Guest Post by Werner Brozek, Edited by Just The Facts:
The above are plots of what the slopes NOAA’s surface temperature anomalies look like for the three intervals 1975 to 2000; 1950 to 2000; and 2000 to 2015. The top one is before adjustments and the bottom one is after adjustments, seemingly in an attempt to get rid of the hiatus. The given slopes are in degrees C/century.
Karl Popper said: “For it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition.”
So exactly what is the definition of a hiatus? NOAA defines a “hiatus” as a slowdown in warming and not a complete stop, so we are NOT talking about a pause with a very slight negative slope when talking about whether or not we are in fact experiencing an “hiatus”. However by talking about a “slowdown”, at least three different elements need to be defined so we can all be clear whether of not a hiatus has indeed occurred.
We need to know how long the recent period is that we are comparing things to. Then we need to know how long the previous period can be that we are using for a comparison. Then we need to know how much higher the previous period needs to be in order for us to have a hiatus. For example, does the previous slope need to be at least 10% or 20% or 30% higher than the most recent slope in order to claim that we have a hiatus?
Let me illustrate why the above are important with an analogy. Suppose Bob is born with a height of 20 inches at birth. Then Bob grows to be 5 feet when his 12th birthday is reached. Then Bob undergoes a huge growth spurt and reaches 6 feet on his 13th birthday. Then his growth rate slows down and he only gains another 4 inches by his 14th birthday. Now the question is: “Did his growth rate slow down?” Probably 97% of people would say the growth rate slowed. But 3%, all climate scientists, would say there never was a change in growth rate. They would say Bob grew 52 inches or 4 inches per year in the first 13 years. And since he grew 4 inches between ages 13 and 14, there was no slowdown. Would you agree?
If I were to define a hiatus, I would say the most recent period must be at least 15 years. And the period preceding it must also be at least 15 years, but not more than 25 years. And the slope of the preceding period must be at least 30% more than the latest slope. By this definition, even NOAA shows a hiatus since the recent ratio for 1975 to 2000 versus 2000 to 2015 is 1.717/1.143 or 1.50 so the preceding period has a slope that is 50% more than the latest slope. Would you agree? Of course, comparing 2000 to 2015 with 1950 to 2000 gives a completely different picture as can be seen on the above diagrams.
Before the revisions, the ratio for the slopes for (1950 to 2000)/(2000 to 2015) was 1.48, so the 50 year period had a slope that was 48% larger. But afterwards, the latest 15 year period actually had the larger slope. In all fairness to Thomas Karl, I am not aware of a precise definition of a hiatus so no one can accuse him of changing definitions. However I do believe it is ingenious of him to compare the recent 15 years with 50 years before that, especially since virtually nothing happened for the first 25 of those 50 years.
The following is from their report: “In summary, newly corrected and updated global surface temperature data from NOAA’s NCEI do not support the notion of a global warming ‘hiatus.’ Our new analysis now shows the trend over the period 1950-1999, a time widely agreed as having significant anthropogenic global warming (1), is 0.113°C dec−1, which is virtually indistinguishable with the trend over the period 2000-2014 (0.116°C dec−1).”
The above statement perplexes me. They appear to be satisfied that they have proven to themselves and hopefully others that no hiatus occurred. But in doing so, they have, in my mind, proven that there is no catastrophic warming occurring either. A warming rate of 1.16 C/century will not reach 2 C by 2100.
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 some data sets. At the moment, only the satellite data have flat periods of longer than a year. 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 2015 so far compares with 2014 and the warmest years and months on record so far. For three of the data sets, 2014 also happens to be the warmest year. 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 on at least one calculation. 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.
1. For GISS, the slope is not flat for any period that is worth mentioning.
2. For Hadcrut4, the slope is not flat for any period that is worth mentioning.
3. For Hadsst3, the slope is not flat for any period that is worth mentioning.
4. For UAH, the slope is flat since February 1997 or 18 years and 4 months. (goes to May using version 6.0)
5. For RSS, the slope is flat since December 1996 or 18 years and 6 months. (goes to May)
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 at the top 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 the two slopes are essentially zero. 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 18 years, the temperatures have been flat for varying periods on the two sets.
Section 2
For this analysis, data was retrieved from Nick Stokes’ Trendviewer available on his website. 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 14 and 22 years according to Nick’s criteria. Cl stands for the confidence limits at the 95% level.
The details for several sets are below.
For UAH6.0: Since October 1992: Cl from -0.026 to 1.731
This is 22 years and 8 months.
For RSS: Since January 1993: Cl from -0.013 to 1.672
This is 22 years and 5 months.
For Hadcrut4.3: Since July 2000: Cl from -0.017 to 1.371
This is 14 years and 10 months.
For Hadsst3: Since June 1995: Cl from -0.003 to 1.739
This is an even 20 years.
For GISS: Since November 2000: Cl from -0.018 to 1.336
This is 14 years and 7 months.
Section 3
This section shows data about 2015 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. 14ra: This is the final ranking for 2014 on each data set.
2. 14a: Here I give the average anomaly for 2014.
3. year: This indicates the warmest year on record so far for that particular data set. Note that the satellite data sets have 1998 as the warmest year and the others have 2014 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. Periods of under a year are not counted and are shown as “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. sy/m: This is the years and months for row 8. Depending on when the update was last done, the months may be off by one month.
10. Jan: This is the January 2015 anomaly for that particular data set.
11. Feb: This is the February 2015 anomaly for that particular data set, etc.
15. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months.
16. rnk: This is the rank that each particular data set would have for 2015 without regards to error bars and assuming no changes. Think of it as an update 25 minutes into a game.
| Source | UAH | RSS | Had4 | Sst3 | GISS |
|---|---|---|---|---|---|
| 1.14ra | 6th | 6th | 1st | 1st | 1st |
| 2.14a | 0.170 | 0.255 | 0.564 | 0.479 | 0.68 |
| 3.year | 1998 | 1998 | 2014 | 2014 | 2014 |
| 4.ano | 0.483 | 0.55 | 0.564 | 0.479 | 0.68 |
| 5.mon | Apr98 | Apr98 | Jan07 | Aug14 | Jan07 |
| 6.ano | 0.742 | 0.857 | 0.835 | 0.644 | 0.93 |
| 7.y/m | 18/4 | 18/6 | 0 | 0 | 0 |
| 8.sig | Oct92 | Jan93 | Jul00 | Jun95 | Nov00 |
| 9.sy/m | 22/8 | 22/5 | 14/10 | 20/0 | 14/7 |
| Source | UAH | RSS | Had4 | Sst3 | GISS |
| 10.Jan | 0.261 | 0.367 | 0.690 | 0.440 | 0.75 |
| 11.Feb | 0.156 | 0.327 | 0.660 | 0.406 | 0.82 |
| 12.Mar | 0.139 | 0.255 | 0.680 | 0.424 | 0.84 |
| 13.Apr | 0.065 | 0.175 | 0.657 | 0.557 | 0.71 |
| 14.May | 0.272 | 0.310 | 0.694 | 0.593 | 0.71 |
| Source | UAH | RSS | Had4 | Sst3 | GISS |
| 15.ave | 0.179 | 0.287 | 0.676 | 0.484 | 0.77 |
| 16.rnk | 6th | 6th | 1st | 1st | 1st |
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0 was used. Note that WFT uses version 5.6. So to verify the length of the pause on version 6.0, you need to use Nick’s program.
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/tltglhmam_6.0beta2
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.4.3.0.0.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 2015 in the form of a graph, see the WFT graph below. Note that UAH version 5.6 is shown. WFT does not show version 6.0 yet.
As you can see, all lines have been offset so they all start at the same place in January 2015. This makes it easy to compare January 2015 with the latest anomaly.
Appendix
In this part, we are summarizing data for each set separately.
RSS
The slope is flat since December, 1996 or 18 years, 6 months. (goes to May)
For RSS: There is no statistically significant warming since January 1993: Cl from -0.013 to 1.672.
The RSS average anomaly so far for 2015 is 0.287. This would rank it as 6th place. 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 2014 was 0.255 and it was ranked 6th.
UAH6.0
The slope is flat since February 1997 or 18 years and 4 months. (goes to May using version 6.0)
For UAH: There is no statistically significant warming since October 1992: Cl from -0.026 to 1.731. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly so far for 2015 is 0.179. This would rank it as 6th place. 1998 was the warmest at 0.483. The highest ever monthly anomaly was in April of 1998 when it reached 0.742. The anomaly in 2014 was 0.170 and it was ranked 6th.
Hadcrut4.3
The slope is not flat for any period that is worth mentioning.
For Hadcrut4: There is no statistically significant warming since July 2000: Cl from -0.017 to 1.371.
The Hadcrut4 average anomaly so far for 2015 is 0.676. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.835. The anomaly in 2014 was 0.564 and this set a new record.
Hadsst3
For Hadsst3, the slope is not flat for any period that is worth mentioning. For Hadsst3: There is no statistically significant warming since June 1995: Cl from -0.003 to 1.739.
The Hadsst3 average anomaly so far for 2015 is 0.484. This would set a new record if it stayed this way. The highest ever monthly anomaly was in August of 2014 when it reached 0.644. The anomaly in 2014 was 0.479 and this set a new record.
GISS
The slope is not flat for any period that is worth mentioning.
For GISS: There is no statistically significant warming since November 2000: Cl from -0.018 to 1.336.
The GISS average anomaly so far for 2015 is 0.77. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2014 was 0.68 and it set a new record.
Conclusion
It appears as if we need to have a precise definition as to exactly what is required to officially have a hiatus. Until we do, any one can use whatever criteria they wish and declare the hiatus over, or to have never occurred, according to their definition. This is one illustration as to how much more climate science needs to mature.
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RSS and UAH update:
The satellites will not show a record in 2015.
After 6 months on RSS, the average is 0.304, and this would rank in 6th place if it stayed this way. However it will probably go up to third place before the end of the year. But a new record is virtually ruled out since the anomalies for the rest of the year would then need to average 0.796. This was only beaten once and that was in April 1998 when it was 0.857. It cannot be ruled out that the June anomaly of 0.391 may rise to 0.796 by December, but there is no way that 2015 could end up in first or even in second place on RSS. The pause stays at 18 years and 6 months, but goes from January 1997 to June 2015.
With the June anomaly of 0.329 for UAH, it would rank 4th if the average stayed at 0.204. It also may end up in third place, but it will not set a record. The pause stays at 18 years and 4 months, but now goes from March 1997 to June 2015.
By lowering the temp. data at the beginning of the hiatus, it makes the slope
of the last 15 years larger but decreases the slope of the 1950-2000 and this is
what makes both slopes now very similar in this data set. I agree that it is odd to
include 1950 to 1975 as this region is fairly flat and at the start of that time frame
there may not have been enough GHGs to cause AGW. But including them
is what lowers the slope so that it is similar to 2000 to 2015 (as you pointed out).
How about the slope from around 1945 through 1975 (or ’77) – isn’t there a downward (cooling) slope there?
Just to give one case:
Temperature Anomaly trend
Jan 1937 to Jan 1975
Rate: -0.191°C/Century;
CI from -0.489 to 0.108;
Go to the site listed in section 2 for any others for NOAA since WFT does not show NOAA.
The straight green, red, and blue lines in the first two graphs look like crude attempts to fit an overall sine wave, where the blue line is approaching the peak thereof, and eventually to come down the other side with a negative slope.
NOAA basically used the green and blue lines from the second graph to prove there was no longer a hiatus, unlike what the green and blue lines showed in the first graph. I added the red line since I think the red line should be compared to the blue line to determine if there is a hiatus.
Thanks, Werner Brozek. An interesting article.
I see the “pause” as notorious change in slope, from a very positive slope to an almost null slope.
As in
http://www.cru.uea.ac.uk/documents/421974/487107/gtc_feb2015.gif/1abb0fcd-aecc-4cc3-ac4c-b6ea634379ea?t=1424695677621
From http://www.cru.uea.ac.uk/
At what cost this futile guessing game of the study of the next million years of climate chaos?
Get egos under control and try to get even a 10 day rain event known in advance.
Get egos under control and get the path of hurricanes with in 100 mikes of land fall points.
After all it is not all about you.
Ulric Lyons has been absolutely spot on for the first half of this year already. This is a solar signal so his UKcentric forecast will work globally, albeit more loosely (I would guess if you were in the UAE or Antarctica a couple degrees C up or down would not dessicate you or squeeze more moisture out of the air, etc)
http://blog.metoffice.gov.uk/2015/04/13/more-warm-weather-this-week-but-whats-in-store-for-the-summer/
The noise of crickets in that place is louder as it is surrounded by deafening silence. Pearls before swine comes to mind.
On the other hand, Obama knows what the tax and spend goal of the climate change cult is up to.
There have been many illustrations as to how much more climate science needs to find some integrity.
I also believe that while important to determine a “hiatus/pause”, it is also important to show the divergence from the climate models. Whether “hiatus/pause” or “slowdown”, the alleged warming does not match the “projected/predicted” warming.
True, and Lord Monckton has been covering that very well. See: http://wattsupwiththat.com/2015/07/02/el-nio-begins-to-curtail-the-pause/
I prefer the charts showing the effect of PDO and Adjustments:
http://wattsupwiththat.com/2015/06/30/bloombergs-alarming-graph-are-we-really-on-track-for-4c-global-warming-by-2100/
Forget hiatus. How about “stagnation”?
So what does the NOAA tall tale look like in say 2023 if the temperature stagnation continues.
The scale is one eighth of a degree Celsius. This graph need error bars.
Section 2 has some error bars. However if you want much more, see Nick Stokes’ site here: http://moyhu.blogspot.com.au/p/temperature-trend-viewer.html
When you analyze noise, you get garbage. When you resort to analyzing adjusted noise, you get research grants.
How on earth did we get here?
+1 Mike. You just won the Internet.
…much to our collective dismay. Still, his observation is 100% accurate.
best summary of climate science in 20 words or less!
Becasue, to use a term put forward by Dr Judith Curry, the result is “politically useful.”
By contrast, politically un-useful Climate related results are largely now discarded or ignored.
Why are linear trends used rather than polynomials? I’ve never understood that. You can see both long term and short term trends with the latter.
It is much easier to compare the slopes of two lines than to compare polynomial shapes.
Except the starting and ending points of two straight lines are “eyeballed”… you can pick one point and I can pick another. Can’t do that very well with a polynomial expression.
It’s easy to determine the slope of a tangent line to any point (x, p(x)) on a polynomial by taking its derivative evaluated at x: p'(x).
You can fit any order of polynomial, of course. We determine “goodness of fit” and determine how much of the fit is statistically justified. If you use more terms than is justified, you have overfit the data. This means your trend line is responding to random, spurious patterns in the data as well as real trends. Overfit trends actually do not describe the data as well as the simpler fits, even though they look better. If you make predictions on what future data sets will look like, the overfit trends invariably do worse than the simpler cases. That is why we use the higher order fits for “entertainment purposes only, no predictive value”.
In an extreme case, you can overfit pure noise and end up with a “hockey Stick”, as was famously done, once.
Faustian Bargain, anyone?
So – a semantic shell game. The sort of thing a shyster lawyer specializes in. And where or where in this administration would we find a shyster lawyer?
Easy: just throw a ball up in the air and when it lands, take the nearest lawyer.
/grin
It is worse than that! First the data gets adjusted. Then the semantic shell game begins on data that many people really have questions about.
Rather than throwing about arbitrary numbers to determine if the slopes are different, there should be statistical tests applied. Those test should compare whether the slopes from the various time periods are significantly different from 0, and whether the slopes of the different time periods are statistically different from the slope in the entire time period.
There must be a statistical test for it, but unfortunately I don’t off hand know what those tests are and I’m away on a project so I can’t look it up.
Here are some stats for NOAA, but only for the adjusted data:
Temperature Anomaly trend
Jan 1975 to Dec 1999
Rate: 1.712°C/Century;
CI from 1.228 to 2.196;
Temperature Anomaly trend
Jan 2000 to May 2015
Rate: 1.256°C/Century;
CI from 0.645 to 1.868;
The site mentioned in section 2 can be used for any other time and data set you wish.
Those confidence intervals overlap, so it is not even statistically significant to claim the slopes are different.
That is an excellent point that I had not considered! Perhaps talking about a % change is the wrong metric and we need to see if confidence limits do not overlap.
However I just checked it out on RSS, and even there we had an overlap. So by this metric, no data set has a pause at all.
Hey, who captured jimmi_the_dalek and replaced him with a skeptical replica?
You play semantic games.
There is simply no need for these games. There is also no need for the term “hiatus”. The term “hiatus” presumes that the activity will resume. That presumption relies on, as they say, “facts not in evidence”.
Hence, we use the term The Great Pause. The definition is easy. The Linear Least Squares slope is negative. By mathematical definition, you are cooling, not warming. Hence, the warming has stopped. The definition is simple and cleanly cuts the difference between warming and cooling. That is why I, and others, have adopted it.
On another note, the satellite and weather balloon data sets diverge radically from the surface based data sets, particularly in these last 18 years. No good physical theory as to why this is so has ever been offered by those maintaining the surface data sets.
In the article by NOAA, they say: “The apparent slowdown was termed a “hiatus”.
I wish we had a specific definition as to exactly what constitutes a hiatus, but we do not. Perhaps this post will inspire people to come up with a definition that all will agree with.
I do see your point, and agree that formal definitions are needed, as always in science. But I think NOAA is engaging in semantics and spin control here, for political purposes. That will make general agreement difficult.
‘A pause, interruption, or break in continuity.’ THAT is the specific definition in the English language. We don’t need a new definition. ‘Hiatus’, ‘Pause’, whatever ALL imply that you know future events. The ‘pause’ button on your DVD player temporarily holds the play. It is there to suspend play, and implies that you wish to resume. We do NOT know future events, so it cannot be termed a pause or a hiatus. According to RSS, the warming anomaly has stopped…ceased…halted. If it resumes, then it paused.
Why do you bother with the fake temperature curves in your two first figures? Use satellite data to show hiatuses. I said hiatuses in plural because there is not just one but two of them. The second one that you do not know about is the one in the eighties and nineties. It has been wiped out in the ground-based temperature records by over-writing it with a fake warming called “late twentieth century warming.” The crooked temperature purveyors responsible for that scientific crime are HadCRUT, GISS, and NCDC. They are connected by common data processing that unbeknownst to them left its footprints on all three publicly available temperature curves. Fortunately they still do not control satellites which makes it possible for anyone to download the record of this hiatus in the eighties and nineties from either UAH or RSS satellite temperature databases. If you do that you will find that both hiatuses will show up in the same satellite record. I discovered it in 2008 while doing research for my book “What Warming?” It is pretty obvious that you have not done your homework and read my book. This hiatus is shown as figure 15 in the book. Figure 24 shows the modus operandi of HadCRUT3 in wiping it out. The hiatus in the eighties and nineties goes from 1979 to 1997, a stretch of 18 years by a coincidence. Together the two hiatuses block out 80 percent of the warming that should have happened according to Arrhenius during the satellite era. The other twenty percent is taken up by the super El,Nino of 1998 and a short warming starting in 1999. Neither one has anything to do withe greenhouse warming. As a result, we can say that there has been no greenhouse warming whatsoever in the satellite era that began in 1997. This kills AGW, period. Among other things the greenhouse theory of Arrhenius is shown to be false and the Miskolczi greenhouse theoy or MGT is proven correct because it correctly predicts the presence of these hiatuses. If the pseudo-scientists of global warming do not like this it is their own fault for thinking that a non-existent warming can be real.
Actually, Bob Tisdale often talks about step changes due to El Ninos. But my point in this article was to question whether or not NOAA was really successful in getting rid of the hiatus by their own rather vague definition.
Werner – it is not a criticism of you to say that you did not know about the hiatus. Bob Tisdale does not know either but he spouts misinformation about ENSO. Nobody who did not make a special effort to use satellites and analyze the data knew about this hiatus either. I did know, even before a hiatus was a hiatus. From time to time I called attention to this but nothing happened, nobody responded. One simply does not expect such bold forgery involving non-existent warming from supposedly reliable temperature sources. Looking at the over-all picture there was a distinct upturn of temperature in the second half of the seventies that abruptly ended with the arrival of the hiatus in 1979. I can understand that this might have upset them and simply look like a random error at first. This could have been the reason for the first correction they made in order to to contnue the trend of the seventies. But when from year to year one correction after another had to be applied somebody should have suspected that all is not well.And when the super El Nino arrived and temperature went through the roof it looked like justification for what they had done. There was also a parallel ENSO trace that may have confused them because no one understood El Nino at the time. There were five El Nino peaks in this ENSO wave train. Even recognizing them may have been beyond their capabilities. The middle one of these El Ninos turned out to be the one that Hansen declared in 1988 to be the tip of his hundred year warming. If you want to start from scratch by downloading satellite data your first step should be outlining the basic trend with a magic marker as I did. Next I marked the midpoints between an El,Nino peak and its neighboring La Nina valley, as defined by the magic marker trend. And what do you know – the dots lined up nicely as a horizontal straight line. There is no computer program that can duplicate this. It is a fashion to smooth temperature curves by using such things as thirteen year moving centered averages. They give you a smooth-looking curve that has nothing to do with reality. It destroys all the EL Nino peaks and with it the information they carry. These dopes actually don’t know that these El Ninos.have been produced since the Panamanian Isthmus rose from the sea. And none of them know that so-called “volcanic coolings” are nothing more than misidentified La Nina valleys. La Nina? What is that?
You may wish to take this and other thing up with Bob Tisdale. I am certainly not an expert on La Ninas and ENSO.
There is much too much concentration on immediate / short term of temperature changes. The big picture is much more informative.
Our current beneficial, warm Holocene interglacial has been the enabler of mankind’s civilisation for the last 10,000 years. The congenial climate of the Holocene spans from mankind’s earliest farming to the scientific and technological advances of the last 100 years.
Judging from the usual lengths of past interglacial periods, after some 10,000 – 11,000 years the Holocene epoch could well be drawing to its close. A climate reversion to full, encroaching, glaciation is therefore foreseeable, if not overdue, in this century, the next century, or this millennium.
Looking at climate change from a century by century or on a millennial perspective and using Ice core data but reducing it to century and millennial averages the overall millennial difference during the Holocene since ~8000BC has in total been a cooling of ~-1.8°C.
The early Holocene encompassing the “Climate Optimum” of ~ 7000BC and continuing for about 7000 years has been relatively constant with a temperature loss of only about -0.05 degC per millennium
However since 1000BC up to the present day the temperature drop was at about 10 times that rate at ~0.5degC / millennium.
The last millennium 1000AD – 2000AD has been the coldest of the Holocene overall.
Most of the Holocene temperature loss ~-1.5°C has been in the last 3 millennia since 1000BC.
The scale of temperature changes that alarmists anticipate because of Man-made Global Warming and their view of the disastrous effects of additional Man-made Carbon Dioxide emissions, the much vaunted and much feared “fatal” tipping point of +2°C would only bring Global temperatures back to the level of the very congenial climate of “the Roman warm period”.
If it were possible to reach the “potentially horrendous” level of +6°C postulated by Warmists, by the inclusion of dubious but major positive feedbacks from additional water vapor in the atmosphere, that extreme level would still only bring temperatures to about the level of the previous Eemian maximum. The world has been there and survived before.
Current modern warming does not even bring temperatures back to those of the Medieval warm period.
Looked at from the point of view of the most recent 3 millennia which have experienced accelerated cooling, a continued natural climate change towards a colder climate would now seem more, rather than less, likely.
In other words all policy decisions to curtail warming are facing in exactly the wrong direction.
see
https://edmhdotme.wordpress.com/2015/06/01/the-holocene-context-for-anthropogenic-global-warming-2/
That may be true. However the big debate is whether or not the big picture is relevant due to our fossil fuel usage.
W.B.
As far as I can see, that’s been asked and answered by ed. It seems that the big picture is indeed relevant. This whole dog and pony show is predicated on the belief that a few degrees of warming would be cataclysmic. I don’t know about you, but I find the prospect of another ice age far more terrifying.
I agree, but then I live in Canada. Going by the number of global deaths due to cold versus due to heat, it is obvious that the best change for now, if any, would be more warming.
For another analysis, see “Can Mankind Really Expect To Tame Earth’s Climate And Remove It From Cosmic Control?”
http://gsjournal.net/Science-Journals/Research%20Papers-Climate%20Studies/Download/6066
The paper provides a link to a YouTube video of the Thermal Vise that has “squeezed” the earth during the past 400,000 years and will do so again.
That may be true, but “we” will have to cross that bridge when we come to it. In the meantime, let us do (or not do) what is best for our children and grand children.
Funny how everyone knew what hiatus meant before it was used for the break in global warming.
Then it became a living word subject to much confusion, manipulation and interpretation.
hi·a·tus
hīˈādəs/
noun
a pause or gap in a sequence, series, or process.
“there was a brief hiatus in the war with France”
synonyms: pause, break, gap, lacuna, interval, intermission, interlude, interruption, suspension, lull, respite, time out, time off, recess; informal breather, letup
“the spring hiatus gave us time to rethink our next project”
Clearly NOAA is also re-inventing the words, honesty, integrity and ethics.
Why do you bother with the fake temperature curves in your two first figures? Use satellite data to show hiatuses.
I agree 100% with the above statement made by Arno.
Fool me once shame on you, fool me twice shame on me. NOAA data is manipulated and should not be shown.
I agree. But then we would be accused of cherry picking our data sets. Hopefully articles like this one will help to prove that it is justified.
The surface and satellite data sets have their pros and cons, but a good case can be make for the satellites.
The surface sets are long and they are where we live, but they are
corruptnoisy and subject to continuousalterationadjustment. (e.g.: 1910 is colder now than it was in 1910, but not as cold as 1910 will be in 2020.)The satellite sets are truly global and uniformly measured, but aren’t as long and aren’t down where most people live.
I was encouraged to see the new UAH version more closely matched His Lordship’s favorite RSS set, but discouraged to see the Lower Trop numbers were weighted even farther up from the surface. The old set centered around 6,000 ft up, but the new version 6 favors around 12,000 ft. I mean, who lives at 12,000 ft?
Then I realized Drs Keeling work there. That’s the neighborhood of the MLO CO2 station, so now we’re getting our CO2 and temperature curves from the same place.
http://www.rockyhigh66.org/stuff/UAH_weighting.png
Mike, unless there is a manifest change is the atmospheric lapse rate over time, the satellite data is a very good indicator of any warming of the Earth.
It is FAR better than any surface temperatures which are highly manipulated, irregularly spaced, and subject to large human caused UHI and other effects.
CO2 does not change the lapse rate.
There is NO warming in the satellite record.
There is NO warming effect from CO2
Mike:
“The surface sets are long and they are where we live, but they are corrupt noisy and subject to continuous alteration adjustment. (e.g.: 1910 is colder now than it was in 1910, but not as cold as 1910 will be in 2020.)
The satellite sets are truly global and uniformly measured, but aren’t as long and aren’t down where most people live.”
You need to add to the satellite bit:………..
Also have to be continually altered.
If you don’t know why look here:
https://en.wikipedia.org/wiki/Satellite_temperature_measurements
“The sensors deteriorate over time, and corrections are necessary for orbital drift and decay. Particularly large differences between reconstructed temperature series occur at the few times when there is little temporal overlap between successive satellites, making intercalibration difficult.[
Oh, and UAH is now on V6 (big changes from v5.5)
The absolute temperatures would be colder, but due to the lapse rate, the trend should not change.
As for CO2, that is relatively well mixed in this range.
Toneb:
Thanks for your comments. I noted v6 on the chart.
The satellite data isn’t altered. Its interpretation may change as the conversion algorithms are updated, but the raw data is still there. That isn’t the case with surface data sets, cf. USHCN v1 with v2.
The Wikipedia paragraph you quote is marked “citation needed” for a reason: it isn’t the case. Once the second MSU satellite launched, there was only one four month stretch without at least two satellites reporting data. Judging by the observation times chart, all satellite intercalibrations had at least a week’s worth of data.
The Wikipedia page is on Connolley’s watch list, so it is and will remain warmist biased.
There is no hiatus
No need to debate us
We’ve got the best science
And the best PR status
So don’t ask for our data
You’ll be met by laughter
Because the science is settled
For now and hereafter.
And if after that, a flaw has been found
We’ll adjust the past temps a bit further down.
The last millennium 1000AD – 2000AD has been the coldest of the Holocene overall.
Most of the Holocene temperature loss ~-1.5°C has been in the last 3 millennia since 1000BC
edhoskins says which is spot on.
Going forward the long term climate drivers Milankovitch Cycles, Solar Variability (secondary effects),and these factors which moderate the first two factors those being , Geo Magnetic Field Strength (enhancing solar variability when weak)., Land /Ocean Arrangements., Ice Dynamic are all in an overall cooling pattern since the Holocene Optimum.
The warm periods since the Holocene Optimum being tied to solar variability which is superimposed upon the general climatic trend. MEDIEVAL ,ROMAN warm periods to name two.
Further refinement to the temperature trend since the Holocene Optimum ,coming from ENSO, PDO/AMO phase and Volcanic Activity.
I would say all the above when combined and superimposed upon one another can account for all of the climatic changes since the Holocene Optimum – Present Day.
Therefore going forward the trend in the global temperature should be down as soon as the maximum of solar cycle 24 ends and solar activity in general remains at sub-solar levels which it has been since 2005, and approaches my low average value solar parameters going forward, with a sufficient duration of time at or around these values.
Solar Flux 90 or less, AP index 5.0 or less, Solar Wind 350 km or less to name some of them.
These values much above these levels during the maximum of solar cycle 24 through today , although the maximum of solar cycle 24 is very weak, however the balance of this decade going forward should feature these low solar parameter readings as the very weak maximum of solar cycle 24 ends ,and once this is takes place I fully expect the global temperature trend to be in a jig saw down trend.
“Ingenious of him” (Karl)
You meant “ingenuous”–or maybe “disingenuous”
Or maybe genius? I will let our English pros sort that out.
It might take a genie to undo the damage they’ve done. 😎
Difficult though it is to fire federal employees, I hope there will be wholesale house-cleaning at NOAA and NASA GISS under a new, GOP administration, but am not holding my breath. Maybe retirement offers the leading offenders can’t refuse, in order to join Hansen as full-time activists, as if they aren’t already.
“The given slopes are in degrees C/century.”
That’s 0.00x C/year. Where can one find an instrument with that resolution? These are statistical constructs, i.e. fabrications, hallucinations. Where are the error bars?
The site in section 2 gives some information.
The top two graphs are very misleading. NOAA has chopped off the top and bottom of the graphs. If you include the top and bottom, it is obvious that temperatures have peaked and are now on a plateau.
I take full responsibility for the graphs. While some high points and perhaps some low points got chopped off, my focus was on the slope lines and their value. If you wish to duplicate what I did, go to:
http://www.moyhu.blogspot.com.au/p/latest-ice-and-temperature-data.html#NCAR
Keep in mind that only the bottom graph can be duplicated. The data for the top graph is no longer there at the site listed above.
By the way, it is much more complicated than WFT so I had a rather steep learning curve and a lot of help from Nick to be able to do what I did and then make jpg out of them.
S/B: “…began in 1979…” not in 1997. Sorry.
So we will just re-analyze when they come back and bend the slopes up further. You know, we are getting so used to this egregious readjustment process to make things the way they want and to do away with the critique points that skeptics have made, that it is beginning to seem normal, even to skeptics. This is not normal at all. You either robbed the bank or you didn’t. There is no halfway alternative. I’m getting a little tired of analyses that make you want to scream. Doing them is just as much fanciful and wrong as them cooking the data.