Guest essay by Barry Wise
Christopher Monckton has pointed out that a trend of zero or smaller can be calculated stretching back over 18 years, but critics have pointed out that this encompasses the super el Niño of 1998 and so biases the trend downward while the overall temperature is still rising. Of course they also don’t mention that the el Niño biases the trend upward when the trend is viewed in it’s entirety. Now Lord Monckton has identified a valid point and so do his critics. What if we look at how the trends vary over differing lengths of time? Can Lord Monckton be validly accused of cherry picking or are his critics nit picking? This article will attempt to show a broader view of how the trends have varied over time, both from the beginning of the the record and from the end.
To begin, at what point do we say that a trend of a given length makes sense in terms of whether it’s an indication of future global temperatures or just a statistical anomaly? Obviously the longer the better, or so one might surmise, but then that’s assuming that the data represents a linear trend. The more data you have the less any additional point will affect the overall trend. Given that, one might expect the trend to oscillate around a given value with a reduced amplitude as it zeroed in on the actual trend.
So what actually happens? For this exercise I’ll use RSS lower troposphere data since that is what Lord Monckton used. Here is the RSS data for the full period of the data from 1979 to the present with the 1998 el Niño shaded in grey and showing the least-squares linear-regression trend line for the entire data set. The el Niño time period is based on data from El Niño and La Niña Years and Intensities. The slope of the line is approximately 1.2 K/century which, as it turns out, is below the low end of the IPCC projection (1.9 to 4.2K/century) but is consistent with a doubling of CO2 with no secondary effects.
Let’s look at how the trend has varied starting from the earliest data. I’ll start with a minimum length of ten years (an arbitrary length but shorter lengths give widely varying trends that make it hard to read the graph) and I’ll increase the length in one month increments. The trends are plotted based on the end date used for the data of each trend, with the full data shown below as a reference. The shaded area brackets the 1998 el Niño so we can see where it enters into the computation of the trends. Notice how much the trends vary prior to the el Niño. Everything from about 1.6 down to .4 K/century. This would indicate that data that is less than 20 years (at a minimum) is unreliable to discern the trend over a longer term. Notice too how the trends peak with the el Niño but immediately start tailing off. By the end of the data the trend is at the 1.2 K/century we calculated before and the change in the trend is flattening out. Also of note is the rapid rise of the trends when the el Niño occurred.
Now let’s look at how the trends changes as we increase the length in one month increments starting at the present and working backwards to see how Lord Monckton’s 18 year 8 month value fits into the changes that occur as we vary the length of the data. In a similar fashion to the previous chart, I started with a minimum data length of ten years. Notice that not only are there negative trends where the el Niño data is included but there are also negative trends prior to that data. Additionally, the trends prior to including the el Niño are even more pronounced, longer and extend back to June 2000 which is over 15 years. Also of note is that this includes the 2010 el Niño which, by it’s relative location, should bias the trends in a positive direction at these lengths. At no point does the trend exceed .5 K/century for the data after the 1998 el Niño. Just prior to the el Niño the trends are approximately .7 K/century.
This article has just been my attempt to show a broader view of how the temperature trends have evolved. I make no claim to whether Lord Monckton or his critics are correct. In summary we now have over 35 years of satellite data with over 15 years post 1998 el Niño showing little, no or even negative trends at that length. The data prior to the el Niño also shows trends that are at or below that the IPCC has promoted, not to mention the entire record. While some have critiqued Lord Monckton’s trend because of the inclusion of the super el Niño I would question their consistency because I haven’t seen a similar complaint based on the much larger effect that it had on the trend from the beginning of the record. Given the lack of a positive trend post el Niño, it would appear that there was a step that occurred in the earth’s atmosphere’s temperature. The present el Niño is being touted as being another massive one. Will it too show a step?
“While some have critiqued Lord Monckton’s trend because of the inclusion of the super el Niño I would question their consistency because I haven’t seen a similar complaint based on the much larger effect that it had on the trend from the beginning of the record.”
It has little effect on the trend from the beginning, because it comes almost in the middle of that RSS record. Trend is like a see-saw – masses at the end tilt either way, but in the middle, very little. Try the trend removing those years.
What you see in Fig 3 as you go back from present time is the gradual diminution of the “weight” of the El Nino. But it doesn’t tilt the other way.
Nick, I think he means the trend from late 70s to late 90s.
I guess the author has not read how M of B does his algorithm.
Axiom one says the starting point of the sequence is the most recently released RSS official number.
There is NO arguing about that; that is Christopher’s rule, so get used to it.
Axiom two says the next number in the sequence is the official RSS number for the month preceding the current one.
Axiom three says, apply the standard text book calculation method for computing the trend between the second number and the first number, and calculate whether that number is statistically significantly different from zero, based on all the data between the first number and the second number.
Axiom four says, if the result of three, is that the trend is not statistically significantly different from zero, then replace the second number with the official RSS number for the month preceding the current second number, and then repeat the trend calculation for the new longer data set.
Keep doing this until the trend is statistically significantly different from zero; then stop.
Nothing in the algorithm is in any way dependent on the numbers or the origin of the numbers; they only have to be the numbers RSS officially publishes, and their values are completely irrelevant, as regards performing the set of steps Monckton laid out.
So nobody is picking anything, either cherry or plum.
Statistics deals with real numbers that are exactly known. So the results of any statistical computation are also exact, since the algorithms are published in any reputable Statistical mathematics text book. There is NO room for uncertainty or introduction of bias by the practitioner. You either got it correct or you made an arithmetical error.
The stat maths algorithm for “average” is well known. You sum all of the numbers in the finite data set of real numbers. That result must be determinate, since the set is finite. Then you divide by the number of elements in the finite set, which is also a finite number, and the result is “average”
For example take the set of integers; 0, 1, 2, 3, 4, 5, 6, 7, 8, 9. Their sum is 45. There are ten integers in the set, so the “average” by rule is 4.5.
4.5 is NOT an integer, so if there were no numbers besides integers, then the result of computing “average” could be nonsense. The result of a lot of other types of statistical algorithmic calculations can also be nonsense; but you have to follow the rules. You could resolve the above “average” result, by inventing an entirely new class of numbers that are not integers.
What is the average of the set: ( I, V, X, L, C, D, M ) ?? is it a real number, or just nonsense ?
g just ruminating .
In answer to George E. Smith, the mean of the set {I, V, X, L, C, D, M} is exactly CCXXXVIII.
The prominence of the 1998 el Nino makes no significant difference to the slope (or lack thereof) of the RSS trend-line, because its influence is more or less exactly offset by the prominence of the 2010 el Nino. It is really as simple as that, but the usual suspects, desperate to discredit the inconvenient truth of the Pause, complain about “cherry-picking” etc., etc. It is just a further demonstration of the instinctual intellectual dishonesty of the climate-Communists.
They are cultural Marxists, not communists. They take control and politizise everything that can promote their ideology. Listen to the lyrics in John Lennons Imagine and have the dummies guide to cultural Marxism.
Dang !
Lord M of B went and actually did the Romantic math, and got a real number.
So today we all learned something Christopher. At least the Roman set gives a real number for its average. I wasn’t going to hip shoot it, but I guess it tickled you just too much to leave alone.
And yes it is funny how the cherry pick rumors never seem to die.
Thanx for the answer.
g
I’m well aware of what you’re pointing out.
You didn’t seem to get what I was driving at. Look at Fig 2. Calculating trends going forward from 1979 you can see a sharp increase in the trend as the end date reaches the el Niño. In fact the el Niño data doubles the trend. The data post el Niño sends the data back down as you would expect. Do you really think that anyone who is pro AGW would have tempered their positions based on the el Niño biasing the data in the early 2000’s?
“Do you really think that anyone who is pro AGW would have tempered their positions based on the el Niño biasing the data in the early 2000’s?”
==========================================================================
It is, IMV, irrelevant what they would do. The question is what does CAGW theory project? They predicted continues warming at a rate much faster then the observations.
Since the question asked by C.M. is “How long has their been no warming in the trend” cherry picking is not possible! ENSO cycles have been known to exist for some time. The IPCC models supposedly incorporate all the known physics. None, as in zero of their models show a period of zero warming like this.
Another fair question to ask is; “What year was the atmosphere the warmest?” Not cherry picking here either, as the answer determines the year!
Heat is not relevant to yesterdays T or tomorrows. Temperature is what it is now, period.
1998 was easily the warmest year since the satellite record began. 2015 will not be warmer then 1998. At the present rate of warming 1998 will remain the warmest year for a very long time, and by a significant margin.
The warming from 1979 until 1998 almost warmed as CAGW theory predicted. CAGW proponents cannot both use the 1998 El Nino, (plus positive PDO and AMO) to support their theory, and then discount the same event, post that event. Well they can, and they do try, but it is scientifically baseless. C.M questions are not.
Let us see what happens when PDO and AMO are strongly negative, and we have a strong La Nina. (The opposite of 1998) I think there will be a step down in GMT, just as there was a step up post 1998. Possibly the entire satellite record will show no statistically significant warming. “Much ado about nothing” indeed.
If they complain about cherry picking and you choose a date after the 1998 el Nino and the following La Nina – say 2001, they will get a significant downward trend… and will complain again.
That’s a model, not a climate mechanism.
I can draw the same diagram with electrical components. It’s still a model, not a climate mechanism.
Peter
It would be interesting to extend the time line to the beginning of the last century and see if the trend has changed in global warming, incorporating the steps.
Mr. Buckingham, hi
Here is something you could consider
Global temperature trends from about 1860’s coincide with the (inverted) Earth’s magnetic dipole change trends for the same period.
http://www.vukcevic.talktalk.net/MV-DrS.gif
Correlation fails before 1850, since for the dipole data, accurate geo-magnetic measurements are required from both hemisphere, and those are extremely scarce from the south hemisphere before 1850s (magnetometer was invented by Gauss in 1833, and took couple of decades before it was in wider use).
For going further back the delta of the Arctic magnetic field (magnetic pole area) is the best available alternative
http://www.vukcevic.talktalk.net/LLa.gif
That is not to say that the Earth’s field drives the climate. Unless there is a common cause to both geomagnetic changes and solar activity (running in contra correlation) then the sun is the prime candidate, but science so far has failed to resolve the conundrum.
Be aware, the above is vehemently opposed by the status quo advocates, but science will eventually get there. I occasionally bring the above to the attention of readers despite insults and unpleasant ad hominem to which I am often subjected to.
Interesting correlation. Are there any papers suggesting a possible solution for this phenomenon?
Nope, no papers, I came across it only recently. I doubt that any peer reviewed science magazine would publish it for the time being, but that doesn’t bother me.
Dr. S set out to invalidate my findings but inadvertently proved the correlation. Now he is pulling all the stops to bring it down. Such is the nature of the current status-quo advocacy.
Hi Vuk
Is there any way to predict the future direction of the Earth’s magnetic field, or do we just wait and see?
Hi Mr. Barraclough
Nice to here from you again. No, not that I know off, or that could be demonstrated beyond doubt.
Reply to Ben Palmer October 20, 2015 at 12:49 am:
Simple solution, Ben, tax magnets! A tax on gas works (cough) so why not a tax on Gauss!
Are we going to die horribly for magnetosis?
Do you need to build big magnets?
Just looking at that, baldly stated, the higher the magnetic flux the greater the temperature.
For every magnetic field there is an induced electrical field.
Water[H2O] is weakly dipolar and attracts further water molecules.
Perhaps the water molecules tend to flow along the electrical field to areas, altitudes and latitudes,
where the greenhouse effect of water vapor is amplified.
Hence the correlation between electromagnetic fields and heat retention.
Thanks for presenting this information.
Please view comments.
https://rclutz.wordpress.com/2015/10/18/arctic-ice-great-leap-upward-oct-17/comment-page-1/#comment-681
Harry’s tax on magnets sounds very… attractive.
“Interesting correlation. Are there any papers suggesting a possible solution for this phenomenon?”
I have seen papers many years ago suggesting link with climate and Earth’s magnetic field. None have linked very recent temperature changes with the Arctic’s magnetic field, but they have suggested previously when the magnetic field moves North, the climate warms and when the magnetic field moves South, the climate cools. This matches the period since during the LIA and the warming since.
What are nothing new are the suggested relations between mass extinctions and magnetic reversals and the Earth’s magnetic field link with climate has been reviewed by numerous papers in the past.
http://www.jstor.org/stable/30064982?seq=1#page_scan_tab_contents
http://link.springer.com/article/10.1007/BF01626048
Describes about the possible solution.
“The possibility of a connection between cosmic radiation and climate has intrigued scientists for the past several decades. The studies of Friis-Christensen and Svensmark reported a variation of 3–4% in the global cloud cover between 1980 and 1995 that appeared to be directly correlated with the change in galactic cosmic radiation flux over the solar cycle. However, not only the solar cycle modulation of cosmic radiation must be considered, but also the changes in the cosmic radiation impinging at the top of the atmosphere as a result of the long-term evolution of the geomagnetic field.”
http://www.sciencedirect.com/science/article/pii/S027311770400242X
Thanks Vuk,
And the future plot is…………..??
R
@ Lewis P Buckingham
To be more precise, ….. the above should read … “the greater the increase in temperatures”.
Anyway, as I was reading vukcevic’s commentary my thoughts were akin to yours, to wit:
Now vukcevic’s graphs show a good correlation between the Arctic’s magnetic field (magnetic pole area) “intensity” changes from 1850/70 to present … with the calculated Global Average Temperatures variations for the same time period.
Thus I got to thinking, ……. what affect if any, does the daily, weekly, monthly, yearly or decadal magnetic field “intensity” changes in the lower latitudes (non-polar) have on the near-surface temperature measurements …… and/or is there a similar correlation? .
If the Arctic’s magnetic field “intensity” has been changing …… then I have to assume that the magnetic field “intensity” values as defined by the followin graphic have also been changing, to wit:
Magnetic field of Earth based on IGRF 1990 (Blakely):
Isodynamic map showing total intensity, contour interval 2,500 nT
http://geophysics.ou.edu/solid_earth/notes/mag_earth/magnetic_field_a.gif
Source of graphic: http://geophysics.ou.edu/solid_earth/notes/mag_earth/earth.htm
Further to the comments by Matt G and Samuel C. Cogar
http://www.vukcevic.talktalk.net/AT-GMF.gif
http://www.vukcevic.talktalk.net/AGT.jpg
There is no significant signal that has a period of 3(2?) periods in the global temperature record. Global temperature is pretty close to ~1/f noise, which means the maximum noise is where the frequency is low – i.e. one that is a couple of periods as you shown above, is mostly likely noise, which you nicely bandpass filtered for to get the nice high correlation. The most noise is the one that shows up in the trend, as that’s as close to DC as you can get in a windowed sample.
You can take random noise and get any correlation you want with the right filter and delay with another signal. I believe that’s what you’ve done here.
If you can find a signal in temperature above the noise floor, THEN you can make valid comparisons. Good luck with that. This paper here pretty much shows there’s no interesting signal except for ENSO and seasonal variation above the noise floor:
https://www.dropbox.com/s/lw1kzdfjw0ifcdo/10.1.1.28.1738.pdf?dl=0
Peter
PS: You can make the same argument about C02 of course…
and again:
“ which you nicely bandpass filtered for to get the nice high correlation.”
Mr Sable
It would help if you specified what ‘bandpass filtered’ graph you are referring.
I have not done any.
Crutem4 and Loehle annual temperatures are as downloaded.
Earth’s magnetic intensity on annual scale moves very little so curves appear to be very smooth.
I hope that helps, if not you welcome to come back and clarify.
@ Peter Sable
I don’t think you or anyone else has a clue as to what the “noise level” is in the US temperature record …… let alone the Global temperature record. Said records prior to, say 1950/60, were never meant to be used for calculating “average temperatures” so no one really cared how accurate they were …… simply because a +-5 degree F temperature was “close enough” for 2 to 5 day local weather forecasting.
The observable fact is, the average surface temperatures have been increasing during the past 100+ years, …… but it is the “low” temperatures that have increased, ….. not the “high” temperatures. In other words, the surface has not been “cooling down” as much during its normal cool or cold periods. (night time, winter months, etc.)
Thus it is my learned opinion that if one wants to calculate a more reasonable Yearly Average Temperature increase for 1880 to present …. that they only include the daily recorded “low temperatures” as per recorded in the historical Temperature Record data.
If one “averages” all the highs and lows together then they end up with “meaningless” data other than for appeasing the public’s curiosity.
Mr. Cogar above is absolutely correct. 360 years of the CET instrumental records show that January’s temperatures, the coldest month of the year have risen 4 (four ) times as fast as for July, the warmest month of the year July since 1660, or 7 (seven) times as fast since 1770.
http://www.vukcevic.talktalk.net/J-J.gif
Climate change doesn’t mean warmer world, it means less cold world.
Ozone is diamagnetic, ie it is forced out of the magnetic field.
Sorry if I missed them, vukcevic. Are there any independent page links to to data plots or theories?
One or two hypothesis (including my own) but no theories that are accepted
Data links, yes
the less accurate from NOAA up to date
http://www.ngdc.noaa.gov/geomag-web/#igrfwmm
and more accurate, but not user friendly from ETH Zurich up to 1995
http://www.epm.geophys.ethz.ch/~cfinlay/gufm1/model/gufm1
Thanks, sometimes I tend to think there is a blocking high pressure to subdue such information. add this to the sunspot and trade market correlations and you’ll have some idea that tracking of these numbers may have been known for quite sometime with regards to man’s history under the Sun.
Bandpass means you’ve filtered out high and low frequencies.
Yearly means you’ve filtered out all frequencies greater than 1/1year. Or rather, HadCRUT did it for you. Which I find crude from a DSP standpoint, as any lunar information will alias badly, any random phase delay in the auto-correlated daily temperature over year boundaries will alias badly, etc…
130 year window means you’ve filtered out all frequencies less than 1/(130*2).
Yes, that’s nitpicking, but the real problems is because you are comparing to the dipole signal which is bandpassed by the earth itself (I don’t know, I haven’t looked at the metrology, but it’s what you implied), you are implicitly bandpassing the comparison (the regression) at the implied pass frequency of about (1/(130/3years)).
It’s fine to do that, IF the temperature signal wasn’t pink noise with spectral components at all frequencies proportional to 1/f. Unfortunately, if you read the referenced paper, the temperature does have components at all frequencies and the periodiogram graph looks like pink noise.
When you have pink noise you must assume that any of the possible time-domain outputs are possible given an infinite history of temperature, and so you must compare things like the spectral energies, or do a Monte Carlo analysis on the time domain analysis to determine if you’re just not getting lucky.
The frequency domain of that version of analysis is in the paper I cited. I’m working on a time-domain equivalent since frequency domain analysis doesn’t work well for low frequencies that we are attempting to work with. Don’t have anything publishable yet, but the paper I cited is a pretty good start.
Peter
It’s not that hard, you just run an FFT on the data after properly windowing it. All 3-4th year engineering students should be able to do this (well not including computer folks, they seem to never learn this stuff. But MechE and EE for sure do).
Or you could just read the paper. I’ve considerable experience in DSP and IMHO this paper outlines a properly skeptical method to view whether you’ve got signal or noise.
They manage to find the ENSO signal, so it’s not like there’s NOTHING there despite all the munging and bad metrology. There’s real data there. But only for ENSO, not for anything else. Everything but ENSO and seasonal is below the 95% confidence of the noise floor.
Peter
So do you have a mechanism to suggest that the magnetic field is related to this change? And if so, why haven’t you graphed it that way instead of just HadCrut4?
Or did you just get lucky?
Don’t get me wrong, I think you might have something here. But you should be your own harshest critic. I’m must doing that for you 🙂
Peter
Is one of you talking about daily temperatures and the other about Janurary/July? Please clarify, I’m confused.
Peter
Peter Sable
“So do you have a mechanism to suggest that the magnetic field is related to this change?”
Yes I do, and it is nothing extraordinary. Here is a clue
http://physicslearning2.colorado.edu/pira/static/pira200/waves/3a2010.gif
Let’s assume that the red coloured object is made out of two parts
– hole system is in an equilibrium for a short period of time
– bottom red part suddenly falls off
what do you think might happen to the rest of the system?
correction : – whole system is in an equilibrium
Reply showed up in wrong thread, trying again:
That’s a model, not a climate mechanism.
I can draw the same diagram with electrical components. It’s still a model, not a climate mechanism.
Peter
No it is not model, just rotate it 180 degrees, it is mechanics of the mechanism driving the geomagnetic undulations and the climate change since the last ice age; hence strong correlation, there is one more clue for you. The mechanism is better known as the isostatic postglacial uplift.
there is one more clue for you. The mechanism is better known as the isostatic postglacial uplift.
Are we playing 20 questions, or “let’s google this for fun and profit”? Or are we doing science?
Why don’t you just say something about the geomagnetic condition of the Earth causes M which causes Q which then causes the global temperature to change. I just don’t know what M and Q are. If you do, please say so, and then we can concoct a way to see if we can falsify M and Q. If we can’t, then you might have something.
Peter
Why assume I know more than any other average Joe Blog, or that the climate oscillations run along a single branch flow chart.
@ vukcevic – October 21, 2015 at 8:02 am
I thank you, I thank you, I thank you ….. because I have been looking for a temperature graph like that one ….. for the past 15+ years ….. and have saved the “.gif link” to it in my GW MSWord file for future reference.
—————–
@ Peter Sable – October 21, 2015 at 12:54 pm
We are talking “both”, ….. although vukcevic selected the “daily temperatures” for January and July because …. 1) they are normally the two (2) coolest and warmest months of the twelve (12); ….. and 2) far, far less historical temperature “data” was required for processing to achieve the desired results.
There is no difference between the “daily temperatures” for all 12 months of the year and the “daily temperatures” for January and July ….. except for the “time period” in question.
And ps, …. vukcevic graph would have looked the “same” iffen he had chosen the months of January-February and July-August, …. the 2 coolest and the 2 warmest months.
Like I have stated many time before, on different forums, as copied from my MSWord file, to wit:
“If the Average Summer Temperatures had been increasing at the same rate as the Average Winter Temperatures, which they should have been if atmospheric CO2 is the culprit, then 100+ degree F days would now be commonplace throughout the United States during the Summer months. But they are not commonplace and still only rarely happen except in the desert Southwest where they have always been commonplace.
Now, instead of saying that “the Earth is warming” it is more technically correct to say “the earth has not been cooling off as much during its cold/cool periods or seasons”.
One example of said “short term” non-cooling occcurs quite frequently and is commonly referred to as “Indian Summer”. http://en.wikipedia.org/wiki/Indian_summer
Given the above, anytime the earth’s average calculated temperature fails to decrease to the temperature recorded for the previous year(s), it will cause an INCREASE or spike in the Average Temperature Calculation results for that period ….. which is cause for many people to falsely believe “the earth is getting hotter”.”
Lotsa’ luck splicing the earlier and later temperature records together in any fashion that would not be controversial. Always seems to end up an “oranges to apples” comparison without statistical adjustments. And its in those “adjustment” details that the Devil lives.
“ which you nicely bandpass filtered for to get the nice high correlation.”
Mr Sable
It would help if you specified what ‘bandpass filtered’ graph you are referring.
I have not done any.
Crutem4 and Loehle annual temperatures are as downloaded.
Earth’s magnetic intensity on annual scale moves very little so curves appear to be very smooth.
I hope that helps, if not you welcome to come back and clarify.
The problem I have with any temperature series is that AFAIK, temperature records are merely maxima and minima, and not periodical measurements throughout the 24 hour period. So what if some city in some region measured a ‘record high’? Of course such claims are sometimes debatable and sometimes wrong. But the point I’m making is that it is equally important to know for how long a maximum temperature was sustained.
If you’re taking temperature every 30 mins, then you have something valuable, I think.
Then again, I really am not well versed in the fine details of meteorology, climatology or statistics.
Slippery stats
A good statistician can conjure any result you want from any data – by simple cherry picking.
Example:
Just before a meal you feel hungry; after a meal you feel stuffed full.
Suppose you breakfast at 8.15, lunch at 13.15, evening meal at 19.15.
If I record your feelings every half hr – the plot will show you are fit, well nourished & content….average.
But:
If I record your feelings at 8.00, 13.00, & 19.00 – the plot will show you are constantly hungry –
You could be Anorexic, have worms or cholera !!
Or:
If I record your feelings at 8.30, 13.30, & 19.30 – the plot will show you are constantly full –
You could be Morbidly obese with all the breathing, heart, liver, kidney & mobility problems !!
So which outcome would you LIKE to show ? the statistics can prove they’re all ‘true’.
Well I don’t agree with your conclusions. You presumably processed the subjects “feelings” according to the rules.
It is what you interpreted those results to mean, wherein lies your error.
They don’t really mean anything. If people didn’t try to apply “meaning” to every simple mathematical computation, life would be much simpler.
There is no meaning to any statistical calculation; other than what somebody has chosen to ascribe to that result.
Willis earlier tried to assert that in tossing a coin eight times ( or one roll of eight coins) that it was rare to get the sequence: H, H, H, H, H, H, H. H
Well it’s a 1 in 256 probability.
On the other hand if you get the sequence : T. T, T, H, T, H, H, T , that also has a 1 in 256 probability of occurrence. So eight heads in a row, is in no way unlikely or a rare occurrence. ANY other sequence of eight flips has exactly the same probability. And all of them are four times more likely than getting ten tails in a row.
g
There could be a book title here: “How to Lie With Statistics”. Oh wait, that’s been used already..
Do you know any coin biased to produce T, T, T, H, T, H, H, T?
The temperature of the ocean’s top 300 meters is a better indicator of global warming effect.than atmospheric or surface temperatures. Unfortunately we don’t have very good data, but it’s getting better. The key is to advocate many more buoys taking data, and have a professional outfit free of political influences consolidate it and deliver a sound analysis. The data we have over the last 15 years should be pretty decent, but it’s ignored.
http://judithcurry.com/2014/01/21/ocean-heat-content-uncertainties/
PS: if anybody has a recent analysis showing data from say 1985 to 2015 please post a link?
What about the temperature of the soil, say one meter down? Surely that would show a great integral of temperature over time and it would remove errors of time of reading, spikes etc. It would also be cheap to do.
Is this done anywhere? I have searched extensively but find no readily accessible data.
Keitho, here’s an overview about geothermal gradients and global warming:
http://esrc.stfx.ca/pdf/Beltrami2.pdf
I’ve worked with deep well temperature data, and I think it’s possible to refine the technique. This requires drilling about 1000 meters into a fairly uniform texture low permeability rock. A few dozen boreholes would cost about $100 million.
Thank you Fernando and Joe for your thoughtful responses. I am now off to read and understand a bit more.
Keitho:
At first blush that seems like a good idea. But my guess is that such an approach would turn out to be subject to a great degree of interpretation. Yes, the temperature at depth is a type of low-pass filter if not strictly an integral. But what that particular filter is at a given location depends on the local material’s volume heat capacity and heat conductivity–the latter of which may additionally be season-dependent in at least the mid latitudes. And the subterranean measurements would not eliminate the urban-heat-island effect.
Moreover, the depth required to filter out intra-year variation may need to be significantly greater than a meter. To filter out most (but not all) of the diurnal variation, the temperature profile depicted in Willis Eschenbach’s post “Time Lags in the Climate System” had to reach 35 centimeters. That suggests that you’d need to go down to sqrt(365) * 0.35 = 6.7 meters to obtain a similar attenuation of the annual variation if the material were uniform.
In short, the approach may not be cheap, and one can only guess at how much “homogenization” government-funded curators of indexes based on such subterranean records would find justification for in the parameters mentioned above.
the recent pause buster solution shows that the official temperature “keepers” are not interested in accuracy, they are interested in a result to keep their masters happy. when BO says jump, they jump. when BO says the globe is warming, they make darn sure that their records say the globe is warming. if they don’t, they are replaced with someone that is a “team player”.
What is the basis on which you make that assertion ??
So if I have one buoy taking measurements, how do I get it to simultaneously read the Temperature at points 100 metres apart in depth (four of them). How about every ten metres. I’ve never ever been in any body of water that had the same Temperature throughout a depth of ten metres.
So what is the Temperature of a body of water that is 300 metres in depth.
Do you understand the Nyquist sampling theorem ??
The simple solution is a “liquid immersed” auto-recording thermometer/thermocouple in all Surface Temperature Stations. The liquid itself would function as a “filter” for all short-term variations in temperature ….. thus negating the need for individual “averaging” of daily temperature readings.
Superfluous apostrophe alert – second sentence.
Here is a 2014 study by McKitrick and Vogelsang showing the temp in the trop troposphere from 1958 to 2012. BTW isn’t that single jump the 1976 PDO change? So where is the impact from Co2?
And here is an interesting quote——-
“This is a guest post by Ross McKitrick. Tim Vogelsang and I have a new paper comparing climate models and observations over a 55-year span (1958-2012) in the tropical troposphere. Among other things we show that climate models are inconsistent with the HadAT, RICH and RAOBCORE weather balloon series. In a nutshell, the models not only predict far too much warming, but they potentially get the nature of the change wrong. The models portray a relatively smooth upward trend over the whole span, while the data exhibit a single jump in the late 1970s, with no statistically significant trend either side.”
http://climateaudit.org/2014/07/24/new-paper-by-mckitrick-and-vogelsang-comparing-models-and-observations-in-the-tropical-troposphere/
Sorry. Just can’t help myself, but –
To avoid all accusations of cherry picking, take the long term average, four and a half billion years or so.
Crustal temperature then – very hot – molten even.
Crustal temperature now – not nearly so hot – little molten crust in evidence.
Conclusion – the surface has cooled, regardless of atmospheric composition.
Prognosis – barring unforeseen circumstances, the Earth will continue to cool, until it reaches a temperature at which it is isothermic throughout, beyond the Sun’s influence during at least one orbital period.
This will take a very long time, if it has taken four and a half billions years to create a solid crust of around 20 km on average.
Still plenty of heat left in the ol’ gal yet!
Cheers.
Your model fails at the outset. Consider 4.5 Bn years to get to this point, now how long to get a solid core, and no magnetic field? Certainly, it will take longer than 5 Bn years.
Your problem is, the sun is due to go nova in about 5.5 Bn years. At that point, the temperature will rise, the oceans will boil, the glaciers will melt, the atmosphere will be stripped away, and it really will be worse than we thought.
Yes, but solar power will become economically viable.
Hehehe
Worse than that, latest estimates suggest that, because of the increasing solar luminescence, Earth will be a hothouse in maybe half a billion yrs & lifeless in a billion (atmosphere & water cooked away).
But that’s still plenty of time to move the Earth outward or leave. 🙂
Lord Monckton simply asked a question, “How far back in time from today can we find a flat line for temperature?” Since the question was first posed, the flat line has grown to 18 years and 8 months. If we had good data going back 1,000 years the flat line might be 900 years. If the current El Nino results in a substantial step increase in temperature, the answer will be 0 years and 0 months. The question is neither right or wrong. No cheery picking. Just a question.
We sort of have data going back 10,000 years but limited locations. Interesting discussion about the trends here
http://www.nipccreport.org/articles/2011/nov/16nov2011a2.html
Hi eVince
Your description of what Monckton did seems to be the one he gave himself when he described it a little while ago. This is probably just me being thick and getting hold of the wrong end of the stick, but I don’t quite get it. If I log on to thegwpf.com their header graphic shows the temperature for 2013 to be lower than that for 2014. That means that if we take 2014 as being the last year in the Monckton search period, we can’t even go backwards one year without a rise in temperature over that period.
I’d really like to know what I’m getting wrong here, if you are anyone else can tell me. Thanks in advance.
The keyword in Monckton’s question is FAR. “How far back back in time …”. Going back from 2014 there are more than a few years when the temperature was higher than 2014. But we are not looking for annual temperatures. We are looking for a TREND in temperature. The longest zero trend we can find is 18 years and 8 months. Hope this helps 🙂
I presume that you have some understanding of statistical mathematics.
When you have a “scatter plot” of data points, perhaps on a time scale, but not necessarily, for some reason, people decide to see if there is some “trend” indicated by that plot; say a change with time trend.
For any given data set of fixed points, there is just one unique line, which can be drawn through that set of points. That line has the property, that the sum of the squares of the data point offsets from that line, is minimized. Any other line with a different slope or a different starting point, will result in a larger sum of squares error.
For some people, that line is considered the best fit straight line graph for those data points.
There is a built in presumption, that all of those data points would fall exactly on that line, if it wasn’t for “errors”. One also might presume, that those errors in the data points have some normal (Gaussian) distribution of probability of occurrence, and one can compute a standard deviation for that set of points, as some metric for the likelihood that those errors are just random.
One can establish a criterion relative to some measure like a standard deviation, that one accepts as evidence for the deviations being real or just random noise. Maybe 1 times the standard deviation (sigma) is chosen.
One could then say that deviations less than that criterion were “not statistically significant.”.
In the Monckton algorithm, he settled on the slope of that trend line as being of interest; not the absolute value of any temperature it might pass through. And he simply asks if the statistics of that particular data set, are such that the slope of the trend line is not demonstrably different from zero.
As you add in more data points, the errors presumably gradually get smaller; but the significance cutoff point is different for each run, with a different number of data points.
Obviously, with only two points, a start and an end, the actual value of a slope between those two points, could be quite large and still not be statistically significant, as being different from zero.
So M of B is not any kind of arbiter in this question; he posed the problem, and gave its description, and he lets the numbers fall where they may.
It is ultimately, the common rules of statistical mathematics, that determine the outcome, and Christopher, did not make up his own statistics.
I’m a disciple of Lord Rutherford, who said; ” If you have to do statistics, you should have done a better experiment. ”
It is in what people choose to presume that statistical results mean, where lies the hanky-panky. They don’t have any intrinsic meaning at all. It’s just another fictional creation of the human mind; like all of mathematics.
But much of mathematics provides us with invaluable tools to describe how our models work; which is not the same as describing how the real universe works.
g
A very good article Barry.
What the two directions of the analysis show is that it was a sustained warming from arount 1993/4 to 1999 that is the main contribution to overall “trend”. or average rate of warming. The super El Nino came at the end of the period but it is not whole story. Neither is this picture a particularly good match to a steadily increasing radiative forcing.
Neither can this rise be explained by volcanic cooling of Mt Pinatubo which had a sheilding effect which was mostly gone with in two years after the eruption in mid 1991.
It may however be attributable to secondary effects of the eruption on the chemical composition of the stratosphere.
http://climategrog.files.wordpress.com/2014/04/uah_tls_365d.png
https://climategrog.wordpress.com/?attachment_id=902
https://climategrog.wordpress.com/2015/01/17/on-determination-of-tropical-feedbacks/
Its pretty amazing how blatantly obvious the lower stratospheric opacity over the satellite era can easily explain global warming and the current pause, and it is shocking how there is little or no published information on this. If this potential fact that SO2 laden strato-volcanoes do in fact have a net warming effect on the climate it could help explain many historical climate trends as well as make climate models potentially work. But the truth about how climate works seems to be a matter of personal opinion on both sides of the table.
Climate change (including global warming), the pause, and on-going down trend are explained (R^2=0.97 since before 1900) at http://agwunveiled.blogspot.com and also in a peer reviewed paper published in Energy and Environment, vol. 25, No. 8, 1455-1471
The RSS northern polar temp trend on the sea ice page shows a trend of 0.315K/dec. Looks to me like there’s been no rise for around 20 years. Is the start point (1979) typical of the northern polar temps during the 70s? Is this 1979 data heavily/unduly influencing the trend?
the sensitivity of OLS trends to endpoint selection and to influential observations may be overcome with robust tests for trend. The other advantage of robust trends is that they are relatively insensitive to data adjustments that may have been to alter the OLS trend. Please see http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2631298
I’ve just read (rather, skimmed through) your paper. Very interesting, but needs quite a bit of effort and thought to get properly to grips with it.
For me, handling daily data is really too difficult. Can you see a possibility of some type of way of addressing monthly averages using similar or related techniques? I think I need to read your paper much more carefully, don’t you!
I read the heading and the abstract. Didn’t see word one about what One Line Statistics is. So didn’t bother to download paper.
People who write in gibberish, get the readership they are seeking.
That was a rather hasty response, I feel. Why not abandon any prejudgement and look at what Jamal has done.
Yeah, that el Nino thingy is a real indicator of monkeys burning stuff. That the nasties fall back on it EVERY time and just couldn’t wait for the next ‘big’ one to show us oil-funded, pitiful, unafraidy-types their ‘truth’, all the while ignoring its history and provenance, was enough to convince me they are nothing but scared, groupthink, confirmation bias ignoramuses. They are impoverishing this generation and stealing our children’s inheritance and claiming it will save them based on twisted logic and government-blood-money. That is how insane this has all become. Sorry. /rant.
They dismiss clues from the very Nature that they claim they are defending from one of its components – us.
“Declines in solar activity cause the negative NAO/AO which causes more poleward warm sea water transport and weakens the vortex bringing warmer air into the Arctic, which melts the ice.” – Ulric Lyons
^ that and ENSO emphatically expose CO2 ‘forcing’ of global delta T to be as effective as Reid Bryson’s ‘spit’.
Why should there a linear trend? When you use the proposal of Dr. Trenberth, then the rise of the temperature since 1950 is explained by the pacific decald shift 1976, between 1976 and 1986 there is no temperature rise, the next rise is caused by the El Nino 1986 to 1989. Fraom 1989 there again is no rise until the 1997/98 El Nino and afterwards no rise again until today. This proposal explaines far better ther temperature since 1950 than any linear model.
Someone help me out here-
The 60 year cycle of temperatures seems to be moderately accepted, so how can you derive any trend on half a cycle or even a full cycle? Especially if you have little idea of what harmonics may be at play and are assuming that the 60 year cycle is all that there is.
Personally, I think that the sun has a bunch (good scientific term) of cycles , which seem to be obvious over the time we have been measuring temperature. But the harmonics are less obvious other that the cycles we see are not consistant in temperatures observed at the inflection points (can be hotter or cooler) so something is driving that.
Trends are meaningless until we understand the underlying drivers. The basic requirement of any experiment is to control the variables, and we have little idea of what they are.
We need to remember, when we are accused of cherry picking 1998, that the double La Nina which followed effectively cancelled out the El Nino.
Even the Met Office had to admit this in 2013, in their paper “The recent pause in global warming”
The start of the current pause is difficult to determine precisely. Although 1998 is often quoted as the start of the current pause, this was an exceptionally warm year because of the largest El Niño in the instrumental record. This was followed by a strong La Niña event and a fall in global surface temperature of around 0.2oC (Figure 1), equivalent in magnitude to the average decadal warming trend in recent decades. It is only really since 2000 that the rise in global surface temperatures has paused.
https://notalotofpeopleknowthat.wordpress.com/2015/04/10/the-global-temperature-standstill-simply-explained/
So whether the pause started in 1998 or 2000, you can take your pick, but it is real and not the result of cherry picking.
Let us pretend for a moment, for the sake of argument, that we could know the average temperature of planet earth to the nearest whole degree from the end of the Little Ice Age until the present. What would we expect to see?
I would expect to see a very slight warming trend overall as the planet’s temperature recovered from those very cold days. I would also expect that there would be many ups and downs over that time span and that these last few decades are nothing special.
After all, CO2 does not “warm the surface” the way the alarmists, warmists, and luke-warmists claim. Someday, when the CO2 delusion has abated, we will see what a madness this fear of good old CO2 was.
~ Mark
I will second that……
A system that hasn’t reached thermal equilibrium doesn’t have a meaningful temperature.
Thankfully, our planet hasn’t reached thermal equilibrium, and it therefore doesn’t have a “global temperature”.
The global averaged temperature construct is an extremely crude climate index, an abstraction that provides no useful information about what happens at any point on the ground in the real world.
But it does serve a purpose.
Oh Dear, it looks like everyone who uses energy is out of luck. Without a meaningful temperature, our heat engines will not work. Neither will anything else.
quote:
============
“Once attained, the Maxwell-Boltzmann distribution persists indefinitely. The gas molecules have come to thermal equilibrium with one another, and we can speak of a system as having a temperature only if the condition of thermal equilibrium exists.”
-Principles of Modern Chemistry, 4th ed., p. 119
=============
A heat engine works by converting heat, not temperature, into mechanical work.
@ Khwarizmi
Heat flows form a higher temperature to a lower temperature. A heat engine can extract energy to do work in the process. Without temperature, you can not have a temperature difference. Without temperature, Thermodynamics does a “Crash and Burn”.
I have NO idea what Principles of Modern Chemistry is talking about.
When I was at Grammar School (1950’s) doing “O” level Physics and Chemistry, the word “temperature” was said to define the level of heat in a body. Thus higher temperature = more heat in the body and Vicky verca.
You mean a temperature difference, surely??
People who understand the kinetic basis of temperature would have no problem understanding the words in the quote, TonyL.
http://galileo.phys.virginia.edu/classes/252/kinetic_theory.html
No thermal equilibrium, no meaningful temperature.
Sorry.
Not many people live in city centers or near city airports, where most of stations are placed in urban areas. Most people live in the suburbs that can easily be a few degrees cooler and therefore even the 0.1% don’t reflect most of the people where they live.
The other main issue is that people don’t live in a global average temperature and that resembles nobody on planet Earth. The all point in climate is measuring the energy net balance of the planet and 0.1% of just the surface is a very poor way of going about it. The satellite is by far the best way of measuring this because it records a 3d map of the troposphere. The weather network was only set up for measuring temperatures with intent of weather forecasting. It was never intended for and barely remotely adequate enough for use with climate and measures much less area of the polar regions than the satellites do.
Ever notice- in all those thermometer cartoons, they have the wrong end stuck in their mouths. 🙂
Otherwise it will just look like a straw or something.
I am not sure that the thermometer is the wrong way around.
According to cAGW, it is the atmosphere that is warming causing the patient (planet Earth) to over heat, so arguably it is right to measure the atmosphere. it is not over heating from within, but rather heating from without and on that basis the ball of the thermometer should be in the atmosphere.
The surface temperature thermometers are certainly the wrong technique for measuring the atmosphere correctly. Only 0.1% of the planets surface at 1.25 m doesn’t represent the atmosphere much at all. The atmosphere is suppose to warm more than the surface not the other way round. This highlights the deliberate tampering of surface data, when it warms more than the atmosphere. The cherry picking between different stations over decades results in a significant bias.
The weighting of unequal observations in grid data also causes a significant bias. Estimated data related to model also causes significant bias, when the surface should warm less than the atmosphere. The estimated temperatures are adjusted to behave like the atmosphere should in the model, not the surface. The atmosphere is not warming like in the model, so the estimated temperatures are incorrect for the surface too.
Matt G says
Only 0.1% of the planets surface at 1.25 m doesn’t represent the atmosphere much at all
On the other hand, probably 90 per cent of the world’s population spend their lives very close to that 0.1 per cent, and that is what most people care about – not the temperature of the troposphere
Not many people live in city centers or near city airports, where most of stations are placed in urban areas. Most people live in the suburbs that can easily be a few degrees cooler and therefore even the 0.1% don’t reflect most of the people where they live.
The other main issue is that people don’t live in a global average temperature and that resembles nobody on planet Earth. The all point in climate is measuring the energy net balance of the planet and 0.1% of just the surface is a very poor way of going about it. The satellite is by far the best way of measuring this because it records a 3d map of the troposphere. The weather network was only set up for measuring temperatures with intent of weather forecasting. It was never intended for and barely remotely adequate enough for use with climate and measures much less area of the polar regions than the satellites do.
If I am not mistaken, all intrinsic properties of thermodynamic systems can ONLY be determined at thermal equilibrium.
But who is paying attention to such details.
g
In terms of the RSS trend, one should also take into account that there were two large volcanoes in 1982 and 1991.
This reduced RSS temperatures by 0.35C in the year after the eruption and then it took 3 years before temperatures recovered.
These volcanoes also destroyed Ozone in the stratosphere which shows the impacts more clearly. Ozone has still not recovered from the 1991 eruption, so it is a good thing these large volcanoes do not happen that often.
Bill Illis:
Do you have a citation for this claim? I’d be interested in the physical mechanism that allows for such long-term impact on stratospheric ozone which is constantly being created/destroyed by normal processes.
“A step in the temperature” … nonsense!!
Please read Natural habitats of 1/f noise errors. which covers the commons errors of the inexperienced when looking at 1/f type noise as found in the climate.
Figure 2 – it took me a bit to realize that the lower curve is not “Temp Anomaly K/century” but just “Temp Anomaly in K” as in Fig 3. (and differently scaled in Fig 1).
I had the same problem.
LOL! Rod Zeman is already having a field day with rhis on WUWT FaceBook page! Someone please pop over and put the fool out of his misery!!!
So if you changed the base period of the anomaly wouldn’t that change the anomalies which would then change the trend lines?
No, it changes the intercept of the line but not the slope. It’s just an offset.
Thanks.
Has nobody ever heard of LOESS? All this bickering about bias from choosing start points could be put to rest if people just plotted the LOESS fit for the satellite era. I’d post an image, but I’m not sure how. But a LOESS fit shows that the RSS TLT plot levels off, after 1997-98 at the end of 2001 at about 0.25, and has remained essentially zero since then (declining ever so slightly to about 0.24).
Step increase, anyone? And yes, I’m not the first person to suggest this. But I’m unaware of anyone calling attention to it using LOESS (though I wouldn’t be surprised if someone has).
But LOESS is just another way (actually, set of ways) of filtering the data; making one choice does not eliminate arguments by proponents of other choices.
Look, I have no illusions about Christopher Monckton’s honesty or accuracy in general. But in this case he has been clear about his criterion and made no claims that its result is the be-all and end-all. And in my opinion that criterion should be considered a pretty good objective measure of “the pause” for those to whom that concept means something.
That said, I think Mr. Wise has done a service by reminding even those of us who had previously but not recently gone through similar exercises that the lower troposphere’s trend for the satellite era does, for whatever reason, exceed a kelvin per century; it’s something I confess I’d forgotten.
I agree with you, LOESS is available in statistical analysis software like Minitab, for example and easy to use:
http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/graph-options/exploring-data-and-revising-graphs/adding-smoother-lines-to-graphs/
It is nice to have to look at data and help find trends but still you need to input arbitrary smoothing functions and play.
I would stay with what Lord Monckton is doing. Use linear least squares analysis and calculate R-sq value as the guide to accept or reject a trend is the basic requirement. If no R-sq value is presented with linear regression plots, forget it, you can’t claim anything, but I see this done here again and again. Please, no more.
blcjr used LOESS but the description of his finding is no more and no less better than Lord Monckton, in fact it may have given blcir a “smoother” curve (from his description it did) but then “so what”? What can he claim? A prettier grahp? I don’t blame him for using such, it makes you think about possibilities, but no more. I say, stay with it Lord Monckton. And wait! How long will this pause last? Maybe with a short intermission?
Yes,with all the warming coming during a positive PDO and AMO and El Nino and strong Sun and increase in surface insolation.
It is beyond all comprehension that anyone would plot a straight line linear trend line from late 1979 to late 2015 through the RSS data. One thing that is immediately apparent from that dat that there is no such straight linear trend.
If one looks at the data, a couple of things are clear.
First, that there is much yearly/biennial variation.
Second, it is clear that as from launch in late 1979 through to say the end of 1996 (ie., through to the run up to the 1997/8 Super El Nino), there is no statistically significant trend. the temperature is essentially flat lined at about the 0 degC anomaly if one considers the temperatures post the 1997/8 Super El Nino, once again there is no statistically significant trend and once again, the temperature is essentially flat but this time at a bout the 0.25degC anomaly level.
I would suggest that the correct interpretation of the RSS data set is that it shows flat temperatures (with no statistically significant trend) until the 1997/8 Super El Nino, then a step change in temperatures of about 0.25degC coincident upon that event, following which there has been no statistically significant tend in the temperatures to date. In other words, it shows a one off isolated warming event coincident upon the 1997/8 Super El Nino.
There are in effect two pauses of approximately 17 years in duration. The first pause runs from launch up to the run up to the 1997/8 Super El Nino. The second pause runs as from that event to date.
There is no first order correlation with CO2.
the fact that the step change is coincident upon the 1997/8 Super El Nino does not mean that it was caused by it, but that Super El Nino must be regarded as the prime suspect. The question is why has it resulted in a step change in temperatures, and why have has the atmospheric warming that was caused by that event not yet dissipated and not yet returned to around the 0 deg C anomaly level (if indeed that is the cause).
We will have to wait and see whether following the strong 2015/6 El Nino there is another step change in temperature and if so whether following that event temperatures trend level albeit at a higher anomaly level, or whether a La Nina that may follow the 2015/6 El Nino cancels out any warming such that the 2nd pause continues.
We should know a lot more by 2019/20.
What is the lifetime of water vapour in the atmosphere? Sorry for asking such an obvious question but I’m finding answers all over the board from 10 days to months and years.
Water vapor has infinite lifetime in the atmosphere (nearly) We have always had water vapor in the atmosphere and always will.
So some of it comes and goes, but then one water molecule works as well as another.
Residence times are just BS.
I agree with you about trying to fit a linear trend from 1979 to 2015.
But this, to me, is irrelevant.
There is only ONE thing in your post that is relevant:
“There is no first order correlation with CO2.”
Thank you.
rd50,
Nor is there any measurable 2nd order corellation with CO2. Nor any 3rd order corellation.
As Willis E has noted, if CO2 causes any forcing, it is only a small, 3rd-order effect, which is swamped by 2nd-order effects. And both those small forcings are swamped by 1st-order forcings.
That’s why we have no measurements of CO2 causing global warming. Almost all the warming effect of CO2 has been used up in the first few dozen ppm. Adding more now causes unmeasurably small global warming. We could add 20% more CO2, or 30% more, or 50% more without causing any measureable global warming.
Looking at this chart, you can see that even if CO2 doubled from present concentrations of ≈400 ppm, any global warming would be too minuscule to measure:
Yes, thank you for the added graph. This is what is important.
I also answered to someone below with two graphs. Easy to find them in all colors!
Yes, in some short periods, we can find that temperature increased while CO2 was increasing. No problem, anybody can run least squares linear regression analysis between the two for the periods between 1978 and 2000 as shown in the graphs posted below and the R-sq value will be about 0.8, quite good evidence to follow an hypothesis . But then what? The period before and the period after??? No positive correlation there.
R2 = 0.004 for monthly CO2 PPM between 1979 and 2015.
To Matt G
Yes. I believe you. Nothing there.
And indeed this is what is important, not that we have observed a very slight increase in temperature.
Fine, give me a slight increase in temperature. I want it. Positive outcome with it.
And indeed this is what is important, not that we have observed an increase in CO2.
Fine also, give me a slight increase in CO2 (or even a big increase in CO2 up to about 800 ppm or so).
Positive outcome with it.
Yes, we should wish some increase in temperature and in CO2. The combination of both is great for mankind.
Wow, This must be a very special thread….it posted twice !! LOL…
Getting his critics to admit that it was hotter in 1998 than now seems like progress.
One factor that could indicate who has the better argument is what happens as time goes by and the “no trend” effect gets longer. If, after a year, the “no trend” is only a year longer, still starting at the same point (whether at or some time shortly before the El Nino), that would be strong evidence that the 1997 El Nino has (at least temporarily) overwhelmed the trend and perhaps should be normalized to filter out the outlier effect.
However, if, after a year, the trend has extended by more than a year, with the latest period of “no warming” allowing you to set an earlier start date for the trend, then that would be strong evidence that the 1997 El Nino has not overwhelmed the trend and the cessation of warming is real.
Note, I did not use the word “pause” anywhere in that comment. That was deliberate–it is not and logically cannot be a pause until after the warming starts up again. I’d like to see skeptics stop using that inaccurate, pro-CAGW word.
What do you mean “logically cannot be a pause until after the warming starts up again”
What if it starts cooling?
You believe it can only start warming again? What about cooling? Not possible?
rd50, Seriously? What I mean is plain, it’s basic English–something cannot be a pause in the trend unless the trend resumes at the end of the pause. In this case, that means there is no pause in the warming unless and until the warming resumes. If the warming does not resume, then it is not a pause. Period. What it does instead is irrelevant to the point.
Well there is no evidence that it is a pause by your definition, since that can’t be determined until it starts warming again.
So it isn’t a pause; it’s a stop, and it will either change to warming or apparently more likely a cooling; but right now it has stopped.
I suggest including a test of statistical significance of the slope.
When the data series includes an anomalous event, such as the el-Nino and la-Ninas of 1998 to 2000, it should be considered whether Least squares is the appropriate tool.
Chris4692; you simply are not paying attention.
The Monckton algorithm DOES INCLUDE a test of statistical significance.
The algorithm does not stop UNTIL there is a statistically significant non zero trend.
“…at what point do we say that a trend of a given length makes sense in terms of whether it’s an indication of future global temperatures or just a statistical anomaly?”
We may just be confusing the two meaning of the word “trend”. For example, take 100 numbers from a trendless series such as a random walk. A “trend” can be calculated, but it does not imply anything about the future which is the other common meaning of the word “trend”.
Global temperatures may not be a random walk, but statistically Lord Monckton has shown that we cannot differentiate the MET temperatures since 1850 from a random walk.
If global temperatures are deterministically chaotic (no, that is not a contradiction; that is the meaning of chaotic) with many drivers and interaction, we would expect the temperature series to appear somewhat like a Gaussian random walk.
Others have studied the past climate record and arrived at similar conclusions. Note the 0.5 C trend claimed in their study
“Climate has varied in the past and can be expected to do so in the future. Mankind has adapted
to both cool and warm periods, and trade and economic growth over the past 300 years has greatly
increased our ability to do so. In that context, forecasts of climate are of little value unless they are for a
strong and persistent trend, and are accurate.
The IPCC “forecasts” are for a strong and persistent trend, but they have been inaccurate in the
short term. Moreover, there is no reason to expect them to be accurate in the longer term. The IPCC’s
forecasting procedures violate all of the relevant Golden Rule of Forecasting guidelines. In particular,
their procedures are biased to advocate for the hypothesis of dangerous manmade global warming.
We found that there are no scientific forecasts that support the hypothesis that manmade global
warming will occur. Instead, the best forecasts of temperatures on Earth for the 21st Century and
beyond are derived from the hypothesis of persistence. Specifically, we forecast that global average
temperatures will trend neither up nor down, but will remain within half-a-degree Celsius (one-degree
Fahrenheit) of the 2013 average.
This chapter provides good news. There is neither need to worry about climate change, nor
reason to take action”
http://www.kestencgreen.com/G&A-Skyfall.pdf
Here is a link to an Excel file that produces an adjustable RSS chart that might be useful. It will let you see how changing the start and stop points for the regressions will change the trend. It has adjustable smoothing that is superimposed over the original data. It has an update button to download the latest RSS data. You must allow Excel to run macros for the update function to work.
https://www.mediafire.com/?5f12zar174q44qz
If you need for me to send the file directly as an attachment just let me know.
I created this with Excel 2003. It should run on newer versions of Excel. I would be interested to know if the program doesn’t run on some newer version of Excel.
The VBA code is protected to avoid the possibility of someone adding code that might be harmful.
C. Bruce Richardson Jr.
richardson@swbell.net
To cut a long discussion short, this contribution shows again that Lindzen & Shou were probably very much in the ballpark when they came up with the +/- 1.2C for a doubling of CO2. “The iris effect acts to reduce the sensitivities from the range, 1.5°–4°C, to the range 0.64°–1.6°C.”
I know this is really, really off topic, well kind of. It is about temperature. http://news.yahoo.com/freezing-migrants-cry-foul-german-cold-bites-074636764.html
The Paris conference is soon to start, Many of us have been expecting early freezes and snow. It already has been snowing early in many places but not much.
My thought is how will it be presented Paris, if there is a bad early freeze in German etc and many of the refugees perish from it?
Perhaps I’m to Machiavellian.
michael
And yes the thought that it could happen to those people frightens me.
It will be blamed on Glo.Bull Warming no matter what happens !!!!
9 inches of snow in Syracuse NY.
Interstate 81 was closed.
Accidents etc., 10 Centigrade
Never before in mid-October.
Does this mean anything.
No
El Niño events are not climate. They are not heat sources – they represent a cooling event, in fact, because they release accumulated heat from the ocean. That energy necessarily passes through and warms the atmosphere briefly, but ultimately is gone forever. It is an impulse. For long term trends it can and should be ignored, IMO. It does have value to global warming alarmists as a event to sensationalize, though, so it appeals to the news cycle hysteria mongers.
If it’s perceived to be bad, it’s climate. If it’s perceived to be normal or beyond human control it’s just a brief event that can be ignored.
I’m surprised they haven’t started claiming that our SUVs are creating holes in the sun!
http://www.dailymail.co.uk/sciencetech/article-2894840/Mystery-sun-s-south-pole-Nasa-reveals-huge-coronal-hole-solar-surface-winds-jet-500-miles-SECOND.html
This is the new normal. We’ve loaded the dice toward sun holes with our reckless negligence toward Gaia.
Ah, you made a point that got me started on this essay. I veered off into the trends though but originally I was curious about what an el Niño meant in terms of the effect on the energy budget of the earth. From that point of view the ocean is a heat storage unit (think capacitor) that when the el Niño occurs releases it across a resistance (the atmosphere) to ground (space). Some gets left behind that we see as the temperature change in the atmosphere. I know that’s a really rough analogy so please will any commenters not explain why it’s not like electronics and the ocean isn’t a capacitor. In any event, I agree that el Niño’s effectively remove heat from the system as a whole when total heat content is considered.
You are spot on, dp.
There were essentially no El Niño events during the Holocene Climatic Optimum when the planet was significantly warmer than the present. The world was then dominated by La Niña events. El Niño events start to be more frequent after the Mid-Holocene Transition, during the Neoglacial period, and therefore are a feature of a cooling planet.
The more the planet has to cool, the more El Niño events take place. As they take heat from the ocean and place it into space they are net contributors to the planet cooling.
In the last 12 years we have had 6 El Niño events (>0.5° in El Niño 3.4 area). This is some sort of Holocene record. An average of one El Niño every two years, yet global temperatures barely have changed. It is very difficult to sustain the opinion that El Niño events cause warming in the face of this evidence. They are significant contributors to the lack of warming.
I see the step function across the 1998 el nino.
This has been pointed out before by many, and is often called the climate shift.
Eye balling I see about a 0.25 degree shift up in the average level. (see fig. 1, RSS data).
It will be interesting if the current big el nino will give another step up, even after the next la nina.
And why do those earth cartoons always show the thermometer with the wrong end in the mouth?
Because the warmists have many things backwards !
IMHO the actual slope of 1.2 deg/century is the best estimate of global warming going forward. I trust the actual data more than the IPCC models. This rate of warming is caused by some combination of nature and anthropogenic. Man’s activity became significant around 1960 or so. Before that, any warming was natural. Warming from 1800 to 1960 was occurring at a rate of around 0.5 deg/century. So IMHO a reasonable projection is that natural warmingwill continue at a rate of 0.5 deg/century and man’s activity will add additional warming at a rate of 0.7 deg/ century.
These figures imply that
1. Warming is not occurring at a catastrophic rate.
2. Efforts by the UN, the EPA, etc. to reduce carbon emissions will have a negligble impact on global warming.
Barry. – you say
“To begin, at what point do we say that a trend of a given length makes sense in terms of whether it’s an indication of future global temperatures or just a statistical anomaly? Obviously the longer the better, or so one might surmise, but then that’s assuming that the data represents a linear trend. ”
Earth’s climate is the result of resonances and beats between various quasi-cyclic processes of varying wavelengths combined with endogenous secular earth processes such as, for example, changes in the earths magnetic field. It is not possible to forecast the future unless we have a good understanding of the relation of the climate of the present time to the current phases of these different interacting natural quasi-periodicities which fall into two main categories.
a) The orbital long wave Milankovitch eccentricity,obliquity and precessional cycles which are modulated by –
b) Solar “activity” cycles with possibly multi-millennial, millennial, centennial and decadal time scales.
The convolution of the a and b drivers is mediated through the great oceanic current and atmospheric pressure systems to produce the earth’s climate and weather.
After establishing where we are relative to the long wave periodicities, we can then decide which is the appropriate length of the temperature time series required to illustrate whatever working hypothesis one is suggesting and based on past patterns make reasonable forecasts for future decadal periods.
For forecasts of the timing and extent of the coming cooling based on the natural solar activity cycles – most importantly the millennial cycle – and using the neutron count and 10Be record as the most useful proxy for solar activity check my blog-post at
http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
The most important factor in climate forecasting is where earth is in regard to the quasi- millennial natural solar activity cycle which has a period in the 960 – 1020 year range. For evidence of this cycle see Figs 5-9. From Fig 9 it is obvious that the earth is just approaching ,just at or just past a peak in the millennial cycle. I suggest that more likely than not the general trends from 1000- 2000 seen in Fig 9 will likely generally repeat from 2000-3000 with the depths of the next LIA at about 2650. The best proxy for solar activity is the neutron monitor count and 10 Be data. My view ,based on the Oulu neutron count – Fig 14 is that the solar activity millennial maximum peaked in Cycle 22 in about 1991.
http://3.bp.blogspot.com/-QoRTLG14Siw/VdOUiiFaI5I/AAAAAAAAAYM/NxQVb2LMefk/s1600/oulu20158.gif
There is a varying lag between the change in the in solar activity and the change in the different temperature metrics. There is a 12 year delay between the activity peak and the probable millennial cyclic temperature peak seen in the RSS data in 2003.
http://3.bp.blogspot.com/-gH99A8_0c6k/VexLL1zC7AI/AAAAAAAAAaQ/T50D6jG3sdw/s1600/trendrss815.png
There has been a slight cooling temperature trend since then .There is likely to be a steepening of the cooling trend in 2017- 2018 corresponding to the very important Ap index break below all recent base values in 2005-6. Fig 13.
I suggest that the trends as shown on the RSS plot above show most clearly what is actually going on i e that we are just past a millennial peak in a solar activity cycle.
If 2003 was a maximum in the millennial cycle of 980 years, then the previous minimum has to be located at 1513. This cannot be correct as we know that temperatures were significantly lower around 1650-1750, and even early 19th century. The position of the millennial cycle is uncertain and therefore no forecasts can be made from it.
The last peak was at about 990 +/- therefore we might expect the current peak to be between 1950 and 2010. – the data suggests about 2003.
You assume that the shape of the curve is symmetrical – it isn’t .
The minimum on the 50 year moving average is at about 1630. I use the simplest assumption which is that the shape of the curve from 990 – 2003 will repeat from 2003 -3013.
Of course ,in the real world,no cycle ever repeats exactly but I believe that my assumption is about as good as anyone can do at the present state of our understanding and that it will but us in the ballpark for longer term forecasting and climate policy purposes.
http://2.bp.blogspot.com/-4nY2wr6L-WY/U81v9OzFkfI/AAAAAAAAATM/NA6lV86_Mx4/s1600/fig5.jpg
I see, you base your theory in a particular temperature reconstruction that shows a particular peak at 990. But you know that we don’t really know if that particular peak existed or was a millennial maxima, don’t you? All we know is that between about 950 and 1300 the world was warmer than before and after.
No, I don’t assume that. Usoskin et al. 2007 have demonstrated that solar cycles are about solar grand minima. Grand maxima do not show any periodicity. There are no warming events in the Holocene, just cooling events and recovery. 8.2, 5.5, 4.2, 2.8 Kyr events and LIA are all cooling events. You have to understand the nature of solar cycles, because looking for peaks is wasting your time.
Javier See Fig 5 at.There are perfectly good peaks close enough to 10, 000. 9,000. 8,000. 7,000. 2,000.1,000.and the present.
http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
For a complete discussion of the cycles See all of Section 2 at the link above.
In order to make forecasts you don’t actually have to understand solar cycles ( although that would be nice) – simply see that they exist in the data,
1. That is a single proxy from one location. You make a mistake if you assume that it represents global climate. Other proxies have other peaks.
2. Just because those peaks are separated ~1000 years you assume that they are solar in origin, yet you have no evidence of that, at all.
3. In fact the spacing of the last 4 peaks that you mention (you conveniently forget peak at -1500) is 1150 years according to Ole Humlum. You cannot reconcile that spacing with a cycle of 980 years. By the third cycle the accumulated difference is already 510 years which is half cycle.
So no, they are not perfectly good peaks, they do not support a 980 year cycle, you have no evidence that they represent global changes, and you have no evidence that they correspond to changes in solar activity.
The ~1000 year solar cycle is real, but you are not seeing it in that GISP2 graph. If you would bother to really study the subject that you write about you would have noticed in wavelet analysis of reconstructed solar activity that the ~1000 year solar cycle essentially disappears between 6000 and 1500 years ago. As it happens with many cycles, it weakens and becomes undetectable only to return for the last two oscillations.
Eyeballing graphs and peak assignation will not get you on the right track to understand Holocene climate.
Javier
You say “The ~1000 year solar cycle is real, but you are not seeing it in that GISP2 graph. If you would bother to really study the subject that you write about you would have noticed in wavelet analysis of reconstructed solar activity that the ~1000 year solar cycle essentially disappears between 6000 and 1500 years ago. As it happens with many cycles, it weakens and becomes undetectable only to return for the last two oscillations.”
My point exactly – the 1000 year cycle is real – and I agree that these cycles appear and disappear when using wavelet analysis and it does indeed return for the last two oscillations – the ones most relevant for forecasting the next 1000 years-which is my chief interest.
You also say
“1. That is a single proxy from one location. You make a mistake if you assume that it represents global climate. Other proxies have other peaks.”
Look at the other evidence of a long lived millennial cycle which I linked above in Section 2.3 at
http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
And of course there are other peaks – see the smaller amplitude 60 year cycle discussed in Section 2.4
As to the solar connection see figs 6 and 10 – 14.
You have to put all the data together to make a complete picture.
The millennial solar activity peak at 1991 fits remarkably well with a possible millennial RSS 2003 temperature peak. (See Fig 3 at
http://adsabs.harvard.edu/full/2005ESASP.560…19U )
Javier
Wavelet analysis shows the solar millennial cycle very well at 2024 years which is certainly close enough to the window I am suggesting.
http://www.pnas.org/content/109/16/5967/F4.large.jpg
Sorry – typo – should be 1024 years.
The Fig is at
http://www.pnas.org/content/109/16/5967.full
TSI
http://woodfortrees.org/plot/pmod
what point do we say that a trend of a given length makes sense
===============
as a general rule, any trend that changes with the length of the sample is not a trend. it is an artifact of the sample size.
Cherry picking is not including the 1998 El Niño. It would be starting at the peak in 1998, which would give the lowest trend. The critics who allege cherry picking are projecting their own proclivity for cheating with the math and data.
The 1998 El Nino actually causes the zero trend to disappear.
If it were not for the 0.26C warming from that El Nino and associated events, the ZERO trend would cover the WHOLE 37 YEARS of the satellite record.
It’s really far more simple than all of this, but I do appreciate the article’s detail.
If you take a trend for as far back as it can go and essentially equal zero…..Monckton is simply correct. Period. That’s not cherry picking. If the time period for this was 2 months, it would be meaningless. Almost 19 years! It’s quite notable.
Even if this trend continued for 100 years , the warmists would still say ” Your cherry pickin’ the data ” !!!!!
There is no cherry picking because it is from present to the past.
It was no different when the planet was showing warming to the present back in 1999.
http://www.woodfortrees.org/plot/rss/from:1985/to:1999/plot/rss-land/from:1985/to:1999/trend
The fourteen years of warming was not cherry picked back then because it represent the recent warming to the present. Comparing no warming to the current present has been no different to this. Before then global temperatures were cooling from the beginning of the satellite data.
http://www.woodfortrees.org/plot/rss/to:1985/plot/rss-land/to:1985/trend
The problem is those calling this cherry picking, have no other than to do this because they can’t defend it and avoid confrontation. They are hypocrites because back in the 1990’s the alarmists were only doing the same thing. In both cases rightly so because all it is doing is showing how the present is behaving from the recent past.
It is much worse though because the no warming period is considerably longer than the warming period in the first place and the ignorance of this just shows what a scam global warming has been and increasingly become.
Plotting temperature vs time is really a straw man.
Why not plot CO2 on the x-axis vs temperature on the y-axis over the last 20 years and see what the regression looks like?
Here is more than you want:
http://www.climate4you.com/images/HadCRUT4%20GlobalMonthlyTempSince1958%20AndCO2.gif
and even more:
http://www.climate4you.com/images/HadCRUT4%20GlobalMonthlyTempSince1958%20VersusCO2.gif
If you include HADCRUT4 since 1958 and include satellite data instead from 1979 there is only 13/14 years that rise with CO2. Therefore that means only ~23% of data matches with the trend of CO2 and those that do lag global temperatures between 1 and 10 months.
http://i772.photobucket.com/albums/yy8/SciMattG/Derivative%20RSSvCO2_zps6tiwpduo.png
Matty G,
The data shows that ∆CO2 is caused by ∆T.
That cause-and-effect relationship is found on all time scales:
[click in chart to embiggen]
Agree, the graph also shows the same thing over the recent satellite data.
Stealey, both of your charts are “overlays”
..
[?? .mod]
@’tim r’, or should I say ‘David’,
You are wrong as usual.
Look at the “Note”, right in the middle of the bottom chart in my post above. It states:
NOTE: TEMPERATURE CAUSES CO2 CHANGE
Cause-and-effect, see?
The chart above is a long term, 740,000 year view showing that changing global T is the cause of changing CO2. And here is a short term chart from 1960, showing the same cause-and-effect:
So you see, they are not overlay charts. Only the alarmist cult uses overlay charts to claim CO2 is a cause of changing T. But overlay charts don’t show any cause and effect. Thus, the alarmist cult can hide the fact that the only charts available show that ∆T causes subsequent ∆CO2.
But nice try, ‘David’.
http://zfacts.com/metaPage/lib/zFacts-CO2-Temp.gif
http://www1.ncdc.noaa.gov/pub/data/cmb/images/indicators/global-temp-and-co2-1880-2009.gif
Mr. Penn, hi
Whatever happen to the ‘pause’ in your first graph
as you can see here there is a good correlation and the PAUSE !
http://www.vukcevic.talktalk.net/GT-GMF1.gif
To Alan Penn below.
You posted two graphs below.
Certainly want to look at both.
So, please cite the source or give us a link.
I gave my graphs with full link in my post.
Please do the same.
Should be To Alan Penn above!!
Barry, you are believing the climate scammers’ nonsense: “…but is consistent with a doubling of CO2 with no secondary effects.”
Not according to this:
http://wattsupwiththat.com/2010/03/08/the-logarithmic-effect-of-carbon-dioxide/
What is ‘Beginging”?
Well, well well. What do we have here but another non-reader? If you had read my book “What Warming?” you would not have come out with all these non-sensical claims. First, your figure 1 is worthless. Putting a linear fit on data that are non-linear is equivalent to demoting all observations to random noise. And figure 2 is a fantasy. A basic thing you miss is that there is a discontinuity in this temperature region brought on by the appearance of the super El Nino of 1998. You must not combine the right and the left sides of it into one statistical mishmash. You are not the only one doing that. This stupidity is flagrant in the CMIP5 horsewhip display that attempts to, but fails, to incorporate the hiatus into itself. Lets take an overview of the data involved. I suggest you read my book and have figure 15 out to follow it. The base of my figure 15 is a combination of UAH and RSS satellite data, plotted on the same curve. They are so close to one another as to be ibdistinguishable when plotted together but you do get a noticeable reduction of noise. You will notice also that I used a magic marker to outline the trend line that includes five El Nino peaks on the left. The super El Nino itself is not part of this ENSO wave train so I left the magic marker off. It i obviously of different otigin. The magic marker starts again on the right side and is contnued until the present. There is no way you can follow this path with any statistical curve. The noise that necessitates using the magic marker comes from the cloudiness variable, combined with the changing view from the orbit. This sets the maximum noise amplitude. As soon as the super El Nino emds it is followed by a short step warming that starts in 1999. It looked at first like another El Nino starting up but it went higher. In three years it raised global temperature by one third of a degree Celsius and then stopped in 2002. That short and intense period is very likely caused by the mixing action of the returning waters of the super El Nino. This makes the year 2002, not 1997, the proper starting point for the hiatus. For the next five years temperature vacillated about a high level mean and never came down to its previous level as I had expected. I started calling it the twenty-first century high. But then a La Nina appeared in 2008. This is the cooling that Trenberth cursed in his Climategate email. It was followed by an El Nino in 2010. I thought the regular ENSO oscillations had finally returned but I was wrong – the El Nino of 2010 was followed by more of the vacillations that we saw at the beginning of the century. As the El Nino watcheers have told us we should get an El Nino this winter but I think not – that peculiar vacillation is still going on. Before taking up this behavior let us see what the El Nino wave train on the left tells us. It is a classic El Nino oscillation induced by a side to side sloshing of the pcean water in tropical Pacific. Its power source is trade winds and its natural period is about four and a half years. An El Nino wave is first formed in the werstern Pacific at the Indo-Pacific warm pool. It crosses the ocean along the equatorial counter-current and runs ashore in South America. Nino3,4 is an observation post El Nino watchers use. It sits in the middle of the equatorial counter-current and measures water temperature as the El Nino waves go by. Several months after one has passed global air temperature rises and we notice that an El Nino has arrived. The lag time is due to the fact that an El Nino wave at Nino3.4 location still has to traverse half the ocean before reaching South America. Once there it spreads north and south along the coast, warming the air above it. Warm air rises, joins the westerlies, and we finally notice the arrival of an El Nino. To close the cycle a back flow takes place. Any wave that runs ahore must also retreat and when it does so water level behind it drops by as much as half a meter. Cool water from below then fills the vacuum and a LacNina has started. As much as the El Nino warmed the air a La Nina will now cool it and mean ocean temperature remains the same. I took advantage of this in figure 15 and marked the half way-points between an El Nino peak and the bottom of its neighboring La Nina valley with dots. These dots show the time history of global mean temperature as the wave train developed. They define a horizontal staight line which which extends from 1979 to 1997. This defines the length of the hiatus of the eighties and nineties that IPCC has decided to disappear. What they have done is to show a fake warming hey call “late twentieth century warming” in its place. I discovered that HadCRUT3 was the source of this fake warming (figure 24), even put a warning about it into the preface of the book, but nothing happened. Later I found that GISS ac NCDC were its co-conspirators. Changing official temperature records to fool other scientists is a scientific crime. It needs to be investigated by RICO and appropriate punishments used as necessay. The fact that the temperature plateau has persisted throughout this century is very likely due to the deep stirring up pf subseurface warm layers by the super El Nino. The origin of the super El Nino is not the same as ENSO. It is a rare phenomenon of possibly centennial occurrence. The irregularity of twenty first century El Ninos could be related to variability of Pacific wind patterns. The westerlies that carry warm El Nino air and the trade winds blow in opposite directions. The dividing line between them is somehere south of the Mexican border. If, for any reason, that dividing line should move north more of the warm air would get trapped into the return flow of the trades. This could weaken or even suppress the El Nino. It is possible that the hiatus that followed the super El Nino has some influemce over winds but that is a speculation. That “blob” of warm water near Northwest coast may likewise be another symptom of irregular winds in the Pacific. Apparently those people who get billions to do climate research are not doing any reasearch that could explain these mysteries.
Ignoring the computational mandate that temperature change occurs as a transient in response to the time-integral of net forcing (not directly with the instantaneous value of the net forcing itself) is all too common.
If earth’s magnetic dipole is considered to be a forcing on temperature, its effect on temperature must be in accordance with the time-integral of a math function of the geomagnetic dipole, not directly with the magnitude of the geomagnetic dipole itself. Thus the graphs at vukcevic Oct 20, 12:24 am actually demonstrate that global temperature is NOT driven by the geomagnetic dipole.
The two factors that do drive average global temperature (R^2=0.97 since before 1900) are identified at http://agwunveiled.blogspot.com
The reality is that the 1997 – 2001 El Nino and associated events causes a STEP change of approximately 0.26ºC
Without that step change, there is basically NO WARMING AT ALL in the RSS satellite data.
http://woodfortrees.org/plot/rss/from:1979/plot/rss/from:2001.2/trend/plot/rss/from:1979/to:1996/trend/plot/rss/from:2001.2/trend/offset:-.26
The slight warming trend from 1979-1997 has been essentially cancelled by the cooling trend since 2001.
The current El Nino hasn’t yet provided the spike that the 1998 and 2010 El Nino’s did. It will be interesting to see if it does, but if it doesn’t the cooling afterwards could take us back down to where the satellite record started.
ps.. putting straight lines through step changes is a mugs game.
“The current El Nino hasn’t yet provided the spike that the 1998 and 2010 El Nino’s did. It will be interesting to see if it does, but if it doesn’t the cooling afterwards could take us back down to where the satellite record started.” Andy, this would not be allowed to happen. There is no way, no way at all, that all the people with a significant investment in CAGW, either by way of money or reputation, would simply accept that data. Sorry to be cynical.
Notice also that the 2010 La Nina/El Nino did not have any effect on the general cooling trend since 2001.
No step change… just a pair of cancelling spikes.
I disagree. El Chichón, Pinatubo and Hudson caused the step change. El Nino did sweet fanny adams over the longer term and probably resulted from the latter two. [1800 x 3200px, 542kB image].
http://s12.postimg.org/bmuc6dujf/UAHCO2.png
A step change to the temperature of the planet would mean a step change to the energy content of the planet which is clearly impossible. There was no massive, sudden influx of energy. Even a sudden change in net forcing would affect temperature only as the effect of the time-integral of the change to net forcing was accumulated. Thus a step change in REPORTED temperature indicates nothing more than a change in method of data acquisition or reduction.
No, you’re equating atmospheric temperature with the total heat energy of the planet. The oceans act as an energy sink which is not measured by the atmospheric temperature. When an el Niño releases that energy there is a rise in the temperature of the atmosphere as that energy is radiated into space. Some gets absorbed by the gases that are sensitive to the wavelengths of the released energy which raises the temperature of the atmosphere but it is energy that was already in the system. Just not in the atmosphere. How long that energy stays in the atmosphere is an interesting question.
ENSO represents a tiny fraction of the earth’s surface. Regardless of how and where temperature is measured (as long as it is done consistently and meaningfully), it must change slowly in response to the time-integral of the net forcing. Sudden significant changes in the average temperature of the planet can not happen even with the process you described. See the differences in the graphs for annual and 5-year smoothed measured temperatures Figures 1 and 1.1 in the analysis at http://agwunveiled.blogspot.com
On temperature trends of interest
CET is the longest instrumental record going back to 1659. While the summers’ trend-line is almost flat, the winters show greatest trend increase since. January as the coldest month shows nearly 3C rise in the average temperatures since the early 1770s, giving a clear indication of the LIA ending and the start of current long term warming period.
http://www.vukcevic.talktalk.net/CET-LIA.gif
CET: January & February 11 year moving average
And look how steady that warming trend is.
(no I don’t mean the orange line, ignore that and look at the general trend.!)
Ups and downs, sure, but no sign at all of any CO2 forced acceleration. NONE WHATSOEVER !
Critics of LMofB’s pause graph don’t understand it. I’ve explained to a few who thought he cherry picked the data how it works. Helpful
This is not the kind of data for which fitting a trend line makes a great deal of sense. We can roughly characterise it as “noisy but steady up to some time in the 90s, noisy but steady at about 0.25 higher thereafter, clear anomalies in 1998 and 2010, time of shift not well defined.” We can also say, “this is a time series; it is highly positively autocorrelated, and this gives the appearance of cycles, but 1998 and 2010 still stand out”. The thing that hits you in the eye like a poke from a clue stick is not a trend but VARIATION. You can fit a straight line to any data set, but whether the result has any practical importance is another matter. As the “Scottish Sceptic” demonstrates with his 1/f noise page, an apparent trend may be an entire illusion, and you will fall for it if you don’t start by trying to understand the nature of the variations in the data.
The Monckton test for the length of the pause is “a sequential test for change of mean”, more precisely the stopping rule for such a test. As such, it is in the vernacular sense of the word, biased. This should give no comfort to his critics: sequential tests try to stop *early*, so he is doing the very reverse of “cherry-picking”.
Nicely presented. I like your reasoning and presentation:
” The thing that hits you in the eye like a poke from a clue stick is not a trend but VARIATION. You can fit a straight line to any data set, but whether the result has any practical importance is another matter.”
Indeed more Monckton, Don’t change the approach. He is there, not predicting, simply observing. Keep observing!
Is the Y Axis in the bottom image for Fig 2. correct? It looks like it should be K not K/Century. In Fig 3 it is just K.
Gas thermodynamics is not something I normally comment on.
This article from phys.org published yesterday may be of some interest:
Scientists experimentally demonstrate 140-year-old prediction: A gas in perpetual non-equilibrium
October 19, 2015 by Lisa Zyga report
“Now for the first time, physicists at JILA, the National Institute of Standards and Technology, and the University of Colorado at Boulder have experimentally realized a three-dimensional cloud of gas that never reaches thermal equilibrium,”
Read more at: http://phys.org/news/2015-10-scientists-experimentally-year-old-gas-perpetual.html#jCp
http://phys.org/news/2015-10-scientists-experimentally-year-old-gas-perpetual.html
Evince, in replying to my question you say,
The keyword in Monckton’s question is FAR. “How far back back in time …”. Going back from 2014 there are more than a few years when the temperature was higher than 2014. But we are not looking for annual temperatures. We are looking for a TREND in temperature. The longest zero trend we can find is 18 years and 8 months. Hope this helps 🙂
Yes, it does help. I hadn’t thought of it like that. Thanks a lot.
MCT.
Some debate around Monckton. We all now that the IPCC and alarmists cut the curve at the peak of 98 El Ninjo and user this all the way until 2013, with no updates. These days the do not show temperaturer curves in their propaganda.
I do not consider that enough attention is being made of the fact that there are two 9not one0 pauses in the RSS data.
In a theory which requires that whenever there is a rise in CO2 there must always be a corresponding increase in temperature (because of the increased forcing caused by the increased level of CO2 in the atmosphere), a period when there is no corresponding rise in temperature potentially contradicts and invalidates the theory.
Of course, Earth’s climate is complex, it is a dynamic system never in equilibrium with a number of lags such that there is much variation in temperatures on a short timescale which can mask the effect/signal of rising CO2. So there is obviously an issue as to how long must a lack of warming go on for, or how long must a period of cooling go on for before it invalidates the CO2 warming theorem. Santer initially suggested that a period of 15 years would be problematic, later he revised that to 17 years.
But in the RSS record there are two periods of about 17 years duration where there is no statistically significant warming trend. the first runs from 1980 (the start of the data set) through to 1996 (ie., up to the run up to the Super El Nino of 1997/8), and the second pause runs from that event (say 1999) to date.
One pause of more than 15 years duration would be potentially problematic for the basic tenet of the CO2 warming theory, but two pauses of this duration are more than twice as problematic. The chances of there being two such pauses running closely on from one another is remote.
Of course, it may be that 15 years is too short a duration to contradict the theory because of the constant out of equilibrium dynamics of the system, but that said, I do consider that sceptics should emphasise the fact that we are looking at two pauses not just one pause in the RSS data.
Whatever, the position may be, all one can say is that the signal to CO2 (if any at all) is so small that it cannot be eeked out from the noisy signal of natural variation such that it cannot be detected by our best measuring and most sophisticated equipment within the limitations of that equipment. If the limitation of that equipment and resulting error margins thereto are small, then climate sensitivity must likewise be small (if any at all). if on the other hand the limitations of that equipment and error bounds are large, the climate sensitivity to CO2 could likewise be large (although of course, it could well be non existent).
The satellite data set is extremely problematic to the CO2 warming theorem since there is zero first order correlation between CO2 levels and temperature in that data set. As I say, I consider that the first period when there was no warming (1980 to 19960 to be as problematic as the second period when there has been no warming (the infamous pause).
If you insist that the last 18yrs of the RSS record is meaningful then so is the first 18yrs.
So see this….
http://woodfortrees.org/plot/rss/from:1978/to:1997/trend/plot/rss/plot/rss/from:1997/to:2015.8/trend/plot/rss/trend
OK
So we have a mean trend-line for the whole record (purple). … the sensible option.
We have the trend (blue) for the last 18yrs.
We have the trend (red) for the first 18yrs.
Now for there to have been a true hiatus then the red line when extended forward in time should be ABOVE the blue. Correct? Or else we are still “warming” above the initial trend.
Do that.
Err, it doesn’t even cross the blue line until ~2025!
I do not intend this analysis to do anything other than to highlight the absurdity of calling the last 18yrs on the RSS record a “hiatus”.
If you wanted to argue anything by cherry-picking it out to confirm your bias then actually a warming step is more correct – that still remains above the initial long-term trend.
Clue: the big Nino of 97/98 biases things horrendously – a known satellite sensing anomaly.
Which is why UAH (which version?) as well as RSS do NOT measure surface temps meaningfully.
No one claims that the satellite data set measures surface temperature. It does not. It measures atmospheric temperature. but according to the CO2 theory, the atmosphere must warm, and it is this that causes the surface to respond by surface warming.
It is not cherry picking to analysis the data set as a whole. So the question is, what does this data set inform, when looked at as a whole.
You are correct that the 1997/8 Super El Nino sticks out like a sore thumb. It is the only significant warming to be seen in the satellite data set. The satellite data set reveals a one off warming in and around that event. Since the 1997/8 Super El Nino “horrendously” biases matters, it is interesting to ponder upon what the data set might have shown had that Super El Nino not taken place.
Your plot shows three trend lines.
First, the purple line is a straight line linear trend fit, and the data does not suggest such linear response, and I would suggest that such a line is not a reasonable interpretation of the data, and what it is informing.
Second, the red line deals with the period prior to the 1997/8 El Nino, and it is apt to look at that period since as noted at the outset the 1997/8 Super El Nino sticks out like a sore thumb. The red line shows very slight warming, but not statistically significant warming.
Third, the blue line deals with the period post the 1997/8 Super El Nino. It shows slight cooling, but not significantly significant cooling.
The data set when looked at as a whole shows initially a no statistically significant trend period lasting approximately 16 or so years. Followed by significant rapid one off warming coincident upon the 1997/8 Super El Nino. Followed by a second period of no statistically significant trend lasting approximately 16 or so years.
What is the significance of this? Well that is moot, since it is not clear whether a period of no warming lasting 5 or 10 or 15 or 20 years (or whatever) is really significant or not, but much depends upon the claimed levels of Climate Sensitivity to CO2. The higher the claimed sensitivity, the more relevant periods without warming become. Although, the significance of such periods may be moot as far as the CO2 theorem is concerned, I would suggest that it is highly relevant as far as the models are concerned, such periods are very important for testing their worth.
First, at no time prior to about 2013 was there any claim that the models projected/predicted periods of 15 years (or so) without warming. Now it is claimed that some models do project/predict this, although no detail is given, and in particular no detail as to the level of CO2 during such period; obviously the forcing is less when CO2 levels are at say 320 to 340 ppm, than it is when CO2 is at 380 to 400ppm. It is therefore important to know at what level of CO2, some models project/predict periods of 15 years (or so) without warming. Is this early in the 20th century, mid 20th century, late 20th century, or the 21st century?
Second, whilst we are told that some models project/predict periods of 15 years (or so) without warming, how many models project/predict two such periods closely following on from one another.
Svalgaard may have just confirmed all the Electric universe theories he never had. 🙂