This post made me think of this poem, The Arrow and the Song. The arrows are the forecasts, and the song is the IPCC report – Anthony
I shot an arrow into the air,
It fell to earth, I knew not where;
For, so swiftly it flew, the sight
Could not follow it in its flight.
I breathed a song into the air,
It fell to earth, I knew not where;
For who has sight so keen and strong,
That it can follow the flight of song?
– Henry Wadsworth Longfellow
Guest Post by Ira Glickstein.
The animated graphic is based on Figure 1-4 from the recently leaked IPCC AR5 draft document. This one chart is all we need to prove, without a doubt, that IPCC analysis methodology and computer models are seriously flawed. They have way over-estimated the extent of Global Warming since the IPCC first started issuing Assessment Reports in 1990, and continuing through the fourth report issued in 2007.
When actual observations over a period of up to 22 years substantially contradict predictions based on a given climate theory, that theory must be greatly modified or completely discarded.
IPCC SHOT FOUR “ARROWS” – ALL HIT WAY TOO HIGH FOR 2012
The animation shows arrows representing the central estimates of how much the IPCC officially predicted the Earth surface temperature “anomaly” would increase from 1990 to 2012. The estimates are from the First Assessment Report (FAR-1990), the Second (SAR-1996), the Third (TAR-2001), and the Fourth (AR4-2007). Each arrow is aimed at the center of its corresponding colored “whisker” at the right edge of the base figure.
The circle at the tail of each arrow indicates the Global temperature in the year the given assessment report was issued. The first head on each arrow represents the central IPCC prediction for 2012. They all mispredict warming from 1990 to 2012 by a factor of two to three. The dashed line and second arrow head represents the central IPCC predictions for 2015.
Actual Global Warming, from 1990 to 2012 (indicated by black bars in the base graphic) varies from year to year. However, net warming between 1990 and 2012 is in the range of 0.12 to 0.16˚C (indicated by the black arrow in the animation). The central predictions from the four reports (indicated by the colored arrows in the animation) range from 0.3˚C to 0.5˚C, which is about two to five times greater than actual measured net warming.
The colored bands in the base IPCC graphic indicate the 90% range of uncertainty above and below the central predictions calculated by the IPCC when they issued the assessment reports. 90% certainty means there is only one chance in ten the actual observations will fall outside the colored bands.
The IPCC has issued four reports, so, given 90% certainty for each report, there should be only one chance in 10,000 (ten times ten times ten times ten) that they got it wrong four times in a row. But they did! Please note that the colored bands, wide as they are, do not go low enough to contain the actual observations for Global Temperature reported by the IPCC for 2012.
Thus, the IPCC predictions for 2012 are high by multiples of what they thought they were predicting! Although the analysts and modelers claimed their predictions were 90% certain, it is now clear they were far from that mark with each and every prediction.
IPCC PREDICTIONS FOR 2015 – AND IRA’S
The colored bands extend to 2015 as do the central prediction arrows in the animation. The arrow heads at the ends of the dashed portion indicate IPCC central predictions for the Global temperature “anomaly” for 2015. My black arrow, from the actual 1990 Global temperature “anomaly” to the actual 2012 temperature “anomaly” also extends out to 2015, and let that be my prediction for 2015:
- IPCC FAR Prediction for 2015: 0.88˚C (1.2 to 0.56)
- IPCC SAR Prediction for 2015: 0.64˚C (0.75 to 0.52)
- IPCC TAR Prediction for 2015: 0.77˚C (0.98 to 0.55)
- IPCC AR5 Prediction for 2015: 0.79˚C (0.96 to 0.61)
- Ira Glickstein’s Central Prediction for 2015: 0.46˚C
Please note that the temperature “anomaly” for 1990 is 0.28˚C, so that amount must be subtracted from the above estimates to calculate the amount of warming predicted for the period from 1990 to 2015.
IF THEORY DIFFERS FROM OBSERVATIONS, THE THEORY IS WRONG
As Feynman famously pointed out, when actual observations over a period of time contradict predictions based on a given theory, that theory is wrong!
Global temperature observations over the more than two decades since the First IPCC Assessment Report demonstrate that the IPCC climate theory, and models based on that theory, are wrong. Therefore, they must be greatly modified or completely discarded. Looking at the scattershot “arrows” in the graphic, the IPCC has not learned much about their misguided theories and flawed models or improved them over the past two decades, so I cannot hold out much hope for the final version of their Assessment Report #5 (AR5).
Keep in mind that the final AR5 is scheduled to be issued in 2013. It is uncertain if Figure 1-4, the most honest IPCC effort of which I am aware, will survive through the final cut. We shall see.
Ira Glickstein
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Are you sure you are going to 2012 and not 2011? 2010 was a very warm year and the next one would be 2011. However in the end, the conclusion is about the same since 2012 is just a bit warmer than 2011 so far, but since the graphs move up as well, the effects almost cancel. You do not say which data set is being used, but the latest 2012 anomaly and the 2011 anomalies for 6 sets are shown below.
2012 in Perspective so far on Six Data Sets
Note the bolded numbers for each data set where the lower bolded number is the highest anomaly recorded so far in 2012 and the higher one is the all time record so far. There is no comparison.
With the UAH anomaly for November at 0.281, the average for the first eleven months of the year is (-0.134 -0.135 + 0.051 + 0.232 + 0.179 + 0.235 + 0.130 + 0.208 + 0.339 + 0.333 + 0.281)/11 = 0.156. This would rank 9th if it stayed this way. 1998 was the warmest at 0.42. The highest ever monthly anomaly was in April of 1998 when it reached 0.66. The anomaly in 2011 was 0.132.
With the GISS anomaly for November at 0.68, the average for the first eleven months of the year is (0.32 + 0.37 + 0.45 + 0.54 + 0.67 + 0.56 + 0.46 + 0.58 + 0.62 + 0.68 + 0.68)/11 = 0.54. This would rank 9th if it stayed this way. 2010 was the warmest at 0.63. The highest ever monthly anomalies were in March of 2002 and January of 2007 when it reached 0.89. The anomaly in 2011 was 0.514.
With the Hadcrut3 anomaly for October at 0.486, the average for the first ten months of the year is (0.217 + 0.193 + 0.305 + 0.481 + 0.475 + 0.477 + 0.448 + 0.512+ 0.515 + 0.486)/10 = 0.411. This would rank 9th if it stayed this way. 1998 was the warmest at 0.548. The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2011 was 0.340.
With the sea surface anomaly for October at 0.428, the average for the first ten months of the year is (0.203 + 0.230 + 0.241 + 0.292 + 0.339 + 0.351 + 0.385 + 0.440 + 0.449 + 0.428)/10 = 0.336. This would rank 9th if it stayed this way. 1998 was the warmest at 0.451. The highest ever monthly anomaly was in August of 1998 when it reached 0.555. The anomaly in 2011 was 0.273.
With the RSS anomaly for November at 0.195, the average for the first eleven months of the year is (-0.060 -0.123 + 0.071 + 0.330 + 0.231 + 0.337 + 0.290 + 0.255 + 0.383 + 0.294 + 0.195)/11 = 0.200. This would rank 11th if it stayed this way. 1998 was the warmest at 0.55. The highest ever monthly anomaly was in April of 1998 when it reached 0.857. The anomaly in 2011 was 0.147.
With the Hadcrut4 anomaly for October at 0.518, the average for the first ten months of the year is (0.288 + 0.209 + 0.339 + 0.526 + 0.531 + 0.501 + 0.469 + 0.529 + 0.516 + 0.518)/10 = 0.443. This would rank 9th if it stayed this way. 2010 was the warmest at 0.54. The highest ever monthly anomaly was in January of 2007 when it reached 0.818. The anomaly in 2011 was 0.399.
On all six of the above data sets, a record is out of reach.
[Werner Brozek: Thanks, you are correct that the base chart shows observed temperature “anomaly” only up to 2011, not 2012. I used 2012 in my annotations with the hope that, when the official AR5 is released in 2013, they will include an updated version of this Figure 1-4 with 2012 observed data. Please notice that I drew my black arrow through the higher of the two black temperature observations for 2011, which kind of allows for 2012 being a bit warmer than 2011. As you point out, “… in the end, the conclusion is about the same since 2012 is just a bit warmer than 2011 so far, but since the graphs move up as well, the effects almost cancel.” – Ira]
“IPCC SHOT FOUR “ARROWS” – ALL HIT WAY TOO HIGH FOR 2012”
Not completely accurate, the 4th arrow went so high it didn’t hit anything and is currently chasing the Voyager space probes.
Hey, You couldn’t do the same for the methane type of animation for the methane predictions could you? I think that would be even funnier. Talk about desperation in the face of real data.
Cheers
I believe they should compare the trend of “business as usual” scenario, and not that of the “center line”, let alone the lower end, with the measured temp trend. This is because things (esp. CO2 emission) have proceeded at least in a BAU mode, and actually in a faster-than-BAU mode, due to rapid industrialization of China, India etc.
But then, it is unmistakably clear that the two trends are far, far, far apart from each other.
IIRC, Lance Wallace said similarly on another thread today or yesterday.
They are about to miss even more (further?)
http://rt.com/news/russia-freeze-cold-temperature-379/
h/t to BobN who pointed me at it…
So about those land temperatures… which way they gonna go?…
By the time Hansen and friends massage the Russian and Arctic winter temperatures, 2012 will be a new record high, just ignore the minus sign again or invert the data no problem at all.
Are politicians and bureaucrats capable of remorse?
So much ado over so little, an almost unmeasurable imagined change.
It would be a good addition.
E.M.Smith says “So about those land temperatures… which way they gonna go?…”
Now that depends on who does the calculations !!
In Hansenworld, for example, freezing causes global tempertures to go upwards. !!!
William Tell says:
“I shot an arrow into the air,”
Hey wait there, I thought you used a cross-bow??
so you should say “I fired a ‘bolt’ into the air”
E.M. Smith
l don’t think it will be just Russia who will be suffering.
The jet looks to be setting up eastern Canada for some of the same treatment around the 25th-27th Dec. l think its going to be a long hard winter for many in the NH this season.
l hope Climate science will be sitting up and paying attenion to this winter, because its looking like it could be the shape of things to come.
Wars prevented: 0
Genocides prevented: 0
Climate catastrophes prevented: 0
The United Nations. Where never before have so many been paid so much to do so little. But they are determined to set a new record next year.
There’s an error in the chart. The oval labeled “2012” should read “2011,” and the heading “1990 to 2012” should read “1990 thru 2011”. The last year, shown by vertical bars or dots on the chart, is 2011, not 2012. (2012 will be somewhere between 2010 and 2011.)
It is important to understand that even if temperatures should suddenly rise and start resembling the predicted values the theory is still wrong. The models have failed. There is no allowance for going back and adjusting values after the fact. My guess is that with a dozen years of new data it is possible to hind cast a close fit but that in doing so future values are in no way worth worrying about.
I suspect the IPCC will repaint the side of the barn to add a bullseye where the arrows hit.
I sneezed a sneeze into the air.
It fell to earth, I know not where.
But cold and hard were the looks of those
In whose vicinity I snoze.
–S. Lee Crump, Boys Life, Aug. 1957
Somehow I thought that most of those predictions were actually a range of predictions, each one based on different levels of projected CO2? Am I confusing this with other projections? If not, can we remove the predictions that were based on reduced CO2 levels and only show the ones that were based on ‘business as usual’ (the closest to the actual record) emissions?
Sorry for re-posting this again but their time for continued failed
predictionsprojections has to run out sooner or later. They can’t keep missing the mark and fail to re-visit the ‘theory’. Remember that we have had 16 years on statistically insignificant warming – unless it begins to rewarms to a significant degree, then what next?—————————–
—————————–
Thanks, Ira. Or do it as follows. Determine the slope of linear regression at which we would have concluded from the data that there was warming, using significance level alpha. Plot the regression line on the figure with colored bands. The colored area below that line relative to the total colored area and divided by 0.9 estimates beta, the probability of a type II error. Both IPCC and skeptics have a right on equal error rates. If beta < = alpha, the model is falsified.
Ira–
As Tokyoboy (9 PM above) and Roger Knights (9:43) point out, picking the middle point of each set of IPCC projections is not correct. The reason is that their projections are based on scenarios (estimates of what will happen, such as “business as usual” or CO2 regulation of some sort). So the single estimate you should pick in each case is the one corresponding most closely to the associated scenario. In the case of the first Assessment Report (FAR) that estimate is the uppermost line associated with their “Business as Usual” assumption, since hardly any regulation is evident when one looks at the exponential rise in CO2. In general, probably an estimate close to the highest one in the next three reports is the one that most closely approximates what actually happened.
Picking the middle estimate as though it was the IPCC “best” estimate is actually picking an estimate based on a failed scenario. The entire graph (particularly the addition of the even larger “error bounds” in gray) was prepared by the IPCC to allow them to say their estimates were within the uncertainty bounds. But it is simply another case of hiding the decline (the decline in this case being the refusal of the observed temperature to match the projections.)
Ira has fallen into the trap set by the IPCC. Ira or someone should carry out the program outlined above, which is not quite as easy for the later reports as for FAR.
[Lance Wallace, Tokyoboy, and Roger Knights: Of course you are correct that, had I chosen the “business as usual” scenario predictions which correspond to the actual rise in CO2, my animated arrows would have had a higher slope and the separation of the IPCC from reality would have been greater. I used the central IPCC predictions (which correspond to the centers of the colored “whiskers” at the right of the chart) to avoid being accused of “cherry picking”. In other words, if the IPCC is off the mark based on my central predictions, they would have been even more off the mark had I used “business as usual”. Ira]
Ira quotes
As Feynman famously pointed out, when actual observations over a period of time contradict predictions based on a given theory, that theory is wrong!
———
Hmmm. Yes if your observations are in fact correct.
The trouble with Ira’s observation is that he has done a straight line fit with the starting point constrained to be the starting point of the aligned series. If he did a straight line fit without that constraint he would get a very different answer.
Aligning all of the series at some arbitrary time is somewhat arbitrary and is not a sensible way of comparing the various trends.
Maybe Ira needs some statistical expertise. Go and talk to McIntyre. He’ll sort you out.
[LazyTeenager: I do not claim to be any kind of statistical expert, though I do have a working knowledge of statistics from my long career as a system engineer and from my PhD dissertation. However, all the temperature “observations” are on the IPCC base chart and were done by the IPCC researchers and authors. All I did was draw some animated arrows atop the IPCC data. I started my arrows at the center of the Global temperature “anomaly” value as graphed by the IPCC. You say “If [Ira] did a straight line fit without that constraint he would get a very different answer.” I have no idea where one would start a “straight line fit” other than at the starting point of each analysis. Please be more specific about the “very different answer” you expect from a different “straight line fit”. To me, “very different answer” implies that it would show that the IPCC actually hit the mark four times (or even once :^). advTHANKSance. Ira]
Lazy Teenager:
Expound please?
Are you having a problem with a liner average starting at the date the report was put into effect?
Maybe you are seeing something here that I missed.
LazyTeenager is, in this instance, dead right. Given the data in this figure and its error bars, an unconstrained linear fit would not falsify the predictions. One has to hindcast the models to 1980 (when it was almost exactly the same temperature as it was in 1990) to do that.
However, LT (presumably skilled in statistical analysis himself, teenager and all) also knows at a glance that even an unconstrained linear fit is bogus. The “error bars” on the data points are clearly meaningless. The data points themselves are not iid samples drawn from the same process. The shaded regions are bogus — they are nothing like a statistically meaningful confidence interval. The centroids of the shaded regions are not even plotted so that one cannot even determine and compare the linear trend to the presumably nonlinear trends plotted. And if one attempted to fit a nonlinear function to the data using the bogus error bars, one might not get one that has positive curvature at the present time, presenting a real problem for the models!
What, exactly, are these models? They aren’t. They are composite predictions of many models. In fact, they are composite predictions of many runs each of many distinct models. Some of the runs of some of the contributing models no doubt came close to the data (enough to produce their lower-shaded boundaries, presuming that those boundaries aren’t freehand art drawn by someone seeking to create a pretty graphic and were actually produced by some sort of computational process — I leave it to LT to tell me if he thinks that there is the slightest chance that this figure was produced by means of performing an actual objective statistical process of any sort, as it makes precisely the error it accuses Mr. Glickstein of making by starting at the year 1990 with a constrained point). Which models were, to some extent, verified by the data? Why are they not given increased weight in the report? Which models were completely and utterly falsified by the data? Why are they not aggressively omitted and the model predictions retroactively repaired?
LT, Mr. Glickstein is, as you have observed, not a statistics god. However, a large part of statistics isn’t math, it is common sense. It is having the common sense to look at (and, if one is honest, present) the data robustly, not a cherrypicked 12 year segment on a fifteen year graph. I don’t have the energy to grab the graph, overlay it with all 33 years of UAH LTT and/or RSS, and invert the model wedgies into the past, still pegged at 1990, but then, I don’t need to. You know exactly what it would look like. It would be a complete and utter disaster — for the models. Mr. Glickstein has the common sense to see that the data and the models are not in good agreement, even in the narrow time frame plotted.
Do you?
rgb
[rgbatduke: THANKS for your conclusion that “…Glickstein is … not a statistics god. However … [he] has the common sense to see that the data and the models are not in good agreement, even in the narrow time frame plotted. Do you?” – Ira]
LazyTeenager says:
December 20, 2012 at 2:04 am
I have a sneaking suspicion that Dr. Hansen knows how to correct any observations to fit with his failed models/predictions. There, problem solved!
LazyTeenager;
The trouble with Ira’s observation is that he has done a straight line fit with the starting point constrained to be the starting point of the aligned series.
>>>>>>>>>>>>>>>>>>>>>>>>>
Starting it in the year it started at the temperature it started at is arbitrary? I tried reading what you wrote by examining random words in your comment and it turns out it makes more sense that way than just using arbitrary starting points like the beginning of sentences and following the words in sequential order. Very clever.
CET trend since 2006 to November 2012. Minimum Temperature approximately MINUS 1°C. Maximum Temperature approximately MINUS 1.25°C.
Before too long IRAs prediction as well as the IPCC projections will turn out to be far too optimistic (where optimism correlates with rising temperatures). The ocean buffer has had a slight thermal top up after the solar cycle 23 minimum but with the peak of cycle 24 currently upon us this top up will be rapidly exhausted as the solar magnetic fields and solar activity collapse on the downside of 24 and into the all but absent solar cycle 25. This winter will not be so bad and maybe next winter (relatively speaking) in the northern hemisphere but thereafter there will be a major collapse in global temperatures for several decades with harsh winters and collapsing grain harvests. Mean temperatures will fall by 2.5 degrees Celcius in the temperate latitudes and more at higher latitudes by 2021.
It is all going to be very unpleasant as we will be thoroughly unprepared because of Piltdown Mann and the Team.
That is my prediction.
Stay Cool!