HadSST3 Sets Records, RSS Not So Much (Now Includes July Data)

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

WoodForTrees.org – Paul Clark – Click the pic to view at source

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.

WoodForTrees.org – Paul Clark – Click the pic to view at­ source

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.

WoodForTrees.org – Paul Clark – Click the pic to view at source

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.

WoodForTrees.org – Paul Clark – Click the pic to view at source

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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September 6, 2014 12:40 pm

Pamela Gray
 
September 6, 2014 at 9:16 am
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.
Globally, July is about 3.8 C warmer than January. But to know how warm a slightly warmer north Pacific ocean really is, that would take a different graph. I saw one recently here on a comment at WUWT, but I do not recall where. Perhaps some one knows.

September 6, 2014 12:55 pm

Eric
 
September 6, 2014 at 10:14 am
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?
It seems clear that the south pole is gaining ice and the north pole is losing ice over the last 30 years, so I do not think that the degree of surveying is a factor.
As for the latter point, one must keep in mind the following: ice + heat water
Of course, this equation works both ways. So if ice is produced, heat is evolved. And if water is produced, heat is lost. So when a larger amount of sea ice melts, larger amounts of cold water are produced. And this could indeed be “plunging south”.

September 6, 2014 1:08 pm

Greg Goodman
 
September 6, 2014 at 9:49 am
It may be interesting to plot RRS / 2.0 against SST with the means aligned.
It looks interesting! I scaled RSS by 0.5 and offset Hadsst3 by -0.22. The alignment is close!
[caption id="" align="alignnone" width="640"] WoodForTrees.org – Paul Clark – Click the pic to view at source[/caption]

September 6, 2014 1:17 pm

David Smith
 
September 6, 2014 at 10:02 am
It’s good to recall that wind speed connects SST and tropospheric temperature. 
What you say makes perfect sense. Do you have any data that indicates that wind speed in the north Pacific has been lower over the last three months than at any other time?

NZ Willy
September 6, 2014 1:29 pm

HadSST3’s pattern is clearly annual, with SST maxima during the Artcic sea ice minima. Therefore they are counting Arctic open water temperatureas as 4C warmer than the ice-covered norm, while the Antarctic ice-covered areas are not being counted — so a very denormalized method. RSS does not do this. That’s my take on this.

Reply to  NZ Willy
September 6, 2014 2:22 pm

HadSST3’s pattern is clearly annual
In terms of absolute temperatures, that is the case for all temperature sets. However anomalies should automatically reflect this. But what we have here are record high June and July anomalies for Hadsst3, but RSS had June as the fourth warmest and July as the fifth warmest on record.

September 6, 2014 1:31 pm

lgl
 
September 6, 2014 at 10:04 am
Nothing special with 2014
Taking the mean of 6 is certainly one way to make the records over the last two months disappear! I wonder what taking the mean of 12 will do once December is in. I think it will show a new high peak for Hadsst3, but not for RSS.

September 6, 2014 1:38 pm

Steven Mosher
 
September 6, 2014 at 10:14 am
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

I would not expect them to be exactly the same, but due to the lapse rate and due to the fact that 71% of Earth’s surface is ocean, I would expect a reasonably close relationship.

September 6, 2014 1:53 pm

Kristian
 
September 6, 2014 at 11:04 am
HadSST3 definitely appears to be running somewhat high.
Thank you! I just hope that if Hadcrut4 sets a record this year, that it would be a real record and not one where 71% of Earth was running higher than it should have been.

September 6, 2014 2:09 pm

Stephen Richards
 
September 6, 2014 at 12:11 pm
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] ?

First of all, do you agree that it is mainly the north pole and not the south pole that would cause the most discrepancy? If so, it would mean very little difference. Here is why:
RSS goes to 82.5 degrees north.
 
With the circumference of Earth being about 40000 km, the distance from 82.5 to 90 would be 7.5/90 x 10000 = 830 km. So the area in the north NOT covered is pir^2 = 2.16 x 10^6 km2. Dividing this by the area of the earth, 5.1 x 10^8 km2, we get about 0.42% NOT covered by RSS in the Arctic.

September 6, 2014 2:20 pm

In relation to the scaling difference between air and SST I thought I’d try some manual fiddling on WTF. It is clear that RSS can be scaled by about a factor of two but there is a mismatch in the long term rise. RSS is damn near flat yet there is a small rise in SST.
Unlike his Lordship, I’m not in the habit of using RSS, I tend to use UAH. I have confidence in the team there and they make accessing the data clear easy and total. All datasets, daily if you want it. So I flipped the data on the plot to use UAH TLT and voila:
http://www.woodfortrees.org/plot/uah/from:1997/offset:-0.12/scale:0.65/plot/hadsst3gl/from:1997/offset:0.331/offset:-0.65
It matches hadSST3 pretty closely, accepting the scaling idea. Both inter-annual and decadal variability seem to match well. Not saying that they necessarily have to, or that this is proof that both UAH and hadSST3 are “right” but it’s an interesting observation.
Anther interesting feature that now becomes visible is that for a lot of this short period the air temps are lagging by what looks like 6 to 12m. Sadly with the rather limited possibilities on WTF it is not possible to shift the time axis to identify the lag any better, I’ll have to run this through gnuplot locally and regress the lag.

Reply to  Greg Goodman
September 6, 2014 2:30 pm

Thank you! So UAH would have proved my point equally well as RSS. However if there is a lag factor, then the satellite data had better spike quickly.

Reply to  Werner Brozek
September 6, 2014 3:28 pm

I don’t think TLT is going to show the same thing, the lag is only a few months and I don’t see any sign of it happening.

Reply to  Werner Brozek
September 6, 2014 3:49 pm

I agree there. UAH version 5.5 just came out for August and it dropped from 0.221 to 0.118. And this happened after Hadsst3 set an all time record in June.

Reply to  Greg Goodman
September 6, 2014 2:28 pm

Ah no. Werner, how you do you manage to link the visible graph into a comment?

Reply to  Greg Goodman
September 6, 2014 2:32 pm

I think justthefacts did that.

Reply to  Greg Goodman
September 6, 2014 3:34 pm

Thanks, I think he must have saved it elsewhere and put it in as a link, the graph is on WUWT. I don’t think you can get a png image link off WTF.

Reply to  Greg Goodman
September 6, 2014 3:44 pm

This should do it:
http://climategrog.files.wordpress.com/2014/09/uah_hadsst3_offset-0-58.png
Same with 12mo filter:
http://climategrog.files.wordpress.com/2014/09/uah_hadsst3_offset-0-58_12mlp.png
We can see that the divergence start in mid 2013, after the low-passed data ends. It does seem to coincide with the Arctic ice recovery.

Bill Illis
September 6, 2014 2:39 pm

As I have noted before, the Ocean SST records have become corrupted because somebody left a huge amount of seasonality in the numbers (on purpose I assume so that once per year they could claim records are being set).
July is always very high now in the HadSST3 record and August is always high in the NOAA OISSTv2 record because they have screwed up the seasonality which any first year stats student couldn’t even do.
http://s27.postimg.org/3l47jbac3/Northern_Oceans_Had_SST3png.png
It is disturbing to me because even the AMO values are now useless because of this deliberate obfuscation.

Reply to  Bill Illis
September 6, 2014 3:11 pm

That’s a very good point about hollering records based up on anomalies. I would not say they’ve screwed it up but it is a problem with one size fits all annual “climatologies” when the annual cycles change in magnitude over the decades. The Cryo Today Arctic ice “anomaly” is pretty unclear since 2007 for the same reason, which is why I did and adaptive anomaly.
https://climategrog.wordpress.com/2013/09/16/on-identifying-inter-decadal-variation-in-nh-sea-ice/
If they want to play alarmist games, it serves to leave base period in a segment with less annual variability. If you remove the residual seasonality, this year would not get past 2009-2010 levels.
Personally I don’t like all this “anomaly” game at all. To get rid of the annual cycle you need to use a low pass filter. This means you loose a bit of data and have to wait about a year longer for the numbers, but climate changes over decades so all the excitement with monthly updates is a bit silly anyway, most of the time.
Having removed the remaining annual variability, I found I was over-scaling TLT a little.
http://www.woodfortrees.org/plot/uah/from:1997/scale:0.58/mean:12/mean:10/mean:8/plot/hadsst3gl/from:1997/offset:-0.242/mean:12/mean:10/mean:8
The filter looses 14m at the end, so the last point is about March 2013. The match is pretty good.

September 6, 2014 3:17 pm

Just for the record here is the same processing on RSS:
http://www.woodfortrees.org/plot/rss/from:1997/scale:0.58/mean:12/mean:10/mean:8/plot/hadsst3gl/from:1997/offset:-0.242/mean:12/mean:10/mean:8
I think Spencer and Christy are correcting for some orbital decay problem that RSS does not.

Reply to  Greg Goodman
September 6, 2014 3:42 pm

I sure hope version 6 comes out soon. That was supposed to narrow the gap.

Greg
Reply to  Werner Brozek
September 7, 2014 2:34 am

According to Roy Spencer, the difference is minimal, at the level of hundreths of a degree, so they will still not be saying the same thing.
However, it may take away the slight difference at the end w.r.t hadSST3 where UAH is _slightly_ higher.
Though it would be nice if the two were telling the same storey it is healthy to have competing teams competing on a dataset. There is too much work going on to try to “homegenise” everything and most of it is polical expedience, not science.
I think John Christy ( Spencers boss ) has identified what he considers to be uncorrected errors in RSS processing.
I find the UAH team quick to correct identified errors and more transparent. Rare qualities in climate science and ones that build confidence in thier work.
Though many here may “prefer” the way RSS data looks, I have more confidence that Christy’s team are the better interpretation of the raw data.
IIRC the RSS team include data from slightly higher latitudes, that may also account for some differences.

Reply to  Werner Brozek
September 7, 2014 6:09 am

Part of the problem is that we are talking about so little in the first place, namely 0.7 C over 160 years that a few hundredths over 30 years could make more difference than we think. I guess we will have to wait and see.

September 6, 2014 3:40 pm

UAH update:
The version 5.5 August anomaly dropped to 0.118. As a result, the 8 month average is 0.197 which would tie it for 7th place.
RSS further information. As you know, the time for a slope of 0 is now 17 years and 11 months with the August number.
The negative slope for 215 months is “slope = -5.54517e-05 per year”. So since the negative slope for 15 years is more negative than the positive slope for 16 years “slope = 2.67567e-05 per year”, one could say that to the nearest month, the absence of warming is indeed 18 years.
From Walter Dnes:
“A bit of reverse engineering shows that if September RSS comes in between +0.218 and +0.270, the slope will be slightly negative for October 1996 to September 2014.”
Since the August value was 0.193, it would require a bit of a spike to avoid 18 years next month. And should it stay at 0.193, then the pause would be 18 years and 1 month with the next anomaly.

Nick Stokes
September 6, 2014 5:11 pm

Werner,
You give these pause periods:
“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).”

Two months ago the corresponding periods were:
“1. For GISS, the slope is flat since September 2004 or 9 years, 9 months. (goes to May)
4. For Hadcrut4, the slope is flat since January 2001 or 13 years, 5 months. (goes to May)
5. For Hadsst3, the slope is flat since January 2001 or 13 years, 5 months. (goes to May)
6. For UAH, the slope is flat since January 2005 or 9 years, 5 months. (goes to May using version 5.5)
7. For RSS, the slope is flat since September 1996 or 17 years, 9 months (goes to May).”

GISS, HADCRUT and RSS much the same, but in that two months the Hadsst3 pause has shrunk by 8 years, and UAH by over three. I think this will continue, and surface measures will have a shrinking pause; it’s partly present warmth, but also the 2008 dip receding into the past. I’ve set out some plots here.

Reply to  Nick Stokes
September 6, 2014 7:09 pm

I agree with you on Hadsst3, but not on UAH, version 5.5. The August anomaly just came out and the 0.118 was below the zero line such that the time for a slope of zero jumped to January 2005, or 9 years and 8 months.

jl
September 6, 2014 6:05 pm

And isn’t the bigger picture the fact that even if they all show warming, that’s still not proof as to the cause of the warming- which is the whole point, right?

Reply to  jl
September 6, 2014 7:10 pm

You are correct. However if there were no warming, there would be no warming to explain. That would make life very simple. But if the warming is half of what the models predict, then that has to be explained.

wayne
September 6, 2014 6:14 pm

Dropping all of the means to zero with [offsets] as rgb suggested I fail to see the ‘record’. Does WFT have the latest data yet? Is that what is missing? They all are adjusted data so I see little insight in this exercise… well except they all seem to be adjusting just enough to keep all plots of recent records flat, anomaly-wise that is.
http://www.woodfortrees.org/plot/uah/from:2008.4/offset:-0.21/plot/uah/from:2008.4/trend/offset:-0.21/plot/rss/from:1996.8/offset:-0.229/plot/rss/from:1996.8/trend/offset:-0.229/plot/hadcrut4gl/from:2001.05/offset:-0.478/plot/hadcrut4gl/from:2001.05/trend/offset:-0.478/plot/hadsst3gl/from:2009.1/offset:-0.380/plot/hadsst3gl/from:2009.1/trend/offset:-0.380/plot/gistemp/from:2004.65/offset:-0.59/plot/gistemp/from:2004.65/trend/offset:-0.59

Reply to  wayne
September 6, 2014 7:11 pm

wayne
 
September 6, 2014 at 6:14 pm
Dropping all of the means to zero with offets as rgb suggested I fail to see the ‘record’. Does WFT have the latest data yet?
I do not think rgb meant what you think since he did not talk about the line of zero slope at all. He talked about the average value and aligning that. So if one set had a average value of 0.5 and the other of 0.3, he intended the 0.3 to be raised by 0.2 so relative trends could easily be seen.
As for WFT, after the data is posted, they automatically upload at the time of the next upload. I do not know your time zone, but it happens to be at 8:00 P.M. Mountain daylight time.

September 7, 2014 3:04 am

The record is in the monthly anomaly and is mainly due the annual variability being larger now than it was for the arbitrary period that is used as the reference “climatology” , which is Bill Illis’ gripe.
If the annual cycle was of a lesser amplitude this years, we’d be seeing “record” warm anomalies in the winter.
I don’t think aligning the mean is the most informative. There is also a scaling issue since air has a very different heat capacity and so does land. The best way to do it would be by regression fitting both an offset and scaling parameter to minimise the residual difference between the two datasets.
I have done a quick grab at doing manually as noted above.
http://climategrog.files.wordpress.com/2014/09/uah_hadsst3_scale_0-58.png
They are both very close until about March 2013 where we see the divergence start to appear.
.

Reply to  Greg Goodman
September 7, 2014 3:32 am

As Bob Tisdale originally pointed out, most of this up swing in the global average is due to northern and north-eastern Pacific SST, Bering Sea and Str of Labrador.
My reading of this is that melting of ice over most of the reference period was absorbing heat from the surface waters. It takes considerable energy to melt the ice. (78 times more than to warm it by 1 degree Celcius) !
This means that the summer part of the annual SST cycle would have been attenuated by the energy going into melting ice. Since the ice has been recovering for the last two years now we see less heat than before going into melting ice and thus a larger summer excursion.
This is reflected in the larger magnitude annual cycle and the positive anomaly that remains once the “average” annual cycle of the earlier reference period is subtracted.
Conclusion: the record anomalies of this years summer months are not a sign of continued AGW, but a result of the end of the “catastrophic” loss of Arctic sea ice and the notable increase in ice volume over the last two years.
The effect of less heat going into ice melting in the summer and the heat being dumped by the massive freezing and increase in ice volume measured by Cryosat2 last year will mean and increase in SST in the regions communicating with Arctic ocean.
Alarmist scientists need to explain what is driving this “unprecedented” increase sea ice despite the notably warmer regional SST.

Reply to  Greg Goodman
September 7, 2014 5:57 am

This makes a lot of sense. Now we just need a graph of ice volume in the Arctic superimposed on a graph of ocean anomalies in the north over the last 30 years. But does anything like that even exist? Areas of ice are one thing, but volumes are much tougher to measure.

Reply to  Greg Goodman
September 7, 2014 5:42 am

There is also a scaling issue since air has a very different heat capacity and so does land.
A scale of 0.7 for RSS versus Hadcrut4 comes pretty close.
http://www.woodfortrees.org/plot/rss/from:1997/offset:0.376/scale:0.7/plot/hadcrut4gl/from:1997

Reply to  Werner Brozek
September 7, 2014 6:14 am

The whole HadCRUT idea is flawed. You cannot average the temperature of land and water.
Especially when it can be seen that land temps change at twice the rate of SST. It’s like trying to work out the average colour of a box of paints.
The answer is muddy brown, you then spend 30 years arguing whether is it browner than it used to be and if the trend continues for the next 100y what shade of shit we will be in.
You will also notice that it does not fit anywhere near as well as UAH TLT.

Reply to  Werner Brozek
September 7, 2014 7:19 am

The whole HadCRUT idea is flawed. You cannot average the temperature of land and water.
Of course you are correct. As well, you cannot compare a 1 C rise of -40 C dry Arctic air with a 1 C rise of moist tropical air at + 40 C. But we were forced to use the tools we had, especially before the satellite era. Then some want to throw deep ocean water into the mix which may have gone up from 3.8 C to 3.9 C and pretend that will come back to bite us somehow.

David A
September 7, 2014 4:17 am

Would not long continues high pressure allow solar insolation to warm the surface?

Reply to  David A
September 7, 2014 6:03 am

I suppose a long blocking pattern would do something. This relates to an earlier comment about less wind causing less evaporation. So combined with less ice melting, we may be on to something.

Reply to  David A
September 7, 2014 6:20 am

Lot’s of things affect climate. The objective is to explain what is happening.
If you have reason to suggest that there has been an unprecedented change in arctic cloud cover over the last 18mo , please show evidence, otherwise such sweeping and banal comments don’t really advance the discussion.

Reply to  Greg Goodman
September 7, 2014 7:25 am

If you have reason to suggest that there has been an unprecedented change in arctic cloud cover over the last 18mo , please show evidence, otherwise such sweeping and banal comments don’t really advance the discussion.
I do not agree here. By bringing out ideas like this, we may be prompted to perhaps start looking for things that we may not even have thought of looking for. Who knows what we may find? It may lead to nothing, but on the other hand, it may lead to something useful.

David A
Reply to  Greg Goodman
September 7, 2014 6:24 pm

“Banal comments” ? I suggest a mirror Sir. I am talking of the very long term high pressure over the North Pacific. High pressure keeps cloud cover away. Bob Tisdale has done posts on this. Also in such high pressure areas their is a general tendency for winds to be reduced. (There are exceptions) Did you not see the high pressure chart next to the record anomaly SST chart. They are both red in the same area in numerous areas, including the North Pacific. http://wattsupwiththat.com/2014/09/06/hadsst3-sets-records-rss-not-so-much-now-includes-july-data/#comment-1729203 (SST warming through solar insolation with reduced winds is both logical and a current observation.)

September 7, 2014 6:24 am

Anthony, what is going on with comment positioning?
Since the recent changes ( nearly ) every time I post a comment, the page refreshes at some position about 20 comments in arrears.
I had not commented earlier since I thought it would get ironed out and I have not been able to note why or where it dumps me but it’s very rare for it to return to my last posted comment, whether it is at the end of the thread or a reply to something higher.
REPLY: No idea, no other complaints. Try a different browser. This is also the wrong thread for such discussions -A

Reply to  Greg Goodman
September 7, 2014 6:25 am

About the last 5 posts here have all returned me to Nick Stokes comment.
http://wattsupwiththat.com/2014/09/06/hadsst3-sets-records-rss-not-so-much-now-includes-july-data/#comment-1729464
No idea why ;?

Reply to  Greg Goodman
September 7, 2014 7:55 am

No ….all fine here. Close/refresh/clear cache. Whatever the problem is it is local to your machine.

Reply to  Greg Goodman
September 7, 2014 7:56 am

Are you using some offbeat browser? Or, a browser that hasn’t been updated for a long time?

Nick Stokes
Reply to  Greg Goodman
September 7, 2014 2:27 pm

Greg Goodman September 7, 2014 at 6:25 am
“No idea why ;?”

It’s telling you something :).
I think all that is happening is that as you write, other comments have been added upthread, pushing everything down. You refresh to that lower position.

Reply to  Greg Goodman
September 7, 2014 4:39 pm

If that is the case for Greg, perhaps he should do what I do, namely write the whole comment on a new page, and once it looks good, copy and paste it to where it is wanted.

Pamela Gray
September 7, 2014 7:25 am

Anomalies, especially global anomalies tell us whether or not temperature has risen relative to each part of the ocean. It does not tell us absolute temperature. It is even worse when used globally.
I have encountered many people who believe that when the eastern equatorial Pacific is red with anomalous heat, it is hotter than the western Pacific (because it is shaded in a hue less than hot, hot, hot. I have even encountered people who think the “red hot color” of the northern Pacific means it is now the hottest part of the all the ocean surfaces. People at the street level of understanding of CO2-driven downwelling longwave infrared radiation will go on to explain how that heat is caused by CO2 in the air there heating up that part of the ocean. In addition, this kind of metric allows the presenter to use incredibly bright red colors for oceans that will, regardless of the colors we paint them in, freeze hanging fruit right off the tree.
Global and regional absolute temperatures down to SW infrared penetrating depth is a much better metric when talking to street level people. And will usually cause quite a surprised look, followed by questions like, “Is that what we are supposed to have our collective panties in a twist over?”

Reply to  Pamela Gray
September 7, 2014 7:33 am

People at the street level of understanding of CO2-driven downwelling longwave infrared radiation will go on to explain how that heat is caused by CO2 in the air there heating up that part of the ocean.
Then there is the problem to explain how CO2 just manages to heat one part of the ocean and not the rest. And why does CO2 heat the Arctic and not the Antarctic?

Pamela Gray
September 7, 2014 7:42 am

Greg, you mistake ocean warming processes by thinking each area of ocean water heats up due to a local phenomenon in that area. That paints ocean processes with too broad a brush. Ocean warming is more likely, in the upper northern latitudes, to be caused by waters that were warmed elsewhere, moving into those areas. Melting ice and glancing solar caused heating would be a very tiny drop in the bucket compared to unimaginably huge amounts of warmer than usual water invading northern ocean areas. CO2 need not apply.

Reply to  Pamela Gray
September 7, 2014 10:51 am

Pamela, I agree. I don’t see how the abnormal North Pacific warming spikes of the last year, year and a half would have anything to do with the sea ice cover in the Arctic basin.

Catcracking
Reply to  Kristian
September 7, 2014 9:33 pm

Kristain,
That’s an interesting conclusion; but some of us fail to see how if the ice mass increases by 40%, one can be certain that that all that heat released is not at all involved in warming spikes since it has to show up somewhere, either in the atmosphere or in the water temperature. Do you know if anyone has calculated the amount of heat released and determined where it has shown up? Not being a climatologist I don’t know, it is just a question of interest. Another coincidence, the ice growth has occurred over the last 2 years and the warming spikes occurred over the same timeframe.

Reply to  Kristian
September 8, 2014 5:52 am

Much of what I say here has been said elsewhere, but with nested replies, it is easy to not see it.
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.
As for the energy released, that can be calculated by multiplying the heat of fusion (334 J/g) for water by the mass. And that heat would marginally warm very cold air. But there is always more colder air to replace any air that may have been slight warmed.

Catcracking
Reply to  Kristian
September 8, 2014 8:37 pm

Werner says,
“As for the energy released, that can be calculated by multiplying the heat of fusion (334 J/g) for water by the mass. And that heat would marginally warm very cold air. But there is always more colder air to replace any air that may have been slight warmed.”
I came to this site as a skeptic on many things but also including global warming. I believe that skepticism is an important aspect as an Engineer even though we frequently become a PIA. As such, I remain to be convinced that forming a massive amount of ice has only a marginal effect absent more data/calculations. We are aware of the heat released in theory, but has anyone calculated the total hear release for the 40% area increase in ice. How much mass is involved? I don’t know.
Furthermore I fail to see how we know the heat does not go into the water as well as the air. Maybe the air ultimately removes some of the heat heat from the water?
Any further explanations appreciated.

Reply to  Kristian
September 8, 2014 10:31 pm

Keep in mind that this 40% increase happened over 365 days so it is not as if a whole bunch of ice formed at once and created huge amounts of heat. The formation of ice would occur in two general places.
One is at the surface where very cold air that is below freezing causes water in contact with it to freeze. If the heat from this freezing heats the water to above freezing, then it would melt as soon as it froze, but that does not happen. So it must be the air that is warmed. However if the air is warmed to above the freezing temperature of sea ice, then it would melt it right away. Since this does not happen, the air must warm slightly, but still stay below freezing. If it is windy while the freezing is occurring, you may never be able to detect any slightly warmer air.
The other place where freezing occurs is under existing ice. So let us pretend we have a metre of ice and air at -30 C above the ice. So ice in contact with air is at -30 C. But ice in contact with sea water may be at -2.0 C for example. So you have this gradient of temperature inside the block of ice. And if we assume the freezing point of sea water is -1.8 C, some water at the bottom of the ice freezes. This might temporarily warm the bottom of the ice to -1.9 C from -2.0 C. But it would not warm the sea water, otherwise it would melt what it just froze. But keep in mind the air is still -30 C above the ice, so even if the ice at the bottom warmed a bit for a few minutes, the cold would conduct down to the bottom of the ice and cause more freezing.
As for calculating exact amount of warming, that could be done in a closed system for example if you had a super insulated garage at -20 C. Then if you brought in a kilogram of water at 0 C and let it freeze, you could calculate how much the air would warm if you know the volume and density of air in the garage. But with an atmosphere that is tens of kilometres thick with all kinds of winds to boot over a huge area, then any calculations that you could do would not be very meaningful. Perhaps the polar vortex that hits you may be at -38 C instead of -40 C if it were not for a lot of freezing occurring on the way.

Pamela Gray
September 7, 2014 7:45 am

Werner, when I bring that one up, all manner of silly explanations issue forth from watermelons. No wonder we still have people voting for climate change politicians. They don’t understand their own premise let alone natural variation.

Pamela Gray
September 7, 2014 7:48 am

Greg, you appear to be stuck in last place forever. Or actually Nick has. Your last comment that includes a link to Nick appears to be forever moving to the last comment in this post. So either it is the last word, or it is in last place regarding this topic. Now that is a funny glitch! LOL!!!!

Reply to  Pamela Gray
September 7, 2014 7:54 am

No he isn’t all fine here. Close/refresh/clear cache. Whatever the problem is it is local to your machine.

Pamela Gray
September 7, 2014 7:57 am

There! Someone fixed it! Greg, your comment that contained a link to Nick’s data has returned to its normal place in the thread and Nick’s link is no longer in last place. The poltergeist has apparently moved on. Dang. I rather liked having Nick’s link in last place. It was such a well done study in gnat anatomy.

Reply to  Pamela Gray
September 7, 2014 8:10 am

Nobody fixed anything on this end.

Reply to  Anthony Watts
September 7, 2014 8:47 am

OK, if no one else ( apart from Pam ) is reporting problems…
I didn’t bother mentioning it before but I thought you should be aware. Maybe others are also no reporting it.
Presumably related to new threaded format, I’ve never seen it before. It’s annoying but I can live with it 😉

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