Global Warming Concensus Broken

[tomclarke]

I think many people on this thread are missing the point. GC models are based on physics and tested (not fitted) over 100,000s of years of historical data.

So the fact that the recent 50 years of data may be difficult to disambiguate from noise effects (aerosols, which can be modelled well, PDO which cannot, yet) is not the point.

There are uncertainties, and mechanisms which have not yet been modelled. But nothing to stop people from modelling them, and it is agreement between a lot of different models that makes the case convincing.

Also there is absolutely no reason to expect remaining unmodelled effcts to be negative rather than positive feedback. For example biomass can generate methane on decay etc. What we DO know is that CO2, which significantly forces climate, has increased over last 50 years in an unprecedented way.

Best wishes, Tom

PS - I have not read the latest IPCC report (1K pages). What does it say about biomass? I think it would be helpful to compare it (in entirety) with statements being made on blogosphere before rubbishing it?

[MSimon]

Tom,

I just posted something by Pielke that says that they are fitted.

For them to be unfitted there would have to be no parameterization.

Let me hit it again:

The conclusion with respect to the Real Climate posting on “What is tuning” is that they inaccurately presented the actual limitations of parameterizations. They also did not accurately report that tuning involves many more tunable corefficients than they report.

Their sentence that

“Surprisingly, there are very few of these (maybe a half dozen) that are used in adjusting the models to match the data ”

is incorrect. The students in each of my modeling classes (see for the classes for modeling and scroll to the bottom of each for the students’ class presentations where they decomposed parameterizations in order to quantify the number of tunable parameters) have documented the large number of tunable parameters within each of the parameterizations. There are no exceptions; all parameterizations involve a number of tunable parameters.

Real Climate is “surprised” that there are “maybe a half dozen” tunable parameters. They should have not been surprised but have looked in more depth to ascertain if their conclusion was correct (which they are not). Climate Science would be glad to post a guest weblog from Real Climate if they disagree with the Climate Science conclusions.

Readers on want an in-depth analysis of the number of parameters used in selected parameterizations in atmospheric modeling can view this in chapters 7 to 9 my book

Pielke, R.A., Sr., 2002: Mesoscale meteorological modeling. 2nd Edition, Academic Press, San Diego, CA, 676 pp

http://climatesci.org/2008/11/28/real-c ... te-models/

[MSimon]

http://climatesci.org/2008/05/21/can-th ... s-of-data/

Over the last 4 years the oceans have been cooling. I am unaware of any model that predicts this.

In the Litmus Test, I proposed the values listed below as the amount of global warming that must be achieved so as to NOT reject the IPCC claim of continuing global warming (1 * 10**22 Joules corresponds to 0.61 Watts per meter squared). This value is below the IPCC 2007 estimate of global average radiative forcing of 1.72 Watts per meter squared (see Figure SPM.2 in the IPCC SPM).

These values can be compared with the best estimate of the annual average upper 700m ocean heat content change averaged over the last 4 years (which is when the data is most robust) based on the analysis of Willis et al. (2008; see) [and thanks to Josh Willis for providing this follow on analysis]. He estimates the global average warming rate for this time period, based on the upper ocean data, as -0.076 Watts per meter squared with one standard error as +/- 0.214 Watts per meter squared. This yields a best estimate of heat change of -0.48 * 10 ** 22 Joules over the last 4 years. The most positive value (using one standard deviation) is 0.88 * 10 ** 22 Joules.

-0.076 Watts per meter squared is cooling.

Thus the value of global warming of the last 4 years fails to agree with the IPCC projections (the values are not even close!). The agrument that this is too short of a time is spurious unless the modellers can account for where else in their model results the missing Joules went.

Moreover, this is not too short of a time period to compare with the models. Heat, unlike temperature at a single level as used to construct a global average surface temperature trend, is a variable in physics that can be assessed at any time period (i.e., a snapshot) to diagnose the climate system heat content. Temperature not only has a time lag, but a single level represents an insignificant amount of mass within the climate system.

The answer to the question on this weblog “Can the IPCC model projections of global warming be evaluated from just several years of observed data” is YES. The conclusion for the past four years is that the model projections are not skillful on this time period.

So if the earth is warming and the oceans are not (or not much) where is the heat going?

[tomclarke]

Willis et al published anomalous ocean cooling results in 2006 but noticed errors in their data and corrected the original paper (published August 2007):

Received 9 April 2007; accepted 17 July 2007; published 18 August 2007.

Citation: Willis, J. K., J. M. Lyman, G. C. Johnson, and J. Gilson (2007), Correction to “Recent cooling of the upper ocean”, Geophys. Res. Lett., 34, L16601, doi:10.1029/2007GL030323.

for those without access to online databases there is a copy here:
http://oceans.pmel.noaa.gov/Pdf/heat_2006.pdf

The 2008 paper is not yet published so it seems premature to quote from it (I also do not ahev it, and can't find a pre-publication copy). From anti-AGW websites the abstract includes:

Despite excellent agreement of seasonal and interannual sea level variability, the 4-year trends do not agree suggesting that systematic long-period errors remain in one or more of these observing systems.”

Consistent with the (published) note of anomalous results due to errors.

So this data hardly seems strong evidence as yet.

Furthermore - I though you said the models all predicted cooling till 2015? In which case one might expect ocean termpratures to decrease as well?

Given the large variabaility on many different time scales from long-term weather formations (el nino), solar output change, etc, I am sure you will not use the fact of decadal variability in global temperatures, which the models predict, as a reason to distrust them.

What I don't understand is why it is necessary for anti-AGW websites to leap upon flakey data and (model-predicted) medium-term cooling trends. None of this is inconsistant with the very carefully argued and debated conclusions of the IPCC reports, as our "best guess" of prediction probabilities. The threat posed by GW is a long-term 50-100 year threat.

And yes, of course it is all about probabilities - nothing is certain in this life except death.

best wishes, Tom

[tomclarke]

Re overfitting

Pielke has long attempted to argue against AGW (which does not of course invalidate his arguments). the issue of overfitting and tunable parameters is complex, and we need to know exactly which parameters are tunable and how they are tuned.

My understanding is that although individual aspects of the physics are not well understood theoretically, or too complex to model, they can be extrapolated from specific measurements relating to that aspect, independently from the global temperatures. So the models are fitted in specific areas to particular physical processes, not to temperature trends.

Are climate models just a fit to the trend in the global temperature data?

No. Much of the confusion concerning this point comes from a misunderstanding stemming from the point above. Model development actually does not use the trend data in tuning (see below). Instead, modellers work to improve the climatology of the model (the fit to the average conditions), and it's intrinsic variability (such as the frequency and amplitude of tropical variability). The resulting model is pretty much used 'as is' in hindcast experiments for the 20th Century.

......
What is tuning?
We are still a long way from being able to simulate the climate with a true first principles calculation. While many basic aspects of physics can be included (conservation of mass, energy etc.), many need to be approximated for reasons of efficiency or resolutions (i.e. the equations of motion need estimates of sub-gridscale turbulent effects, radiative transfer codes approximate the line-by-line calculations using band averaging), and still others are only known empirically (the formula for how fast clouds turn to rain for instance). With these approximations and empirical formulae, there is often a tunable parameter or two that can be varied in order to improve the match to whatever observations exist. Adjusting these values is described as tuning and falls into two categories. First, there is the tuning in a single formula in order for that formula to best match the observed values of that specific relationship. This happens most frequently when new parameterisations are being developed.

Secondly, there are tuning parameters that control aspects of the emergent system. Gravity wave drag parameters are not very constrained by data, and so are often tuned to improve the climatology of stratospheric zonal winds. The threshold relative humidity for making clouds is tuned often to get the most realistic cloud cover and global albedo. Surprisingly, there are very few of these (maybe a half dozen) that are used in adjusting the models to match the data. It is important to note that these exercises are done with the mean climate (including the seasonal cycle and some internal variability) - and once set they are kept fixed for any perturbation experiment.

......... (not really relevant, but may help some)......
How are models evaluated?
The amount of data that is available for model evaluation is vast, but falls into a few clear categories. First, there is the climatological average (maybe for each month or season) of key observed fields like temperature, rainfall, winds and clouds. This is the zeroth order comparison to see whether the model is getting the basics reasonably correct. Next comes the variability in these basic fields - does the model have a realistic North Atlantic Oscillation, or ENSO, or MJO. These are harder to match (and indeed many models do not yet have realistic El Niños). More subtle are comparisons of relationships in the model and in the real world. This is useful for short data records (such as those retrieves by satellite) where there is a lot of weather noise one wouldn't expect the model to capture. In those cases, looking at the relationship between temperatures and humidity, or cloudiness and aerosols can give insight into whether the model processes are realistic or not.

Then there are the tests of climate changes themselves: how does a model respond to the addition of aerosols in the stratosphere such as was seen in the Mt Pinatubo 'natural experiment'? How does it respond over the whole of the 20th Century, or at the Maunder Minimum, or the mid-Holocene or the Last Glacial Maximum? In each case, there is usually sufficient data available to evaluate how well the model is doing.

Are the models complete? That is, do they contain all the processes we know about?
No. While models contain a lot of physics, they don't contain many small-scale processes that more specialised groups (of atmospheric chemists, or coastal oceanographers for instance) might worry about a lot. Mostly this is a question of scale (model grid boxes are too large for the details to be resolved), but sometimes it's a matter of being uncertain how to include it (for instance, the impact of ocean eddies on tracers).

Additionally, many important bio-physical-chemical cycles (for the carbon fluxes, aerosols, ozone) are only just starting to be incorporated. Ice sheet and vegetation components are very much still under development.

It is complex to work out what is Ok and what not Ok when constructing models. you would not expect it to be otherwise when modelling such a large and complex system. But if there is a hole in how they are constructed somone point me to the specific detailed arguments (referencing the original peer reviewed papers) and it should not be difficult to get a peer-reviewed refutation published. If, on the other hand, you argue that due to some conspiracy the peer-review proxcess is broken instead, all that is needed is to publish such a paper (written properly, with references) on an anti-AGW blog and invite a response. I have to say that academic papers tend to get published when internally consistent regardless of overall conclusion, so I don't think peer review is broken.

From the above - the comments quoted out of context make sense in terms of number of tunable parameters. As always, the devil is in the detail. Look with suspicion on arguments which omit it! (The IPCC report is 1K pages, remember. It and summarises a much larger volume of work).

[gblaze42]

It would be interesting, though, to see just how much extra C02 is released from plant respiration and obvious increase of biomass decay that this increase would cause, considering that it is a substantial ~20% increase!

I have not seen this factored in on GW calculations.

Plants aborb CO2, instead of releasing it. The models do take this into account-- plant life is actually a negative feedback in that as temperatures warm and leads to more plant life, the extra plant life helps to soak up the CO2.

They also do release CO2 during respiration. They may absorb more CO2 but as plant life continues to grow, they would be adding more CO2 to the atmosphere depending on how fast they grow. Not being a biologist, just an EE/physicist, I can't say for sure how much is added or absorbed.

Personally, I think the increased dead zones in the oceans are much more of a concern right now than GW. With more than 400 spots around the world and increasing, dead zones have a much more far reaching effect on the world.

[Josh Cryer]

The very fact that you used the word "denier" earlier is concerning, Josh.

"Denier" is a noun of faith. "Skeptic" is a noun of honor in science.

Duane

I don't see any honor in ignoring links I give and repeating the same thing (hint, one of the links suggests the best guess for the multiplier, and surprisingly it's a lot closer to his own number than he thinks). A skeptic is responsive, a denier or a "believer" will just reiterate their position without evidence, or modify their language or position in order to reduce their own necessity for data while expecting more data from you.

[Maui]

They also do release CO2 during respiration. They may absorb more CO2 but as plant life continues to grow, they would be adding more CO2 to the atmosphere depending on how fast they grow. Not being a biologist, just an EE/physicist, I can't say for sure how much is added or absorbed.

The way I've always thought of it (and maybe this is wrong), is that most of the carbon contained in a plant has been absorbed via CO2 intake. So, as you say, once a plant has reached full size (or on a bigger scale once a forest is grown) there is no longer any net absortion of CO2 from the atmosphere. But in creating new plant life that didn't previously exist, it is banking carbon that would otherwise end up as CO2 up in the atmosphere.

[Mike Holmes]

Something that I like to needle the greens about, there are more trees in the USA today than there were when the settlers first arrived. Wisconsin, where I live as an example, was savanna when white folks first came here, except for the far northern parts of the state. Now it's heavily forested all over - even farmland has more trees in between plots than formerly existed there when it was a savanna. Our cities are full of trees (I have 5 big trees on my miniscule city plot, for example).

In terms of sequestering as much carbon in plants as possible, we're doing our part on that end of the equation. There are limits, of course.

And, hey, turns out that planting trees might be AGW in action! https://publicaffairs.llnl.gov/news/new ... 12-02.html

Those savannas had a much higher albedo than the current, greener cover.



Mike

[bcglorf]

<I>
GC models are based on physics and tested (not fitted) over 100,000s of years of historical data.
</I>

My beef with this is where the datasets are coming from. We don't have direct measurements of any variables going back any more than 100 years, and the ones that go back even that far are of questionable accuracy. The unprecedented warming all occurs at the same point that the data switches from indirect to direct methods. Better still, our biggest measure of GC models accuracy is temperature, and the direct data for temperature is already KNOWINGLY bad to the point that it is corrected to take Urban Heating into account. With that underlying data being the only way we can calibrate or verify the GC Models, I consider their predictions for the recent century as rubbish as the data they are fed.

[tomclarke]

Josh,

I take your point about people who are open to evidence and those with a priori and unchangeable beliefs.

Still I myself am uncomfortable with the word "denier". It implies there is a creed and sides. Much better to be open-minded and argue the evidence assuming all antagonists are equally interested in the truth. I find this effective. If they are twerps who can not or will not think they will expose themselves as this, there is no need to insult them. And if they have valid concerns meeting these helps to elucidate the problem.

Mostly I find the realclimate site - especially the long sets of posts commenting on articles - useful. But when it becomes evangelical and talks about deniers it is I think adopting unwise tactics.

[scareduck]

Now MSimon is saying the data is wrong. Anyone who believes global warming exists should not look at the data because it is misleading.

It really does depend on the data, though. From what I can tell, data archiving, modification, and selection are all significant faults. Steve McIntyre at Climate Audit has a recent post that illustrates this pernicious lack of transparency.

[MSimon]

The satellite data is IMO the most trustworthy of the lot. Unfortunately it only goes back to '79.

The European data has lots of breaks due to wars. The Chinese data is very bad. South America has only 6 or 7 stations with continuous records of 100 years or more. And Africa is probably the worst of the lot.

Ocean measurements have recently gotten better but there is only a few years of that. I was unaware that the ocean cooling trend data have been corrected.

I find it interesting though that all the "corrections" I have seen in the data point to warming. I would expect a more random distribution of errors.

Not to worry. We saw something similar with the Millikan oil drop experiments. So when there is rough parity between hot warmists and luke warm warmists I'm sure we will get closer to the truth.

[MSimon]

tom,

Hansen, Barnett and others concluded that thet models did track closely with the observed ocean heat content trends. Climate Science weblogged on this; e.g. see

http://www.climatesci.org/2006/04/10/co ... rediction/

and

http://www.climatesci.org/2005/08/08/co ... e-posting/

The Climate Science proposal is just to continue to compare with the models once the Argo data is corrected.

Comment by Roger Pielke Sr. — April 6, 2007 @ 6:32 am

http://climatesci.org/2007/04/04/a-litm ... quirement/

=========

The update:

Willis, J. K., D. P. Chambers and R. Steven Nerem, 2008: Assessing the Globally Averaged Sea Level Budget on Seasonal and Interannual Time Scales. Journal of Geophysical Research-Oceans (in press).

An important conclusion from the paper is that

“Despite the short period of the present analysis, these results have important implications for climate. First, from 2004 to the present, steric contributions to sea level rise appear to have been negligible. This is consistent with observations of ocean surface temperature, which show relatively little change in the global average between 2003 and 2006 [Smith and Reynolds, 2005, see NCDC global surface temperature anomalies]. It is in sharp contrast, however, to historical analyses of thermal expansion over the past decade [Willis et al., 2004] and the past half-century [Antonov et al., 2005; Lombard et al., 2005; Ishii et al., 2006]. Although the historical record suggests that multiyear periods of little warming (or even cooling) are not unusual, the present analysis confirms this result with unprecedented accuracy.”

The above paragraph reinforces a conclusion reached on Climate Science that global warming, at least as diagnosed by tropospheric and upper ocean heat content (see), has not been occurring since 2004. It is impossible to know if this lack of warming will continue, but these observations are inconsistent with the predictions of the long-term global climate predictions, such as reported in the 2007 IPCC report.

http://climatesci.org/2008/02/15/import ... published/

I have not incorporated all the links into the text. Follow the urls given for the missing links.

*

[tomclarke]

Simon,

I suspect this. Any error that implies cooling gets lots of publicity from anti-AGW groups. It becomes high profile. Then it is corrected, you hear about this.

Other errors just get corrected quietly, and no-one highlights it.

In any case the true argument is not warming vs cooling (though some think it is). The true argument relates to how accurate are the climate models.

If they are not accurate it is arguable more alarming tham if they are accurate - since we really have no handle on the effects that putting so much fossil CO2 in the atmosphere will have.

Best wishes, Tom