My article this week at Forbes.com digs into some fundamental flaws of climate models
When I looked at historic temperature and CO2 levels, it was impossible for me to see how they could be in any way consistent with the high climate sensitivities that were coming out of the IPCC models. Even if all past warming were attributed to CO2 (a heroic acertion in and of itself) the temperature increases we have seen in the past imply a climate sensitivity closer to 1 rather than 3 or 5 or even 10 (I show this analysis in more depth in this video).
My skepticism was increased when several skeptics pointed out a problem that should have been obvious. The ten or twelve IPCC climate models all had very different climate sensitivities — how, if they have different climate sensitivities, do they all nearly exactly model past temperatures? If each embodies a correct model of the climate, and each has a different climate sensitivity, only one (at most) should replicate observed data. But they all do. It is like someone saying she has ten clocks all showing a different time but asserting that all are correct (or worse, as the IPCC does, claiming that the average must be the right time).
The answer to this paradox came in a 2007 study by climate modeler Jeffrey Kiehl. To understand his findings, we need to understand a bit of background on aerosols. Aerosols are man-made pollutants, mainly combustion products, that are thought to have the effect of cooling the Earth’s climate.
What Kiehl demonstrated was that these aerosols are likely the answer to my old question about how models with high sensitivities are able to accurately model historic temperatures. When simulating history, scientists add aerosols to their high-sensitivity models in sufficient quantities to cool them to match historic temperatures. Then, since such aerosols are much easier to eliminate as combustion products than is CO2, they assume these aerosols go away in the future, allowing their models to produce enormous amounts of future warming.
Specifically, when he looked at the climate models used by the IPCC, Kiehl found they all used very different assumptions for aerosol cooling and, most significantly, he found that each of these varying assumptions were exactly what was required to combine with that model’s unique sensitivity assumptions to reproduce historical temperatures. In my terminology, aerosol cooling was the plug variable.
Ted:
The power of models is not to test a hypothesis that X will do Y to system Z. Their power is in ((((((generating)))))) the hypothesis that X will do Y to system Z,
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A computer program is a set of rules based on either a theory or hypothesis. In AGW’s case it would be a theory.
In my mind people generate the hypothesis or theory.
So explain to me how a computer generates a hypothesis.
Wally:
Also, further observation of system is no replacement for experimentation. Future observation will not validate a model, nor test any hypothesis. In some sciences that is the best you can do, but it does not change the fact that you can not actually test the hypothesis.
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Future observation can and does validate models. All of life is a model trying to explain the outside world to ourselves. We make up all kinds of tests to see what’s true or not.
http://www.skepticalscience.com/climate-models-intermediate.htm
Hansen validates his model from back in 1988.
NetDr:
The scenario B is independent of either A or C. Given the rules of the model what is the predicted temperature projections of the observations.
Scenario B comes the closest. Keep in mind that these scenarios are guesses of future co2 emissions.
teora:
All models start out wrong. They are not perfect. Within the bounds of uncertainty, can they give us useful information. Trends of warming can give us what the future will contain. Again given the links in my other posts Hansen has done just that with 80’s level of understanding the science of climate. What do you think the models can do today?
PaulD:
[18] It is important to note that in spite of the threefold
uncertainty in aerosol forcing, all of the models do predict a
warming of the climate system over the later part of the 20th
century. The warming is in essence bounded by the fact that
climate sensitivity is a positive quantity and the total
forcings used by modelers are also positive. This implies
that the total forcing of the 20th century cannot be negative,
i.e. the negative aerosol forcing cannot be larger than the
positive greenhouse forcing, which bounds the magnitude
of the total aerosol forcing.
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In the conclusion this helps the modelers decide how to make the rules of the program. I haven’t taken the time, but its starting to look like that Warren is skewing the information to make his own point. That point is getting weaker. If the temperature is rising on the earth then it constricts the negative values of the different aerosols.
PaulD:
[19] It could also be argued that these results do not
invalidate the application of climate models to projecting
future climate for, at least, two reasons. First, within the
range of uncertainty in aerosol forcing models have been
benchmarked against the 20th century as a way of establishing
a reasonable initial state for future predictions. The
analogy would be to weather forecasting where models
assimilate information to constrain the present state for
improved prediction purposes. Climate models are forced
within a range of uncertainty and yield a reasonable present
state, which improves the models predictive capabilities.
Second, many of the emission scenarios for the next 50 to
100 years indicate a substantial increase in greenhouse
gases with associated large increase in greenhouse forcing.
Given that the lifetime of these gases is orders of magnitude
larger than that of aerosols, future anthropogenic forcing is
dominated by greenhouse gases. Thus, the relative uncertainty
in aerosol forcing may be less important for projecting
future climate change.
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Warren Meyer is the professional denier (liar). Thanks for pushing me Paul on reading this article. Aerosols have a short lifetime and the important GHG’s have a very long lifetime in the atmosphere. It’s co2 that is the main boogeyman.
PaulD:
If the model’s could make accurate forecasts, that would be a reason to think that they might be accurate. The comparisons of forecasts v. empirical data, however, undermines the case for the models.
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Would you like to support your case? How does forecasts v emperical data fall apart? Any examples?
Grateful:
p.s. I am trying to do my bit by openly disagreeing whenever a CAGW sentiment is expressed in front of me. I stick to firm short statements such as “there are other valid, competing theories of climate change” and “there are many highly credentialled scientists who do not believe that CAGW is significant.” At first I was amazed at the virulence (including assault) of the responses. But now I am used to it and have not been silenced. That’s price of freedom of speech, I suppose.
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The past contains evidence that we are exceeding the past in rapidly carbonizing our atmosphere.
http://www.skepticalscience.com/co2-rising-ten-times-faster-than-petm-extinction.html
But now that we humans have embarked on a global warming experiment, there are some useful lessons from the past:
The rapid pulse of PETM CO2 followed by rapid warming (figure 2e) indicates high climate sensitivity.
CO2 does indeed appear to have a long atmospheric lifetime.
Ocean acidification (of the deep sea at least) can occur even under conditions of CO2 release much slower than today.
Present acidification of the ocean is far greater than the PETM, and is probably unprecedented in the last 65 million years.
Whether the plants and animals upon which humans depend can survive the present rapidly changing environment remains to be seen.
http://scienceandpublicpolicy.org/images/stories/papers/reprint/albedo_and_olr.pdf
9. CONCLUSIONS
Observations of upper tropospheric water vapor over the last 3-4 decades from the NCEP/NCAR reanalysis data and ISCCP data show that upper tropospheric water vapor appears to undergo a small decrease while IR or outgoing longwave radiation (OLR) undergo a small increase. This is opposite to what has been expected from the GCMs. These models have erroneously exaggerated the magnitude of the water vapor
18
feedback. They have also neglected the strong enhancement of albedo which occurs over the rain and cloud elements.
We should disregard what the GCMs have been saying about global warming from CO2 doubling. We should not set mandatory quotas on replacement of fossil fuel energy with renewable energy (wind, solar, etc.) at this time. The honest and objective science to support such serious energy utilization changes is just not there.
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As soon as I see SPPI I know that it is a denier funded source. This attempts to look like science but with a fossil fuel message. Science papers do not have a political message to them. They are about science.
The top of the atmosphere is going through an imbalance of less radiation leaving than is coming in. That is why the earth is increasing in temperature.
@Renewable:
“All models start out wrong. They are not perfect. Within the bounds of uncertainty, can they give us useful information. Trends of warming can give us what the future will contain. Again given the links in my other posts Hansen has done just that with 80′s level of understanding the science of climate. What do you think the models can do today?”
Switching topics at its best. You were flaunting a graph of past temperatures overlaid with model output as proof that that model can be believed to predict the future. What happened to that idea? Do you admit you were wrong or not?
I have created computer models professionally, but not climate models. There are many similarities. Adjusting an unknown like aerosols to make things “fit” is common but misleading, if we really understood the process only one estimate of sensitivity is correct, the others are simply wrong.
Hindcasting is a good first step, but only a first step, and impresses the technically illiterate far more than it should. Forecasting is the proof of the pudding and so far the models fail miserably by predicting 2 or more times too much warming.
The fact that multiple estimates of sensitivity all hind-cast correctly should give even the technically illiterate reason to doubt them
You wrote:
******Would you like to support your case? How does forecasts v emperical data fall apart? Any examples? ******
You must be blind. I have shown above that the AR4 models and Hansen’s 1988 model have predicted more than 2 times too much warming. [bait and switch fools only fools]
You wrote:
********Warren Meyer is the professional denier (liar). Thanks for pushing me Paul on reading this article. Aerosols have a short lifetime and the important GHG’s have a very long lifetime in the atmosphere. It’s co2 that is the main boogeyman.*******
You missed the point as usual.
The short term aerosols are necessary for the alarmists to explain the cooling from 1940 through 1978. The negative PDO during this time explains it very well and no aerosols are needed.
It is funny how undocumented imaginary aerosols supposedly mimic the documented PDO cycle.
Teora:
Switching topics at its best. You were flaunting a graph of past temperatures overlaid with model output as proof that that model can be believed to predict the future. What happened to that idea? Do you admit you were wrong or not?
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Where are you looking to take this conversation? What models do you think are bogus? Any examples? Are there models that are doing a good job?
Netdr:
Forecasting is the proof of the pudding and so far the models fail miserably by predicting 2 or more times too much warming.
The fact that multiple estimates of sensitivity all hind-cast correctly should give even the technically illiterate reason to doubt them.
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What is wrong with running multiple forecasts? Its the forecast that you put weight behind that counts.
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Forecasting is the proof of the pudding and so far the models fail miserably by predicting 2 or more times too much warming.
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As the scientists view warming, they are accurate. You and the scientists disagree how much warming there has been.
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You missed the point as usual.
The short term aerosols are necessary for the alarmists to explain the cooling from 1940 through 1978. The negative PDO during this time explains it very well and no aerosols are needed.
It is funny how undocumented imaginary aerosols supposedly mimic the documented PDO cycle.
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As the scientists view warming, they are correct. As you view warming they are wrong.
PDO is an oscillation. If the ocean is the source of warming, then the ocean should be cooling from releasing its energy to the atmosphere. The worlds oceans are increasing in temperature also. This is verified with measurements of the oceans.
@Renewable:
“Where are you looking to take this conversation? What models do you think are bogus? Any examples? Are there models that are doing a good job?”
I am looking to take this conversation to a resolution of the following quandary: either the fact that the output of a model closely resembles past events means that model can predict the future, or it doesn’t. Your opinion on this? After we resolve this, we can move further, but no earlier.
@Renewable:
To remind you, you wrote the following:
“Figure 1: Comparison of climate results with observations. (a) represents simulations done with only natural forcings: solar variation and volcanic activity. (b) represents simulations done with anthropogenic forcings: greenhouse gases and sulphate aerosols. (c) was done with both natural and anthropogenic forcings (IPCC).”
Please elaborate on what point you were trying to make here, with the graph of past events demonstrating model output vs actual data.
New technology does indeed cost more and the cost will come down in time. That is not the issue. Wind and solar backup needs are based on basic math and engineering. Example: hydraulic storage (or compressed air) needs to generate the power , pump it to storage, and recover the energy through a turbine. Three times as much electrical equipment is needed: generate, pump, and recover. Also, over 25% of the power will be lost due to inefficiencies. Since the actual/nameplate is only 30%, the installed wind capacity must be 3.3 times the power ultimately used. The pumps must be correspondingly bigger. Only the final turbines match the ultimate load. Obviously, huge dams and reservoirs are needed as well. Clearly, the cost of all this will be several times the current cost of energy.
Thermal standby is questionable. Only open cycle gas turbines can be started up quickly.. Their efficiency is lower than a base load power plant. Thus, the 70% of the time it is running uses up most if not all the energy saved during the 30%. This all aside from the huge capital cost.
Bottom line: We are right back to the basic problem: Wind and solar are only viable if there are government subsidies and FREE standby power. Thus we are limited to a small percentage of the power load. PLEASE don’t tell me the Spaniards are doing it so it must be right. Their government is pulling the plug on subsidies as they have already run up a $40 billion debt to build wind and solar plants.
All this is fundamental and cannot be altered by “improveents with time”. Some optimization might be achieved by tying together large areas so as to average out the wind effect. If it were possible to do this so that the whole system ran at 30% rather than vary from 0% to 100% with an average of 30%, some savings in the pumping part of the system might be achieved. This is another reason why COMPLETE engineering studies are needed, not just pulling out one piee of the system. Note that in the UK, the wind died down last winter and zero power was produced for a period of time.
On a positive note, wind and solar might be OK on a small scale at remote locations. As an example, the Mexican government installed small solar panels and batteries in Boquillas, Mex. A local proudly showed me his unit. This supplied power to one small lightbulb.
If there ever was a good demonstration of the need for sound and complete engineering analysis, the “renewable energy” area is it. Instead, we have mindless zealotry and “the Spaniards are doing it”.
Salts for thermal salts are cheap. No doubt. I guess huge, insulated stainless steel tanks to but it in is free? The solar plant described was 19.9 MW. 28000 metric tons of salt required. How much salt for many tens of thousands of MW? I guess we put it in little tiny free stainless steel tanks. Good thinking!!
Renewable
As usual you didn’t provide an example of a reasonably correct climate model or defend either of the ones I cited.
You also miss the point about the PDO cycle. There is a long slow warming of about 1/2 ° C per century which is not a problem. Superimposed on this there is a 60 year sine wave which crested in about 1998. This sine wave made it APPEAR to have warmed faster than it actually did. The apparent acceleration in warming from 1978 to 1998 is wholly due to excess El Nino’s over La Ninas.
CO2 is not needed to explain it.
The 1/2 ° C warming is probably from coming out of the little ice age plus feedbacks, but, for the sake of argument, if it is because of CO2 so what ? It isn’t a problem for mankind so it is a moot point of interest only to scientists.
Don’t bother to tell me that some climate scientists disagree with me. That is a poor argument.
At least one peer reviewed study agrees with what I posted.
http://www.reportingclimatescience.com/news-stories/article/global-warming-temperature-rise-may-be-lower-than-predicted.html
Renewable
.
The clowns at skepticalscience can’t seem to understand that the 60 year PDO cycle causes no overall warming but it can and does cause APPARENT warming over a 20 – 30 year period like from 1978 to 1998.
.
It causes sane men to believe stupid things like that warming is accelerating in the last 1/2 of the 20’th century. So far in the 21 ‘st century there is no sign of warming though because the sine wave is cresting and turning downward like all well behaved sine waves..
Renewable guy quotes the kheil article.
Renewable: Almost all climate science articles now published that contain information that is damaging to CAGW also contain a little disclaimer at the end claiming that the findings are not so bad after all. The Kheil article is devastating for those who claim that the ability of models to hindcast is evidence of their reliability. That was Warren’s point in the main post. He doesn’t misrepresent the article at all. The “little disclaimer” (i.e. “it could be argued”)at the end of the article does not change the findings of the article on this point. Moreover, the “little disclaimer” that you quote is simply not very convincing. All the IPCC climate models demonstrate an ability to hindcast, yet they have vastly different climate sensitivities. So how does one choose which model to believe?
You can use a Fourier series to fit any data. By fitting past data perfectly, it doesn’t tell us anything about future data. Only a rigorous model, based on first principles and with no “fudge factors” can be a true and accurate future-predicting model.
The climate models all are full of fudge factors for aerosols, clouds, solar radiation, etc. None of these are well understood, let alone based on first principles. Thus they are empirical models with some sound science thrown in. Nobody with modeling experience would argue with a straight face that they can predict the future with such models. I could tell war stories all day of empirical engineering models that led to financial disasters.
How anyone can argue that we should destroy our industrial civilization based on future projections calculated by these models is a mystery to me.
teora:
@Renewable:
To remind you, you wrote the following:
“Figure 1: Comparison of climate results with observations. (a) represents simulations done with only natural forcings: solar variation and volcanic activity. (b) represents simulations done with anthropogenic forcings: greenhouse gases and sulphate aerosols. (c) was done with both natural and anthropogenic forcings (IPCC).”
Please elaborate on what point you were trying to make here, with the graph of past events demonstrating model output vs actual data.
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TO show viability of models. To reproduce the surface temperature. If you remove certain aspects of the data the model output diverges from the observations in a wider manner.
netdr:
Renewable
.
The clowns at skepticalscience can’t seem to understand that the 60 year PDO cycle causes no overall warming but it can and does cause APPARENT warming over a 20 – 30 year period like from 1978 to 1998.
.
It causes sane men to believe stupid things like that warming is accelerating in the last 1/2 of the 20′th century. So far in the 21 ‘st century there is no sign of warming though because the sine wave is cresting and turning downward like all well behaved sine waves..
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http://www.skepticalscience.com/Is-Pacific-Decadal-Oscillation-the-Smoking-Gun.html
Figure 3: Monthly PDO index (blue) versus monthly global land ocean temperature anomanly (red). Smoothed data and trend lines are added.
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In the graph in figure 3 the pdo does seem to influence the rate of temperature increase.
[19] It could also be argued that these results do not
invalidate the application of climate models to projecting
future climate for, at least, two reasons. First, within the
range of uncertainty in aerosol forcing models have been
benchmarked against the 20th century as a way of establishing
a reasonable initial state for future predictions. The
analogy would be to weather forecasting where models
assimilate information to constrain the present state for
improved prediction purposes. Climate models are forced
within a range of uncertainty and yield a reasonable present
state, which improves the models predictive capabilities.
Second, many of the emission scenarios for the next 50 to
100 years indicate a substantial increase in greenhouse
gases with associated large increase in greenhouse forcing.
Given that the lifetime of these gases is orders of magnitude
larger than that of aerosols, future anthropogenic forcing is
dominated by greenhouse gases. Thus, the relative uncertainty
in aerosol forcing may be less important for projecting
future climate change.
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Copied right out of the article. Aerosols are short lived and GHG’s are long lasting. A more important question to answer is how does it effect the outcome. I imagine a lot more can be varied than just the aerosols. More importantly is there is no secret here.
And does the model still do its job for us in showing trends. I’ve got a feeling this is just being blown out of proportion. Given the importance of understanding aerosols, the temperature trend for the future is still going up.
Renewable:
“Please elaborate on what point you were trying to make here, with the graph of past events demonstrating model output vs actual data.” — “TO show viability of models. To reproduce the surface temperature. If you remove certain aspects of the data the model output diverges from the observations in a wider manner.”
I assume by the viability of a model you assume its usefulness in predicting the future. So, how exactly does the graph of past events that you provided show the viability of the used model in predicting future events? Please be exact.
** And does the model still do its job for us in showing trends.
Does the broken clock still do its job for us in showing the correct time twice a day?
That’s assuming the trend is even correct, of course.
teora:
Renewable:
“Please elaborate on what point you were trying to make here, with the graph of past events demonstrating model output vs actual data.” — “TO show viability of models. To reproduce the surface temperature. If you remove certain aspects of the data the model output diverges from the observations in a wider manner.”
I assume by the viability of a model you assume its usefulness in predicting the future. So, how exactly does the graph of past events that you provided show the viability of the used model in predicting future events? Please be exact.
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http://www.giss.nasa.gov/research/briefs/schmidt_04/
Testing Climate Models
Model assessment occurs on two distinct levels — the small scale at which one evaluates the specifics of a parameterization and the large scale at which predicted emergent features can be tested. The primary test bed is the climate of the present era, particularly since 1979, when significant satellite data started to become readily available.
The 1991 eruption of Mount Pinatubo provided a good laboratory for model testing (see the figure). Not only was the subsequent global cooling of about 0.5 °C accurately forecast soon after the eruption, but the radiative, water-vapor, and dynamical feedbacks included in the models were quantitatively verified.
More than a dozen facilities worldwide develop climate models, whose ability to simulate the current climate has improved measurably over the past 20 years. Interestingly, the average across all models almost invariably outperforms any single model, which shows that the errors in the simulations are surprisingly unbiased. Significant biases common to most models do exist, however — for instance, in patterns of tropical precipitation.
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This is a blog discussion. Being exact suggests to me you want to be very highly demanding. I doubt you will change your mind on models from my discussion with you. I suggest you read this article and then get back with me. I will be happy to go over the article discussing your point of view.
mux:
** And does the model still do its job for us in showing trends.
Does the broken clock still do its job for us in showing the correct time twice a day?
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What about the models are broken?
Ted:
Speaking of inefficiencies, coal at very best is 45% efficient. More like 35%. The rest is wasted. If a storge process is 60 to 80% rouned trip efficient, its starting to look better than the origonal efficiency. Getting wind onto the power lines is better than 90% efficient.
Renewable:
The efficiency of thermal power plants is limited by thermodynamics. Water is vaporized and superheated, then run through a turbine. The superheat is recovered as electrical energy, the heat of vaporization is lost to the condenser. (This is a brief simplistic explanation). The max theoretical efficiency is about 45%. However, the steam turbine efficiency (in the 70’s) brings it down to 35-38% overall. Question: Have you ever heard of thermodynamics? Have you ever used a pressure-enthalpy diagram?
Supercritical boilers were tried years ago to improve the thermo efficiency (only slight improvements are theoretically possible), but ran into problems due to silica solubility in supercritical steam, with attendent turbine problems. Believe me, engineers have wrung out the most efficiency they can. Buy a thermo book! The energy is not “wasted”. That’s all of it that can theoretically be used.
P.S. I loved your coal eff. comment. My engineer friends think it is hilarious! Thanks.
P.P.S. Getting coal-generated power onto the power lines is also 90% efficient.
Renewable:
You are very fond of saying “the Spaniards are doing it”. An excellent article on the state of the Spanish wind energy situation at:
masterresource.org
“Spanish Wind Revisited”
by Robert Peltier, Apr 13, 2011
If you want to follow the Spaniards into folly, be my guest.
Ted:
http://en.wikipedia.org/wiki/Economy_of_Spain
More recently, the Spanish economy had benefited greatly from the global real estate boom, with construction representing an astonishing 16% of GDP and 12% of employment in its final year. According to calculations by the German newspaper Die Welt, Spain had been on course to overtake countries like Germany in per capita income by 2011.[18] However, the downside of the now defunct real estate boom was a corresponding rise in the levels of personal debt; as prospective homeowners had struggled to meet asking prices, the average level of household debt tripled in less than a decade. This placed especially great pressure upon lower to middle income groups; by 2005 the median ratio of indebtedness to income had grown to 125%, due primarily to expensive boom time mortgages that now often exceed the value of the property.[19] A European Commission forecast had predicted Spain would enter a recession by the end of 2008.[20] According to Spain’s Finance Minister, “Spain faces its deepest recession in half a century”.[21] Spain’s government forecast the unemployment rate would rise to 16% in 2009. The ESADE business school predicted 20%.[22]
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It appears that Spain has a serious debt problem. The article you suggested seems to want to blame renewable energy for Spain’s problems.
@Renewable:
“The 1991 eruption of Mount Pinatubo provided a good laboratory for model testing (see the figure). Not only was the subsequent global cooling of about 0.5 °C accurately forecast soon after the eruption, but the radiative, water-vapor, and dynamical feedbacks included in the models were quantitatively verified.”
Please elaborate what was the prediction, when it was made and how it was verified.
Everything else in your quote is fluff.
This is actually misleading:
“Interestingly, the average across all models almost invariably outperforms any single model, which shows that the errors in the simulations are surprisingly unbiased.”
I bet when you read this, you thought, hey, this is good, the models might be faulty, but maybe we can trust their average. But that’s not how it works at all! You can’t just take the average of a couple of models, you have to have a scientific basis for taking that average. Look, any model is basically a statement “here, I am making these assumptions about how things are, and based on that, this is what I think will happen in the future”. If you take a couple of models which failed to predict the future – each on its own accord, it does not follow at all that their average will not fail to predict the future. You have to justify the average, develop a theory, whatever.
Well, that’s Gavin we are talking about, so I am not surprised at misleading statements in the least.
@Renewable:
I will save you the time as regards Pinatubo.
Hansen’s paper was written quite some time into the period where the effects of Pinatubo were expected to be felt, when a significant part of the effect has already materialized. The paper had several wildly varying scenarios with predictions of short-term effects on global temperatures ranging in magnitude between 0.2 deg C and 0.7 deg C. There were quite a number of reservations in terms of “we don’t have enough data on this and that and also that, and all these things can significantly alter the results, so be careful”, allowing for yet more leeway in interpretation of whether the predictions have ultimately realized. As a result, anything that could have happened with the global temperatures over the course of several next years, save maybe unexpected terraforming attacks from aliens, was destined to fall into the bounds of the “predictions” in the paper. Which happened, and some 6 years after it was declared that the predictions came true and the science behind them was ingenious.
That’s it.
This discussion has taken many twists and turns. I would like to try one more time to bring it back to the topic of the main post. Here is my question to Renewable: Now that you have read Kheil’s article, is there anything that Warren has written in the main post with which you disagree? Be specific and provide a quotation of any portions of the main post that you want to contest.
My skepticism was increased when several skeptics pointed out a problem that should have been obvious. The ten or twelve IPCC climate models all had very different climate sensitivities — how, if they have different climate sensitivities, do they all nearly exactly model past temperatures? If each embodies a correct model of the climate, and each has a different climate sensitivity, only one (at most) should replicate observed data. But they all do. It is like someone saying she has ten clocks all showing a different time but asserting that all are correct (or worse, as the IPCC does, claiming that the average must be the right time).
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http://www.realclimate.org/index.php/archives/2008/11/faq-on-climate-models/
Starting with the assumption all models are wrong, what can we learn from running the model, what are its strengths and weaknesses.
The author wants to compare modeling to telling time. You can start out by saying all clocks are wrong. Which clock is the right time. The right time in actuality is being improved based on a more recent technology that is adaptable. That becomes the right clock. All other clocks will be wrong to some degree. But I’m not throwing my wrist watch out, because it is not keeping time with the atomic clock. I can gain a lot of good with my watch.
There will be a best model for the climate in the world. More than likely it will come from Hadcrut or Giss. They aren’t written the same way and have strengths and weaknesses. The models are then compared to observations made in the real climate. The difference then I would imagine becomes the uncertainty in the model. It is labeled (the uncertainty) studied and understood.
How to view the model in its reliability is how you choose to frame the issue. Warren is framing it with if each model is correct then why do we have differences?
In reality each model is wrong to a degree, and vary in how they are wrong.
The model is a very useful powerful tool as long as you understand its limitations. Warren is encouraging an up or down vote, with most of you preferring the down vote. He is doing his job of selling the model as something you don’t and shouldn’t believe in.
The argument I have been making is that Hansen got it right enough within the limitations of a model that I believe he had a hand in writing from the 1980’s. Nearly 25 years later, do you think the models have improved?
teora:
@Renewable:
I will save you the time as regards Pinatubo.
Hansen’s paper was written quite some time into the period where the effects of Pinatubo were expected to be felt, when a significant part of the effect has already materialized.
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Hansen wrote his paper which came out in 1988 and predicted what a large volcano would do to the climate. In 1991 a very strong volcano went off, Mt Pinatubo. It was studied intensively for its effect on the climate.
I would be curious where you got your information.
teora:
Please elaborate what was the prediction, when it was made and how it was verified.
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I have posted this several times.
http://www.skepticalscience.com/climate-models-intermediate.htm
Figure 2: Global surface temperature computed for scenarios A, B, and C, compared with two analyses of observational data (Hansen 2006).
Renewable
I have already refuted this bogus apology for Dr Hansen’s model’s failure. Why keep citing it ?
Claiming that a part of the model is off by x % therefore the model is only off by x % shows sloppy thinking skills.
The multiplication factors etc make the final output over 2 times too high. That is pretty bad.
THE POLITICIANS AND DECISION MAKERS LOOKED AT THE AMOUNT OF WARMING FORECASTER WHEN MAKING DECISIONS SO THAT IS THE ONLY FAIR WAY TO EVALUATE THE RESULTS. [Anything else is bait and switch]
The true test of a model is predicted warming vs actual warming. That is what the congressman looks at when allocating money.
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Anything else is bait and switch.
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[Singling out CO2 and blaming it for the error is simplistic. The amplification factors were wrong too and they amplified a small error into a much larger error.] The silly rabbits at skepticalscience need to be more skeptical.
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Dr Hansen’s projections:
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http://cstpr.colorado.edu/prometheus/archives/hansenscenarios.png
1988 Observed [anomaly ].31 ° C
2011 predicted anomaly = 1.0 ° C
Projected warming = .69
Semi reality as shown by GISS.
http://data.giss.nasa.gov/gistemp/graphs/Fig.A2.txt
Temp 1988 =Year .31 5 year avg .25
Temp 2010 =Year .63 5 year avg .56
Actual warming = Year .32 5 year avg .32
Predicted / actual = .69/.32 = 215 %.
That proves the model is terribly inaccurate.
I saw the discussion in skeptical science and a child could have poked holes in it but the moderators block any attempt to do so.
I posted about what I posted here and it kept disappearing. They fear actual discussion like the plague.
Saying “I know what the problem was and have fixed it.” is wishful thinking and must be proven by performance over the next 20 years or so. Since the rate of warming is so low and probably going negative soon he will have to adjust the model again and again. It is like driving a car by looking in the rear view mirror.
The horse player who fixed his model hopes against hope that his fix makes his model correct but only future performance will tell if it is. I remain skeptical.
June 16, 2011, 7:22 am
Renewable:
“Hansen wrote his paper which came out in 1988 and predicted what a large volcano would do to the climate. In 1991 a very strong volcano went off, Mt Pinatubo. It was studied intensively for its effect on the climate. I would be curious where you got your information.”
I was talking about the paper on Pinatubo specifically which Hansen wrote in 1992.
You are talking about a different paper, fine, let’s look into it. Where’s the great prediction that turned out to be oh so precise and ingenious? That effects from an eruption of a volcano will generally lower rather than raise global temperatures? That’s cool, but too imprecise. Maybe the paper contained some numbers which later turned out to match the reality very closely? Nope, the aerosol numbers in the 1988 paper are significantly vaguer than those in the 1992 paper, and the numbers in the 1992 paper are already so vague they cover all that could possibly happen bar a hundred new large eruptions. So, what is the prediction from Hansen 1988 that you think turned out so great?
Now, since I believe I am asking you to clarify your position for the third or fourth time, please, do me a favor. Be specific. Point to numbers and graphs in the 1988 paper, then point to numbers and graphs that demonstrate that these predictions turned out great. Otherwise it is getting tiresome.
Renewable.
You [and skepticalscience] haven’t refuted a single point I made.
Was the amount of over estimation of warming from 1988 to present 215 %? Yes or No
Is overall temperature warming or lack of warming the correct metric to use ? Yes or No ?
Who even knows or CARES what variables these predictions were based on or how far off they are ?
[Certainly not a congressman.]
Actually, you know, Renewable, don’t answer me, and simply say what’s wrong with numbers cited by netdr (Hansen’s prediction: 1.00 deg, observed: 0.31 deg). Do you say that Hansen’s prediction was different from 1 degree? Or do you say that the observed warming was different from 0.31 degree? Or do you say that this is a great and close match?
For the record Hansen’s model included a simulated volcano or else the predictions would have been even higher.
See for yourself.
http://pubs.giss.nasa.gov/docs/1988/1988_Hansen_etal.pdf
Look at Paragraph 4.2
True. And Hansen overestimated the cooling from Pinatubo roughly by an order of 2 (which is huge).
And I got the numbers in my post above wrong – the numbers should be not 1 predicted vs .31 observed, but rather .69 predicted vs .32 observed. Sorry for that.
Renewable: I think you are reading into Warren’s posts things that he did not say. Your statement that Warren is trying to compare modeling to telling time completely misses the point of his analogy. If you don’t see that, I am not sure that I can explain it to you. You seem to be interpreting Warren’s post so that you can respond to it with something you read elsewhere that is not really relevant.
Obviously, all climate models are wrong to a degree, and it is possible to learn things from models even though the contain simplifying assumptions that are not exactly correct. I understand the point of the real climate link you provided, but it is not relevant to the point Warren is making.
Finally, you ask, “Nearly 25 years later, do you think the models have improved?” In fact, while models have become more sophisticated, scientists have not significantly reduced the range of climate sensitivities predicted by the models.
By the way, for all you guys that are fathers
HAPPY FATHER’S DAY 🙂
Dr Hansen’s projections:
NetDr:
http://cstpr.colorado.edu/prometheus/archives/hansenscenarios.png
1988 Observed [anomaly ].31 ° C
2011 predicted anomaly = 1.0 ° C
Projected warming = .69
########################################################
Why are you comparing the 1988 observed anomaly to the 2011 predicted anomaly?
wouldn’t it be better to compare predicted and observed in the same year?
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Semi reality as shown by GISS.
http://data.giss.nasa.gov/gistemp/graphs/Fig.A2.txt
Temp 1988 =Year .31 5 year avg .25
Temp 2010 =Year .63 5 year avg .56
Actual warming = Year .32 5 year avg .32
Predicted / actual = .69/.32 = 215 %.
####################################################
Looking to label something a glaring failure and you found something to match your point of view.
He guessed at a higher co2 rate than there actually was.
He estimated sensitivity slightly higher than what observations show.
what does this model run tell us?
With more co2, temperatures will rise.
He did a model run of a large volcano before pinatubo.
Natural variability shows up in the model run rather than a straight line.
With input of slightly higher values he got a slightly higher projection of temperature. Given the starting values, the model did spectacular for its time.
I respect your background Net, but for whatever reason you aren’t reading the material and applying it. And I know you have the abitlity to understand it if you want to.
When you dig down into the details, Hansen did a great job for back in that time.
I’m sure there is more.
All models cannot show the climbing trend of temperature without co2 in them however close they are. Co2 affects our climate at low and high co2 levels both. Co2 never stops acting like a ghg or takes coffee breaks.
Teora:
Modelling the aftermath of the Mount Pinatubo volcanic eruption
When Mount Pinatubo erupted in 1991, it provided the opportunity to test how successfully models could predict the climate response to the sulfate aersol injected into the atmosphere. The models accurately forecast the subsequent global cooling of about 0.5 °C soon after the eruption. Furthermore, the radiative, water-vapor, and dynamical feedbacks included in the models were also quantitatively verified (Hansen 2007).
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Figure 2: Observed and simulated global temperature change during Pinatubo eruption. Green is observed temperature by weather stations. Blue is land and ocean temperature. Red is mean model output (Hansen 2007).
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I suppose if you want to go deeper we can go into the Hansen 2007 paper looking at the mount pinatubo effects on climate.
It seems you want to focus on just a few end result numbers as though that is the only meaning the model has.
The model is much than that as I’ve discussed in previous posts.
Teora:
Now, since I believe I am asking you to clarify your position for the third or fourth time, please, do me a favor. Be specific. Point to numbers and graphs in the 1988 paper, then point to numbers and graphs that demonstrate that these predictions turned out great. Otherwise it is getting tiresome.
########################################################
What I’m not able to do is to put in the correct starting points into his model. You are way focused on only the numbers rather than what the model is really doing. Hansen’s starting points were slightly off in a high way and the model came out high. That is a good thing. If the model had come out low, then the model would need some more work.
If you also notice that he also has hindcasting into the graph.