Guest post by Bob Tisdale
What Do Observed Sea Surface Temperature Anomalies and Climate Models Have In Common Over The Past 17 Years?
One word answer: NOTHING!!!!
OVERVIEW
In this post, we’ll compare satellite-based sea surface temperature anomalies (Reynolds OI.v2) for the past 17 years to the multi-model ensemble mean of the climate models that were prepared for the 2007 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change. We’ve already showed how poorly the models simulate the warming rates of the global oceans on an individual ocean basis for the entire 30-year term of the Reynolds OI.v2 sea surface temperature data. Refer to the posts here and here, and more recently here. So the failings of the models come as no surprise. But this post does present something that will come as a surprise to many of you.
The choice of 17 years is based on the Santer et al (2011) paper, Separating Signal and Noise in Atmospheric Temperature Change: The Importance of Timescale. In the abstract, Santer et al (2011) conclude with:
Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.
Since sea surface temperature anomalies are not as variable as lower troposphere temperature (TLT) anomalies, we’ll assume that 17 years would also be an acceptable timescale to present sea surface temperature anomaly trends on a hemispheric, or greater, basis. This was the foundation for an earlier post that compared models and the same sea surface temperature dataset. And we’ll also divide the oceans into their individual basins to illustrate why I’ve presented, as one combined dataset, the Indian and Pacific Oceans from pole to pole.
While the failings of the models might come as no revelation, something else might—but first a note to build the suspense. Combined, the Indian and Pacific Oceans from pole to pole (90S-90N, 20E-70W) represent about 75% of the surface area of the global oceans. See Figure 1. It’s a map of the global oceans that’s been divided into two sections: the “Indian & Pacific Ocean Plus” and “Atlantic Ocean Plus” where the “Plus” is used to note that the datasets have been extended to the South and North Poles.
Figure 1
Why are we dividing the ocean into those two subsets? Here comes the surprise.
The sea surface temperature anomalies for the combined Indian and Pacific Oceans from pole to pole show basically no warming for the past 17 years. None, nada, zip. See Figure 2. The cooling of the entire Pacific Ocean is strong enough since 1995 and the Pacific is so large that we can merge its data with the still-warming Indian Ocean data and wind up showing the combined dataset has not warmed for 17 years. Again, the Indian and Pacific Oceans represent 75% of the surface of the global oceans and together they have not warmed in 17 years.
Figure 2
Also illustrated in Figure 2 is the multi-model ensemble mean for the IPCC’s climate model simulations of the sea surface temperature anomalies for that portion of the global oceans. The model data continued to climb contentedly skyward, projecting a blistering warming rate in sea surface temperatures for the “Indian and Pacific Oceans Plus” dataset of about 0.151 deg C per decade. That monumental divergence between models and observations for such a large part of the globe is a significant problem for the hypothesis of anthropogenic global warming—and for the alarmist proponents who believe in that hypothesis—a hypothesis that makes its presence known only in climate models, not in observational data. Anthropogenic Greenhouse Gases are supposed to force sea surface temperature to warm. The model mean of the climate model simulations of sea surface temperatures presented in this post show the response of the models to that forcing, yet the satellite-based sea surface temperature data for 75% of the global oceans show that they are not reacting to the anthropogenic forcing—not at all. One might think the modelers ought to reevaluate the assumptions they’ve made to divine the effects of greenhouse gases on sea surface temperatures, especially when they consider that 70% of the surface of the Earth is covered by ocean. Their assumptions just aren’t working.
FOR THOSE THINKING THE “ATLANTIC OCEAN PLUS” WILL COME TO THE RESCUE
If you’re for some reason hoping the data for the rest of the global oceans, the “Atlantic Ocean Plus” data, will make up the difference, you’re about to be disappointed. As illustrated in Figure 3, the models are showing a warming rate that’s about 50% higher than what has been observed. That’s not too good. Then when you consider the blatantly obvious model failings for the “Indian & Pacific Ocean Plus” subset, you wonder how the climate-model based anthropogenic global warming charade can continue. Yet it does.
Figure 3
A FEW PRELIMINARY NOTES FOR NEWCOMERS TO MODEL-DATA PRESENTATIONS
The Reynolds OI.v2 sea surface temperature anomaly data is available for download from the NOAA NOMADS website and from the KNMI Climate Explorer. NOAA uses the bases years of 1971-2000 for anomalies. But we’re looking at the period of January 1995 to March 2012 and that extends outside of those base years. The base years are not adjustable at the NOAA NOMADS site, but they are adjustable at the KNMI Climate Explorer. I used the data through the KNMI Climate Explorer so that I could change the base years for anomalies to 1995-2011. This helped to reduce the strong seasonal signal that appears in the data of some ocean basins. The North Pacific (0-65N, 100E-90W) sea surface temperature anomaly data from NOAA, for example, has a very strong seasonal component, as shown in Figure 4. Using the base years of 1995-2011, also illustrated, the seasonal component is drastically reduced. And as shown, the trends are basically the same, so minimizing the additional seasonal component makes no difference to the model-data comparisons in this post. (And yes, the sea surface temperature anomalies of the North Pacific have been cooling for the past 17 years.)
Figure 4
The multi-model mean sea surface temperature dataset is identified as TOS (ocean surface temperature) at the KNMI Climate Explorer and is available through its Monthly CMIP3+ scenario runs webpage. If you were to scroll up to Figure 2, you’ll note that there are major year-to-year variations in sea surface temperature anomalies that don’t appear in the multi-model mean data. Those observed major variations are caused by El Niño events (the upward spikes) and La Niña events (the downward ones). There are a few things to keep in mind about the model-mean data and the resulting curves. They represent the average of the climate model simulations at the CMIP3 archive, which was used in the IPCC’s AR4. There are a couple dozen climate models in the archive and some of the models include multiple simulations. For example, GISS presented 9 simulations (ensemble members) for its Model-ER and 5 ensemble members for its Model-EH. Some of the climate models attempted to model the El Niño-Southern Oscillation; others didn’t. The models that tried to simulate ENSO did a poor job and none of them could match the observed frequencies and magnitudes of El Niño and La Niña events. And since each model simulation has a different frequency and magnitude for their ENSO signals, they are smoothed out when the models are averaged. But that’s a good thing. That leaves a signal that is supposed to represent the forced component of the models, which is why we use the multi-model mean.
The reasons I’m presenting the multi-model mean were discussed in more detail in an earlier post Part 2 – Do Observations and Climate Models Confirm Or Contradict The Hypothesis of Anthropogenic Global Warming?, under the heading of CLARIFICATION ON THE USE OF THE MODEL MEAN. Please refer to that discussion.
MODEL-DATA COMPARISONS FOR THE INDIAN AND PACIFIC OCEANS
As shown in Figure 2, there has been no warming of the “Indian & Pacific Ocean Plus” sea surface temperature anomalies since 1995. That doesn’t mean that one of the individual ocean basins has not warmed. See Figure 5. The Indian Ocean (60S-30N, 20E-120E) sea surface temperature anomalies have warmed, except it’s at a rate that’s about 42% of what was simulated by the IPCC’s climate models. And as noted earlier, the North Pacific data shows that it has cooled. So has the South Pacific (60S-0, 120E-70W). Refer to Figures 6 and 7. Think about that for a moment. Not only has the largest ocean on this planet not warmed in agreement with the models, it’s actually cooled over the past 17 years.
Figure 5
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 6
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 7
THE OTHER OCEAN BASIN THAT’S COOLING
The Southern Ocean (90S-60S) is the ocean “basin” that surrounds Antarctica. It has cooled over the 30-year term of the Reynolds OI.v2 dataset. See the graph here from this post. Since January 1995, the rate at which it’s cooling is even stronger. The difference between the rate that it’s cooling and the rate the climate models say it should be warming is 0.14 deg C/decade.
Figure 8
LET’S NOT FORGET THE OTHER OCEAN BASINS THAT WARMED
At the other end of the planet, the Arctic Ocean (65N-90N) has warmed over the past 17 years at a rate that’s about 2.5 times faster than the model simulations. See Figure 9. Surprisingly, we often hear from climate alarmists that the Arctic is warming faster than projected by climate models, with all of the dire consequences of that warming thrown in heighten the risks they perceive. But the doomsayers are actually heralding yet another failing of the climate models. The observations are the target the models are shooting for, and in the Arctic, the models have missed the planet the target’s nailed to.
Figure 9
In the North Atlantic (0-70N, 80W-0), the observations are warming at a rate that’s about 65% of the rate simulated by the models, Figure 10. And as shown in Figure 11, in the South Atlantic (60S-0, 70W-20E) over the past 17 years, the models are doing remarkably well. There, the trend is only about 31% too high. So we’ll give the modelers a “B-” for one basin.
Figure 10
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 11
AND HOW WELL DO THE MODELS SIMULATE HEMISPHERIC AND GLOBAL SEA SURFACE TEMPERATURES?
In the Northern Hemisphere, Figure 12, according to the models, the sea surface temperatures should be warming about 3.4 times faster than has been observed for the past 17 years. The model performance in the Southern Hemisphere is even worse, Figure 13. There, the models show a warming rate that is about 8.5 times higher than the actual warming rate. In total, for the global oceans, the models have projected a warming that’s 5 times higher than the rate the oceans have actually warmed. The model trend isn’t 50% higher, not twice as high, not three times. The models are off by a factor of 5. Written another way, global sea surface temperatures have warmed at a rate over the past 17 years that’s only 20% of the rate projected by the multi-model mean of the climate models presented to the CMIP3 archive for use by the Intergovernmental Panel on Climate Change in its 4thAssessment Report published in 2007.
Figure 12
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 13
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 14
CLOSING
For more than a year, in posts here at Climate Observations and in cross posts at WattsUpWithThat, we have presented and discussed numerous ways in which the climate models show no skill at being able to simulate the warming, or lack thereof, of global surface temperatures. Keep in mind global surface temperature is the metric most commonly used to define global warming.
This post was primarily intended to show that 75% of the surface area of the global oceans, the Indian and Pacific Oceans from pole to pole, has not warmed in 17 years. This lack of warming opposes the continued rise in anthropogenic greenhouse gases—which only appear to make the sea surface temperatures warm consistently in climate models. There’s nothing alarming about the rate at which sea surface temperature anomalies have warmed. In fact, the 30 rise in sea surface temperatures can be explained by natural factors. So the only thing that should be sounding any alarms is the lack of skill shown by the climate models.
IF YOU’D LIKE TO LEARN MORE ABOUT THE FAILINGS OF THE IPCC’s CLIMATE MODELS
As illustrated and discussed in If the IPCC was Selling Manmade Global Warming as a Product, Would the FTC Stop their deceptive Ads?, the IPCC’s climate models cannot simulate the rates at which surface temperatures warmed and cooled since 1901 on a global basis, so their failings illustrated in this post are not abnormal.
Additionally, the IPCC claims that only the rise in anthropogenic greenhouse gases can explain the warming over the past 30 years. Satellite-based sea surface temperature disagrees with the IPCC’s claims. Most, if not all, of the 30-year rise in satellite-based global sea surface temperature is shown to be the result of a natural process called the El Niño-Southern Oscillation, or ENSO. This is discussed in detail in If the IPCC was Selling Manmade Global Warming as a Product, Would the FTC Stop their deceptive Ads?, which is available in pdf and Kindle editions. A copy of the introduction, table of contents, and closing in pdf form can be found here.
SOURCE
The modeled and observed sea surface temperature data presented in this post are available through the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Well, if you look at the RSS dataset, there’s been zero trend for 16 years (1997-2012). And the 17 year trend is insignificant, or if real, something mankind can live with. Seriously, Santer’s paper already shows that Catastrophic AGW is a fraud.
Oops. I just noticed the typo in the second to last sentence of the closing. It should read “30-year rise”, not “30 rise”.
In fact, the 30-year rise in sea surface temperatures can be explained by natural factors.
I’ll fix the cross post over at my blog.
Sorry.
“Yes, there is a Santer clause’. I like it.
Better watch out that he doesn’t try to “beat the crap out of you”.
James Hansen, Gavin Schmidt, & John Cook go on a duck hunt together. As they are sitting out in their rapidly warming boat on the rapidly warming lake a skein of mallards comes flapping by. In the same motion Hansen & Schmidt both fire, Hansen’s shot neatly breezing by three feet (0.9144 metres) in front of the lead duck, Schmidt’s wafting a similar distance (±0.0000002m) behind the laggardliest. John Cook leaps to his feet, nearly capsizing the boat, and shouts, “Nailed ’em dead centre!”
Finally! A breakdown of the global story by regions, showing how the “global” warming is not global but a mathematical construct of relative warming and cooling by regions.
Note how many parts are overwarmed in the models: that means that the moderate warming of the result comes from large errors in warming expectations being compensated for by large coolings elsewhere.
The failings in parts and a “success” overall should be very disheartening for those who think the science is settled and certain. For a “success” to be claimed by Hansen et al, it means that they consider their model probabilistic at a global scale, not deterministic at any scale. Which puts huge error bars on what they do, greater than they claim. It certainly puts the boots to any claim about specific weather events being tied to global warming. If your model can’t get an ocean right, it can’t account for a specific hurricane or summer of tornadoes.
How about the same analysis for the land/station data?
The combined results will show where the “success” comes from, i.e. where the errors on both sides are that nullify each other enough to give the warmists their “predicted” global results.
This is great! It shows that climate models fit the real world like badly made clothes: they fit where they touch.
Can someone turn the heat back on, the pool is getting cold. Or is this the missing heat that Dr. Trenberth frets about ?
In Computer Science, there is a universal law called “garbage in, garbage out”, or GIGO. It doesn’t matter what the computer model or software is. You don’t need to know a thing about climate science or whatever field the model is trying to represent. If the input data is fictional, then so will the output. IOW, fictional data is garbage data. So their models MUST give garbage output. The AGW proponents are trying to tell us that the computer can produce correct results with wrong data. I’m with Charles Babbage on this one.
“On two occasions I have been asked, ‘Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?’ I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.”
– Charles Babbage
Bugger! There was I waiting for the kettle to boil for a cup of tea and now you tell me I’ll have to wait even longer. It’s worse than we thought.
Never mind, here in the UK the BBC and Grauniad are concentrating on the “wettest month since time began” or something like that.
You have done another fine job here. The major problem with all this foolishness is faith. Those supporting AGW believe as strongly in it is the faithful of any religious faith believe in their god. Those opposed the reverse. Therefore AGW, yes or no, is more related to faith and politics then to reality. This leaves us atheists allied with all kinds of crazies. Politics and religion make strange bedfellows for sure. I can remember attending geoscience conferences in the late 80’s and pleading with the model obsessed to either fully calibrate or give it up. They did neither. Today it is all falling apart on a technical merit basis. Still widely accepted on an “article of faith” basis.
I suspect AGW will become the creation science of the future sadly much time and energy on both sides will be spent for little or no gain.
Since sea surface temperature anomalies are not as variable as lower troposphere temperature (TLT) anomalies, we’ll assume that 17 years would also be an acceptable timescale
————
Maybe, maybe not. Having ENSO in there with 3 year durations might make this tricky. Not all of the models handle ENSO well.
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way. Where are your papers Mr. Tisdale? Or are you just complaining in some blogs?
The Tyger
William Blake
Tyger! Tyger! burning bright
In the forests of the night,
What immortal hand or eye
Could frame thy fearful symmetry?
In what distant deeps or skies
Burnt the fire of thine eyes?
On what wings dare he aspire?
What the hand dare seize the fire?
And what shoulder, and what art,
Could twist the sinews of thy heart?
And when thy heart began to beat,
What dread hand? and what dread feet?
What the hammer? what the chain?
In what furnace was thy brain?
What the anvil? what dread grasp
Dare its deadly terrors clasp?
When the stars threw down their spears,
And watered heaven with their tears,
Did he smile his work to see?
Did he who made the Lamb make thee?
Tyger! Tyger! burning bright
In the forests of the night,
What immortal hand or eye,
Dare frame thy fearful symmetry?
Figure 3 looks to me like all the observed warming happened up to 2004. Since 2004, there doesn’t look to be any warming whatsoever.
Say Bob,
How’s your supply of salt doing; I figured you must be running low with all the open wounds to rub it in ?
A lot of nice data , and I’m glad you take the time to show it to us Bob. I would say it strengthen’s my own personal belief that any LWIR radiant energy returned from the atmosphere to the surface as a consequence of CO2 (GHG) capture, mostly results in prompt evaporation from the ocean surface, which returns that energy to the atmosphere, and does not store it in the ocean depths.
Thanks for the presentation.
George
Yes, the trends are different, but are they ~significantly~ different? I would very much like to see that question answered by anyone with statistical expertise. Otherwise, we can’t be sure that the different trends aren’t just bad luck (actually we can’t be sure, just have the probability to the contrary arbitrarily small).
[my bold]
The answers are several:
Money, scientific glamor, damage to reputations, the end of the IPCC and I hate to say it but living in denial because there is a consensus and the models must be right and observations wrong. This is it in a nutshell. When are they going to let go and move on to some other scare???
Since water expands when it warms, most of the ocean’s warmth must be in the top 10 metres or so. Currents like the gulf stream can carry water down but how can this warm water stay down?
Do the Argo people seriously think that a significant portion of the ocean’s heat lies 1 km or more below the surface?
Jim Petrie
The models are right, it’s the planet that’s wrong. Will someone please tell the planet to get on board and follow the models predictions.
Two oopses in the post.
I didn’t color code the title block of Figure 3. Here’s a copy of the corrected Figure 3:
http://bobtisdale.files.wordpress.com/2012/04/figure-3-revised.png
Sorry again.
Robbie:
At April 29, 2012 at 1:32 pm you say;
“Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way. Where are your papers Mr. Tisdale? Or are you just complaining in some blogs?”
Yes, Robbie, your post is “laughable”.
First the alarmists claimed in “peer-reviewed magazines” that 10-years of global temperature stasis could occur withgout refuting AGW. As the 10-years approached they change 10-years to 15-years, When 15-years of global temperature stasis passed then Santer said 17-years would be needed.
Tisdale’s article says;
“Since sea surface temperature anomalies are not as variable as lower troposphere temperature (TLT) anomalies, we’ll assume that 17 years would also be an acceptable timescale to present sea surface temperature anomaly trends on a hemispheric, or greater, basis.”
Do you have a problem with that assumption? You do not state any.
And Tisdale’s article provides clear data that 17-years has elapsed of stasis in sea surface temperature rise. You state no fault in this observation that he clearly obtained in “the right and scientific way” and which he has clearly presented here in “the right and scientific way”.
Also, Tisdale has published in “peer-reviewed magazines” although it is not clear what – if any – relervance that has to the above article and/or its contents..
Please return when you have something to say. Until then, please stop wasting space in this thread.
Richard
Robbie says:
April 29, 2012 at 1:32 pm
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way. Where are your papers Mr. Tisdale? Or are you just complaining in some blogs?
My, what an original contribution. If you have some valid criticism of this post, why not raise it here, and I’m sure Mr Tisdale will be glad to respond.
Quite why anyone believes that ‘peer-reviewed magazines’ represent the only ‘right and scientific way’ to discuss technical matters is a mystery to me, particularly in a field in which pal-review has so debased peer-review.
Fact: Human CO2 is tiny compared to the natural CO2. It is even tiny compared to the natural variation of the natural CO2.
Why anybody thinks that human CO2 is a significant or dominant factor in the planetary temperature is utterly baffling.
Observation: The variance of the temperature “signals” in nature are much stronger than the model.
That tells us instantly that the model results are garbage. Anyone who models dynamic systems for a living would tell you instantly, within an instant, that the model results are incorrect. If you rescale the model parameters to yield the observed variance of temperature then you will end up with warming of 100’s to 1000’s of C.
I suspect that there has been a lot of “tuning” to get the result to look acceptable. The model likely “blows up” when sensible estimates of the parameters are used. Would be nice to look over the source code and see what values were used. How viscous was the water in the model? I betcha it was like treacle.
DaveS says:
April 29, 2012 at 2:34 pm – (As he Responds to “Robbie” earlier)
Who is correct? A person who tried to write about continental drift in 1923 – when it would be rejected by every “scientific” journal in the world … but when the continents were moving despite every so-called “scientific” expert in geology and physics?
Was Copernicus wrong when he wrote about circular orbits … despite being afraid of criticism from the “scientific” consensus of globes and spheres that Ptolemy argued for, and that the worldwide scientific press supported? Was Tycho “wrong” when he proposed a combined system of geo-centric and helio-centric orbits?
Name a single time in history when the so-called “scientific consensus” of worldwide so-called scientific thought was correct.
Name a single time in history when the global “scientific societies” were correct in their predictions and assumptions.
Shouldn’t that be “Yes, Virginia, there is a Santer clause”?
timetochooseagain says:
April 29, 2012 at 1:53 pm (Edit)
Yes, the trends are different, but are they ~significantly~ different? I would very much like to see that question answered by anyone with statistical expertise. Otherwise, we can’t be sure that the different trends aren’t just bad luck (actually we can’t be sure, just have the probability to the contrary arbitrarily small).
##############
that is a question that bob won’t address. The problem is he really cant address it on a regional level. the 17 year figure is derived from variations in the GLOBAL metrics. It cant be applied to regional series. Well, you can try to apply it, but it’s really misleading and innumerate.
The 17 year figure comes from a characterization of the SNR in the global number. We already know that models are having a hard time getting regions correct. Region A is a bit too hot, Region B is a bit too cold. That is well known. Its so well known that its on the front burner of research. basically climate modelers have said : we dont get regional predictions done very well, we need to work on that. Thats in the IPCC” along comes Bob. He finds what was already known. He applies a figure derived from SNR in a global metric to the regional scale. bad analysis.
The models do a fair job at global metrics. that is, they are better than a naive forecast.
They admittedly have less skill at a regional level. Addressing that issue is a grand challenge.
This is just standard. We have a system. Its complex in space and time.
I know mathematically that I cant predict behavior of every molecule at every time. So, folks
aim at getting gross systems metrics right, KNOWING that at shorter time scales and smaller
spatial scales the answer will be less accurate. Globally, for example, you predict a 1 meter rise in sea level. and you KNOW that means some places will be more than this average and other places will be less. Ideally, you like to get improved regional skill. that may be computationally impossible. in the end place xyz may see 0 rise, and place xyz2 may see a 2 meter rise.
is a global prediction of 1 meter on average wrong? yes and no. depends what you want to use the prediction FOR.
Bottomline. The models need improvement. And don’t try to apply the SNR derived from a global metric to regional scale statistical problems. Knowing you have a problem and working to fix it, trumps misusing math and not knowing what you are doing.
Presumably this has huge implications for the supposed positive feedback via evaporation.
LazyTeenager says: “Maybe, maybe not. Having ENSO in there with 3 year durations might make this tricky. Not all of the models handle ENSO well.”
Please identify papers that claim “models handle ENSO well.” There are no models that handle ENSO well. Also, the three-year ENSO event during this time period was a La Nina that lasted from 1998 to 2001. What point are you trying to make or are you just attempting to confuse yourself?
He’s not complaining Robbie. He’s analyzing the data. You, on the other hand, are just being a troll. Why don’t you exercise your brain muscles and try to make a logical argument. People would think better of you if you could actually find something wrong with the article.
LazyTeenager says:
April 29, 2012 at 1:29 pm
”Maybe, maybe not. Having ENSO in there with 3 year durations might make this tricky. Not all of the models handle ENSO well.”
Just wondering, can you point to one(just one will do!) model that does handle ENSO?
and, failing that – can you point to a single climate model that handles anything to a reasonable degree of accuracy, say +/- 25%? and preferably from a forecast as well as hindcast perspective?
I must confess, I haven’t noticed or observed one, but then again, I do tend to brush over the models as they seem to be demonstrably inadequate within the climate science meme.
The only ‘warming signal’ of any kind in the last four decades is in an ‘adjusted’ record of surface temperatures, many collected from obviously overheated stations. Naturalists cherry-pick anecdotes of earlier springs or minor range shifts, but nothing beyond natural ecological variability. Otherwise, all they have is the so-called global average temperature,a kindergarten-level statistic with no physical significance whatsoever.
Satellite signals of atmospheric temperature or thermal IR output show NO change.
Every Warmista prediction in the 20th century has proven wildly wrong.
Yet so extensive is the climate brainwashing that even skeptics will admit when pressed
‘Well, yes there’s been warming…”
JUST SAY NO.
Since CO2 went over 350 there has been NO warming.
Robbie says:
April 29, 2012 at 1:32 pm
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion.
But still, Robbie, who you gonna’ believe? Santer’s
peer-reviewerswiddle Warming Elves or you own lying eyes?Steven Mosher says:
April 29, 2012 at 2:55 pm
Thats a bit simplistic, don’t you think, Steven?
As you are so fond of saying, ‘models’ are an essential part of our lives – but they are no good if they are not realistic or plain wrong!
Trying to model a spatially large system – i.e. a global system is largely futile without billions of data points over an adequately temporal frame. I doubt they could even model a regional area with the current data available.
I don’t have a problem with the models being ‘wrong’ or if you prefer, ‘less than accurate’ – that’s fine – but at least the provideers should state the fact openly and advise that they are not used for important policy decisions. That’s called honesty!!
In ISO 9001 – if you cannot calibrate and verify your equipment one is supposed to set it aside with a big label saying ‘DO NOT USE’ – and this remains UNTIL it’s fixed. I honestly believe climate models need to be in this category. When climate science models reach a degree of VERIFIED quality assurance, then we can start to take them more seriously – but ’til then – the ‘DO NOT USE’ sign must be prominently displayed!!
@Mosher:
“The models do a fair job at global metrics. that is, they are better than a naive forecast.”
=====================================
My naive forecast is that the globe will warm at approx. the same rate this century as it did last century. Let’s say .7C / 10 = .07C per decade. The IPCC predicts .2C per decade. Who did better then? The climate model or the naive forecast?
Possibly you can explain what you mean by “naive forecast” and why the IPCC model ensemble is better? If there is a reasonable basis for your claim, that’s fine… But you have the habit of making pronouncements Ex Cathedra here. It’s a bad habit both of Warmists and some who identify as more sceptical.
Robbie says: “Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way. Where are your papers Mr. Tisdale? Or are you just complaining in some blogs?”
I’m not complaining, Robbie. Nor did I take issue (in this post) with Santer et al’s findings. I simply prepared a blog post that illustrates the sea surface temperature anomalies of 75% of the global ocean surface have not warmed in 17 years. And I used Santer et al simply as a reference for the 17-year time span. It appears you didn’t read the post, but simply commented on your own misunderstandings about what was presented in it. By the way, the not-peer-reviewed argument is worn out and tired—and has no bearing on this post. Find something new to use.
Steven Mosher:
In your post at April 29, 2012 at 2:55 pm you say;
“The 17 year figure comes from a characterization of the SNR in the global number. We already know that models are having a hard time getting regions correct. Region A is a bit too hot, Region B is a bit too cold. That is well known. Its so well known that its on the front burner of research. basically climate modelers have said : we dont get regional predictions done very well, we need to work on that. Thats in the IPCC” along comes Bob. He finds what was already known. He applies a figure derived from SNR in a global metric to the regional scale. bad analysis. “
“The models do a fair job at global metrics. that is, they are better than a naive forecast.”
“Bottomline. The models need improvement. And don’t try to apply the SNR derived from a global metric to regional scale statistical problems. Knowing you have a problem and working to fix it, trumps misusing math and not knowing what you are doing.”
NO! The “bottomline” is that the models are fudged to emulate past global warming, they are known to NOT emulate the climate system of the real Earth and, therefore, they should be rejected.
I have repeatedly explained this on WUWT but it seems I need to repeat it again. The explanation is as follows.
None of the models – not one of them – could match the change in mean global temperature over the past century if it did not utilise a unique value of assumed cooling from aerosols. So, inputting actual values of the cooling effect (such as the determination by Penner et al.) would make every climate model provide a mismatch of the global warming it hindcasts and the observed global warming for the twentieth century.
This mismatch would occur because all the global climate models and energy balance models are known to provide indications which are based on
1.
the assumed degree of forcings resulting from human activity that produce warming
and
2.
the assumed degree of anthropogenic aerosol cooling input to each model as a ‘fiddle factor’ to obtain agreement between past average global temperature and the model’s indications of average global temperature.
More than a decade ago I published a peer-reviewed paper that showed the UK’s Hadley Centre general circulation model (GCM) could not model climate and only obtained agreement between past average global temperature and the model’s indications of average global temperature by forcing the agreement with an input of assumed anthropogenic aerosol cooling.
And my paper demonstrated that the assumption of aerosol effects being responsible for the model’s failure was incorrect.
(ref. Courtney RS An assessment of validation experiments conducted on computer models of global climate using the general circulation model of the UK’s Hadley Centre Energy & Environment, Volume 10, Number 5, pp. 491-502, September 1999).
More recently, in 2007, Kiehle published a paper that assessed 9 GCMs and two energy balance models.
(ref. Kiehl JT,Twentieth century climate model response and climate sensitivity. GRL vol.. 34, L22710, doi:10.1029/2007GL031383, 2007).
Kiehl found the same as my paper except that each model he assessed used a different aerosol ‘fix’ from every other model.
He says in his paper:
”One curious aspect of this result is that it is also well known [Houghton et al., 2001] that the same models that agree in simulating the anomaly in surface air temperature differ significantly in their predicted climate sensitivity. The cited range in climate sensitivity from a wide collection of models is usually 1.5 to 4.5 deg C for a doubling of CO2, where most global climate models used for climate change studies vary by at least a factor of two in equilibrium sensitivity.
The question is:
if climate models differ by a factor of 2 to 3 in their climate sensitivity, how can they all simulate the global temperature record with a reasonable degree of accuracy. Kerr [2007] and S. E. Schwartz et al. (Quantifying climate change–too rosy a picture?, available at http://www.nature.com/reports/climatechange, 2007)
recently pointed out the importance of understanding the answer to this question. Indeed, Kerr [2007] referred to the present work and the current paper provides the ‘‘widely circulated analysis’’ referred to by Kerr [2007]. This report investigates the most probable explanation for such an agreement. It uses published results from a wide variety of model simulations to understand this apparent paradox between model climate responses for the 20th century, but diverse climate model sensitivity.”
And, importantly, Kiehl’s paper says:
”These results explain to a large degree why models with such diverse climate sensitivities can all simulate the global anomaly in surface temperature. The magnitude of applied anthropogenic total forcing compensates for the model sensitivity.”
And the “magnitude of applied anthropogenic total forcing” is fixed in each model by the input value of aerosol forcing.
Thanks to Bill Illis, Kiehl’s Figure 2 can be seen at
http://img36.imageshack.us/img36/8167/kiehl2007figure2.png ]
Please note that the Figure is for 9 GCMs and 2 energy balance models, and its title is:
”Figure 2. Total anthropogenic forcing (Wm2) versus aerosol forcing (Wm2) from nine fully coupled climate models and two energy balance models used to simulate the 20th century.”
It shows that
(a) each model uses a different value for “Total anthropogenic forcing” that is in the range 0.80 W/m^-2 to 2.02 W/m^-2
but
(b) each model is forced to agree with the rate of past warming by using a different value for “Aerosol forcing” that is in the range -1.42 W/m^-2 to -0.60 W/m^-2.
In other words the models use values of “Total anthropogenic forcing” that differ by a factor of more than 2.5 and they are ‘adjusted’ by using values of assumed “Aerosol forcing” that differ by a factor of 2.4.
So, each of the models only gets an approximation to past global warming because this is fixed as an INPUT to the model (by choice of “aerosol forcing” value) and this approximation is NOT AN OUTPUT of the model.
And the fact that each model requires a different ‘aerosol adjustment’ proves that at most only one – and probably none – of the models emulates the climate system of the real Earth (there is only one Earth).
Richard
richardscourtney says: “Also, Tisdale has published in ‘peer-reviewed magazines’…”
It’s been about 40 years since I was published in any type of technical magazine and that was a rebuttal, not a peer-reviewed paper.
The problem that Santer was addressing in his paper is that the Forcings model/theory of climate predicts a uniform warming with increasing forcings. This is the core prediction of the theory. Santer’s 17 years is supposedly the longest period natural variability can mask the warming in the surface temperature. Although, according the Forcings theory, the warming is still occuring. Hence Trenbeth’s ‘missing heat’.
There are 3 possible conclusions.
1. The Forcings model/theory of climate is wrong.
2. Santer is wrong in his 17 years conclusion.
3. The actual forcings are wrong, and the greenhouse effect of CO2 is much smaller than claimed.
Steven Mosher says:
April 29, 2012 at 2:55 pm
The models do a fair job at global metrics. that is, they are better than a naive forecast.
They admittedly have less skill at a regional level. Addressing that issue is a grand challenge.
==================================================================
I do a fair job at darts on a global basis. My throws average out at bulls.
I admittedly have less skill at a regional level. When I throw at the triple 20, I am just as likely to hit 12,5,20,1 or 18.
Bob Tisdale:
re. your post at April 29, 2012 at 3:27 pm.
I did not intend to misrepresent you, and I sincerely and abjectly apologise for any offence my post caused to you. It was a genuine misunderstanding on my part.
Richard
Steven Mosher says: “that is a question that bob won’t address. The problem is he really cant address it on a regional level. the 17 year figure is derived from variations in the GLOBAL metrics. It cant be applied to regional series. Well, you can try to apply it, but it’s really misleading and innumerate.”
I have no need to address it. 75% of the surface area of the global oceans is not regional. That’s what this post was about, the flatness of the sea surface temperature anomalies of the “Indian and Pacific Ocean Plus” SST dataset for the past 17 years, as stated in the closing. And as I noted toward the beginning, the rest of the presentation was for information purposes. Did you read the post, Steven, or just look at the pictures?
Also, if memory serves me well, the Santer et al paper was a statistical analysis of signal-to-noise ratio of the climate models. ENSO is the greatest source of noise in the sea surface (and other surface) temperature records and we know climate models do not model ENSO well—those that try do it poorly. So the source of model noise Santer et al evaluated in their paper really has no relevance in a discussion of sea surface temperature data trends or any other global surface temperature metric, for that matter. I can remove the model data from Figure 2 above with a click of a mouse. And it will not change the fact that the sea surface temperature anomalies for 75% of the surface area of the global oceans have not warmed in 17 years.
Doug Proctor says: “Finally! A breakdown of the global story by regions, showing how the “global” warming is not global but a mathematical construct of relative warming and cooling by regions. ”
Finally, Doug? I’ve been posting regional (basin) sea surface temperature anomalies at my blog for almost 4 years.
Robbie says:
April 29, 2012 at 1:32 pm
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way.
Eh, you are the kind of person insisting an aquatic panmnesia denier can only make a valid point by publishing in a peer reviewed journal on that particular topic.
However, in cases when the majority of peers or at least the influential ones are gone astray in a branch of science, this requirement itself is laughable.
This way it is quite impossible to exclude certain methods applied in fields like Homeopathy, Ufology, Torah Code Research, Phrenology, Reflexology, Eugenics, Astrology, Psychoanalysis, Iridology, Graphology, Alchemy, Lysenkoism, Metoposcopy, Physiognomy, Creation Science or Computational cAGW Theory from the inventory of scientific endeavor, is not it? If so, we are left with nothing but a bunch of New Age crap and traditional science is finished for good.
richardscourtney: No apology was necessary. I just wanted to clear up that misunderstanding.
Regards
Steve Mosher: A postscript: Scroll up to the last model-data comparison. That’s a graph of global sea surface temperature anomalies. The trend of the model projection is 5 times higher than observed.
Jimmy Haigh says: ” “Yes, there is a Santer clause’. I like it.”
I don’t like it. A curious novice looking here for information would have no idea who “Santer” is (lucky them). Nor would he/she know what the significance of the “17 year itch” is wihout first reading the paper. The “Tisdale on” part is superfluous; the post is attributed to Bob Tisdale right below the title. Titles are vital. They are the epitome of Willis Eschenbach’s ‘elevator speech’ concept, and, unless you wish to preach only at the choir, should be designed to draw the new reader in, not make him scratch his head and wander off in confusion.
Steven Mosher says: “We already know that models are having a hard time getting regions correct. Region A is a bit too hot, Region B is a bit too cold. That is well known. Its so well known that its on the front burner of research. basically climate modelers have said : we dont get regional predictions done very well, we need to work on that.”
Yet the IPCC paints the models as being able to perform well on a regional basis. The IPCC in AR4 actually writes that the models do a good job on continental and sub-continental basis. See page 32 (of 84) of Chapter 9 or page 694 of the entire report. It’s under the heading of “9.4.2 Continental and Sub-continental Surface Temperature Change”. It reads:
“The ability of models to simulate many features of the observed temperature changes and variability at continental and sub-continental scales and the detection of anthropogenic effects on each of six continents provides stronger evidence of human infl uence on climate than was available to the TAR. A comparison between a large ensemble of 20th-century simulations of regional temperature changes made with the MMD at PCMDI (using the same simulations for which the global mean temperatures are plotted in Figure 9.5) shows that the spread of the multi-model ensembles encompasses the observed changes in regional temperature changes in almost all sub-continental regions (Figure 9.12; see also FAQ 9.2, Figure 1 and related figures in Chapter 11).”
That’s what the public has been told—those who bothered to read the report.
I generally agree with, and respect, Steven Mosher’s approach to the temperature record. His analogy comparing the various CRU and BEST datasets to a “market index” is, for me, a highly helpful analogy.
The challenge here is that knowing the overall climate — or market index — is doing one thing or another gives me (at least) no basis upon which to invest. If 75% of the companies making up the W-3000 index are all stagnant, one sixth of the remaining are making money, and 1/12th are going bust — is this a good time to re-allocate my entire portfolio and a good basis upon which to do so?
Why not simply do what Hansen calls “business as usual”? Some winners, some losers, some rising tides raising “all boats” — in one basin or another — and some tides leaving some boats stranded on the sand bar.
HE SHINES AND SMELLS LIKE ROTTEN MACKEREL IN THE MOONLIGHT. John Randolph
Steven Mosher says: “We already know that models are having a hard time getting regions correct. Region A is a bit too hot, Region B is a bit to cold. That is well known. Its so well known that its on the front burner of research. Basically climate modelers have said: we dont get regional predictions done very well, we need to work on that.”
Now this is rather interesting. A climate “scientist” publicly admitting doubt about models? The only reason any of these people will admit any type of problem is because RIGHT OUT IN PLAIN SIGHT THEIR ASSES ARE BEING HELD TO THE FRONT BURNER by real scientists.
Eugene WR Gallun
[Moderator’s Note: Eugene, I suspect you are new to this, don’t know about Mosher, and are about to get pounded. Don’t take it personally. What doesn’t kill you makes you stronger. -REP]
Also should have added that Mosher covers up the big errors by admitting small ones. The real take off the papers is that the models don’t get either the parts nor the whole right. Total fail.
Eugene WR Gallun
To REP
HaHa — I am a conservative poet who hung out in the sub-arts for many years. I know all about sticks and stones. And lies. No need to print this. Thanks for the concern.
[REP says: Eugene, poets are always anarchists… just gotta see it. Mosher is an anarchist. Just gotta see that, too. Uhhh.. not sure what you mean by “sub-arts”. -REP]
Robbie says:
April 29, 2012 at 1:32 pm
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion.
And how many people have read “Separating Signal and Noise in Atmospheric Temperature Change: The Importance of Timescale” in this particular peer-reviewed magazine [Journal of Geophysical Research (Atmospheres)] and discussed it? Maybe twenty, which is a *huge* number of letters-to-the-editor for a magazine to publish on a single article.
I guarantee you that more people have read the article online since it was linked on WUWT than did so when it came out in hard copy, and there’s been more actual discussion of it in “some blogs” than there has been in academic circles.
Teaser-titles are also bad because they don’t get correctly indexed by Google, I suspect. Boring, descriptive titles with common keywords are better. Make the teaser-title a subtitle.
Bob Tisdale says: April 29, 2012 at 3:21 pm
A hugely important point in this debate. How important is emphasised by a Skeptical Science page showing (according to Rob Painting of SS) that 93.4% of “global Warming” energy is going into the heat sink that is the oceans.
There is a lovely diagram there putting it all into perspective, showing according to SS that only 2.3% is going into the atmosphere. (if you don’t want to give them the pleasure of your traffic: Oceans 93.4%, Atmosphere 2.3, continents 2.1, glaciers and ice caps 0.9, arctic sea ice 0.8, Greenland ice sheet 0.2, Antarctic ice sheet 0.2) …. And.. I feel there is much to question here given the paucity of measuring stations in some of those regions.)
http://www.skepticalscience.com/Ocean-Heat-Content-And-The-Importance-Of-The-Deep-Ocean.html
If that ocean warming can’t be detected, or such warming detection relies on actually being able to measure a 0.09 C rise over 55 years (ref Willis articles), the planet is looking pretty safe for the immediate future.
Lazyt tenn says:
“Maybe, maybe not. Having ENSO in there with 3 year durations might make this tricky. Not all of the models handle ENSO well.”
What do you mean ‘maybe, maybe not’? Isn’t the science settled..?
http://www.skepticalscience.com/graphics/GW_Components_1024.jpg
There is a lovely diagram there putting it all into perspective, showing according to SS that only 2.3% is going into the atmosphere. (if you don’t want to give them the pleasure of your traffic: Oceans 93.4%, Atmosphere 2.3, continents 2.1, glaciers and ice caps 0.9, arctic sea ice 0.8, Greenland ice sheet 0.2, Antarctic ice sheet 0.2) …. And.. I feel there is much to question here given the paucity of measuring stations in some of those regions.)
http://www.skepticalscience.com/Ocean-Heat-Content-And-The-Importance-Of-The-Deep-Ocean.html
“Please identify papers that claim “models handle ENSO well.” There are no models that handle ENSO well.”
I don’t think there are any models that can predict when ENSO events will happen into the future (I guess you would have to initialise all the starting conditions at a very detailed level to even have a chance of this) but some of them do show realistic (ish) ENSO behaviour e.g.
http://lightning.sbs.ohio-state.edu/paper_enso_decadal_cmep.pdf
“This study evaluates the interdecadal variability of
ENSO in 21 IPCC AR4 CGCMs. 110 years of the 20C3M
simulations are analyzed using wavelet analysis. The results
show that the state-of-the-art CGCMs display a wide range
of skill in simulating the interdecadal variability of ENSO.
The 21 models can be categorized into three groups. The
first group (8 models) shows an oscillation with a constant
period shorter than the observed ENSO period, sometimes
also with a constant amplitude. The second group (5 models)
does not produce many statistically significant peaks in the
ENSO frequency band, but usually produces one or two
prominent peaks (episodes) at period longer than 6 years.
The third group (8 models) displays significant interdecadal
variability of ENSO in both amplitude and period. Therefore,
we do have a number of CGCMs that can produce the
interdecadal variability of ENSO. Among these models,
only the MPI model reproduces the observed eastward shift
of the westerly anomalies in the low-frequency regime.
[13] These results are very encouraging because detailed
analysis of the third group of models, and in-depth intercomparison
among the three different groups may help us to
understand the physical mechanism for the interdecadal
variability of ENSO.”
Bob Tisdale:
At April 29, 2012 at 4:41 pm you say;
“Yet the IPCC paints the models as being able to perform well on a regional basis. The IPCC in AR4 actually writes that the models do a good job on continental and sub-continental basis. See page 32 (of 84) of Chapter 9 or page 694 of the entire report. It’s under the heading of “9.4.2 Continental and Sub-continental Surface Temperature Change”. It reads:
“The ability of models to simulate many features of the observed temperature changes and variability at continental and sub-continental scales and the detection of anthropogenic effects on each of six continents provides stronger evidence of human infl uence on climate than was available to the TAR. A comparison between a large ensemble of 20th-century simulations of regional temperature changes made with the MMD at PCMDI (using the same simulations for which the global mean temperatures are plotted in Figure 9.5) shows that the spread of the multi-model ensembles encompasses the observed changes in regional temperature changes in almost all sub-continental regions (Figure 9.12; see also FAQ 9.2, Figure 1 and related figures in Chapter 11).”
That’s what the public has been told—those who bothered to read the report.”
YES! AND THE IPCC STATEMENT IS NOT TRUE.
This was the subject of my 1999 paper referenced in my above post at April 29, 2012 at 3:22 pm.
That paper used information provided by the Hadley Centre to assess how the Hadley Centre GCM was developed. And that development was as follows.
1.
The GCM ‘ran hot’ (i.e. it showed much more warming over the 20th century than HadCRUT indicated had occurred in reality).
2.
The modelers postulated that sulphate aerosol from industry had provided cooling which negated some GHG warming in reality.
3.
The aerosol washes out of the atmosphere within days so its cooling effect would be near industrial activity (i.e. the postulated aerosol cooling and industrial activity would have similar spatial distribution).
4.
The magnitude of actual aerosol cooling was not (and still is not) known but this did not matter because its magnitude would have to equal the degree of excess warming indicated by the GCM if the postulate were correct.
5.
Therefore, a degree of aerosol cooling was input to the GCM
(a) with magnitude of cooling which forced the model’s indication of 20th century warming to match the observed warming
and
(b) the spatial distribution of the cooling was input to the GCM to emulate the spatial distribution of industrial activity.
6.
This was a sensible test of the postulate that anthropogenic sulphate aerosol cooling was the reason why the GCM ‘ran hot’; i.e. if the postulate were correct then the addition to the GCM of the postulated aerosol cooling would provide similar spatial distribution of warming to that observed in reality.
7.
But the modified model output indicated a very different pattern of temperature changes over the 20th century than was observed; e.g. the model showed most warming where most cooling was observed, and it showed most cooling where most warming was observed.
8.
This result was inconvenient because it disproved the postulate that aerosol cooling was the cause of the model having ‘ran hot’, and nobody could think of another possible cause of the model having ‘ran hot’.
9.
This finding would have caused scientists to reject the model, but the next IPCC Report was scheduled so the Hadley Centre shouted about the match of global warming indicated by the model and observed global warming over the 20th century. And said the models show “regional variations” (they do, but incorrectly).
10.
But this match with past global temperatures was fixed as an input to the model and was NOT an output of the model.
As I pointed out in my above post (at April 29, 2012 at 3:22 pm), long after my paper about the Hadley GCM, in 2007 Kiehle (see reference in the above post) showed that all other climate models also ‘ran hot’ but by different amounts. And he showed that they each adopt the aerosol fix. But they each adopt a different amount of aerosol cooling to compensate for the different degree of ‘ran hot’ they each display. This need for a unique amount of aerosol cooling in each climate model proves that at most only one (and probably none) of the models emulates the climate system of the real Earth (there is only one Earth).
Richard
Good article Bob. The breakdown is quite enlightening.
While one could argue about the magnitude of a rate of surface warming by suggesting heat is being transfered deeper into the ocean bulk, I can’t see how anyone could suggest AGW processes are storing heat in the deep ocean at the same time as the surface is cooling.
At best you could suggest that heat stored in superficial layers during _previous_ periods is still being spread to the depths which have not yet caught up and the current surface trend is cooling due to reduced AGW.
That _reduced_ warming could still be positive on this basis but smaller than the amount being absorbed by the bulk. It could also be negative (ie cooling).
If the smaller ocean basins with less depth and thermal inertia , such as Indian Ocean, are still showing some warming that may be because they are a better indication of short term change or simply regional differences.
Together, this all suggests warming is still positive but decelerating on the inter-decadal time scale.
pouncer says:
April 29, 2012 at 5:22 pm
”Why not simply do what Hansen calls “business as usual”? Some winners, some losers, some rising tides raising “all boats” — in one basin or another — and some tides leaving some boats stranded on the sand bar.”
because to do that the climate alarmists would:
a) have to be honest – i.e. admit they don’t really know what they are talking about
b) admit their models are not performing as required and all predictions are largely useless
c) lose their gravy train funding
and possibly d) get lynched by the general public when the public realise it was a folly all along and could have been avoided by some HONESTY.
markx says:
April 29, 2012 at 10:29 pm
http://www.skepticalscience.com/graphics/GW_Components_1024.jpg
There is a lovely diagram there putting it all into perspective, showing according to SS that only 2.3% is going into the atmosphere.
===========
Sadly that site is neither scientific nor skeptical (in either sense of the word) . The internet if full of [snip . . kbmod] on all areas of life, the hard part is finding sites that are some use.
The eco-fascism of SS is not what I regard as a useful source of information.
markx: Regarding your April 29, 2012 at 9:50 pm and April 29, 2012 at 10:29 pm comments, the metric being discussed on this thread is sea surface temperature, not ocean heat content as you’ve introduced. Two different topics of discussion. But since you’ve linked Ocean Heat Content posts, let me note: We have discussed the natural factors that cause the rise in Ocean Heat Content. We’ve presented them a number of times at my blog and with the cross posts here at WUWT. These factors include ENSO:
http://bobtisdale.wordpress.com/2009/09/05/enso-dominates-nodc-ocean-heat-content-0-700-meters-data/
Shifts in sea level pressure:
http://bobtisdale.wordpress.com/2009/12/30/north-pacific-ocean-heat-content-shift-in-the-late-1980s/
And for the North Atlantic, a multidecadal signal like the AMO, in addition to Sea Level Pressure and ENSO:
http://bobtisdale.wordpress.com/2009/10/04/north-atlantic-ocean-heat-content-0-700-meters-is-governed-by-natural-variables/
BTW, I have no problem giving SkepticalScience “the pleasure of [my] traffic”. I visit once every one to two weeks just to see what papers they’re regurgitating and what erroneous spin they’re putting on them.
PeteB says: “I don’t think there are any models that can predict when ENSO events will happen into the future (I guess you would have to initialise all the starting conditions at a very detailed level to even have a chance of this) but some of them do show realistic (ish) ENSO behaviour e.g.”
Thanks for linking Lin (2007). I would put that in the category of papers that discuss the failure of all of the models. While some (8 of 24) of the models studied in the paper were able to simulate the frequency of the variations in NINO3 sea surface temperature anomalies, only one was able to reproduce another of the very basic properties of ENSO: the reversal of trade winds. But that one model has the other well-known problem of the double ITCZ.
Yeah, I know. I’m being picky. But NINO3 SST anomalies only represent the impact of ENSO on one metric in one tiny little area of the equatorial Pacific. There’s whole lot more to ENSO than variations of equatorial Pacific sea surface temperature.
Regards
Steven Mosher. I sort of agree with your criticism of the “fallacy” of applying Global trends to regional trends. BUt if the models are based on any semblance of physics, I would expect them to work well regionally. Unless the regional physics is overwhelmingly different.
IMO your critique is of the nit-picky kinds.
DEEBEE says:April 30, 2012 at 3:05 am
“Steven Mosher. I sort of agree with your criticism of the “fallacy” of applying Global trends to regional trends. BUt if the models are based on any semblance of physics, I would expect them to work well regionally. Unless the regional physics is overwhelmingly different.
IMO your critique is of the nit-picky kinds.”
No, it’s not nit-picky. Two important things:
1. Variation of measurements for regions is higher. You have to wait longer to get a statistically significant result.
2. Many physical processes are oscillatory on various scales, in space and time. Models can hope to get the nature of the oscillation right, but will always struggle with phase. This is true of any kind of physics. You can predict accurately the frequency of a flute, but not the instantaneous pressure. So with ENSO, say, a model may produce realistic oscillations, but they won’t get the timing right. Same with waves like SAM.
This has little effect on long term climate evolution.
Steve Mosher says,
“The models do a fair job at global metrics. that is, they are better than a naive forecast.”
“Bottomline. The models need improvement. And don’t try to apply the SNR derived from a global metric to regional scale statistical problems. Knowing you have a problem and working to fix it, trumps misusing math and not knowing what you are doing.”
——————————————————————————————————
Sometimes Mr Mosher comments become almost troll like. In this case they cross that line and he is clearly being a troll; ignoring the clearly put summary of the model mean being off by a factor of five on a global basis, and then claiming the author does not know what he is doing. Also in his usuall fashion Mr Mosher makes one comment, then unprofessionally runs away, rearely if ever engaging in reasoned debate.
Nick Stokes says: April 30, 2012 at 4:00 am
“No, it’s not nit-picky. Two important things:
1. Variation of measurements for regions is higher. You have to wait longer to get a statistically significant result.”
—————————————-
if the ensemble mean globally is off by a factor of five, do not expect that you will ever get the regional areas correct. As another poster commented, this does not prevent the IPCC from claiming they do regions well. The same fact applies to your other point about timing. Seventeen years of global failure for ONE earth, how is that for timing?
Love the title!
Thanks for all the reactions: Especially from Mr. Tisdale.
I will make one comment more:
“By the way, the not-peer-reviewed argument is worn out and tired—and has no bearing on this post. Find something new to use.”
That is what Mr. Tisdale said and I disagree (read below).
“I guarantee you that more people have read the article online since it was linked on WUWT than did so when it came out in hard copy, and there’s been more actual discussion of it in “some blogs” than there has been in academic circles.”
That is what Bill Tuttle said and he could be right about that (,BUT…).
When are we going to read this in a reference list of a peer-reviewed article:
– Tisdale B (2012) Tisdale on the “17 year itch” – Yes, there is a Santer clause, Wattsupwiththatt
It looks like: Never! Because this is not how science works. If the skeptical bloggers on Wattsupwiththat want to be taken seriously they should publish their rebuttals in journals and not in blogs. It amazes me that a lot of people, especially the bloggers here, simply don’t understand that.
Svensmark 2007, Xia 2012, Büntgen et al 2011, Spencer & Braswell 2007/2010/2011, Lindzen & Choi 2009/2010, Lüdecke et al 2011 etc etc. Plenty of skeptical examples in the peer-reviewed world. CO2 Science is an excellent example with many peer-reviewed article reviews and what about the immense MWP-project on CO2 Science with a lot of peer-reviewed articles there!
So Mr. Tisdale: If my “not peer-reviewed” argument would be worn out: Then why are a lot of serious scientists still publishing in peer-reviewed journals? Yes of course: They want their scientific research to be taken seriously in the scientific world.
Nick Stokes (April 30, 2012 at 4:00 am) wrote:
“Two important things:
1. Variation of measurements for regions is higher. You have to wait longer to get a statistically significant result.
2. Many physical processes are oscillatory on various scales, in space and time. Models can hope to get the nature of the oscillation right, but will always struggle with phase. This is true of any kind of physics. You can predict accurately the frequency of a flute, but not the instantaneous pressure. So with ENSO, say, a model may produce realistic oscillations, but they won’t get the timing right. Same with waves like SAM.”
What about Earth Orientation Parameters? You can’t make the same argument because of coupling via the solid Earth. Do the climate models reproduce EOP? That’s the only question that matters. For how long will this core issue be ignored?
Bob, I chuckled out loud as each big X appeared on the screen as I scrolled through your – as usual – informative graphs. I never used to read Mosher comments, but then I noticed a lot of people seem influenced by him, so I started following some of his comments. From what I’ve seen so far I conclude that he’s politically motivated rather than driven by a visceral interest in understanding nature. Here he completely misses the point that the models can’t possibly be right globally since they’re wrong and severely wrong for such large portions of the globe (there’s not enough of the globe left to paradoxically leverage the bullseye back around the fantasy-shoot target-arrow). A more important question: Can the models reproduce EOP? I want this addressed by the mainstream. Their models have no credibility WHATSOEVER in the meantime. A side-question (for the mainstream): The way you arrive at the window-dressing wiggle-pattern on your model trend-lines is meaningless & goofy, so why not just gaussian-smooth to reveal more honestly just how ‘complicated’ your thinking really is? I continue to find mainstream climate fantasy models disgusting all the way around as they convey SO LITTLE respect for nature. I admit that Bob lost me when he first started running posts on model output, as I was thinking, “why bother looking at garbage that will make us sick?” …but this post has a legitimate purpose …and the string of great laughs at Bob’s incisive marking (X) was indeed very welcome and very healthy.
Stokes and Mosher;
How do the models work? Do they not work by taking input parameters on a grid cell by grid cell basis, applying modeled forcing to them, and then determining the result? Are the grid cells not then aggregated together to arrive at regional and global predictions?
Are the models grid cells aggregated up, or global trends broken down? If the former, then your arguments are hollow. If the latter, then there is little value in breaking them down into regions since they don’t get global right in the first place.
It is amazing how you, Bob Tisdale, consistently choose not to report error bars on your trends.Why is that?
Robbie;
So Mr. Tisdale: If my “not peer-reviewed” argument would be worn out: Then why are a lot of serious scientists still publishing in peer-reviewed journals?>>>>
Academics publish in journals. Doesn’t make them right. Applied scientists file patents. Are you suggesting that the scientific achievements evident in patents are questionable if they are not accompanied by journal articles to back them up?
If you suppose that the only way to publish serious science is through the journal process, then, on behalf of Bell, Edison, Franklin, the Write Bros, Diesel, Dolby, and SO many others, I mock you with an LOL.
Robbie says:
“If the skeptical bloggers on Wattsupwiththat want to be taken seriously they should publish their rebuttals in journals and not in blogs.”
And how do they do that? Robbie does not understand how climate pal review works: the job of journals is to keep skeptical scientists [the only honest kind of scientist] out of publication. For a [true] example of a physicist trying to correct an obvious mistake in a journal publication, see here.
In the climate peer eview field, true peer review takes place on sites like WUWT, not in one-sided journals where Mann can get published in a month, errors and all, while an esteemed giant in the field like Prof Richard Lindzen must wait a year or more. Lesser known skeptical scientists are routinely rejected out of hand by biased referees running interference.
Robbie’s misunderstanding of “how science works” is based on his naive belief that climate pal review is ‘science’, when in fact it is the primary method of generating federal grants. If it was science, there would be full transparency of all data, methods, code and methodologies used. But as we see, there is no transparency. So how can experiments and hypotheses be replicated and falsified? Fourteen years after MBH98, Mann has still refused to disclose all his code, data and methods. Whatever it is, that is not science.
Robbie doesn’t understand that climate peer review is just a racket based on a monopoly. If you’re not promoting the “Team” narrative, good luck getting published. For a thoroughly researched account of the censorship of skeptical papers, read A.W. Montford’s The Hockey Stick Illusion, available on the right sidebar.
richardscourtney says:
April 30, 2012 at 12:26 am
So, in a nutshell – you’re suggesting/saying that what has actually happened is kind of what every real scientist ‘knows’ is likely to have happened, and that is that it has all been one great big fudgeball of modeling? Worse, one set of fudges have been subsequently used and abused by a following model, etc, etc.
Kev-in-Uk:
At April 30, 2012 at 8:14 am you ask me:
“So, in a nutshell – you’re suggesting/saying that what has actually happened is kind of what every real scientist ‘knows’ is likely to have happened, and that is that it has all been one great big fudgeball of modeling? Worse, one set of fudges have been subsequently used and abused by a following model, etc, etc.”
I answer:
Yes, except that I am not “suggesting” it: I am stating it and have provided evidence which proves it.
Richard
Kristoffer Haldrup says: “It is amazing how you, Bob Tisdale, consistently choose not to report error bars on your trends.Why is that?”
I look at my posts as introductions. I present simple and clean graphs for the majority of my readers (and those here at WUWT), most of whom are not technical people. Anyone who wants to carry an investigation further, by adding error bars for example, is more than welcome to take my lead and investigate the data further.
Robbie says: “So Mr. Tisdale: If my ‘not peer-reviewed’ argument would be worn out: Then why are a lot of serious scientists still publishing in peer-reviewed journals? Yes of course: They want their scientific research to be taken seriously in the scientific world.”
Robbie, you miss the blatantly obvious. This is a blog. This is not a scientific journal. I’m a blogger. I’m not a climate scientist. I have no funding source that requires me to publish or perish. If you want to start throwing a couple of hundred grand at me for funding every year that requires me to publish the results of my research, then I’ll start publishing papers.
But I am the one of very few bloggers in the world who graphs and presents sea surface temperature data. I am well known globally for my posts about the process of El Niño-Southern Oscillation. I present data, discuss it, and animate maps of it because it’s dynamic. People around the world learn from my presentations of data.
The reason your argument is old: It adds nothing to the discussion. Why didn’t you go to the source of the data I linked and determine if I was right or wrong? The data shows, when combined as one dataset, the Indian and Pacific Ocean sea surface temperature anomalies for the past 17 years haven’t warmed. That’s the primary subject of this post. Can you show that I was wrong?
Nick Stokes says: “No, it’s not nit-picky. Two important things:
1. Variation of measurements for regions is higher. You have to wait longer to get a statistically significant result.”
The variability of sea surface temperature data is significantly less than TLT data. The primary topic of this post is the flatness of the Indian and Pacific Ocean subset (90S-90N, 20E-70W), and it represents 75 % of the surface of the global oceans, 75.5% if you want to get nitpicky. The rest of the data is presented because, if I hadn’t presented it, I would have been accused of hiding something. I learned that long ago.
I keep hearing people complain about statistically significant results but no one has bothered to determine if they are for the Indian and Pacific dataset. So I take it as a lot of blown smoke.
You continued, “2. Many physical processes are oscillatory on various scales, in space and time. Models can hope to get the nature of the oscillation right, but will always struggle with phase…”
The models first have to get the processes right. And they are nowhere near being able to manage that with ENSO. Some may be getting better, but as a whole, they’re still at pathetic level. Refer to the discussion of the Lin (2007) paper upthread.
Regards
At the conference in Chicago a couple of years back, there was a presentation on the heat flow patterns in the Pacific. It demonstrated a, roughly IIRC, 18 year time lag from a cooling or warming spike into the center of the Pacific, and when that band of temperatures eventually reached Alaska.
Given that, I would expect that it will be a while before the full impact of cold is felt in the Arctic. ( One might presume a similar pattern for the Atlantic, but with different time constants due to different size and currents).
In 1998 or so we had our peak. A bit later a cold dagger of south polar water ran up the coast of Chile and out into the center of the Pacific. At the time, I noted that there was now a timer running before the Global Warming rant about heating in the Arctic and Canada would run into a coldening North Pacific.
IMHO, these graphs show that initial cold plunge in the Southern Ocean, then the “fall off a cliff” in the North Pacific about 2008, 2011. There’s also an interesting “Spike and plunge” in 1998 / 2000 that is often seen in stock charts. (It’s a natural artifact of many systems. When riding a bike, for example, to turn right, the handlebars are first deflected just a tiny bit left first, that then leans the bike and you enter a right hand turn, the handlebars are then adjusted right to balance the turn. Learning to do that counter intuitive ‘right then left’ is why so many kids fall over when learning to ride a bike… It is taught as a deliberate awareness in motorcycle classes as a 1000 lb superbike does not respond as much to body lean and the handlebars become much more important to understand…) To me that “pop and drop” is the signature event of a major reversal.
Then we get the 18 year time lag to full effect. Call it 2016. Mark your calendars…
BTW, I can only wonder if we did a little study of the Indian Ocean if we might find a longer time period for the Pacific / Southern ocean cold to make it to that ocean. Once that happens, the whole system is in dramatic cooling.
As that cold spike headed up the Chilean coast, it had to suck other water down to the Southern Ocean to replace it. That water would have come from oceans fronting on the Southern Ocean, which would then have pulled other water into those oceans. IFF that water came from the Indian Ocean and / or the South Atlantic, those oceans would have gained replacement water from warmer areas more north (or East in the case of the Indian ocean – from the mid-Pacific…)
IF that has some truth to it, one would expect the Indian and South Atlantic oceans to follow the cooling of the Pacific with some years of time lag. So I’m putting down a “Watch This Space” marker. By 2020 both of those oceans ought to be showing significant cooling trends.
That’s the point where AGW as a thesis is “deep sixed”… as it will be obvious to everyone we’re in a dramatic coldening process of multi decadal length.
This speculation would benefit from looking at an actual map of ocean currents, where they come from and where the go to.
http://www.physicalgeography.net/fundamentals/8q_1.html
Makes it look like the North Indian ocean is a bit isolated with a circulating warm current, so slow to cool. South Atlantic looks to be fed from the Southern Ocean with the North Atlantic a bit isolated (so it ought to lag, too – just NOW getting a warm spike like that seen in the Pacific and Southern back in 1998; so I’d guess about a 10 to 12 year lag).
So a ‘first blush’ look at that (simplified and maybe just surface currents) map would seem to offer some confirmation of the idea. One would also speculate that Australia and the Pacific Islands ought to show the cold turn very rapidly. Wonder if it’s been cold Down Under lately… Any tendency to cold on the West Coast would imply a cooling Indian Ocean ‘on the way’ as the Southern Ocean current has to pass by there first.
Last on the list looks to be Eastern USA / Southern Europe. (Gee, hasn’t it been cold on the West Coast of the USA and warm on the East Coast… I think maybe this thesis ‘has legs’… certainly enough for a ‘dig here!’…)
It would be interesting to plot AMO vs PDO and European / African thermometers vs West Coast USA / Australia / Chile thermometers and see if there is a decade or so ‘offset’ between peaks and valleys. (Another “dig here!”)…
Simple to check, interesting if it plays out…
Robbie says:
April 29, 2012 at 1:32 pm
Haha. Laughable! At least Santer is publishing in peer-reviewed magazines and thus contributing in the scientific discussion. As it should be done the right and scientific way….
_____________________________
Don’t make me laugh.
Scientists and peer-reviewed magazines have lost all credibility so why would Mr Tisdale want to waste his time on the bafflegab that now passes for “Science”
Scientific “trustworthiness” is at a low ebb.
Also as can be seen in many papers discussed here peer-reviewed papers are often Bafflegab because “Bafflegab Pays”
Dick Pothier wrote an article based on Armstrong’s papers.
Dr. J Scott Armstrong’s full paper: http://marketing.wharton.upenn.edu/ideas/pdf/armstrong2/bafflegab.pdf [The full paper seems to have been removed]
So much for the high esteem some place in “peer-reviewed” papers and lofty sounding bafflegab.
Hi Bob
You are still wrong.
If you will go to the last 12 years you might find that earth has actually been cooling.
get a few people good at stats and check my results
http://www.letterdash.com/henryp/global-cooling-is-here
I don’t want to scare you guys but if I take my plot of the drop in maxima to its best case scenario
(linear drop) forward to today, we could already be cooling at about 0.04 degrees C per annum.
In the worst case, if
y= 0.0454 ln(x)-0.1278 (R2=0.994) is true
we could already be cooling at a rate of ca. 0.1 degrees C or K per annum.
Adding more CO2 to the atmosphere won’t help much, I am afraid,
as only a few people will understand.
http://www.letterdash.com/HenryP/the-greenhouse-effect-and-the-principle-of-re-radiation-11-Aug-2011
Steven Mosher: Allow me to rephrase my original question, and comment on a few points:
The question I really wanted answered was more like: Is the (weighted by area naturally) average sea surface temperature trend significantly different from the average of such in models?
You essentially objected to the nature of my early question because it was not fair to the models, expecting them to get too many degrees of freedom of the system correct, am I right? Well, this is a MUCH easier target, and should we not expect models to be able to get the overall average trends correct?
Also, you hinted that you think that on average the difference won’t be a statistically significant. Well, okay, could you maybe work that out? Or somebody else? I just wanted to know.
Finally: Of course the models do better than a “naive” model (I assume this means a constant value, the time average) it would be hard not to. But that is not an interesting question. Well, maybe it is to you since I get the impression you are used to dealing with people you probably would think that the models wouldn’t do better than time average. You naturally assumed, I think, that, since I commented on this site, I must be someone who, say, doubts whether there are any real trends at all. However you are dealing with someone significantly more nuanced than that now. I just want to know, we observe trends that are not exactly equal to the “expected” trends, but just how is the difference really? If it is sufficiently large relative to the kind of differences that arise by chance, then the models probably need to be tweaked. Notice I say “tweaked” not “thrown out”. The models are approximately correct to some order: there are coefficients which require better estimation, and of course better models would be of higher order. Taylor approximations of the “true” mathematical system, more or less. What level of approximately correct is acceptable depends on the situation, of course. In fact, I would prefer that the question of how signficant the differences are be answered in P values, rather reject/fail to reject at fixed signifcance.
Gail Combs says:
April 30, 2012 at 12:58 pm
The lecture was comprised of double talk, meaningless words, false logic, contradictory statements, irrelevant humor, and meaningless references to unrelated topics.
The very essence of Post-Modernism!
Dr Fox was a PoMo.
HenryP says: “You are still wrong.”
I’m not right or wrong, HenryP. I’ve simply presented satellite-based data that shows for the coordinates of 90S-90N, 20E-70W that sea surface temperature anomalies have not warmed over the past 17 years. Are you saying the satellite data is wrong, HenryP?
You continued, “If you will go to the last 12 years you might find that earth has actually been cooling.”
That’s not the time period discussed in this post and cannot be the basis for a statement that I’m somehow wrong.
E.M.Smith: Regarding your April 30, 2012 at 12:18 pm comment, was the topic of discussion a Rossby wave after the 1982/83 El Nino that didn’t arrive until the 1990s and was shown to be impacting climate in the NW Pacific? I recall a paper about that.
Robbie: Further to my April 30, 2012 at 10:49 am reply to you, refer to the linked post that discusses how you can verify the key graph of this post:
http://bobtisdale.wordpress.com/2012/04/30/how-you-can-confirm-the-sst-anomalies-for-the-indian-and-pacific-ocean-subset-have-not-warmed-for-17-years/
Bob Tisdale says:
Are you saying the satellite data is wrong, HenryP?
Henry@Bob
why, yes, essentially.
there are two problems.
Thank heavens you have correctly figured that a turning point was arrived 17 years ago,
(2011-17=1994), see
http://www.letterdash.com/henryp/global-cooling-is-here
but since then we are still looking at extremely small changes in temps. In fact, I calculated that from 2000 we cooled by about 0.2 degrees K, in the atmosphere, on average, globally.. It probably won’t even show yet in the SST’s.
Can you give me any indication of the precision and accuracy of your instruments on board the satellites and how and at what intervals they are calibrated?
The method I used is less dependent on calibration as I looked at the average differences between measurements.
I will bet with you that my observations of surface temps, i.e. the statistical analysis of the data from the weather stations, especially the Maxima, are a better indication of what is happening now.
The plot for the further drop in Maxima, if I take it to the present time, is a bit frightening, is it not?
A tad OT but IMS gobal sea ice is in record territory for the last decade or so:
http://www.natice.noaa.gov/ims/images/ims_data.jpg
and the northern hemisphere SSTs are looking somewhat chilly:
http://weather.unisys.com/surface/sst_anom_new.gif
When the stars threw down their spears,
And watered heaven with their tears,
was meant to be a reference (by Blake) to Svensmark…
HenryP says: “Bob Tisdale says:
Are you saying the satellite data is wrong, HenryP?
Henry@Bob
why, yes, essentially.”
Well then, I suggest you take it up with NOAA and stop telling me that I’m wrong, when I’ve simply presented NOAA data. Having someone tell me I’m wrong, when I’m not, doesn’t sit well with me.
Regards
Henry@Bob Tisdale
Sorry, Bob. I do apologize. I did not mean it (“wrong”) personal. I said I doubted the data, that is telling you and me that there has been no change for the last 17 years.
First of all, if we look at this graph,
http://wattsupwiththat.files.wordpress.com/2010/04/orssengo3.png
you will note that there are peaks up (warming) and down (cooling). It more or less follows the sine curve. Therefore, from a mathematical and statistical point of view there is only a way up and a way down. Either we are cooling or we are warming. If it shows a straight line you can be sure to begin to doubt the results (calibration??) or that someone is fiddling with them, because the pattern of the weather never follows a straight line…..
Currently, my results, that were established independently from orrsengo, are showing a sharp drop in maxima, from 1994, meaning we are cooling.We see the same happening in the Orssengo graph, but for some reason(???) the cooling stopped when the IPCC came with their graph (green line).
Yet my own data seem to suggest that the cooling has not stopped.
So, I ask again, what I asked before, about the accuracy and precision of the data, if you do have some information about this. I am very interested in finding out and I am guessing you are too..
If you don’t know or don’t have any details, just say.
@Bob Tisdale:
The time delay in the Pacific to which I referred was a lag in propagation of surface water temperatures. I think it was due to the time it took for bands of water to move from the central Pacific (where they arrive from along the coast of Chile / Peru) to work their way all the way up to Alaska.
My notes from here:
https://chiefio.wordpress.com/2010/05/17/iccc-day-two/
say:
Hope that helps…
Bob: The AR4 says there will be 0.2 C temp increase per decade in GMT
and HALF OF IT (0.1 C) results from the SLOWNESS in heat release
from the OCEANS…..
…… You wrote nothing about the slowness in ocean heat release which
produces this o.1 C per decade….
I can quote the original IPCC AR4 text…..if you like. The slowness, as I
see it, would be the excess heat stored in the 1990’th being released
in the 2ooo-2010 decade…..
Your comment….?
JS
Joachim Seifert says: “Bob: The AR4 says there will be 0.2 C temp increase per decade in GMT
and HALF OF IT (0.1 C) results from the SLOWNESS in heat release
from the OCEANS…..
…… You wrote nothing about the slowness in ocean heat release which
produces this o.1 C per decade….”
No reason to discuss it. I presented the model mean of the simulations of sea surface temperature from the archive the IPCC used for AR4. The models should be what they’re basing their prediction on. Or are they making predictions without referring to the models?
E.M.Smith: Thanks for the link.
Regards
HenryP says: “I said I doubted the data, that is telling you and me that there has been no change for the last 17 years.”
There’s nothing wrong with the Reynolds OI.v2 sea surface temperatuyre dataset.
“First of all, if we look at this graph,
http://wattsupwiththat.files.wordpress.com/2010/04/orssengo3.png”
That’s irrelevant. Global Land Plus Surface Temperature data is not being discussed. Why’d you link it?
Henry P: Sorry. I put some quote marks on the second sentence in the above comment but didn’t attribute it. Let me correct that and add to it.
Henry P says: “First of all, if we look at this graph,
http://wattsupwiththat.files.wordpress.com/2010/04/orssengo3.png”
That’s irrelevant. Global Land Plus Surface Temperature data is not being discussed. It’s also a curve-fitting exercise that does not represent the actual variability of the HADCRUT dataset. Why’d you link it?