One might assume that people would be happy that the latest version of the Hadley Centre and CRU combined temperature index is now being updated on a monthly basis. The improvements over the previous version in terms of coverage and error estimates is substantial. One might think that these advances – albeit incremental – would at least get mentioned in a story that used the new data set. Of course, one would not be taking into account the monumental capacity for some journalists and the outlets they work for to make up stories whenever it suits them. But all of the kerfuffle over the Mail story and the endless discussions over short and long term temperature trends hides what people are actually arguing about – what is likely to happen in the future, rather than what has happened in the past.
The fundamental point I will try and make here is that, given a noisy temperature record, many different statements can be true at the same time, but very few of them are informative about future trends. Thus vehemence of arguments about the past trends is in large part an unacknowledged proxy argument about the future.
So here are a few things that are all equally true, conveniently plotted for your amusement:
- The linear trend in HadCRUT4 from August 1997 to August 2012 (181 months) is 0.03ºC/decade (blue) (In GISTEMP it is 0.08ºC/decade, not shown).
- The trend from August 1975 to July 1997 is 0.16ºC/dec (green), and the trend to August 2012 is 0.17ºC/dec (red).
- The ten years to August 2012 were warmer than the previous 10 years by 0.15ºC, which were warmer than the 10 years before that by 0.17ºC, which were warmer than the 10 years before that by 0.17ºC, and which were warmer than the 10 years before that by 0.17ºC (purple).
- The continuation of the linear trend from August 1975 to July 1997 (green dashed), would have predicted a temperature anomaly in August 2012 of 0.524ºC. The actual temperature anomaly in August 2012 was 0.525ºC.
The first point might suggest to someone that the tendency of planet to warm as a function of increases in greenhouse gases has been interrupted. The second point might suggest that warming since 1997 has actually accelerated, the third point suggests that trends are quite stable, and the last point is actually quite astonishing, though fortuitous. Since all of these things (and many others) are equally true (in that their derivation from the underlying dataset is simply a mechanical application of standard routines), it is clear that our expectation for the future shouldn’t be simply based on an extrapolation of any one or two of them – the situation is too complex for that.
There are two main responses to complexity in science. One is to give up studying that subject and retreat to simpler systems that are more tractable (the ‘imagine a spherical cow’ approach), and the second is to try and peel away the layers of complexity slowly to see if, nonetheless, robust conclusions can be drawn. Both techniques have their advantages, and often it is the synthesis of the two approaches that in the end provides the most enlightenment. For some topics, the two paths have not yet met in the middle (neuroscience for instance), while for others they almost have (molecular spectrometry). The climate system as a whole is one of those topics where complexity is intrinsic, and while the behaviour of simpler systems or subsystems is fascinating, one can’t avoid looking directly at the emergent properties of the whole system – of which the actual temperature changes from month to month are but one.
We have found some ways to peel back the curtain though. For instance, we know that the shifts in equatorial conditions associated with El Niño/Southern Oscillation (ENSO) in the Pacific have a large impact on year-to-year temperature anomalies. So do volcanoes. Accounting for these factors can remove some of the year-to-year noise and make it easier to see the underlying trends. This is what Foster and Rahmstorf (2011) did, and the result shows that the underlying trends (once the effects of ENSO are subtracted) are remarkably constant:
Another way one might deal with the seemingly contradictory tangle of linear trends is to impose a constraint that any linear fits must be piecewise continuous i.e. every trend segment has to start from the end of the last trend segment. Many of you will have seen the SkepticalScience ‘Down the up escalator’ figure (a version of which featured in the PBS documentary last month) – which indicates that in a noisy series you can almost always find a series of negative trends regardless of the long term rise in temperatures. You will have noted that the negative trends always start at a warmer point than where the previous trend ended. This is designed to make the warming periods disappear (and sometimes this is done quite consciously in some ‘skeptic’ analyses). The model they are actually imposing is a linear trend, followed by an instantaneous jump and then another linear trend – a model rather lacking in physical basis!
However, if one imposes the piecewise continuous constraint, there are no hidden either warming or cooling jumps, and it is often a reasonable way to characterise the temperature evolution. If you looked for a single breakpoint in the whole timeseries i.e. places where the piecewise linear trend actually improves the fit the most, you would pick Apr 1910, or Feb 1976. There are no reasons either statistically or physically to think that the climate system response to greenhouse gases actually changed in August 1997. But despite the fact that August 1997 was shamelessly cherry-picked by David Rose because it gives the lowest warming trend to the present of any point before 2000, we can still see what would happen if we imposed the constraint that any fit needs to be continuous:
A different view, no?
But let’s go back to the fundamental issue – what do all these statistical measures suggest for future trends?
If we assume for a moment that the ENSO variability and volcanoes are independent of any change in greenhouse gases or solar variability (reasonable for volcanoes, debatable for ENSO), then the work by Foster and Rahmstorf, or Thompson et al (2009) to remove those signals will reveal the underlying trends that will be easier to attribute to the forcings. This is not to say that ENSO is the only diagnostic of internal variability that is important, but it is the dominant factor in the global mean unforced interannual variability. Given as well that we don’t have skillful predictions of ENSO years in advance, future trends are best thought of as being composed of an underlying trend driven by external drivers, with a wide range of ENSO (and other internal modes) imposed on top.
We can derive the underlying trend related to external forcings from the GCMs – for each model, the underlying trend can be derived from the ensemble mean (averaging over the different phases of ENSO in each simulation), and looking at the spread in the ensemble mean trend across models gives information about the uncertainties in the model response (the ‘structural’ uncertainty) and also about the forcing uncertainty – since models will (in practice) have slightly different realisations of the (uncertain) net forcing (principally related to aerosols). Importantly, the ensemble mean trend is often closely related to the long term trend in any one specific realisation, while the short term trends in single realisations are not.
In any specific model, the range of short term trends in the ensemble is quite closely related to their simulation of ENSO-like behaviour. I say “ENSO-like”, rather than “ENSO” since the mechanisms resolved in the models vary widely in their realism. Consequently, some models have tropical Pacific variability that is smaller than observed, while for some it is larger than observed (this is mostly a function of the ocean model resolution and climatological depth of the equatorial thermocline – but a full description is beyond the scope of a blog post). Additionally, the spectra of ENSO-like behaviour can be quite different across models, or even for century scale periods in the same simulation (see this presentation on the GFDL model by Andrew Wittenberg for examples). Thus it is an open question whether the CMIP3 or CMIP5 models completely span the range of potential ENSO behaviour in the future – and that is assuming that there is no impact of climate change on the ENSO statistics. Though if there is an effect in the real world, the century-scale variance seen in the GFDL model for instance, would mean that it will take a long time to reliably detect in the observations.
We saw above that the ENSO-corrected underlying trends are very consistent with the models’ underlying trends and we can also see that the actual temperatures are still within the model envelope (2012 data included to date). This is not a very strong statement though, and more work could perhaps be done to construct a better forecast using the underlying trends in the models and statistical models for the ENSO and internal variability components inferred from observations, rather than purely from model realisations. It is also worth pointing out that the CMIP5 estimates of ENSO variance might be significantly improved over what was seen in CMIP3.
So, to conclude, if you think that future ‘global warming’ is tied to the underlying long term trend in surface temperatures, there is no evidence from HadCRUT4 to warrant changing expectations (and no physical reasons to either). However, if you think that the best estimate of the future comes from extrapolating the minimum trend that you can find over short time periods in single estimates of surface temperatures, then you are probably going to be wrong.
References
- G. Foster, and S. Rahmstorf, "Global temperature evolution 1979–2010", Environmental Research Letters, vol. 6, pp. 044022, 2011. http://dx.doi.org/10.1088/1748-9326/6/4/044022
- D.W.J. Thompson, J.M. Wallace, P.D. Jones, and J.J. Kennedy, "Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights", Journal of Climate, vol. 22, pp. 6120-6141, 2009. http://dx.doi.org/10.1175/2009JCLI3089.1
Aaron Lewis @ 38 – “In La Nino, global air temperatures cool, and that heat goes where? Well, some of it goes into the ocean. In the real world, sometimes air does heat water, and sometimes water does transfer heat to air.”
It’s almost as if you’re immune to learning. This is what Professor Minnett wrote in the Real Climate post I directed you to:
“…..how can a forcing driven by longwave absorption and emission impact the ocean below since the infrared radiation does not penetrate more than a few micrometers into the ocean? Resolution of this conundrum is to be found in the recognition that the skin layer temperature gradient not only exists as a result of the ocean-atmosphere temperature difference, but also helps to control the ocean-atmosphere heat flux.
The ‘skin layer‘ is the very thin – up to 1 mm – layer at the top of ocean that is in direct contact with the atmosphere). Reducing the size of the temperature gradient through the skin layer reduces the flux. Thus, if the absorption of the infrared emission from atmospheric greenhouse gases reduces the gradient through the skin layer, the flow of heat from the ocean beneath will be reduced, leaving more of the heat introduced into the bulk of the upper oceanic layer by the absorption of sunlight to remain there to increase water temperature”
You are, of course, entitled to believe whatever you wish, but isn’t misinformation best left to the contrarians?
Hank Roberts @ 49 – google “parameterization”, as it applies to climate modelling. It is not the same as simulating an actual physical process.
Re- Comment by PAber — 4 Nov 2012 @ 1:18 AM:
You say- ” In parallel, on developing the models with an open mind. Not to search for proof of AGHG influence or to scare the public, but to understand what is happening. I track the political efforts on both sides, the “majority” and the “sceptics” (or if one prefers another type of language, the “alarmists” and the “deniers”) and I see that too much of the discussion has changed into nonscientific grounds. Too many scientists have become politicians, ready to support their camp anyway they can.”
Because this statement was made in the context of doing actual climate science, you are referring to a fairly large group of scientists and suggests to me that you must be aware of a sizable subgroup of practicing climate scientists that elicit this behavior. I am not aware of this trend. I would be interested in hearing of some reliable evidence for this statement. Steve
Regarding the issue of non-linearity raised by PAber, Chris Korda, and others:
These are all interesting points, but no model (of any complexity that I am aware of) shows evidence of behavior that deviates significantly from global temperature being a relatively smooth function of CO2 concentration, at least over the range of conditions we are interested in for the global warming problem.
In fact, a substantial body of work has shown that global temperatures are a linear function of CO2 emissions, with the total cumulative carbon emissions from humans providing a useful metric in determining the peak amount of global warming. It is also here where one needs to discriminate between long-lived forcings such as CO2, and short-lived forcing agents such as methane or aerosols, which can dominate the short-term behavior of global temperature, but have no discernible impact on the century-to-millennium scale trend.
It is of course possible that Earth resides rather close to a bifurcation point, analogous to a Snowball Earth scenario, but there’s little indication in the Holocene or Pleistocene record that such a tipping point is readily triggered. These scenarios do play out in simulations over a rather broad range of forcing (Gary Russell’s model at NASA GISS produces such behavior around 8xCO2-16xCO2 due to rapid cloud changes) and one can also look at warm climates of the past (e.g., the Pliocene, with boundary conditions very similar to today, but with a pretty different climate). Identifying where these bifurcations are and the degree to which hysteresis exists in the system is still a big question in climate sensitivity, and one in which some current methodologies of answering the question are inadequate.
re 51
Rob,
My background is chemical engineering. I rose to be Senior Scientist at one of the world’s largest engineering firms because I asked better questions (And, because I was good at finding mistakes, such as unwarranted assumptions.)
My areas of expertise were hazardous waste; environmental fate and transport; risk assessment and control; environmental sampling, analysis, and data management; and climate change.
I find that the use of technical language tends to restrict the paradigms available for analysis of the question. Thus, I try to ask questions in the most general language possible.
I spent a fair amount of time writing US DOE manuals, and I do tend to get stuff correct. I choose my teachers with great care
Actually, there are a fair number of rather competent old guys around, and here, today, you have been condescending to at least two of us.
#54 Chris Colose: I presume you mean a linear function of log(CO_2 concentration).
As for nonlinearities, these are most likely to happen in easily observable effects like sea ice loss.
Aaron,
Fear not. There appear to be many with a similar condescending attitude, and some are not even scientists! You previous points are issues that definitely need to be answered, but have not been addressed thoroughly. Some cannot at the moment. The recent La Nina seems to be the catchall for many of the recent observations; cooling, sea level decline, droughts, floods, Sandy, etc.
I find nothing wrong with posing questions in the most general manner possible. Oftentime, the use of technical language is meant to impress and demean, rather than address the issue at hand. I too feel that the ENSO/atmospheric interaction is much more important in global climate than many other people contend.
My areas of expertise were hazardous waste; environmental fate and transport; risk assessment and control; environmental sampling, analysis, and data management; and climate change.
That may be so old timer, but some of us have been around long enough to know that ounce of prevention is worth a metric ton of remediation, and understand that your work is for the most part a result of bad decisions by these so called experts which have resulted in easily preventable environmental catastrophes, many of them large scale and ongoing. When you can address that, let me know.
Thanks.
[Response: I try a different way. To your point 3 the answer is yes – the ocean surface is on average warmer than the overlying air, because the ocean absorbs a lot of heat from the sun, part of which it passes on to the air above. Your confusion arises simply because we are now discussing how the bulk of the ocean below the skin layer gets heated. Thus we are talking not about the gradient between sea surface and overlying air, but we are talking about the gradient through the skin – i.e., the water temperature difference between the top and bottom of the skin layer, which controls how heat flows across this layer, from the bulk of ocean water below to the surface. Obviously, if you heat the top of the skin layer, this reduces the heat flow across this layer from below. Clear? Or still confusing? -stefan] …
Just guessing here, but I think the above response in the comments for the RC article by Minnett discusses where Rob Painting thinks Aaron Lewis is misunderstanding the skin layer and how the enhanced GHE slows heat loss from the oceans, which, obviously, results in increased OHC.
On Rob’s point about La Nina driving ocean heat to deep layers, that makes sense to me, but I haven’t found much to confirm it on Google Scholar. As for its consequences, one scientist says the additional heat in the 700-meter to 2000-meter layer, and deeper, will come out and get us. Another says it’s locked up in Neptune’s brig for years numbered in the thousands.
El Ninos appear to increase the surface air temperature. La Nina appear to cool it. This seems to be absent of controversy.
But how they do this is really two very different processes, and they are often described as simply undoing the similar work of the other. I do not see how that can be the case.
It all could use a very precise RC article: the different ways and timescales by which heat transfers between the atmosphere and the oceans (including what happens to it), and whether anything actually could stall what appears to be a continual warming of the oceans during the alleged “pause” in global warming?
Re 58
I wish! I did a lot of work on the cleanup of the Hanford Washington plutonium production facility in the 1990s. Much of the worst contamination was a result of structures that my boss had designed as a junior engineer 30 years before.
He was not a bad guy. He built what “management” had told him to build, and management was in a panic over the cold war. By then, they all knew better, but they went ahead and dumped all that radioactive material into the soil.
The lesson is one that should be taken to heart. Not dumping is always cheaper than trying to cleanup afterward. A little thinking and planning can save a huge amount of money, health issues, and even lives. This includes radioactive materials, toxics, and green house gasses.
“Management” is always panicked about something. Then, it was the cold war, now it is the “economy.” The least damage to the economy will be caused by the least emissions of GHG. More AGW will require more government intrusion into our lives. Conservatives should be the strongest opponents of fossil fuel emissions.
Philip,
I actually didn’t have CO2 concentrations in mind, but the relation between cumulative carbon emissions and peak global temperature (something in the neighborhood of 2 C per 1000 GtC) which has been identified as being nearly linear over a reasonable range (see the NAS 2011 Climate Stabilization Report).
Because the human influence on climate can be represented by a single statistic, cumulative carbon, it can provide an alternative metric -just like GWP or CO2-equivalent, in thinking about the evolution of global temperatures.
But concerning the main point, the radiative impact of adding CO2 to the atmosphere in isolation is a solved problem, and it doesn’t feature any rapid behavior changes over a narrow concentration range. Consequently, any ‘threshold’ behavior that exists in the system must arise from the collective interaction of the various feedbacks. Arctic sea ice loss can be an example of a tipping point, but it’s primarily a tipping point for nothing else than itself (i.e., Arctic sea ice loss, and associated ecological systems, etc)– but without much impact on the energy budget of the entire planet or on global climate sensitivity. That doesn’t mean it’s unimportant, but should be kept in perspective for the climate sensitivity issue.
> Rob Painting … google “parameterization”,
> as it applies to climate modelling
Here ya go:
What are parameterisations?
> bad decisions by these so called experts which have
> resulted in easily preventable environmental catastrophes
Those making decisions may believe they and theirs will be exempt from the consequences if the decisions are wrong.
This may have to do with discounting the future value of anything, which economists do.
Some of the previous discussion seemed to confuse two types of linearity (a)climate models for which temperature depends linearly on ln(CO2); (b) CO2 time histories for which ln(CO2/CO2ref) increases linearly with time. First note that (b) is far from true. If we take the NASA CO2 data it is clear that the slope of ln(CO2/CO2ref) changes considerably with time. For example, taking some time periods with roughly constant slope, we have (slope x 1000 for easy reading):
1900 – 34: 1000*slope = 1.23/year (note CO2ref does not affect the slope)
1935 – 49: 1000*slope= 0.114/year (Depression, WWII etc)
1950 – 58: 1000*slope= 1.67/year (recovery stage 1)
1959 – 75: 1000*slope=2.92/year (now things are moving)
1976 – 94: 1000*slope=4.36/year (more and more growth)
1995 – 2011: 1000*slope=5.11/year (China kicks in?)
It is quite evident that the current slope of ln(CO2) is much greater than that for 1900-34.
On the other hand, if you correlate the temperature anomaly to ln(CO2) (see 43 ), then you find a good linear relationship (Anom =0.17+3.12ln(CO2/341) deg K; rsq~0.86). This statistical model predicts a transient 2 deg K increase for CO2 doubling, in good agreement with the big models. To me this is not surprising since 2 deg K only represents a 0.7% increase in the average global absolute temperature. The big problem is that human civilization is extremely sensitive to small changes in the long-term average temperature.
The increasing rate of increase of ln(CO2) presumably reflects economic developments. Having just spent a year in China I would not be surprised to see the slope of ln(CO2) increase quite a lot more. I tried fitting the current CO2 data to a logistics function, and that worked extremely well. If the future is like the past then CO2 will reach 560 ppm by 2060. But given the noise in the temperature signal it may be a while before the consequences can no longer be ignored by anyone.
PAber,
If I may say so, you have an utterly bizarre idea of how physical models are built. You seem to think that unless the entire model springs full grown from the head of Feynmann that it will be worthless for prediction. This is utter horse crap.
Climate models have a pretty good track record of successful predictions.
http://bartonpaullevenson.com/ModelsReliable.html
That you do not realize this is telling. Might I suggest choosing another orifice out of which to speak.
To Ray Ladbury, who wrote:
[PAber,
If I may say so, you have an utterly bizarre idea of how physical models are built. You seem to think that unless the entire model springs full grown from the head of Feynmann that it will be worthless for prediction. This is utter horse crap.
Climate models have a pretty good track record of successful predictions.
http://bartonpaullevenson.com/ModelsReliable.html
That you do not realize this is telling. Might I suggest choosing another orifice out of which to speak.]
A point by point reply is in order:
Working as active physicist for over 30 years I may have some preconceptions as to how one build models and when one judges them to be adequate. No, I do not think they are jump out of someones head “complete and perfect”, except for some very rare, very fortunate cases. Especially for the climate modelling, which attempts to deal with an extremely complex system. So, by all means we should work on improvements, step by step.
But to judge if the current status of the models is good enough to call their results “predictions” is another matter. My remarks were based on the figure provided by Gavin, which show clearly a huge spread of results (both hind- and forecasted. Extrapolated to 100 years these would diverge even more. Yet, we happily postulate, to the public, simple numbers: 3C by the end of the century, or 5C or whatever the current fancy is. I question the validity of using the model results in such political aims. Because science can be (and will be) improved, as we gather more data, make more accurate guesses as for the feedback mechanisms etc. But the public propaganda can not be “retracted” as easily as a research paper.
When 1 standard deviation (to quote Gavin) is about 75% of the modelled effect (see Gavin’s reply to my first post) then, in my opinion, the model result is crap (to use your word). Unless you WANT to use it, for nonscientific purposes.
As for the personal suggestion – this is also very telling. To denigrate someone (anyone?) who disagrees is a clear sign of no other argument. My suggestion – if I may say so – is that your post would look much better without the last remark.
PAber,
First, climate is inherently about trends, so the criterion for a climate model is whether it is getting the trends more or less correct. Climate models do pretty well by such criteria.
Did you even bother to look at the list I linked to, or did you simply dismiss it out of hand? Because, certainly, the list includes some impressive successes that I think deserve more than a dismissive wave of the hand. I will reproduce it here for your benefit in case you find reading a link too burdensome.
That the globe would warm, and about how fast, and about how much.
That the troposphere would warm and the stratosphere would cool.
That nighttime temperatures would increase more than daytime temperatures.
That winter temperatures would increase more than summer temperatures.
Polar amplification (greater temperature increase as you move toward the poles).
That the Arctic would warm faster than the Antarctic.
The magnitude (0.3 K) and duration (two years) of the cooling from the Mt. Pinatubo eruption.
They made a retrodiction for Last Glacial Maximum sea surface temperatures which was inconsistent with the paleo evidence, and better paleo evidence showed the models were right.
They predicted a trend significantly different and differently signed from UAH satellite temperatures, and then a bug was found in the satellite data.
The amount of water vapor feedback due to ENSO.
The response of southern ocean winds to the ozone hole.
The expansion of the Hadley cells.
The poleward movement of storm tracks.
The rising of the tropopause and the effective radiating altitude.
The clear sky super greenhouse effect from increased water vapor in the tropics.
The near constancy of relative humidity on global average.
That coastal upwelling of ocean water would increase.
You can find links to the research on Barton’s page. Some of these predictions are not trivial at all.
You also seem to be confused with respect to the degree of expected. There are about a dozen independent lines of evidence, all of which favor warming of around 3 degrees per doubling of CO2. What is more, the probability distributions for this value are quite asymmetric–it is far more likely that if we are wrong, our estimate is too low than that it is too high.
Then there is the question of what we expect and need from climate models. We do not need to know with any accuracy what the temperature will be on Christmas day 2101. Rather, we need to be able to bound sea level rise and plan for the increase in drought expected. These are more robust results.
Moreover, even if you were correct that the models were unreliable, do you really think that favors inaction? Would you really rather be landing in a storm, at night without instruments than with instruments telling you that the landing will be difficult?
Finally, I really wonder where you have been practicing physics if a bit of rough language offends you. Physicists, of all scientific disciplines, are among the most blunt in telling their colleagues precisely what type of organic matter they are full of. You certainly would not have lasted long working with Pauli or Feynmann.
It is very clear, PAber that you are speaking well outside of your area of expertise. Might I suggest that you not make it a requirement that the voice that is trying to keep you from making an ass of yourself speak to you always in gentle terms.
“physicist” PAber @~66
I’m sorry you ran across our outspoken Ray Ladbury, but some slack should be extended to the first responders to climate nonsense. I’ve seen at least one post from you that raised questions about what you know and where you got your information. His work has been consistently reliable despite his acid tongue, or perhaps because of it.
A google search for you finds this mildly amusing effort about the physics department of Aberstwyth University, but I couldn’t find you.
http://www.youtube.com/watch?v=oR8mAVTn-Pg
As the daughter of a physicist (PW Anderson) who refuses to pronounce outside his specialties though he supports real climate science, I note announcing yourself as a physicist is not enough. (Nor, obviously, am I qualified even scientifically despite my familiarity with a whole lot of information, but I do pass the test of mostly not saying things about stuff I don’t know or understand.) There are some sterling examples of rogue physicists such as Freeman Dyson (technocrat), Lubos Motl (string theory), and too long a list of others, pronouncing outside their knowledge. There are also several who have had their words twisted and now have to defend themselves for opinions they don’t even hold, a depressing artifact of the truth-twisting machine.
I suggest you support your opinions with some more specific information about your experience and qualifications.
Re- Comment by PAber — 6 Nov 2012 @ 2:02 AM:
You say- “To denigrate someone (anyone?) who disagrees is a clear sign of no other argument.”
Ray Ladbury may be cranky, but he is a physicist who does know a fair amount about climate models and has expert experience with risk assessment. So how do you feel about someone who accuses a large group of scientists of scientific misconduct without any support whatsoever? On 4 Nov 2012 @ 1:18 AM, you accused scientists of closed minded searching for proof and trying to scare the public for political gain, and don’t wish to explain yourself. Should I assign your strange inexpert accusations to be politically motivated?
I am wondering how it is political when a large group of scientists, over quite a long period, report data with confidence intervals that provide evidence of potential serious consequences. How do you respond to a group of physicians who tell you that there is some probability of you having a serious condition? How about driving across a bridge or entering a structure that some engineers have condemned on a chance of failure? Are these professionals making political assessments? Steve
I find it dismaying to see some of the best minds in climate science, along with some of the best-informed laypersons I have encountered online, bogged down in this thread in arguing with ill-informed and/or dishonest deniers about whether global temperatures are in fact increasing, and similarly bogged down in another thread in arguing about whether sea levels are in fact rising.
These “arguments” have been long since won, folks. But this is exactly where the fossil fuel interests — who are ultimately the driving force behind all of the denial — want you to be, bogged down in endless arguments over this stuff.
This is not what the world needs from climate scientists now, or from well-informed and deeply concerned lay people.
What is needed, instead, is an emphasis on IMPACTS. On sound, scientific attribution of the onslaught of the weather of mass destruction — droughts, floods, heat waves, wildfires and superstorms — that global warming is already bringing down upon us.
The deniers have already moved on to that — because they know that’s what the public is concerned about now. And the deniers DO NOT WANT YOU TO GO THERE. They want you to go on fighting the battles that you have long since won, about whether global warming is even real, whether any warming has occurred, blah blah blah.
Because they know that once the public understands that global warming means the collapse of the food supply, and the destruction of cities, that there will, at long last, be an overwhelming demand for action.
@67 [Ray Ladbury]
1. Of course I am speaking outside my area of expertise. As far as you stick to strict “deep-down” climate studies. Still, this does not mean I can not evaluate the original post and the accompanying figures. Which – together, comprise a self-standing message addressed to? … {well, this is a question I try to answer by looking at the comments…)
2. While you provided the list of the successes of the models, you have not actually replied to my original point about the figure 4 and the relationship between model results and the observed values. Actually, Gavin was much more honest in answering the issue: the models recreate the observed global temperatures very crudely.
3. My point was simply that using joined linear trends *requires* some sort of explanation at to the origin of the abrupt change. May I ask: did you try to fit the HADCRUT data with linear and with quadratic formula yourself? Which gives a better fit?
Once you do this, as yourself: why, instead of immediately opposing it, not to search for mechanisms that change the trend? Each year, each more advanced data gathering programme brings us closer to understanding. I would accept if the data would show this way or that, without looking for excused, in the old tradition of “if the data do not fit the model, so much worse for the data”.
[Response: This is overly simplistic – data can be misinterpreted or contaminated, comparisons may not be apples with apples, additional unaccounted for effects may be present as well as models being wrong (or incomplete). To think that all apparent mismatches between observations and models must be because the model is wrong is foolish (as would be the converse). Each case is different. In the case of short term trends, one can quickly conclude that they are not predictable without perhaps initialisation of the ocean state at the beginning of the forecast period, and even then, it is very unclear whether there is any skill. They are therefore not a useful guide to the longer term predictions. – gavin]
4. Of course your points that they recreate other specific phenomena better may be valid. At the moment I have not the time to check all these – so I’ll assume you are right. The problem lies in the communication, not in physics: global temperature increase is one of the AGW hallmark signs, one of the most accessible to the public. I’ll repeat my question to Gavin: are you satisfied with the error bands in hind- and forecast?
[Response: The ‘errors’ are related mostly to the spread of single realisations as a function of different paths of the weather. These are not directly predictable beyond a week or so, and statistically, not beyond a a few years (at least experimentally). Is that satisfying? no. Is there much that can be done about it? not really. – gavin]
5. As for action/inaction – well this is an issue that falls far beyond mere climate model quality. Stupid action may be worse than inaction (in some cases). I am not sure if the proposed (or even imposed) actions, such as carbon credits/trading, are sensible. Or if the efforts/money put into some “green” technologies are, in fact, sensible. The problem lies in such a strong coupling between politics, economy, social movements and science. This has carried the polarization into research: funding feuds, quarrels, nitpicking reviews, accusations. This makes the general public susceptible to propaganda (on both sides!), lies, half-truths etc.
6. The blogosphere is even more prone to such discord. I am not surprised by the language you have used – I remarked that your post would be better without the last remark. For the very reason that if you really want to convince me it is better to stick to be polite. Of course, I may have gotten your goal of convincing me wrong. In which case the abusive language may have been the right tool.
> the spread of single realisations as a function of different paths
This should be repeated in simpler, clearer words whenever models are discussed.
Most people, I think, don’t consider that they’re looking at something that is run repeatedly (single realisations, one at a time,) and that runs a bit differently each time (different paths, one at a time) because [help?].
An example: each pingpong ball falls through the array of pegs in the bell curve demonstrator — each falling pingpong ball is a single realization, follows a single path, and ends up in one bin at the bottom. The result is — exactly — a picture of how error bands work out.
Here: https://www.google.com/search?q=bell+curve+ball+drop
Those model a single ball falling.
Now — imagine how a climate model would look.
I know this is old obvious stuff to many readers.
But I am sure it needs to be made clear, repeatedly.
Gavin’s explained it in words understandable by those who, er, already understand and need to be reminded — or who are using talking points.
Sincere new readers may need a little more help.
I am wondering if there are two things in front of us that are actually quite linked:
1. The precipitous decline in Arctic Ice volume that has been described by PIOMAS
2. The 15 year pause in apparent global temperature
Inspection of the PIOMAS Yearly Minimum Ice Volume chart shows me that the Arctic ocean has lost approximately 8000 cubic kilometers of volume since 1997. To melt this ice requires about 163 exajoules per year due to the latent heat that gets taken up when that ice is is melted. This 8000 cubic kilometers of ice has gone away and does not comeback each winter. Can the heat energy mopped up by the disappearance of this ice volume account for this 15 year hiatus in warming? (or is 163 exajoules/yr a “drop in the bucket” in global terms?)
Could it be that the temperature hiatus can be explained by Arctic circulation flows that have been taking the heat north where it has been soaked up as latent heat in this ice phase change? As Arctic ice volume loss, in essence, bottoms out later this decade, will global temperature rise resume “with a vengeance”?
Rob Ellis, you touch on a different question on this issue that I have. When is the cold weather we’ve been getting a kind of Arctic exhalation? The issue I’m reaching for, is when is it a case of cold leaving the Arctic and when more coincidental. I know my phrasing is inelegant and perhaps ambiguous, but I hope somebody can explain the difference between that and the ongoing extremes from the alteration of the jet stream so ably described by Francis et al.
Secular Animist, I have come to believe that answering the assertions of the likes of PAber are part of the function of RealClimate, unlike the endless nonsense proliferated by the likes of Dan H with his condescending tones that he appears to think hide his outright ignorance and political posturing.
Rob Ellis @73 — Due to natural variability, WMO defines climate as 30 or more years of weather data. Each decade has been warmer than the last since the 1950s.
Alternatively, consider the statistical analyses done by Tamino in his Open Mind blog, linked on the sidebar.
2. The 15 year pause in apparent global temperature
The 15-year pause shows up on some the surface air temperature series, but does it make sense versus observations?
1. sea level rise
2. sea ice
3. record high temperatures
4. ocean heat content
On Gistemp the 15-year trend is still positive. It remains positive to 11 years. To me that temperature series better agrees with with what is actually happening on the planet.
JCH @ 59 – “On Rob’s point about La Nina driving ocean heat to deep layers, that makes sense to me, but I haven’t found much to confirm it on Google Scholar.”
Perhaps the best illustration of this is in a paper by Roemmich & Dean (2011) – The global ocean imprint of ENSO. Note the upper 700 metres of ocean (60°N-60°S) shown in Figures 3(a) @ (b. During La Nina heat is buried in the subsurface ocean, whereas during El Nino the surface layer is anomalously warm. Note, also, how the globally-averaged sea surface temperature varies in concert with these ENSO phases – warmer with El Nino, cooler with La Nina.
This is a separate issue to the deep ocean warming in La Nina-like periods suggested by the climate modelling of Meehl (2011). Heat buried in the deep ocean will not re-surface for a very long time.
JCH – Note that the colour bar has been left out of Figure 3 in Roemmich & Dean’s paper, but it is the same as that in Figure 2.
#74–“I hope somebody can explain the difference between that and the ongoing extremes from the alteration of the jet stream so ably described by Francis et al.”
I don’t think there is a difference. When the jet stream meanders so far south, it creates an ‘exhalation’ of Arctic air. (We tend to notice this in Georgia, where I live!)
PAber,
I’ll admit to being sharp tongued–especially when someone violates a basic tenet of science–to-wit, that the experts are most likely the ones who best understand their field, and the probability of them benefiting from the critiques of neophytes is nil.
I worked for several years as an editor at a Physics magazine, and countless times, I ran into such prejudices–usually expressed by physicists who worked in nice, clean laboratories and contended that geophysics, oceanography, atmospheric science…(insert your favorite subfield to diss). I actually heard these educated idjits claim these fields “weren’t really physics/science.”
Now, listen to what I am saying. You are applying the wrong criteria to judging the models. First, the most valuable thing you get from scientific models is not “answers”, but rather insight. Thus, it is a mistake to try to use a model to predict behavior in a single year, or even a single decade. Second, when dealing with a discipline that is inherently concerned with trends, that is the criterion you must apply to the models–do they reproduce the trends more or less properly over the relevant timescales.
The relevant response to your question about whether one should fit a linear trend, two linear trends with a break or a quadratic is not to be found in figure 4,but rather in figure 2. It is quite easy to break the temperature series into decadal subsets that show no trend–and yet the temperature continues to rise over that entire period. Now it may be that this fact is trying to tell us something very profound–perhaps that once the atmosphere warms to a certain point, there is a hiatus in surface warming, and more heat flows into the deep oceans. And then warming resumes. Moreover, such a “hiatus” does not in any way alter the fact that the surface–or really, the top of Atmosphere must reach a certain temperature before equilibrium is restored. Thus, while interesting, this putative effect does not bear on the issue of whether climate change poses a serious threat.
As others have pointed out, I am a physicist. My research is very applied, and risk analysis plays a big role in my day job. I am not a climate scientist. I have devoted several years to trying to understand the field, though. And I would point out that countless other physicists and other professional scientists have made similar efforts, and that we have found that climate science holds together pretty well. This validation of the consensus is reflected in the opinions of our professional organizations and of the National Academies of Sciences in dozens of nations. Might I suggest, that if you are not seeing the concordance, perhaps it is because you are being presented with a learning opportunity rather than that you and you alone have found a deep flaw in a field you have devoted virtually no time to understanding.
Re-comments @ 77 & 78 – the paper is by Dean Roemmich & John Gilson. My bad.
Is the following OK?
1) CO2 (+ some other things) accumulation causes warming.
2) The rate of CO2 emitted has increased continuously, peicewise linearly with the global economy.
3) CO2 has accumulated nonlinearly (faster than straight-line).
4) The effect of accumulated CO2 on temperature is nonlinear (slower than straight-line).
5) Measured temperature has increased continuously but noisily.
If thats all true, then:
6) If CO2 (and others) were halted, so net GHGs were noisily constant, the temperature effect would stabilize? Or the rate of temperature increase would stabilize? I’m trying to get at whether GHGs are proportional to temp change or proportional to rate of temp change.
7) What is the CO2 accumulation-to-temperature-rise time lag like? e.g, if I converted CO2 to pencils faster than the emmision rate, how long would it take for temperature to trend down? Its not immediate, right?
I’m working my way through a view that
8) the globe will not stop increasing GHG emmisions for some decades
9) but it eventually will when other technology is ready (WAG 2040s)
10) so the rate of emmision will be lower than now, but the accumulated emmisions will be greater than now.
I’m trying to decide what happens in my theoretical world if concensus is right. By the IPCC 2007 estimate, temp would be something like 2C higher when my undefined magic tech takes over in the 2040s. How long would it take for temp to stabilize? Does it overshoot?
Someone here must have modelled that scenario. Advice appreciated.
Kevin (82) – I have tried some statistical modeling of the lag from CO2 increases to temperature increases. There is clearly a long term effect, but there is little or no short term effect. As far as I can tell, there is no noticable effect within six years. Some have found a short-term relationship (some 6-18 months) between temperature and CO2, but this is in the opposite causal direction due to out-gassing from the oceans due to increases in ocean temperature.
Thanks Marvell. Six years actually seems short for something as big as the planet.
Is there any literature on the topic?
I’m also now wondering whether the response for adding CO2 and taking it away should be symmetrical. I’m guessing not, it should take longer for temperature to fall in the absence of a fixed CO2 delta than it takes for it to rise with addition of an equal fixed CO2 delta. The shape of the day-night transitions in average hourly temperature charts for single locations should be a clue.
In any case you’ve injured one of my other ideas, that global economic activity like a recession should show up in the temperature anomoly series. The latest temp rise slowdown can’t be related to CO2 reduction during the 2007 crisis, because on a cause-delay-effect timescale it has not happened yet (for the thermometers).
Holy cow I just found the earlier post: “The lag between temperature and CO2. (Gore’s got it right.)” where its implied that the time lag I’m looking for could be thousands of years. At various points in the article it was decades (for methane), hundreds of years or thousands of years (for CO2).
Please clarify.
In this current article we have rising temperatures caused by added GHG like CO2. Is the rise between 1990 and 2000 primarily due to CO2 from the 1980s or from the 1880s?
[Response: The time for temperatures to start to respond to increased CO2 is short – you’ll see significant changes in a decade or two, even though the full response will be slower. The response of the carbon cycle to changes in temperature (and circulation etc.) is much slower (hundreds of years) and this is what you are seeing in the ice cores. – gavin]
Thanks,
So temperature increase from 1990 to 2000 would be due to CO2 from 1989, and also from 1889. The answer reads a bit vague but the answer to the ‘primarily’ condition seems to be 10-20 years before, closer to Marvell’s 6 yrs than the older article’s 100s of years. There should be a curve associated with it.
e.g. for an increment of GHG (like 1 gigaton of CO2) there would be an expected change in final temperature (like 1 degree C – not a real number, but I don’t know the real number). The temperature change would start immediately and settle asymptotically to 1C in a few hundred years.
Then, a historical net GHG emmissions vs time chart could be made with the GHG types broken into chunks of the reference size. I could substitute a delta-T versus time component for each chunk and answer my question about delays. Would be easy to do in Excel VBA if I had that curve.
I’m finding older posts and commentary helpful. Have you considered a FAQ page?
Start Here — the FAQ page
KevinM – In regards to what would happen if emissions ceased, you might want to look at the https://www.realclimate.org/index.php/archives/2010/06/climate-change-commitment-ii/ post.
Thanks KR that article did exactly what I had intended to do. Are any of the preexisting models published? Or at least the major equations that could be put into a C program.
Another off-the-wall question. The earths core is a lot hotter than its crust. Only a few miles under the ocean, its hot enough to melt rocks. Are there any papers that explain how much of earths heat is internally generated.
While the earths surface temperatures and oceans should be heating due to GHGs, there should also be some continuous super-long-term cooling happening when you look at the whole mass of the planet. i.e. in enough billions of years it should become a solid. What is the magnitude of the heat transferring from inside to the surface relative to solar radiation?
KevinM@89: I’ll leave others to give pointers to the models — as to heat from the earth’s interior, searching on the words “earth surface heat flux” will probably get you a long way. This is what they produce in Google Scholar, and this first result seems very informative. (This isn’t intended as one of those snippy “let me google that for you” responses, by the way — I recognize that it’s hard to google without knowing the standard terminology for the thing you’re looking for.)
Interestingly, the heat from the interior of the earth is not just gradual cooling from its time of formation: buried radioactive elements put out a lot of heat. (19th-century cooling-based estimates for the age of the earth were very inaccurate for this reason.)
Never mind.
“Total heat loss from the Earth is estimated at 44.2 TW. Mean heat flow is 65 mW/m2 over continental crust and 101 mW/m2 over oceanic crust. This is approximately 1/10,000 of solar irradiation.”
Forgive my overposting, I’m in a frantic reeducation phase.
KevinM @91 — I strongly recommend Ray Pierrehumbert’s “Principles of Planetary Climate”
http://geosci.uchicago.edu/~rtp1/PrinciplesPlanetaryClimate/index.html