Guest essay by Sheldon Walker
I have developed a new type of graph, which I call a global warming contour map. It displays the warming rate, for every possible trend in an interval. The warming rate is color coded, and can be plotted against any 2 of the variables “start date”, “end date”, and “trend length”.
The global warming contour map makes investigating global warming easy, accurate, and fun. A bright eight year old could use the graph to obtain accurate warming rate information, for any interval that they were interested in.
Detecting a slowdown or speedup, is as easy as spotting a cloud in the sky. The reason for this is simple. Warming rates are translated into different colors, based on the size of the warming rate (e.g. light green means that the warming rate is between 1.4 and 1.8 degC/century). If the warming rate changes, then the new warming rate will be a different color to the previous one. So we end up with a shape on the contour map, which has a different color to the previous color. This is very easy to detect.
Have a look at the following contour map, which covers the interval from 1880 to 2015. A contour map contains a lot of information, so don’t be put off by the amount of detail. Once you learn the color coding rules, the contour map will be a lot easier to understand. The explanation of what the different colors mean, can be found after the contour map. I will explain the main features on this contour map, after you have read about the color coding rules.
Because there is so much detail in a contour map, it is best to look at a large image. I think that I am limited to a small image in this article, so I will put a link after the small image, which will take you to a large image that I put on the Photobucket website. I hope that this works, it is the first time that I have tried this. If you can’t get to the large image, then you could try magnifying the small image using your browser. I know that Chrome has a Zoom control, and I assume that other browsers will have something similar.
For a large image of this contour map, from the Photobucket website, click this link:
The legend for global warming contour maps is here:
Now that you have looked at a contour map, and looked at the legend, we can discuss what is on the map.
Along the bottom of the contour map, there is a line of what appear to be small red flames. These are not real flames, but they do represent a source of heat. These are the natural warming events, like El Nino and the Blob. If you count them, then you will find that there are about 46 of them between 1880 and 2015. Some of them merge together, so an exact count is difficult. That is about one natural warming event every 3 years, and I believe that El Nino’s occur about once every 2 to 5 years, so the number seems about right.
There are often small black regions between the natural warming events. I use black to show cooling, so these small black regions are either the cooling phase of an El Nino, or possibly a La Nina.
Now look at the big black area near the middle of the graph, As I said before, I use black to show cooling, so this appears to be a large cooling event. When I first found this, I thought that it might be an error in the graph. I checked it carefully, and found that it was an approximately 40 year cooling trend, that started about 1935, and finished in about 1975. As soon as I saw the year 1975, I knew what this was. I remembered that in 1976 there was a scare about a possible ice age happening. Time magazine ran 2 cover stories, one about “The coming Ice Age”, and the other about “How to survive the coming Ice Age”. I don’t believe that Time magazine would invent these stories with no evidence. It would make sense if some scientist noticed the 40 year cooling trend, and said something to somebody.
I am going to finish this article here, but I have lots more to tell you about these contour maps.
In my next article I will talk about things that the contour maps show, which are consistent with anthropogenic global warming.
I will also talk about things that the contour maps show, which might not be consistent with anthropogenic global warming.
One of these topics will be a favourite of mine, the recent slowdown. If you look on the global warming contour map that covers from 1880 to 2015, you can easily see the slowdown. As I said earlier, detecting a slowdown or speedup is as easy as spotting a cloud in the sky. Try to find it yourself. Because the map covers from 1880 to 2015, it is not large, but it is clearly visible. In my next article I will show a contour map going from 1975 to 2015, and the slowdown will appear larger because of the smaller interval that the map covers.
The upper limit for black should be -0.2 to match the pattern for all the other intervals.
Well spotted. This is just an error in the legend. The warming rate range for black in the contour map, is anything less than or equal to -0.2
Not bad. But I think the X-Axis as the Trend End Date, Y-Axis as Trend Length.
That way, at an X, you go up to see how long a trend you can make for any slope of the trend line.
It is also that, we are at 2016 and we can see back with data (up the Y axis) as far back as 1880.
In 1880, you couldn’t see forward to 2016.
Also, it is not clear to me what data set you used. No doubt I makes a difference
I think it would be revealing to make a companion map that shows the P90Low Trend estimate (the lower bound of the 80% confidence in slope).
Using Start Date for the X -Axis is good for seeing when things start.
Using End Date for the X-Axis is good for seeing when things end.
Having 2 graphs, one with Start Date and one with End Date, gives you the best of both graphs.
You can always calculate the Start or End Date from the other, by subtracting or adding the Trend Length.
I use end date on the x-axis. The reason is that it puts the apex on the right, and the right edge is the present time, which people are most interested in. New data appears month by month on that axis. Here present time is the hypotenuse, which is not so natural.
Sheldon, here’s another argument why you should use End Date of the trend as the X-Axis. It is a well established fact the graphs have a greater chance of being accepted if they rise from left to right.
It is a joke. But it is also a fact.
Please note: the link to the big image of the global warming contour map has changed.
It is now hosted on Google, and displays a better image.
The link is:
https://photos.google.com/share/AF1QipPWmFNAwhvajgpMfPzgX4au-Pvbq-K1V50WREn-bIceq-UyEd0lih_FjdJhEgmYmg/photo/AF1QipPvFrHQX6mwSvhI5clr4lPed1NXzmoQzOqZNbVo?key=X3RZTVNuS2d5ZU85VjRNMXRGQkZFQVVVbklyZ1dR
Thank you. Photobucket is the most user-unfriendly image site there is.
A whole new chapter for a book on Numerical Origami.
I assume that Prediction is still not one of its features.
G
‘… Light green = normal AGW …’.
================================
This relates to a previous thread ‘Cook etc.’ and comments by Brandon Gates.
Gates quotes the IPCC summary: “More than half of the observed increase in global mean surface temperature (GMST) from 1951 to 2010 is very likely due to the observed anthropogenic increase in greenhouse gas (GHG) concentrations” and assumes that conjecture defines AGW.
It’s begging the question — no-one, not even the Pope, knows what percentage of the warming since 1950 can be attributed to humans, if any.
Great way to present lots of data Sheldon, very clear.
Put’s the ‘Slowdown’ (0.2-0.6ºC/cen warming) in perspective for the little blip it is.
Hi Mat,
You said that it puts the Slowdown in perspective, “for the little blip it is”.
And you mentioned the warming rate 0.2 to 0.6 degC/century, which is dark blue.
Did you ever consider that light blue is also a Slowdown (a medium Slowdown). That makes it bigger.
Did you also consider that dark green is also a Slowdown (a weak Slowdown), This makes it even bigger.
As a Slowdown of any strength (weak, medium, or strong), the Slowdown has lasted for 20 years.
Most climate scientists will tell you that a Slowdown of 17 years means that AGW theory needs to be revised. Guess what, we have reached 20 years.
Does that put things into perspective for you?
The link says Sorry, the person moved or deleted the image.
Read the post a little above your post. It gives a new link for the big image.
Whoops, sorry, should have refreshed
Nice graphic, my congratulations. I greatly enjoy innovative graphical display of numbers.
I didn’t understand the units, however. How much warming is 100% of AGW (presumably Anthropogenic Global Warming) when it is at home? And how on earth have you determined that it is anthropogenic?
w.
‘… Light green = normal AGW …’.
How much warming is 100% of AGW (presumably Anthropogenic Global Warming) when it is at home? And how on earth have you determined that it is anthropogenic?
================================
Precisely.
This comment has been stuck in moderation since around 10 pm:
This relates to a previous thread ‘Cook etc.’ and comments by Brandon Gates.
Gates quotes the IPCC summary: “More than half of the observed increase in global mean surface temperature (GMST) from 1951 to 2010 is very likely due to the observed anthropogenic increase in greenhouse gas (GHG) concentrations” and assumes that conjecture defines AGW.
It’s begging the question — no-one, not even the Pope, knows what percentage of the warming since 1950 can be attributed to humans, if any.
Chris Hanley,
Exactly. Until someone is able to quantify AGW with a verifiable measurement, it remains a conjecture. (One I happen to agree with.) Without measurements there will be endless arguments about the sensitivity number.
Many skeptics of the ‘dangerous AGW’ scare think that since AGW can’t be measured, it must be a very small fraction of global warming from all forcings. The IPCC, of course, disagrees; if they agreed, they would be out of a job.
Sheldon Walker March 13, 2016 at 12:40 pm
Thanks, Sheldon. It appears you are claiming that the IPCC can tell “when AGW is happening” and when it is not.
Surely you must know that if the IPCC could actually do that, the climate debate would be over … they have no more idea than anyone else whether the amount of anthropogenic warming over that period was 0%, 50%, or 100%.
More to the point, I don’t understand why you are using some bogus calculation of what the IPCC says AGW was doing for your color scale. What are you trying to establish? Build a color scale you like and use it, there’s no need to involve the IPCC.
This is an example of what I call my “Occams Razor of Science Writing”, which states:
Don’t multiply subjects unnecessarily.
Each new subject that I include in an essay is just another place for people to find a toehold to attack my ideas. And since people often follow the incorrect rule of “Falsus in uno, falsus in omnibus”, if they can find a flaw in some minor idea that I have unnecessarily introduced, they’ll often claim the whole post is invalidated. That’s why I try to focus each post on a single idea, and ruthlessly cut out extraneous stuff no matter how interesting it might be.
Thanks again for your most interesting article and graphics,
w.
Have you attempted a 3D projection with the warming rate (z-axis) as a contour map? Say rendered in a standard isometric projection? I think it would be spatially striking. I am contemplating having a go if you’d like?
Though beautiful, color tones do not imply any particular sequence or direction to me. Rather the sequence is implied to me by the the shape of the color bands. That is the basis of my question regarding z-axis 3D projection. I am not one of the 10% of males who are color blind. The color wheel, common to artists, is not obvious to me. (ie there is no such color on the visible spectrum as purple)
I agree and suggest to make a version using just a regular white-to-black grey-scale.
like this:
http://www.originlab.com/doc%5Cen/Tutorial/images/Color_Map_Surface_Graph/Tutorial_3DSurfaceMap_05.png
Sheldon,
What I see is a lot more of light green (normal AGW) below the 50-year trend line post 1950 than between the 50-year period from 1900-1949. Bit more yellow (weak speedup) as well.
The oceans are no more a source of heat than CO2 is. They are, however, far better at sequestering it than the atmosphere or land masses.
There is a not yet quantified amount of thermal convection from the earth’s crust to the oceans. Add to that vents plate movement and all manner of sea floor activity, largely unknown, also adds to ocean heat content. None of this is even quantified.
We know a lot less than our “confidence” portrays
We can’t quantify it, but we know it’s a lot.
In other news, fluids heated from the bottom … convect from the bottom.
We can’t quantify it, but we know it’s a lot.
That’s the same argument that supports the ‘dangerous AGW’ scare.
Brandon, I can only surmise you have not lived next to the ocean or other large body of water, and have failed to remember what you read from a 5th grade Science book. Surely you know the basics of land cooling versus ocean cooling at night, regardless of the amount of CO2 in the air. The source of heat felt far into the evening comes from the ocean, not CO2.
Pamela Gray,
I repeat: They are, however, far better at sequestering it than the atmosphere or land masses.
And you’re correct, living next to large bodies of water does tend to reinforce remembered 5th grade science coursework.
What’s it look like using raw, unadjusted data?
here is the data from. Pretty graph useless if data is GISS
It looks colourful but the meaning of the calculated linear trends is subject to some very important limitations.
I use here a slight rearrangement of variables, with start date on the y-axis, end on the x-axis, so then hypotenuse and lines parallel to it represent fixed trend durations. It’s basically the same pixels, with linear re-mapping. Using the start and end year has one plus. You can see on the above plot that there are two types of bar pattern. Many are diagonal SE-NW. This type represents the rises and falls in trend that result going back in time from a dip or peak. For example, there is a reddish streak going back from 1940 on the x-axis. This shows the positive trends leading up to the 1940 peak. And the “pause” shows as a NW trending purple patch on the right. Those are the lower trends leading up to the cool periods of 2008 and 2011-2.
There are also vertical stripes, for example the black one also above about 1940 on the x-axis. These are the reduced trends you get when you start at the 1940 peak going forward. Using start/end on the axes, all these stripes are parallel to the axes – ie orthogonal. That makes their intersections easier to see. And it is those intersections that give rise to pause-type effects – trends that you can draw with a peak at one end and a dip at the other.
There is a place for each choice from start, end and trend duration on the axes. But I think this is quite an important plus for start/end.
I like the interactive bit on the right hand side (ignoring the colourful bit to the left), but the ‘Table of links to sources’ appear to be inoperative.
Vuk,
The table of sources is at the bottom of the page. I think most links (except NOAA) work. I haven’t maintained it with high priority; my primary table is here.
The colorful bit also links (click) to the right side plot.
Thanks, saved a copy.
Thanks Nick, this quick way to compare datasets is useful.
One thing that is missing is the uncorrected ICOADS SST data. Despite the WWII glitch ( which NOAA seems to leave in as well ) it would be good be able to visualise the original data in the same way to assess what the effects of the many adjustments are.
Greg,
There is HADSST3, which is an alternative to NOAA. But yes, I could certainly add ICOADS. Do you have a link for the monthly data?
Nick – Instead of merely rearranging the color coding and structure… how about telling us what this graph is saying to you regarding your view of CAGW. GK
G. Karst:
I believe Nick’s set of graphs has existed for a few years now. Nick didn’t program it in response to Sheldon’s.
ATheoK – thanks – but I would appreciate an answer that reveals more of a warmist view of the data. I do try to understand the warmist’s scientific approach to data, when not inside a echo chamber. GK
G. Karst
“a warmist view of the data”
These MTA plots could be applied to any time series – they are just a way of illustrating trend. Nothing specially “warmist”.
I wrote an article here last month with interpretation of a diagram in terms of “pause” etc. I’ll show the plot below, with annotations, which I originally showed at WUWT here. It’s the same data Sheldon is showing.
http://www.moyhu.org.s3.amazonaws.com/2016/2/noaa_tags.png
Nick Stokes,
Actually, I like your chart better than Sheldon’s. Not to diss Sheldon, but you’ve been doing this for a lot longer. Sheldon’s chart just needs a few more iterations.
It’s interesting to click on the various data sets. Anyone who accepts NOAA or GISS, for example, will see that they downplay cooling, and goose the warming trends.
Satellite data remains the best, most accurate measurements. Any data base that uses surface station records is bound to have discrepancies from being so far out of tolerance.
Agree and suggest to make a version using just a regular white-to-black grey-scale. 🙂
Sheldon: The uncertainty in the warming rate is extremely high for short periods, making the central estimate for the warming trend (and therefore differences in color) almost meaningless. Therefore, you need to also present information about the confidence interval for the warming trend. Perhaps you can gradually reduce the color saturation as the confidence interval widens. Perhaps fully-saturated light green could symbolize a central estimate for warming of 1.4-1.8 degC/century (“normal AGW”) and a 90% confidence interval fully contained by 1.0-2.2 degC/century. A less-saturated light green could symbolize a central estimate for warming of 1.4-1.8 degC/century and a 90% confidence interval fully contained by 0.6-2.6 degC/century. A barely detectable light green could symbolize a central estimate for warming of 1.4-1.8 degC (“normal AGW”) and a 90% confidence interval reaching outside 0.6-2.6 degC. Or perhaps you should leave any trend not known more precisely that +/-1 degC/century blank or white.
A suggestion to pack even more info into a similar graph would be to keep the colour balance according to the warming rate, but to change the colour intensity to capture whether the trend is significantly away from zero. In other words, if two data point give a massive high trend, it would be very pale scarlet….
R.
Yes, and Nick’s graph isn’t as close to ‘Roy G Biv’ as Sheldon’s. The color progression in Sheldon’s chart is more visually pleasing.
(Does anyone remember ‘Bad boys rape our young girls but Violet gives willingly’?)
Nope: however I look at it, I can’t get my head around what you call ‘normal AGW’. I thought ‘AGW’ was an outcome of the chart (if it could be derived), not an input.
Wait. When did Nick become helpful? I’ve been gone a while.
..Hibernating for the winter ??
Otters Love winter!
Sheldon~ Not to quibble (as he proceeds to do so) but there was quite a bit more coverage of the global cooling scare than just Time Magazine. Quite a few MSM outlets gave it coverage, and the reporting included the fact that government organizations such as the CIA, and scientific groups such as the NCDC, also chimed in very loudly.
Further information on the global cooling scare http://kajm.deviantart.com/journal/Remember-that-1970s-Global-Cooling-Scare-564933645
http://wermenh.com/climate/scinews.jpg
https://www.sciencenews.org/sites/default/files/8983
Thanks Ric! Will add that.
Your intention is to present the data in a new format, and I think it works. But labelling the ‘normal’ as AGW does not make sense. Moreover, ‘AGW’ is a description of the data that is a conclusion.
Why not use ‘neutral’ instead of ‘normal ?
Why not use ‘neutral’ instead of ‘normal AGW’?
Please use http://wattsupwiththat.com/test/ for testing and instructions on what you can do with comments.
Here is what I see. The bright red blips are likely related to the 4.7 year and 9-11 year signals one sees in frequency analysis of the global temperature data, and are “natural” in origin (ENSO primarily, with possible solar cycle effects). AGW implies that the amplitude of the red blips should be rising over time, but that I do not see. The warming of the 1930’s (including orange and yellow) exceeds, in amplitude, the warming of the late 20th Century. The greater area of green in the late 20th Century could well be spurious, the result of all the data manipulation that has taken place with land-sea data sets.
Basil
I think change in background ‘average’ colour is another expression of what I call accelerated cosine warming.
https://climategrog.wordpress.com/warming-cosine/
Basically you get less trend over longer periods even when there is ZERO true long term change.
If you mask off the upper part of the triangle plot above 40y length , there is a broader green segment than the earlier green segment. This is probably partly the bias introduced by combinging land and sea data ( which we are still guessing is what this graph shows ). There may well also be some Karlisation depending upon what dataset this is.
“Anthropogenic Global Warming” (AGW) is by definition abnormal, and may not even exist to any measurable extent. So what the heck is “Normal AGW”?
/Mr Lynn
Shhhhhh…don’t spoil it now..will you…:)
AGW suddenly has become normal, you see, climate can be normal now, thanks and only to AGW…….
normal AGW = normal steady climate…what is not to like about it…..it is in light green too,,,,,,,,don’t let this little thing of definition spoil it please………:)
cheers
Thank you!
The colour sequences for orange contradict the others. Dark orange is the warmest, but in all other cases, dark is the coldest.
Roy G Biv, dissed again… ☹
I would like to see a connection between W/m^2 and C/century. IPCC has four scenarios: RCP 2.6, 4.5, 6.0, and 8.5 W/m^2. Of course these CO2 RFs are lost in the magnitudes, fluxes, and uncertainties of the atmospheric heat balance.
Sheldon, one glaring error unless I have missed it, is what dataset you are using.
I assume it is a one of those physically nonsensical land + sea “averages”. https://judithcurry.com/2016/02/10/are-land-sea-temperature-averages-meaningful/
It may be more relevant to plot land and sea data separately
As others have noted, I don’t know what you think “norm AGW” , it is also undefined.
I suspect had you defined it you would be getting shot out of the water. Probably best to remove but if it is there it MUST at least be defined. As you also MUST say what data you are plotting, without which it is meaningless.
Interesting, but this is NOT a new type of chart. It has been used before, long before, now.
http://www.crestmontresearch.com/docs/Stock-Matrix-Index5-11×17.pdf
At last we have got a “normal AGW” at last and in light green stockings……:)
Seems like AGW has changed it’s mind now and has becomed well behaved and normal instead of being troublesome and a Run-away dangerous bugger…..and wearing too seems to have changed in light green from the deep green. 🙂
Way to go………..guys…..
cheers
It’s important to call it Normal AGW. That allows a future delineation into Postnormal AGW. Before it was Normal AGW it should have been called Prenormal AGW. The last vestiges of Normal AGW should be called Prepostnormal AGW.
This degree of stratification will allow Subjective Bayesian analysis, when temperatures begin to decrease, to suggest that AGW causes both warming and cooling.
One thing I think may be interesting in this visual representation is that black plume coming out of 1945 does look anomalous.
All the other traits of the graph of whatever polarity or magnitude seem to lean about 45 deg to the left.
This one trait is nearly straight up. Now this may be because of a cooling which was a climate oddity but it should also be noted that this is the biggest adjustment made to the SST data.
Again I have to guess because you have not labelled what data you are calling “MTA”, you have not even said what that acronym stands for !
So I’m guessing this is a land+sea “average” and that is contains hadSST3 or some data that is apeing the Hadley adjustments to the actual SST data.
I showed in my first article at Judith’s Climate Etc. that Hadley adjustments were making changes to the frequency content of the data which resulted in self-consistent spectral content in ICOADS data
https://judithcurry.com/2012/03/15/on-the-adjustments-to-the-hadsst3-data-set-2/
becoming non self-consistent after Hadley “corrections”:
I think the black plume in your new representation may another expression of this inconsistency introduced by the data processing.
It would be interesting to see you plot done with the original ICOADS SST
Sorry, those links do not seem to working reliably
ICOADS
HadSST3
The point of those two spectral graohs is that the “uncorrected” data shows similar spectral content when comparing the full data set to the spectrum of half the data.
Once it is “corrected” the self-consistent spectral structure is lost.
Greg,
“One thing I think may be interesting in this visual representation is that black plume coming out of 1945 does look anomalous.
All the other traits of the graph of whatever polarity or magnitude seem to lean about 45 deg to the left.”
That is what I was trying to explain here. A peak, like 1940 (and a dip) leaves two trails. One is in the period before. Here the trend is positive, and the plume leans, because the start years are getting earlier as the period lengthens (45°). The other is the trends starting at the peak. These are negative (black) and go vertically, because as the period gets longer, the start is still the same.
As I said there, it’s easier to see if you use the start and end dates as axes. Here is RSS. The short trends are now on the hypotenuse. If you go to 1998 there, you see a reddish streak down, and bluish across (East). The blue is what generates pauses following the peak. The brown is for zero trend, and you can see how it almost reaches the right edge, which is now. And if you look along that bar, and under 2009, you see how it gets reinforced by the effects of that dip, shown as a vertical bluish. That can boost a “pause”, or even revive it. It’s the pattern people are looking for when they say the pause may come back in 2018 (if there is a big dip).
http://www.moyhu.org.s3.amazonaws.com/data/tripics/Xx0_18.png
Nick,
The patterns I’m seeing here, both in your version, and Sheldon’s, remind me very much of wavelet transforms done on the temperate data. Do you think your approach, or Sheldon’s, tells us anything more than we can get using wavelet analysis? If so, could you explain?
Basil
blcjr,
You can regard trend calculation as a sort of (differentiating) filter, and so these plots show the effect of filtering on multiple scales, just as wavelets do. They don’t give the same frequency information, but they do give a multiscale view of trend, which is much discussed.
Again the total reliance of the single step change of the 1998 El Nino to create trends.
The mathematical idiocy of putting linear trends across step changes.
Nick, the canonical ref for ICOADS is http://icoads.noaa.gov/ , though it may be easier to get the monthly data via KNMI.
I don’t follow your explanation of the 1945 black plume.
If this is NOAA SST then it seems to retain the WWII glitch and the black plume anomalous form may just reflect that this is an anomaly in the data ( ie an anomaly that is a-normal , not a climatologist’s anomaly which is perfectly normal ).
It would be good to see what hadSST3 looks like with Sheldon’s method.
Thanks, Greg,
I need the canonical, so I can download automatically. That’s good.
On the black plume, if you look at the gridline running N from 1940, it’s the locus of trends beginning 1940. Since that is a peak year, it’s downhill after that. So the trends along that line are black.
If you go NW from (1940,0), that is the line of trends that end in 1940. They are uphill to the peak, and so are positive.
The MTA method doesn’t say anything about the reasons for peaks and plumes. It just reflects the arithmetic.
“I don’t believe that Time magazine would invent these stories with no evidence. It would make sense if some scientist noticed the 40 year cooling trend, and said something to somebody”
OK, but that was Time Magazine 40 years ago. Read their climate change fluff……
What part of the graph show where everywhere is warming two to three times faster than everywhere else?
I agree with the way to present many trends, but the chart is composition not new and it has been used before not only by myself (see recent paper open acces Int.Jr. Climatology about hiatus of temperature in Spanish mainland)
Poor communication.
Complex difficult to understand chart.
Whose side are you on?
If smoking illegal substances, you are excused — it’s a colorful chart better than most modern “art”.
Good charts are self explanatory in several seconds.
I can’t imagine a chart harder to understand than yours.
Your “grade” is F.
Skeptics need good science and good communications.
This is an excellent example of poor communications.
What a waste of time.
If you know a lot about a subject, you should be able to teach others with simple language and easy to understand charts.
Judging by the grossly excessive complexity of your chart, you must not know much about climate history.
Back to the drawing board.
KISS = keep it simple stupid
PS: Is there a secret decoder ring to help me figure out your chart?
PSS: I’m normally favorably biased toward people named Sheldon, so have tried to be kind to you here!
Why to offend anybody to support the own version of the science? extrange argument
I suspect that I know, but what data set are you using?
Sorry, I left out which dataset this is.
The data comes from the monthly NOAA combined land and ocean temperature series.
This is the dataset that Karl et al adjusted, and claimed that there was no evidence of a slowdown. I find strong evidence of a slowdown.
====================
When I say “normal AGW”, I do NOT mean that AGW is normal. It means “the normal warming rate when AGW is happening”.
I used the interval from 1975 to 1999 to define “normal AGW”. There was consistent warming over this interval, and the IPCC claims that most warming in this interval was caused by AGW.
A linear regression on NOAA data for 1975 to 1999, gives a warming rate of about +1.7 degC/century. So I used the warming rate range +1.4 to +1.8 degC (light green) to represent the usual warming rate when AGW is happening.
====================
If anybody is wondering, MTA stands for Multi Trend Analysis.
====================
I will try to reply to more comments when I have time.
In the comment above this one, I used the wrong units for the warming rate range. It should read:
“So I used the warming rate range +1.4 to +1.8 degC/century (light green) to represent the usual warming rate when AGW is happening.”
What IPCC “claims” is neither here nor there. I don’t see why you adopt their biased interpretation to present the data. They also say “majority” ( ie >=50% ) they do not say ALL , so I don’t know where you go from IPCC to calling ALL warming over that period “normal AGW”.
You have grossly misused the term and I again suggest you remove that column: it is more BS than even the IPCC come out with.
You really need it at the top of the article, what data you are using. Please get our host to add that, not leave it to the reader to dig into comments to find out.
If you can modify the title of you google graph, I suggest removing undefined “MTA” and inserting NOAA v4 or whatever it is.
Sheldon, you should look at the followign discussion of how meaningful land+sea “average temp” is:
https://judithcurry.com/2016/02/10/are-land-sea-temperature-averages-meaningful/
If you want to know about land environment where we live, plot land SAT.
If you want to know about how ocean live forms are affected use SST.
If you want an idea of how changes in radiative “forcing” are affecting the global heat content, you could use SST as your calorimeter. DONT use land + sea which has not physical meaning.
Land + sea “average temp” will be biased by changes in land temp which change about twice as quick as SST. This itself means it will be biased to N. hemisphere which has more land. It also pollutes the whole land+sea average with the UHI bias in land data.
would you like to post the same thing done using hadSST3 , for example. That would be interesting to compare with your main graph.
Your graph indicates:
1) the Earth has warmed substantially since 1880
2) one can cherry-pick statistical noise here and there (through carefully-selected endpoints) that run counter to the very clear long-term trend.
Interesting – I love visualization of data because its so much easier to find the patterns.
First point – The visualization is only as good as the data. I don’t trust the data to be nearly as accurate as people claim it is – that said, the graph can still reveal inte5resting stuff. What data is this anyway? I don’t see what data set is being used… I’ll assume the data is global, not U.S.
The small repeating red blobs are fascinating – its something I knew from experience but nice to see it appear like this. I had no idea it would look so regular.
I always like to check out WWI and WWII in any representation of temperature data – if there was a chance to see man-made deltas on the background of natural variance, these are the places to look. I was surprised that WWI doesn’t seem to show up as a cooling period. Then I looked at WWII – and again no cooling. Really? If smoke and aerosols cool the Earth, how the heck does it not show up in world wars? Makes me suspicious something is wrong. Then I got to thinking about where most of this data is coming from… Could be the cooling effects were more local, and if you are in the middle of an invasion you probably are not reporting temperature. Cold be there is a data bias towards areas that are peaceful so smoke induced cooling might not be seen… Still, suspicious.
I can make out the Dust Bowl era. That seems reasonable.
Somewhere after 1940 it appears that warming sped up (the green mass). That would actually support that CO2 is causing some warming – a position I am comfortable with. (its not that it causes warming I disagree on, only on how much and if its bad for the Earth as a whole).
So, no problem with your graph. I still do not trust any temperature data to be at all accurate. Heat Island Effect is both stronger and more variable than most “scientists” seem to understand. That is where they should be spending time and energy measuring if they want to improve the data.
dcpetterson says:
1) the Earth has warmed substantially since 1880
After cooling substantially during the Little Ice Age. Where does AGW fit in?
And:
…the very clear long-term trend.
Which clearly shows natural global warming. Where does AGW fit in?
CO2 began to ramp up significantly in the 1950’s. But there is little correlation between CO2 and global T. What correlation there is shows that the causative agent is T, which CO2 follows.
So all in all, the alarmist crowd is showing nothing that cannot be fully explained by natural climate variability. In other words, you’ve got nothin’ but bluster.
db,
“After cooling substantially during the Little Ice Age. Where does AGW fit in?”
The Earth is far warmer now that it was before the Little Ice Age. We are even far above the Medieval Warm Period. Even given your odd ideas, AGW is the difference between the time prior to LIA and now. AGW is obvious.
“CO2 began to ramp up significantly in the 1950’s. But there is little correlation between CO2 and global T.”
They are, in fact, almost perfectly correlated. Though the RSS record only shows 37 years and 2 months of No Pause At All (because the RSS record is only 37 years and 2 months long), the GISTemp record shows No Pause At All since the 1950s (over 720 months), when you claim “CO2 began to ramp up significantly”.
If you disagree with Chris Monckton’s methods, you’ll have to take it up with him.
(Yeah, I know, you believe in a Vast Global Conspiracy of Climate Scientists who are Faking Global Temperatures so they can earn sub-middle-class wages and none of them ever has broken their silence, even though doing so would given them a lifetime gig on FOX “News”. Well, anyone who ignores data will believe anything.)
Your insistence that global temperature has been rising due to some “natural climate variability” falls flat given 1) you have no mechanism that explains your alleged “natural” cycles, and 2) global temperatures are now far above anything humans have experienced in at least 20,000 years, which ,means we’ve gone beyond any limits of recorded “natural variability”.
db, I’ll also add that if you look at Sheldon Walker’s graph and start at 1950, the portion of the graph to the right of that (trends starting after 1950) all show shades of greens and orange and red — i.e., warming, on the order of 1.5 degrees per century and above — except for very short-term noise clustered at the bottom of the chart. This is particularly pronounced after 1960.
By your measure — “CO2 began to ramp up significantly in the 1950’s” — you can see that global warming also “began to ramp up significantly in the 1950’s”. The correlation is pretty much perfect.
If you disagree, take it up with Sheldon Walker.
I’m sure heat maps have their use, but I don’t care for them, especially on this subject. It’s global!
I don’t get it. Sorry.
All those short trend “red flames” and “yellow plumes” at the bottom of Sheldon Walker’s graph make it look like a prairie fire at night.
Nice!
😉
You “rainbow” chart is the least useful chart I have ever seen in 19 years of reading several climate change articles and studies every week.
I doubt if 1 in 100 ordinary people selected at random would understand the chart, much less learn anything from it.
It takes quite a few paragraphs in the article just to explain the chart.
Not only does the chart ignore 99.999% of Earth’s climate history, but it also:
(1) Over-analyzes 0.001% of the 4.5 billion years,
(2) Treats very rough average temperature data as if they were 100% accurate,
(3) Makes it almost impossible for a typical person to see recent average temperature trends at a glance:
— downtrend from roughly 1940 to 1975,
—- uptrend from 1975 to 2000, and
——- flat trend from 2000 to 2015.
These three different trends all happened while atmospheric CO2 increased every year.
.
That means the correlation of temperature and CO2 has been negative, positive, and near zero in just the latest 75 year period.
The general public needs to know CO2 is not the ‘climate controller’.
Your chart is mathematical masturbation of low quality data.
And that’s assuming average temperature is a good statistic, despite the fact it hides regional and local climate changes by using a broad average.
It’s not like anyone actually lives in the “average temperature”, nor is average temperature the cause of local weather conditions.
YOU WROTE:
“I used the interval from 1975 to 1999 to define “normal AGW”.
There was consistent warming over this interval,
and the IPCC claims that most warming in this interval was caused by AGW.”
MY COMMENT:
I’m sorry Sheldon, but both sentences are foolish.
This website exists because many people have collected contradictory evidence showing the IPCC is a political organization trying to “prove” a pre-existing conclusion (HUMANS ARE DESTROYING THE PLANET), and not interested in unbiased climate science.
We skeptics don’t take IPCC claims as facts.
In fact, we assume IPCC claims are likely to be biased and misleading … and their current predictions are most likely wrong, as they have been for over two decades so far.
Perhaps you don’t realize the 1975 to 1999 period you seem to love is the ONLY period in the past 4.5 billion years that manmade CO2 and average temperature had a positive correlation.
Do you jump to the conclusion that a very short-term correlation PROVES AGW exists and is significant ?
If so, then why?
You completely ignore contradictory data, just before, and just after, that short period from 1975 to 1999:
— You ignore the negative CO2-temperature correlation from 1940 to 1975, and
— You ignore the near-zero CO2-temperature correlation from 2000 to 2015.
Then you claim: “There was consistent warming over this (1975 to 1999) interval”
Not true: There was no consistent warming, and that fact is obscured by using a global average:
—- The upper half of the Northern Hemisphere warmed a lot more than the southern half of the Southern Hemisphere, per weather satellite data
And those data contradict one “signature” of greenhouse warming — both poles should warm the most — well, the South Pole has not warmed at all since the 1970s.
And don’t get me started on the missing “hot spot” — yet another greenhouse warming “signature” that is missing.
No skeptic should accept AGW without proof (at the very least, proof that the change in average temperature since 1850 was abnormal for our planet — it was not abnormal).
But you accept AGW.
No skeptic would try to “prove” AGW exists by believing the IPCC, as if they had any credibility, and data mining the 1975 to 1999 years.
Good scientists do not data mine and ignore contradictory data.
But you do.
You ignore contradictory data from 1940 to 1975, and from 2000 to 2015.
You also ignore warming in the 1910 to 1940 period that was similar to 1975 to 1999 warming, but is not blamed on AGW.
The 1920 to 1940 warming is evidence that 1975 to 1999 warming is not abnormal, and resembles a prior period of warming from natural causes IN THE SAME CENTURY !
Sheldon “Normal AGW” Walker, your article has done nothing to refute the coming climate change catastrophe fantasy.
Please try to do that in your next article.
And your misleading, unproven phrase: “normal AGW”, should never be used again.