Why Models Run Hot: A Discussion of the IPCC's Overestimation

[phyzguy]

I think this is now a legitimate topic. If not, I apologize. I would like to hear comments on the paper "Why models run hot", discussed in this article. Do people on this forum agree that the IPCC models overestimate the amount of positive feedback in the Earth's climate system.? Or is this new article flawed? I've attached a pdf of the article.

 

[Quantum Defect]

I think this is now a legitimate topic. If not, I apologize. I would like to hear comments on the paper "Why models run hot", discussed in this article. Do people on this forum agree that the IPCC models overestimate the amount of positive feedback in the Earth's climate system.? Or is this new article flawed? I've attached a pdf of the article.

Lord Monckton?

 

[PeterDonis]

Lord Monckton?

He's one of four authors of the paper.

 

[PeterDonis]

Do people on this forum agree that the IPCC models overestimate the amount of positive feedback in the Earth's climate system.?

I've thought that for quite some time. It's important to keep the paper's claim in perspective, however. The paper, as I read it, is not saying that its model should be used to predict what the climate will be like at the end of the century; it is not saying that its model is based on a detailed understanding of how the climate works. It is only saying that its very simple model can make better predictions, as compared with the data over the last couple of decades, than the much more complicated IPCC models, and that should make us skeptical that the IPCC models are modeling things correctly.

 

[Bandersnatch]

I'd be wary of papers whose primary author is a politician with no relevant scientific background and a clear agenda.

 

[PeterDonis]

I'd be wary of papers whose primary author is a politician with no relevant scientific background and a clear agenda.

By PF rules, we should focus on the scientific content of papers and not on who authored them, provided they meet the basic guidelines for acceptable references. This paper was published in a peer-reviewed journal, and it looks like at least two of the four authors have scientific credentials. So it appears to be an acceptable reference.

 

[Bystander]

saying that its very simple model can make better predictions, as compared with the data over the last couple of decades, than the much more complicated IPCC models,

May I paraphrase: "a very simple model provides a better fit of data collected over the past two decades than do complex models that have been generally accepted." Implication: the complex models are "overfitting" the available data.

 

[PeterDonis]

May I paraphrase: "a very simple model provides a better fit of data collected over the past two decades than do complex models that have been generally accepted."

Yes, this is better because it avoids the word "prediction", which doesn't really fit here. (The paper also includes predictions based on the simple model, but those aren't what the claim that the complex models are overestimating feedback is based on.)

Implication: the complex models are "overfitting" the available data.

More precisely: the complex models overfit the data from prior to the past couple of decades, i.e., the data that were used to build the models. Hence, the model results for the past couple of decades don't match as well.

 

[DaveC426913]

Is climate change / global warming no longer a verboten topic on PF? It was for the longest time.

https://www.physicsforums.com/threads/physics-forums-global-guidelines.414380/#post-3929007
Apparently it is fair game again. :)

 

[Bystander]

no longer a verboten

There's a note at the head of the forum regarding this. Stick to refereed sources and omit the politics.

Beg pardon --- there was --- do not ask me where it went.

 

[phyzguy]

I have thought for a while that the IPCC climate models seem to have an unreasonably large amount of positive feedback. It appears, based on what PeterDonis said in Post #4, that he agrees. My logic was that if the climate system had a large amount of positive feedback, we would have seen more climate variability in the past due to various forcings. The authors of this paper say exactly the same thing at the beginning of Section 8.3.2, where they say,

"A plausible upper bound to f may be found by recalling that absolute surface temperature has varied by only 1 % or 3 K either side of the 810,000-year mean [40 , 41 ]. This robust thermostasis [42 , 43 ], notwithstanding Milankovich and other forcings, suggests the absence of strongly net-positive temperature feedbacks acting on the climate."

It seems possible that the developers of the IPCC models incorporated enough positive feedback to fit the temperature data through the early part of the 21st century, and are now finding that the positive feedback needs to be dialed back in order to fit the more recent data. Does anyone know whether there are other checks on the various components of feedback to verify if they are reasonable?

 

[Bystander]

checks on the various components of feedback

How many "feedbacks" have been proposed? Haven't bothered to keep up with them lately. Have they been run independently of one another? Or, do the models allow a "synergy" between/among them?

 

[PeterDonis]

Does anyone know whether there are other checks on the various components of feedback to verify if they are reasonable?

I think part of the issue is that we don't have a good understanding of the mechanisms behind the various feedbacks, so it's hard to check them independently. For example, I don't think there's agreement even on the sign (positive or negative) of the net feedback from clouds, because we don't understand the various effects clouds have well enough to know which ones dominate.

There are also people working on estimating the feedbacks by looking at satellite data; this is basically doing it "from the outside", not testing the various mechanisms separately but just looking at the overall radiation in and out to estimate global effects. AFAIK there is still a lot of spread in the possible feedback values estimated this way as well--largely because we simply haven't been taking satellite data that long.

 

[berkeman]

There's a note at the head of the forum regarding this. Stick to refereed sources and omit the politics.

Beg pardon --- there was --- do not ask me where it went.

Thanks for the heads up! The stickie is back visible again. :-)

 

[Bystander]

back visible again

Thank you --- I'm not having a "golden age moment."

 

[phinds]

Thank you --- I'm not having a "golden age moment."

Ah you probably are and berkeman is covering for you

 

[Bystander]

Ah you probably are and berkeman is covering for you :)

You'll spend the rest of your days proofreading every line you post --- one typo and you're done for.

 

[Bystander]

looking at satellite data;

I got the impression while hunting for information for Loudzoo's thread on IR & ocean evaporation that the satellite data wasn't broad spectrum. Got any details whether they're collecting UV, vis., and IR?

 

[PeterDonis]

Got any details whether they're collecting UV, vis., and IR?

I'm pretty certain satellites can get radiance measurements in the microwave and IR bands. I'm fairly sure they can get them in visible as well. Don't know about UV. As far as using satellite data to infer temperatures, since all of the temperatures in question correspond to spectrum peaks in the IR range, I'm not sure UV data would add much anyway; if you've got microwave, IR, and visible, you've covered the key portion of the spectrum.

 

[Bystander]

I'm not sure UV data would add much anyway

Thee or me either one. I haven't actually sat down and designed a "dream data set" for satellite measurements, let alone whether instrument sensitivity is adequate for my "intuitive" sense that "global" measurements are probably going to be most meaningful if made from at least lunar distance. Sorting direct reflection from scattering? Reflected IR from emitted IR? Which details are even meaningful. Hopefully NASA, NOAA, and JPL have coordinated programs for such purposes, and one of these days it'll show up in "J. Gee. Whiz" for me to play with.

 

[klimatos]

For example, I don't think there's agreement even on the sign (positive or negative) of the net feedback from clouds, because we don't understand the various effects clouds have well enough to know which ones dominate.

I believe that there was a recent AGU study by Robert Shibatani on the 31 known major aerosols that showed a net positive effect of some four watts per square meter. Regardless, we probably have less valid information on albedo forcing that any other major forcing method. We need a sensor that can read the entire planetary disc at one time, and we need data from this sensor for a minimum of thirty years. Not in my lifetime, and probably not in my children's.

 

[D H]

Do people on this forum agree that the IPCC models overestimate the amount of positive feedback in the Earth's climate system.? Or is this new article flawed?

This paper is so very bad that it will receive a good number of citations in the next few months by later papers that show just how bad this paper is. It is so monumentally bad that I won't be at all surprised if it makes its way onto retractionwatch.com.

First, for the claim that "models run hot." This is a false claim. The authors went all the way back to the first assessment report as the basis for their claim that "models run hot" (which they don't). Granted, that very first report had some flaws; it was the very first report, after all. That first assessment did not use tools such as general circulation models, which were in their infancy in the late 1980s. Note that this means that even if the paper by Monckton et al. is correct (which it isn't), that they target the FAR is a fatal flaw in their paper. Later assessments used general circulation models to drive the analyses. The switch to better models in later reports means that that the authors arguments apply only to that very first report.

Even with regard to that very first report, the claim "models run hot" is a false claim. The first assessment presented warming under multiple scenarios, the worst case being the "business as usual" scenario. Monckton et al. cherry-picked that "business as usual" scenario as if it were the report's sole prediction. This scenario assumed cars would continue to have 1990 gas mileage, coal power plants would continue to have 1990 emissions, and that the economy and population would continue growing. That didn't happen. There have been modest improvements in technology since 1990, populations in the developed world have gone stagnant, and the world was hit by two huge economic downturns. The world pumped less CO₂ into the atmosphere than predicated by the "business as usual" scenario, so of course that scenario "ran hot."

Another flaw in the paper is their use of an 810,000 year baseline as proof that positive feedbacks don't exist. That's completely wrong. The Milankovich forcings are rather small. The slight reductions in solar irradiation that result from the Milankovich cycles are too slight in and of themselves to result in a glaciation. We wouldn't have glaciations without positive feedbacks.

The biggest flaw in the paper is the authors silly Figure 5 and the arguments around it. That a sound system designer wouldn't create a system with loop gain of more than 0.1 means that the climate mustn't have a gain greater than 0.1 is a ludicrous non sequitur.

 

[Bystander]

The slight reductions in solar irradiation that result from the Milankovich cycles are too slight in and of themselves to result in a glaciation. We wouldn't have glaciations without positive feedbacks.

I'm missing something here --- or am I?

1) Global mean temperature is a function of some unknown set of feedback parameters which are also functions of global mean temperature?
2) Gains for the feedbacks can be greater than, equal to, or less than zero, but were a net positive to produce however many glaciations over the past 800 ka, and to result in whatever is taking place now?
3) Positive feedback is understood to mean that the effect of whatever "upset" condition is introduced into the global system is amplified over time until some opposite "upset" offsets it, or some other damping mechanism takes over?​

 

[PeterDonis]

The world pumped less CO2 into the atmosphere than predicated by the "business as usual" scenario, so of course that scenario "ran hot."

If I'm not mistaken, though, the "business as usual" scenario is not the only one that has over-predicted actual warming; all of them have, though not all to the same extent (obviously). And the actual CO2 increase, while it has been less than the "business as usual" scenario, as you say, has, if I'm not mistaken, been greater than rise assumed in the other scenarios (except for the "extreme" scenario that used even more CO2 rise than "business as usual", but AFAIK that one is not considered realistic). So I think it is still fair to say that the models "run hot", even if the specific comparison in the paper is not comparing apples to apples.

 

[D H]

I'm missing something here --- or am I?

Quoting from the silly paper,

A plausible upper bound to f may be found by recalling that absolute surface temperature has varied by only 1 % or 3 K either side of the 810,000-year mean. This robust thermostasis, notwithstanding Milankovich and other forcings, suggests the absence of strongly net-positive temperature feedbacks acting on the climate.​

This is sheer nonsense. What "robust thermostasis"?

The Milankovich forcings are very small, about 0.5 watts/meter². That these tiny forcings result in huge temperature swings (minor problem: the 3 K figure itself is a bit misleading; a better figure is swings of 10 K) is evidence to most climatologists that huge positive feedbacks are involved. The feedbacks are obvious. Warmer winters at high latitudes lead to more snow at those latitudes, which increases the albedo. Cooler summers at high latitudes means some of that increased snowfall becomes permanent ice. Permanent ice begets more permanent ice and even cooler summers because of the increased albedo. Cooler summers means reduced absolute humidity, and water is by far the most significant greenhouse gas. More cooling, more snow, more ice. The cooling also reduces CO₂ levels, leading to even more cooling.

The flip side, an interglacial, is also attributable to positive feedbacks. Just as the Earth couldn't enter a glaciation without positive feedbacks, it couldn't exit one without positive feedbacks.

 

[PeterDonis]

That these tiny forcings result in huge temperature swings (minor problem: the 3 K figure itself is a bit misleading; a better figure is swings of 10 K) is evidence to most climatologists that huge positive feedbacks are involved.

I wondered about that 3 K figure too; I had thought it was closer to 10 K as well.

I think it's worth clarifying a point here, though. If we're looking at the start of a glaciation, due to a small negative Milankovich forcing for example, then there can't just be positive feedback involved, because if there were the climate would never stabilize in the glaciation phase; it would just keep getting colder. At some point negative feedback must come into play in order to stop the cooling and stabilize the climate in the ice age state. (Of course similar remarks apply to the transition from ice age to interglacial.) So both types of feedbacks must be present.

Basically, on the theory you are presenting here, the climate is bi-stable: it has, roughly speaking, two stable states (ice age and interglacial), and if the climate is in one of the stable states, it takes a certain amount of forcing to kick it out of that state. Once that amount of forcing is present, positive feedback dominates and moves the climate towards the other stable state; but once it gets close to the other stable state, negative feedback dominates and the climate stabilizes in the other state.

The question then becomes: what if you start with the climate in the interglacial stable state, but you then add positive forcing--causing warming (instead of negative forcing like the Milankovich forcing, causing cooling)? There seems to be a belief that, once there is enough positive forcing present, the same thing will happen that happens when positive forcing kicks the climate out of the ice age state--that positive feedbacks will dominate and accelerate warming. However, the interglacial state is very different from the ice age state, so it's not clear to me that all the same positive feedbacks will be present in the warming direction--note that these must be different from the positive feedbacks in the cooling direction (like ice-albedo feedback) that you describe.

 

[Bystander]

tiny forcings result in huge temperature swings (minor problem: the 3 K figure itself is a bit misleading; a better figure is swings of 10 K)

Over what time scales? Patience, gang --- I'm trying to get back up to speed on just what points are being pursued on the bases of which arguments.

 

[D H]

If I'm not mistaken, though, the "business as usual" scenario is not the only one that has over-predicted actual warming; all of them have, though not all to the same extent (obviously).

That depends on which dataset one uses.

The table below summarizes the warming since 1990 per various temperature datasets.

Source     °C/decade
Satellite-based
RSS        0.11
UAH        0.16
Surface-based
GISTEMP    0.15
NOAA       0.14
HADCRUT4   0.14
Berkeley   0.16

One of the above datasets stands out, in a Sesame Street sense ("one of these things does not go with the other; one of these things doesn't belong"). The silly article used that singular source, the Remote Sensing Systems (RSS) dataset. So-called "skeptics" love RSS. Everyone else says "Hmm. That's funny. Maybe I shouldn't use that."

When one looks at CO₂ forcings based on observed CO₂ levels since 1990, the closest match is scenario B. With the exception of RSS, the observed data are most consistent with scenario B from the IPCC's First Assessment Report.

Note well: I intentionally omitted the uncertainties in the above table. The silly article did the same, so tit for tat. The uncertainties are rather large. All of the datasets are consistent with one another, to within two standard deviations.

After accounting for those uncertainties, each of those observation based datasets is consistent with each of the FAR scenarios. The uncertainties are just too large over a mere 25 year span to rule out anyone of those scenarios. The only thing that can be excluded (with the exception of RSS) is that there has been no warming whatsoever.

The RSS database exhibits the greatest uncertainty. It is consistent with both "business as usual" and "no warming whatsoever." The null hypothesis, "no warming whatsoever," is easily rejected by all but the RSS database.

 

[PeterDonis]

The uncertainties are rather large. All of the datasets are consistent with one another, to within two standard deviations.

After accounting for those uncertainties, each of those observation based datasets is consistent with each of the FAR scenarios. The uncertainties are just too large over a mere 25 year span to rule out anyone of those scenarios.

This seems to me to be the most important piece of information to keep in mind.

 

[klimatos]

The Milankovich forcings are very small, about 0.5 watts/meter².

I was under the impression that the Milankovich forcings (orbital forcings) were independent of any change in the solar constant. The incoming annual global radiation remains constant but the latitudinal and seasonal distribution of this radiation varies with the regular variations in the three controls.

The flip side, an interglacial, is also attributable to positive feedbacks. Just as the Earth couldn't enter a glaciation without positive feedbacks, it couldn't exit one without positive feedbacks.

True without doubt.

 

[Czcibor]

First, for the claim that "models run hot." This is a false claim. The authors went all the way back to the first assessment report as the basis for their claim that "models run hot" (which they don't). Granted, that very first report had some flaws; it was the very first report, after all. That first assessment did not use tools such as general circulation models, which were in their infancy in the late 1980s. Note that this means that even if the paper by Monckton et al. is correct (which it isn't), that they target the FAR is a fatal flaw in their paper. Later assessments used general circulation models to drive the analyses. The switch to better models in later reports means that that the authors arguments apply only to that very first report.

Even with regard to that very first report, the claim "models run hot" is a false claim. The first assessment presented warming under multiple scenarios, the worst case being the "business as usual" scenario. Monckton et al. cherry-picked that "business as usual" scenario as if it were the report's sole prediction. This scenario assumed cars would continue to have 1990 gas mileage, coal power plants would continue to have 1990 emissions, and that the economy and population would continue growing. That didn't happen. There have been modest improvements in technology since 1990, populations in the developed world have gone stagnant, and the world was hit by two huge economic downturns. The world pumped less CO₂ into the atmosphere than predicated by the "business as usual" scenario, so of course that scenario "ran hot."

Can you advice me any comprehensive (meta)study concerning which climate change was predicted and which temperature was actually observed afterwards?

 

[PeterDonis]

I was under the impression that the Milankovich forcings (orbital forcings) were independent of any change in the solar constant.

As I understand it, the Milankovich forcings do include changes in the solar constant; as a result of periodic changes in the Earth's orbital parameters, the annual radiation received by the Earth from the Sun changes. (The latitudinal and seasonal distribution also changes.)

 

[mheslep]

...I would like to hear comments on the paper "Why models run hot"

That Sci Bull paper is not the first journal published material to say as much.

http://www.nature.com/nclimate/journal/v3/n9/full/nclimate1972.html#access, Fyfe, Gillett, Zweir
Nature Climate Change 3, 767–769 (2013) doi:10.1038/nclimate1972, Published online, 28 August 2013

Recent observed global warming is significantly less than that simulated by climate models. This difference might be explained by some combination of errors in external forcing, model response and internal climate variability.

Figure 1: Trends in global mean surface temperature

a, 1993–2012. b, 1998–2012. Histograms of observed trends (red hatching) are from 100 reconstructions of the HadCRUT4 datasethttp://www.nature.com/nclimate/journal/v3/n9/full/nclimate1972.html#ref1. Histograms of model trends (grey bars) are based on 117 simulations of the models, and black curves are smoothed versions of the model trends. The ranges of observed trends reflect observational uncertainty, whereas the ranges of model trends reflect forcing uncertainty, as well as differences in individual model responses to external forcings and uncertainty arising from internal climate variability.

 

[phyzguy]

mhslep - thanks for posting this. I thought that it was generally acknowledged that the models were predicting more warming than we are observing, and so I was surprised by DH's vehement denial in post 22. I though that's why we see many articles trying to explain the "hiatus" in warming. This Nature Climate Change article seems to agree that the models are significantly over-predicting the amount of warming. DH - I expect you must disagree with the plots mhslep has posted. Can you tell us why?

 

[mheslep]

The "Business-As-Usual" scenario, as described in the FAR, defines man-made carbon emissions over time in the https://www.ipcc.ch/ipccreports/far/wg_I/ipcc_far_wg_I_spm.pdf. The carbon emissions BAU graph, as I can make out, gives something less than 10 GtC/yr for 2015, maybe as low as 9 GtC/yr, while the low carbon scenarios are still around 5 GtC/yr as of 2015. As of 2011 per AR5, global carbon emissions from fossil fuels and cement were 9.5 GtC/yr +/- 0.8 (http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter06_FINAL.pdf), growing at 3%/yr.

 

[Catamount]

It's true that if the BAU scenario did outpace what really happened for carbon dioxide, it wasn't by much. However that scenario had enormously higher methane emissions growth than actually occurred, projecting a near linear growth of emissions where the real world saw what appears to be emissions that went from static yearly inputs to drastic decrease, followed by resumed emissions at only a very modest level compared to the 90s. Far from growing from 350ish MtC/yr and blowing past 400, 500, and more, emissions appear to have tanked by 2000, and only modestly resume in the 2010s if concentration numbers are any indication.

http://www.esrl.noaa.gov/gmd/aggi/aggi.fig2.png

Strangely, I'm having a hard time finding emissions numbers past the late 90s, but nevertheless, concentration change has stalled out pretty strongly, especially compared to the ever-accelerating concentrations rise in FAR's BAU scenario. If emissions had increased the concentration would have started changing faster, not stalled out (obviously).Of course, the more important point is going to be that no matter what, these scenarios are going to be overestimations of net forcings, because they're not going to include the hugely negative trends in the ENSO forcing or recent aerosol hikes. Most of DH's points of criticism are very cogent, and that's one of the biggest. FAR didn't use what we'd consider a full and proper GCM. They just used a simple radiation balance model with a little bit of ocean behavior thrown in which appears to have just been there to moderate the rate of change. That's not even going to account for something like ENSO, let alone represent a correct prediction of the trends of such a forcing that would be necessary to build a proper scenario to test.I believe that may also represent a big criticism of Moncton et al taht DH didn't seem to bring up, but I'm just a layman so I'd be happily corrected there: Moncton et al. appear to basically get their past 20ish-years period by modelling all of climate over that recent period as a response to CO2, deriving the level of climatic response to CO2 by simply subtracting the other major forcings in play outlined by the IPCC and just assuming that anything that remains is CO2->temperature response, and then just plotting that sort of sensitivity of temperature to CO2 over time with the assumption that it's going to explain all behavior over the period they're using for comparison of their model to FAR. Is that going to include the influence of any short-term climatic behavior like ENSO? It doesn't seem so to me. So if that bottoms out, and you get a negative forcing that their simple model doesn't account for, it's going to manifest as reduced sensitivity, and we did have bottomed out short-term natural forcings and increased aerosol production from Asia, and oh hey, look what happened! They got really low sensitivity! Is my admitted lack of expertise here causing me to miss some hidden genius to their methods, or is it really that bad?More to the point, are the models, the modern models, actually overestimating warming? Gavin Schmidt and his co-authors in a recent little piece in Nature Geoscience don't think so. When they took their best shot at including the most up-to-date estimates of the forcings, different than what CMIP5 models are using, most of the disagreement between the temperature and the models disappeared

http://www.blc.arizona.edu/courses/schaffer/182h/Climate/Reconciling Warming Trends.pdf

 

[phyzguy]

More to the point, are the models, the modern models, actually overestimating warming? Gavin Schmidt and his co-authors in a recent little piece in Nature Geoscience don't think so.

I'm having trouble reconciling this quote with the following quotes from the Gavin Schmidt paper:

"Climate models projected stronger warming over the past 15 years than has been seen in observations."
"Why most of the model simulations suggest more warming than has been observed is a second question that deserves further exploration."

It seems clear that the models which were published before the data was available predicted more warming that was observed. At least three peer-reviewed studies are in agreement on this point. Of course, now that the data on the last 15 years is available, it is quite possible to adjust the models so that they "retrodict" the observed warming correctly. Are the models now correct so that they will predict the observed warming in the future? There are a variety of expert opinions on this point, and only time will tell who is right.

 

[Catamount]

I'm having trouble reconciling this quote with the following quotes from the Gavin Schmidt paper:
"Climate models projected stronger warming over the past 15 years than has been seen in observations."
"Why most of the model simulations suggest more warming than has been observed is a second question that deserves further exploration."

I see no contradiction at all. Climate models did project stronger warming than was seen, and Schmidt et al's work to correct that was just some preliminary toying, not even published in a formal paper it looks like, with some small remaining disagreement, so of course there's more work/investigation to be done.

It seems clear that the models which were published before the data was available predicted more warming that was observed. At least three peer-reviewed studies are in agreement on this point. Of course, now that the data on the last 15 years is available, it is quite possible to adjust the models so that they "retrodict" the observed warming correctly. Are the models now correct so that they will predict the observed warming in the future?

Unless I'm reading something wrong, then to be clear, Schmidt et al didn't change the models at all. They changed the inputs. I don't see any place where they changed how the models are actually treating climate. They didn't change the ocean mix layer depth or cloud behavior or some other aspect of how climate works. The problem was that the models were being fed incorrect forcings in the first place, so of course they're going to return incorrect temperatures. If the models are working remotely correctly then you can't get correct results by running the wrong scenario through them in the first place. Once that was corrected, the models, otherwise unadjusted, gave results fairly close to observation. This is indication that the models were always working, not some new way to change and fix them.

As they summarize, "Here we argue that a combination of factors, by coincidence, conspired
to dampen warming trends in the real world after about 1992. CMIP5 model simulations were based on historical estimates of external influences on the climate only to 2000 or 2005, and used scenarios (Representative Concentration Pathways, or RCPs) thereafter. Any recent improvements in these estimates or updates to the present day were not taken into account in these simulations. Specifically, the influence of volcanic eruptions, aerosols in the atmosphere and solar activity all took unexpected turns over the 2000s"

That's not them saying "the models are doing something wrong"; that's them saying "we didn't put the right data into the models".

As for whether models can predict warming, I'm not sure what you mean. Obviously they will never be able to predict the future, but models have been making correct predictions about forcing-temperature response, including multidecal temperature trends, for decades. Even Hansen et al 1988 was doing that fine for awhile, and other works have successfully predicted other aspects of climate as well (eg Hansen et al. 1992 successfully predicting the Pinatubo response). As far as I can tell, they largely just diverge when the real-world forcings diverge from the scenario in the model, and that's not the model's fault. Do models still need work? Sure. Are they completely off-base about how they treat climate? I really don't think so, especially where sensitivity is concerned, because high sensitivity makes sense of an awful lot of climatic observations, and every attempt at constraint, regardless of method and observation, returns a fairly similar value, whether it's ECS from the Last Glacial Maximum (and even outliers there, like Schmittner et al. 2011, still don't diverge hugely), or via water vapor feedback measurements from Pinatubo, or any of half a dozen other radically different methods, all basically returning the same range of numbers (~2.5-3C for most likely values).

The long and short of it is that as best as I can tell Moncton et al's basic contention about sensitivity just doesn't make any sense, and hillariously bad methods aside, is essentially entirely irreconcilable with basically every observation about climate ever made.

 

[PeterDonis]

The problem was that the models were being fed incorrect forcings in the first place

But if we're trying to use the models to make predictions, we don't know the forcings in advance.

Also, one of the items they corrected was ENSO, which is not an external forcing; it's an internal mode of variability. If they can't correctly predict ENSO's behavior, then that's a significant limitation in the models themselves, not in the data they're being fed.

 

[Catamount]

But if we're trying to use the models to make predictions, we don't know the forcings in advance.

Also, one of the items they corrected was ENSO, which is not an external forcing; it's an internal mode of variability. If they can't correctly predict ENSO's behavior, then that's a significant limitation in the models themselves, not in the data they're being fed.

In short, you're saying computer models will never (at least within in foreseeable future timeframe) be able to literally predict the future. I think that was always understood.

Computer models by their very nature can only offer scenarios, giving some idea of how climate might behave under certain conditions. That's a very powerful tool both for learning why climate behaved certain ways in the past for scientific curiosity, and offering risk assessments or useful geoeningeering data going forward. That they'll never be crystal balls is not, as far as I'm concerned, a weakness, because neither is anything else in science.Yes, the inability to explain what ENSO is going to do is a concern, because that is perhaps within the purview of what models are supposed to do. I'm not sure ENSO is ever really going to matter on multidecadal timescales, and if it doesn't it's neither here nor there. Is that really relevant to a discussion of Moncton et al (2015)? I don't think it is, because unless there's a relationship between CO2 change and ENSO behavior, it's not going to change climate sensitivity on any timescale (ie neither TCR nor ECS). At most, it's just one in a big list of source of semi-random fluctuation in the climate system, and mostly just on scales of a few years as far as I know. That climate is going to fluctuate in ways we can't predict for a long time, and that the best we can do is figure out how we might be biasing long term trends as it does, seems to go without saying.

 

[PeterDonis]

I'm not sure ENSO is ever really going to matter on multidecadal timescales

I'm not so sure. If the fraction of time that ENSO spends in the La Nina mode as opposed to the El Nino mode can change on those timescales, then that's a potentially significant change in the climate, even if each individual cycle only takes a few years to run.

 

[PeterDonis]

That they'll never be crystal balls is not, as far as I'm concerned, a weakness, because neither is anything else in science.

There are no perfect crystal balls anywhere in science, true. But the degree to which science's crystal balls approach perfection varies greatly between scientific fields. And what really matters is the accuracy of prediction that is possible relative to the accuracy that is needed to make it sensible to invest huge amounts of resources. In some fields, we have that level of accuracy--in astronomy, for example. If astronomers were to say that they predict that a certain asteroid will hit the Earth in, say, 2037 unless we do something, that prediction would be worth betting large amounts of resources on. But climate science is not one of those fields. That doesn't mean it isn't a valid science; it just means it hasn't reached that level of accuracy.

 

[Catamount]

I think we're largely on the same page here.

I agree that ENSO could definitely count for a lot more than we realize. On the rare occasions I had an opportunity to take a climatology course here or there, the first person I studied under actually lamented that we knew far, far too little about just about all teleconnections, largely because the focus for research just hasn't been there until very recently. He liked to characterize the state of the research by the IPCC Assessment Reports, and I suppose that is their purpose, and I recall him noting that in summarizing the science TAR barely mentioned teleconnections, and that it wasn't until the later research that made it into AR4 that there seemed to be a general scientific consensus that they were actually something really important.

It doesn't of course mean that ENSO is anything important, but yeah it definitely could be. Who knows, maybe external forcings even do influence the time spent in positive or negative phase or the magnitude of one or both.I do also agree that climatology doesn't come anywhere near the accuracy of some other fields of science. I'm loathe to call that a criticism, because it's generally a very hard science to get good data for, but you're right that that has significant implications when weighing climatology's predictions in any kind of risk assessment. Now it should be noted I think that, as Mike Mann is fond of saying "uncertainty cuts both ways", ie things could well be worse than climatologists understand them to be rather than better, but generally speaking I agree that we have to be careful in discussing potential actions to take not to get overzealous given the uncertainties.

Of course, one of the big advantages of dealing with climate vs an asteroid is that if we're smart, we may have opportunity to have our cake and eat it: deal with potential climatic change while doing things we ought to be doing anyways. There needn't be steep net costs to any endeavor outside of their utility in mitigating climatic changes. Unfortunately I fear that might be getting too far outside the purview of this discussion. I'm new on this forum, so I'm sure you know better where that line is drawn than I.

 

[PeterDonis]

it should be noted that, as Maike Mann is fond of saying "uncertainty cuts both ways", ie things could well be worse than climatologists understand them to be rather than better

This is true, but it doesn't make the climatologists' ability to predict what will happen any more accurate, so scientifically speaking it's irrelevant. It could be relevant in a discussion about judgment calls outside the purview of science, but that's a separate issue; see below.

if we're smart, we may have opportunity to have our cake and eat it: deal with potential climatic change while doing things we ought to be doing anyways.

I agree; but as you say, this is getting into the area where PF discussions are generally not supposed to go, since we're now starting to talk about matters of judgment in an area where science's ability to tell us what will happen is limited, rather than the science itself.

 

[johnbbahm]

I was looking at the GISS data set, and noticed something that may be part of the reasons the
Models are running hot.
http://data.giss.nasa.gov/gistemp/tabledata_v3/SH.Ts+dSST.txt
http://data.giss.nasa.gov/gistemp/tabledata_v3/NH.Ts+dSST.txt
The higher anomaly temperatures seem to occur in the colder months of the hemisphere.
temperatures averages , are unlikely to be from higher highs during the
"winter" months, the low temperatures must not be going as low, and increasing the average.
I was trying to think why CO2 would only preform it's quantum greenhouse function during the night.
I was thinking of a population inversion, from sunlight excited nitrogen, vibrationally exciting CO2.
During the daytime, there is likely an endless supply of excited nitrogen, continuously pumping
any available CO2.
The 14 um ground emission finds no absorbers, because they are all busy, in the sunlight hours.
At night the CO2 does absorb and re-emit, but the effect is like a thin layer of clouds.
This would be enough to mess the models up a bit.
It would also be fairly easy to test.
A daytime blue sky spectrum, should not have much of CO2 primary lines at 9.6 and 10.6 um.
If those lines are there, they did not come from being pumped at 14 um.

 

[Bystander]

The higher anomaly temperatures seem to occur in the colder months of the hemisphere.

"Seem?" There's not really anything in the table that reaches out and grabs attention one way or the other.

temperatures averages , are unlikely to be from higher highs during the
"winter" months,

Do you have any basis for such an assertion?

the low temperatures must not be going as low, and increasing the average.

Are you aware of the various methods used for measurements of daily highs and lows and how they've changed over the past century?

 

[johnbbahm]

"Seem?" There's not really anything in the table that reaches out and grabs attention one way or the other.

Do you have any basis for such an assertion?

Are you aware of the various methods used for measurements of daily highs and lows and how they've changed over the past century?

In the GISS data set, 3 months out of 12 NH and 12 SH caused the majority of the increase.
Those months were March, April, and December of the Northern Hemisphere.
The zone maps further broke it down to show the highest average zones were between 44 and 90 degrees north.
What is the likelihood of places say north of a line about Columbus, OH reporting record breaking annual highs,
in March, April, and December?

I am aware the GISS talks about this http://data.giss.nasa.gov/gistemp/abs_temp.html
I think their answer should raise questions about consistency of sampling.
"Q. What do we mean by daily mean SAT ?
A. Again, there is no universally accepted correct answer. Should we note the temperature every 6 hours and report the mean, should we do it every 2 hours, hourly, have a machine record it every second, or simply take the average of the highest and lowest temperature of the day ? On some days the various methods may lead to drastically different results."

 

[D H]

In the GISS data set, 3 months out of 12 NH and 12 SH caused the majority of the increase.

The data do not warrant you saying that. You cannot look at one year. All it takes is a prolonged warm spell in December to completely mess up the statistics for that particular December, or a prolonged cool spell in March.

Climate, and hence climate change, is what happens over longer periods of time. When you look at (for example) the years 2001 to 2014, you'll see

• That temperature rise is more evenly distributed across the calendar than it is for anyone year.
• That there's a lot more year-to-year variability from late fall to early spring than there is from late spring to early fall. Summertime is easy to predict in much of the world. It's going to be hot. Fall, winter, and spring? That's when weather forecasters don't do so well at forecasting.
• On an even longer scale, you'll see that the shift from winter to summer is getting earlier in the year, and the shift from summer to winter is getting later in the year.

 

[D H]

Actually 2014 being the hottest year was directly influenced by those 3 hot months in the NH.

Even if you only look at 2014, what you wrote a couple of posts back ("In the GISS data set, 3 months out of 12 NH and 12 SH caused the majority of the increase.") is not true.

Picking the northern hemisphere data from the three months that exhibited the greatest warming in the northern hemisphere and the southern hemisphere data from the three months that exhibited the greatest warming in the southern hemisphere is naturally going to result in more than 1/4 of the warming (which is what you'd get if the warming was uniform across the calendar). That's to be expected; you've cherry-picked the most extreme data. It does not account for the majority ("over half") of the increase. It's more like 1/3.

 

[johnbbahm]

Even if you only look at 2014, what you wrote a couple of posts back ("In the GISS data set, 3 months out of 12 NH and 12 SH caused the majority of the increase.") is not true.

Picking the northern hemisphere data from the three months that exhibited the greatest warming in the northern hemisphere and the southern hemisphere data from the three months that exhibited the greatest warming in the southern hemisphere is naturally going to result in more than 1/4 of the warming (which is what you'd get if the warming was uniform across the calendar). That's to be expected; you've cherry-picked the most extreme data. It does not account for the majority ("over half") of the increase. It's more like 1/3.

Actually, I just look again, they averaged NH and SH month by month, if just one month March NH 2014 dropped to normal,
I used 80, it brings the average down to 66, and there are still two more abnormally high months.
If I substitute in an abnormally high 85 for each of those months the average for the year drops to 65.
So it is true that those 3 months in the NH threw off the average.