooops! It actually looks brown to me. However what happened was that I had to drop Hadcrut3 since they seem to have been discontinued, so other colours got automatically switched and I forgot to check that. Thanks!
Anomalous warming is different than absolute temperature data. With anomalies, warmth is relative to THAT area. The absolute temperature the tropics may have indeed been hot, hot, hot in 1998. But the absolute temperature rise in the North Pacific still means that one must wear an insulating scuba outfit to keep from freezing one’s family jewels off. So the rise in trend may be up but the absolute temperature may be down.
Unfortunately, with anomaly graphs, it leaves the impression that absolute temperatures are hotter now than they have ever been in the satellite record. Not necessarily true. It would be useful to display global absolute temperature along side anomaly trends in order to prevent making the assumption that global anomaly graphs depicts the same thing as absolute global temperature data.
Good comment about the “family jewels,” Pamela. I have often wondered how many people see those anomaly charts and think the air/water/whatever is boiling hot.
“Not necessarily true.”
If the anomaly is positive, the absolute temperature is warmer than the average of the reference period. Necessarily.
Greg Goodman September 6, 2014 at 8:38 am
UK Met Office Hadley Center – HadSST3 – Click the pic to view at source[/caption]
International Comprehensive Ocean-Atmosphere Data Set (ICOADS) – Click the pic to view at source[/caption]
To be more precise it is centred on Berring Sea area and also Labrador Str between Canada and Greenland.
Yes, and there is also a warm patch in the Eastern Pacific off of Vancouver, which you can sorta see that on HADSST3’s fuzzy map;
[caption id="" align="alignnone" width="850"]
or you can see much more clearly on the right bottom pane of this ICOADS graphic:
[caption id="" align="alignnone" width="850"]
thanks, I was looking for something like that but did not have time. Most of the warming does seem to be in regions connecting with the Arctic Ocean.
If it’s not the heat dumped by the freezing water, it would seen odd that record SST accompanies an “unprecedented” recovery in ice volume.
Would not long continues high pressure allow solar insolation to warm the surface?
The general Coriolis circulation is clockwise in N. Pac. , that would cause the warming in Bering Sea to spread down the west coast.
Yes, the North Pacific Gyre, or more precisely, Oyashio and Kuroshio currents would cause the warming to spread to California current;
Canadian Museum of Nature – Click the pic to view at source[/caption]
[caption id="" align="alignnone" width="850"]
but from the ICOADS image above, it also looks like the Alaska current may also be bringing anomalously warm water back to the Bearing Sea.
Based on these maps it looks like the most heavily surveyed area is also the warmest. However, the area that is surveyed less (southern oceans) appears to be colder relatively speaking. Could it be that if the southern oceans were more heavily surveyed it would even out the anomaly? Also, if the Arctic sea ice is on an upswing could that be causing a greater amount of cold water to be plunging south into the Bearing Sea thereby displacing and forcing up warmer water?
Werner, your figure 1 isn’t really a fair comparison. If you’re going to do this and comment, you should at least line up the means, not the peaks, especially when the peak in RSS is clearly an isolated event, probably from its sensitivity to a discrete event in the ongoing Super El Nino.
I think I’m going to contact William Briggs and see if I can get him to do a good statistical rant on the subject of using anomalies as a free-floating hidden parameter of climate model presentations (given that all of the data we ever see is produced by a model — there is no such thing as raw data on any graph produced in climate science, pretty much ever). I just finished reading his 5 episode rant on the simplest of topics — has the climate grown warmer or cooler, and how would we know — but he doesn’t discuss the subtle ways one can manipulate or be misled about outcomes just from things like this — exactly where do you put the base of an anomaly computation when it is the anomaly of a different model leading to a new model that you actually present.
rgb
Yes, land air temps tend to change about twice as fast as SST. Aligning the mean would make more sense.
Rate of change dT/dt : land surface air temps ( BEST ) vs SST
http://climategrog.files.wordpress.com/2013/05/land-sea-ddt.png
It may be interesting to plot RRS / 2.0 against SST with the means aligned. ( By eye the scaling may be more like 2.5 )
That would probably the recent rise in SST stand out even more.
Looking again at the graph, there is an extended period in 1970s when SST was cooling but BEST shows warming. That will leave BEST land record with a permanent warming offset.
UHI ?
rgbatduke
check your email please
Anthony
When Capt. Cook surveyed the the coasts north of the Bering Strait in 1778 he observed ice pack to the north “10 to 12 feet high” as far as he could go (east and west). –AGF
Do you know off hand what month that was?
August 18: http://libweb5.princeton.edu/visual_materials/maps/websites/pacific/cook3/cook3.html
Thanks
In 1956 the Soviets proposed damming the Bering Strait to promote Arctic and North Pacific warming: http://books.google.com/books?id=QuEDAAAAMBAJ&pg=PA135&dq=1954+Popular+Mechanics+January&hl=en&sa=X&ei=jLnBT_OmOpT3gAfc2_WlBQ&ved=0CD4Q6AEwAjgy#v=onepage&q&f=true
I can see how that might warm the Pacific, but think the Arctic would freeze over north of such a dam.
Likely I should read the article. Now you’ve gone and done it. My schedule will be in ruins.
Of course, the law of unintended consequences would kick in, and we’d wind up with ice-age weather. After all, the Bearing Strait was all dry land back then.
(credit Wikipedia)
Thanks
It’s good to recall that wind speed connects SST and tropospheric temperature. The lower the wind speed, the lower the ocean evaporation. Lower ocean evaporation leads to higher SST. Lower ocean evaporation also leads to lower mid-tropospheric temperature as there’s less condensation of moisture in the troposphere (condensation warms the mid-troposphere).
Nothing special with 2014
WoodForTrees.org – Paul Clark – Click the pic to view at source[/caption]
http://www.woodfortrees.org/plot/rss/from:1997/mean:6/normalise/plot/hadsst3gl/from:1997/mean:6/detrend:0.1/normalise
[caption id="" align="alignnone" width="640"]
(Image added for easy reference. JTF)
Why are they different?
Why think they should be the same
One measures set globally
The other estimates air temperature kilometers above
The land and ocean
The question was why are they different, not why aren’t they the same when they should be.
If both are accurate what does it tell us? “Why are they different?”
justthefactswuwt ,
If you can, please consider increasing the size of the lines used in the WFT plots and avoid combining shades of red and green in the same ‘spaghetti’ plot. The increased line size gives those of us with ‘red/green’ color blindness more pixels to help resolve the color differences. About 7% of the male population and 0.5% of females are afflicted with varying degrees of red/green color blindness. It’s carried through the mother’s X chromosomes and is a recessive trait so female offspring (X-X chromosomes) must inherit 2 afflicted X chromosomes but male offspring (X-Y chromosomes) need only inherit 1 afflicted X chromosome. Lucky us, eh fellers?
I routinely ‘zoom’ these plots to aid color resolution ….. but still struggle with it.
Mac
Unfortunately, users cannot control the thickness of the lines or the line colors on WFT. However, you raise a good point. Perhaps if someone was to make a small donation to Paul Clark’s tip jar;
https://www.justgiving.com/WFT/
and ask him to change his default line colors (along with a suggestion of what colors might work better) and to increase the thickness of his lines a bit, he might do so on his site;
http://www.woodfortrees.org/
when he has an opportunity.
Lines look fine to me.
If you don’t like it, you can get the processes data off WTF, download gnuplot and produce whatever you like. ( it’s what WTF uses ) .
WFT, not WTF
Thanks, but for a tool that does little for climate discussions than to offer people the means to continue the obsession of fitting linear models to data that has nothing linear about it and whose main data processing tools are the running mean and the detrend,
You can’t even plot the difference between two datasets.
I wrote to Paul several times suggesting how he could include so less distorting filters and pointing out the issues, He was not interested ( in a fairly offhand way ).
I retain the reference WTF.
Can anyone point me to some discussion/criticism of the Arctic sea ice they show on this chart, which data goes back to c.1953? Thanks.
http://nsidc.org/icelights/2011/01/31/arctic-sea-ice-before-satellites/
“Those records show that Arctic sea ice has been declining at an increasing pace since 1979—enough data to see a strong signal of climate change. ”
” Shipping records exist back to the 1700s, but do not provide complete coverage of the Arctic Ocean. However, taken together these records indicate that the current decline is unprecedented in the last several hundred years.”
No error bars on either the sat data nor the earlier data to show how uncertain the early data is. Just pretend it’s all the same.
No break indicating the difference data.
Same “std dev” scale for the ensemble, taken from the 1968-1996 satellite period.
A jump ( drop ) of 2 std dev where they graft the two datasets together that gives the impression of a fairly even decline since 1968. Blend the two datasets together with a running mean.
Now, if they’d more correctly, used a different line for the different data that mannian “trick” would stand out a mile.
What more do you need to know about their “science”.
HadSST3 vs. ERSST.v3b (1998-2014):
http://i1172.photobucket.com/albums/r565/Keyell/HadSST3vsERSSTv3b_zpsb615cf5e.png
HadSST3 vs. HadISST1 (1998-2014):
http://i1172.photobucket.com/albums/r565/Keyell/HadSST3vsHadISST1_zpsbb5b4978.png
HadSST3 vs. Reynolds OI.v2 (1998-2014):
http://i1172.photobucket.com/albums/r565/Keyell/HadSST3vsOIv2_zpsa386e47d.png
ERSST.v3b vs. HadISST1 vs. Reynolds OI.v2 (1998-2014):
http://i1172.photobucket.com/albums/r565/Keyell/SSTa98-143datasett_zpsd468ae57.png
HadSST3 definitely appears to be running somewhat high. Also notice how OI.v2 (the global dataset Tisdale normally uses) appears to shift up by ~0.025 degrees at the 2012/13 transition relative to the ERSST and HadISST datasets, seemingly ‘catching up’ with HadSST3. A permanent feature?
All data from KNMI Climate Explorer.
UPDATES
With the RSS August anomaly of 0.193, the average is 0.258 over 8 months. This would rank in sixth place if it stayed this way. To set a record in 2014, the average anomaly over the next 4 months needs to be 1.134. The highest ever anomaly for RSS was in April of 1998 when it was 0.857.
For UAH version 5.6, the anomaly would have to jump from 0.199 to 0.768 and stay there for the next four months to break a record. The highest ever anomaly on version 5.6 was set in April of 1998 when it reached 0.663. Version 5.6 would come in fourth if the anomaly average stayed where it is after 8 months.
There is no way that any satellite data will come in first or even second for 2014. So the 1998 records are safe this year.
Further to Section 2 where I gave numbers according to Nick’s program, Dr. Ross McKitrick has come up with slightly different numbers for the times for no statistically significant warming for three of the data sets.
His times are as follows:
Hadcrut4: No statistically significant warming for 19 years.
UAH: No statistically significant warming for 16 years.
RSS: No statistically significant warming for 26 years.
rgbatduke
WoodForTrees.org – Paul Clark – Click the pic to view at source[/caption]
September 6, 2014 at 9:29 am
Werner, your figure 1 isn’t really a fair comparison. If you’re going to do this and comment, you should at least line up the means
Thank you! I have aligned the means for RSS and Hadsst3 since 1996.75. The basic conclusion of course does not change. See:
[caption id="" align="alignnone" width="640"]
Graph updated in the article accordingly. The original graph is below for reference sake:
WoodForTrees.org – Paul Clark – Click the pic to view at source[/caption]
[caption id="" align="alignnone" width="640"]
Greg Goodman
September 6, 2014 at 8:38 am
This article mentions the effects of evaporation but it is the latent heat of fusion ( freezing/melting ) of water that may be more pertinent.
You bring up an interesting point in that it may explain the sea surface temperature. My focus was more on why RSS did not follow suit, and for that, evaporation and condensation would be more important.
No, your evaporation argument could affect air temps, that’s fine but if you are trying to explain a difference a change to either could be the cause.
If it explains the change in SST at high northern latitudes, which is basically where the _global_ rise is coming from in the data, then it could account for the discrepancy and answer your question.
Greg, Werner, lgl, rgbatduke:
Ah, but the “Arctic warming” that is ever-so-often claimed is the LAND (tundra, forest, taiga, swamp, marsh, and wetlands) area of the “Arctic” between 60 north and 70-72 north latitude. There is almost NO land north of 72 north latitude – and that either completely ice-covered (Greenland) or isolated islands. The “ice-covered” arctic lies almost entire north of 70 north latitude (the north coasts of Alaska and Canada’s Yukon is below 70 north, the of Canadian arctic is almost entirely islands separated by ice-filled straits, then you have the central ice-covered highlands of Greenland, and one stub of a Siberian peninsula. )
thus, “Arctic warming” can be entirely ascribed to CO2 -> Because EVERY tree, bush. scrub, moss, and algea up there is darker, longer, fuzzier, greener, and longer-lived BECAUSE of the extra fertilizer now in the air up north. A darker albedo heats the arctic LAND and thus heats the air around the Arctic ocean. Which, by the way, is the ONLY place where the thermometers are measuring a warmer arctic.
Up where the arctic ocean ice actually is, the DMI summer temperatures since 1959 have been increasingly getting colder since 1959. (Winter – none sunshine days! – above 80 north latitude have been about 5 degrees warmers since 1959 … Again, NOT due to CO2 but that can be due to the decreased albedo of the trees and brush sticking up above the snow. It is ONLY “AVERAGE” Arctic annual temperatures that have increased.
Else, why would winters be warmer when there is no sunshine to heat the air through increased CO2 concentration?
No, your evaporation argument could affect air temps, that’s fine but if you are trying to explain a difference a change to either could be the cause.
Good point! Thanks!
http://brunnur.vedur.is/pub/trausti/Iskort/Jpg/1935/1935_08.jpg
Try this for old sea ice maps.
Nice. Note that the white bit is labelled “state of ice unknown”. Don’t assume it ice because it’s white 😉
Werner Brozek
September 6, 2014 at 11:31 am
Because RSS doesn’t include data from the poles, how would that change things in your [opinion] ?
http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCEQFjAA&url=http%3A%2F%2Fweather.unisys.com%2Fsurface%2Fsfc_daily.php%3Fplot%3Dssa%26inv%3D0%26t%3Dcur&ei=H1wLVMrmEIivyATfzYC4Cg&usg=AFQjCNHhezMokwDrS6s1KBmclNR0rKpZcQ&bvm=bv.74649129,d.aWw
A C Osborn
September 6, 2014 at 9:04 am
You would also expect the Lower Trop temps to reflect any surface increase as the Water warms the Atmosphere.
Do they even match Area wise?
By aligning the means as Dr. Brown suggested, and as shown above, there is some relation, although RSS has larger areas, both positive and negative, but this seems to break down very recently.
Air temps are more volatile as I already pointed out.
Someone posted a graph of “normalised” temps which partly aligns things thought I’m not sure that it provided the most appropriate scaling.
The chart shows sea surface temperature anomaly is very variable all over the globe and happens to be well above normal only in the Northern Pacific which would in turn serve to limit above average temperatures in the lower troposphere due to the high sea surface temperature in the Northern Pacific to areas ONLY around the Northern Pacific which would be 100% water which would warm at rates similar or less then the rate of the water beneath it.
Secondly this warming of the Northern Pacific is causing an atmospheric circulation pattern which is causing the majority of N.H. land areas to the east of it to have much below normal temperatures.
Hence the average global air temperature does not correspond to the record average high sea surface temperatures which is due mainly to the N. Pacific warm sea surface temperature anomaly. It’s effects on the lower troposphere air temperature being local in nature while at the same time causing lower then normal lower tropospheric air temperatures to land areas to the east of it. Areas like the Eastern Two Thirds of the U.S.A. which experienced a very cool summer.