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?
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“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
@ur momisugly 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.
@ur momisugly 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.
@ur momisugly 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.
—————–
@ur momisugly 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.
@ur momisugly 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…