Guest commentary from Richard Millar (U. Oxford)
The recent Lewis and Curry study of climate sensitivity estimated from the transient surface temperature record is being lauded as something of a game-changer – but how much of a game-changer is it really?
The method at the heart of the new study is essentially identical to that used in the much discussed Otto et al. (2013) study. This method uses a simple equation of the energy balance of the climate and observations of global temperature change and estimated ocean heat uptake anomalies along with a time series of historical radiative forcing (code), in order to make inferences about the equilibrium climate sensitivity (ECS – the ultimate equilibrium warming resulting from doubling carbon dioxide concentrations) and its shorter-term counterpart the transient climate response (TCR – the warming at point of doubling after carbon dioxide concentrations are increased at 1% per year). [Ed. An overview of different methods to calculate sensitivity is available here. The L&C results are also discussed here].
Lewis and Curry use an updated radiative forcing estimate over that used in Otto et al along with slightly different assumptions over the periods used to define the observational anomalies. They use the latest IPCC numbers for radiative forcing and global temperature changes, but not the latest IPCC ocean heat content data. Their result is a 5 – 95% confidence interval on ECS of 1.1–4.1K and for TCR is 0.9-2.5K. These confidence intervals are very consistent with other constraints, from paleo or emergent observations and with the range of GCM estimates. For the TCR, arguably the more important measure of the climate response for policy makers as it is a better predictor of cumulative carbon budgets, the 5-95% confidence intervals are in fact almost identical to the AR5 likely range and similar to the CMIP5 general circulation model (GCM) estimated 5–95% range (shown below).
Figure 1: The 5-95% confidence ranges for transient climate response (TCR) taken from various studies as in Fig. TS.TFE6.2 of IPCC AR5 WG1. The green bordered bar at the top of figure is the estimated 5-95% range from the CMIP5 GCMs. blue bordered bar at the top of the figure is the 5-95% range from the Lewis and Curry (2014) study. The grey shading represents the AR5 consensus likely range for TCR.
There is a difference between the Lewis and Curry 17-83% confidence intervals and the IPCC likely ranges for TCR and ECS. However, for all quantities that are not directly observable, the IPCC typically interprets the 5-95% confidence intervals as likely ranges to account for the possibility that the model used to derive the confidence intervals could be missing something important (i.e. non-linearity that would not be captured by the simple models used in Otto et al and Lewis and Curry, which can particularly be a problem for ECS estimates using this method as the climate feedback parameter is assumed to be constant in time) [IPCC AR5 WG1 Ch10.8.2]. In this case, accounting for more complete surface temperature changes (Cowtan and Way, 2013), or the hemispheric imbalance associated with aerosol forcing (Shindell, 2014), or updates in the OHC changes, may all shift the Lewis and Curry distribution. [Ed. This expert judgement related to structural uncertainty was also applied to the attribution statements discussed here before].
The median estimate of the TCR from Lewis and Curry (1.3K) is towards the lower end of the IPCC likely range and lower than the CMIP5 median value of around 1.8K. A simple way to understand the importance of the exact TCR value for mitigation policy is via its impact on the cumulative carbon budget to avoid crossing a 2K threshold of global surface temperature warming. Using the Allen and Stocker relationship between TCR and TCRE (the transient climate response to cumulative emissions) we can scale the remaining carbon budget to reflect different values for the TCR. Taking the IPCC CO2-only carbon budget of 1000 GtC (based on the CMIP5 median TCR of 1.8K) to have a better than 2 in 3 chance of restricting CO2-induced warming to beneath 2K, means that emissions would have to fall on average at 2.4%/year from today onwards. If instead, we take the Lewis and Curry median estimate (1.3K), emissions would have to fall at 1.2%/year. If TCR is at the 5th percentile or 95th percentiles of the Lewis and Curry range, then emissions would need to fall at 0.6%/year and 7.1%/year respectively.
Non-CO2 emissions also contribute to peak warming. The RCP scenarios have a non-CO2 contribution to the 2K peak warming threshold of around 0.5K [IPCC AR5 WG1 – Summary for Policymakers]. Therefore, to limit total warming to 2K, the CO2-induced contribution to peak warming is restricted to around 1.5K. This restricts the remaining carbon budget further, meaning that emissions would have to fall at 4.5%/year assuming a TCR of 1.8K or 1.9%/year taking TCR to be equal to the Lewis & Curry median estimate of 1.3K (assuming no mitigation of non-CO2 emissions).
While of some scientific interest, the impact for real-world mitigation policy of the range of conceivable values for the TCR is small (see also this discussion in Sci. Am.). For targets like the 2 K guide-rail, a TCR on the lower end of the Lewis and Curry and IPCC ranges might just be the difference between a achievable rate of emissions reduction and an impossible one…
References
- N. Lewis, and J.A. Curry, "The implications for climate sensitivity of AR5 forcing and heat uptake estimates", Climate Dynamics, vol. 45, pp. 1009-1023, 2014. http://dx.doi.org/10.1007/s00382-014-2342-y
- A. Otto, F.E.L. Otto, O. Boucher, J. Church, G. Hegerl, P.M. Forster, N.P. Gillett, J. Gregory, G.C. Johnson, R. Knutti, N. Lewis, U. Lohmann, J. Marotzke, G. Myhre, D. Shindell, B. Stevens, and M.R. Allen, "Energy budget constraints on climate response", Nature Geoscience, vol. 6, pp. 415-416, 2013. http://dx.doi.org/10.1038/ngeo1836
- K. Cowtan, and R.G. Way, "Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends", Quarterly Journal of the Royal Meteorological Society, vol. 140, pp. 1935-1944, 2014. http://dx.doi.org/10.1002/qj.2297
- D.T. Shindell, "Inhomogeneous forcing and transient climate sensitivity", Nature Climate Change, vol. 4, pp. 274-277, 2014. http://dx.doi.org/10.1038/nclimate2136
- P.J. Durack, P.J. Gleckler, F.W. Landerer, and K.E. Taylor, "Quantifying underestimates of long-term upper-ocean warming", Nature Climate Change, vol. 4, pp. 999-1005, 2014. http://dx.doi.org/10.1038/nclimate2389
- M.R. Allen, and T.F. Stocker, "Impact of delay in reducing carbon dioxide emissions", Nature Climate Change, vol. 4, pp. 23-26, 2013. http://dx.doi.org/10.1038/nclimate2077
Richard Millar, you write
“They use the latest IPCC numbers for radiative forcing and global temperature changes, but not the latest IPCC ocean heat content data”.
The statement that Lewis and Curry (2014) does not use the latest IPCC ocean heat content data is simply untrue.
Section 3.2 of the paper explicitly states that it uses the climate system energy accumulation observational best estimates and uncertainty ranges shown in Box 3.1, Figure 1 of AR5, which extend to 2011, the final year of all the analyses carried out in the paper. The change in ocean heat content accounts for the bulk of the accumulation. Gregory Johnson is acknowledged in the paper for supplying the underlying data.
Your Figure 1 does not reveal that the Otto et al (dark green) and Lewis and Curry TCR distributions are much more heavily skewed than those from the other studies, as they (particularly Lewis and Curry) take greater account of forcing uncertainty. Whilst their 5-95% ranges may look similar to those of other studies, the bulk of their probability is concentrated towards the lower end of the 5-95% range. I would also question the 5-95% range of 1.2 – 2.4 °C TCR range shown for CMIP5 models, presumably taken from Table 9.5 of AR5. I have sourced TCR values for 33 of the 38 CMIP5 models used for the RCP8.5 runs. 9% (3 models) have TCRs of 2.5 °C or above; several others have TCRs of 2.3 or 2.4 °C.
I will not waste time arguing in this venue about the validity and/or relevance, or lack of it, of Shindell (2014), Cowtan and Way (2013) or the Allen and Stocker TCR/TCRE relationship.
The first “Lewis and Curry” link points back to this article, not the original paper as I would have expected.
[Response: Actually it points to the reference list at the bottom. -gavin]
Nic Lewis, I have one question for you. How could you seriously muck up an analysis that even a non-climate scientist like myself can do properly?
Why didn’t you use an OHC content that is closer to 0.8 W/m^2 ?
Dear NicLewis,
If you use OHC-Data from IPCC why you got 0.51W/m^2(or 82.3 ZJoule) Heat-uptake for 1995-2011 in best estimate, when at the same time the Heat-Uptake for 1995-2011 from IPCC-Data give a Value arround 130 ZJoule (or arround 0.80W/m^2). You self linked it here: http://niclewis.wordpress.com/the-implications-for-climate-sensitivity-of-ar5-forcing-and-heat-uptake-estimates/ its easy to see by plotting the heat.txt.
To be honest, do you trust you own Model which is saying from 1995-2011 was the Heat-Uptake arround 8.23*10^22 Joule, when at same time we recorded only in 0-700m this value and you argue, thats best estimate? Lower bound i would say..
Hi Nic,
My reading of your paper (section 3.2) was that you are using an update on the base period system heat uptake used in Otto et al and AR5? If this is not the case, then I will happily be corrected on this point.
As to the source of the estimated 5-95% range for TCR from the CMIP5 models (1.2-2.4K), it is taken directly from the range stated on page 84 (TFE.6) in the AR5 technical summary.
In the figure I am comparing like-for-like 5-95% TCR ranges, as that is what is relevant when comparing to the AR5 likely range. The bars are added to reflect the style of the original figure in AR5. I explicitly discuss the median estimates of your work and how they are on the lower end of the estimated ranges (which are indicative of the skew in the likelihood density along the confidence interval). Indeed, the point is explicitly made that if the TCR is 1.3K, as opposed to 1.8K, whilst both require significant mitigation relative to today’s emissions trends if a 2K goal is to be achieved, it might make the difference between an achievable average rate of mitigation and an unachievable one.
WHT and Christian,
Are you talking about 0.8W/m2 OHC flux over the whole Earth surface or just ocean surface? Lewis & Curry’s 0.51W/m2 is for whole Earth surface.
“I will not waste time arguing in this venue about the validity and/or relevance, or lack of it, of Shindell (2014), Cowtan and Way (2013) or the Allen and Stocker TCR/TCRE relationship.”
Well Nic you’ve already avoided responding to the concerns regarding not using Berkeley Earth and Cowtan and Way (2013)at Climate Audit. Your own response to the same concerns was:
“I haven’t studied Cowtan & Way 2014 in any detail. It is accordingly unclear to me whether its method of reconstructing data in unobserved regions is substantially superior to those used by MLOST, GISS or JMA, even assuming that it is desirable to carry out such infilling…”
to which I responded:
“Then perhaps its time you read CW2014 and the 3 subsequent updates online. If you did you would see that cross-validation tests, tests against local out-of-sample data, reanalysis data, satellite data (AIRS, AVHRR/MODIS skin temperature) all show that the method adopted by CW2014 and BEST (sea-ice as land) outperform other methods. Simmonds and Pauli (In press) QJRMS have look in detail at our record as well…
Implicitly by using Hadcrut4 or MLOST you infill the global average – try that with cross-validation and you see clearly how that method introduces increasing bias with higher latitude. MLOST has even less high latitude coverage than CRU…”
9 days and waiting…
Using C&W instead of HadCrut4, delta-temperature in the main result goes from 0.71C to 0.78C, and the TCR “best” estimate goes up proportionally i.e. 1.33C -> 1.45C.
C&W is definitely a more defensible choice, as bias coverage in HadCrut4 prevents an “apples-to-apples” comparison. This is especially true since, as James Annan points out, Lewis and Curry have failed to “mask off” the corresponding model SAT.
http://julesandjames.blogspot.ca/2014/10/much-ado-about-sensitivity.html
Discussion between Nic Lewis and Robert Way at ClimateAudit:
Nic Lewis at CA:
“It has been claimed that incomplete coverage of high-latitude zones in global temperature datasets biases down their estimate of the rate of increase in GMST. However, over the long periods involved in this study there is no evidence of any such bias. The increase in GMST per the published HadCRUT4v2 global dataset, used in the study, exceeds rather than underestimates the area-weighted average of the calculated increases for ten separate latitude zones, which method gives a full weighting to each zone.”
Robert Way:
“There are three available datasets that go back to 1850. CW2014, Hadcrut4v2 and BEST. Both CW2014 and BEST show about 10% more warming using your preferred base and final periods (1859-1882; 1995-2011). Is the rationale for not including coverage bias or either of these datasets discussed in more detail anywhere?”
http://climateaudit.org/2014/09/24/the-implications-for-climate-sensitivity-of-ar5-forcing-and-heat-uptake-estimates-2/#comment-731849
Also see:
http://climateaudit.org/2014/09/24/the-implications-for-climate-sensitivity-of-ar5-forcing-and-heat-uptake-estimates-2/#comment-732815
Robert Way again:
“If you haven’t read the papers or tested the methods then its hard to accept your reasoning for not including. Your intuition is not the same as actually looking at the data. I just do not understand how from a communications standpoint it makes sense to even open yourself up to the cherry-picking accusation from those you’re trying to convince of your papers credibility.”
Meanwhile, Gavin Schmidt quantifies the ECS adjustment implied by Durack et al OHC:
Revision. Taking account of actual data used (AR5 total heat accumulation), Durack makes 15% diff. ECS -> 1.1-4.7ºC [instead of 1.1-4.1ºC]
https://twitter.com/ClimateOfGavin/status/518928639615070210
If possible, I’d be very grateful if someone could adapt Figure S1 panels C & D of Rogelj et al. 2014 by adding a “case k” to the original cases a-j, where case k would represent the Lewis and Curry.
In addition, an adaptation of Table S3 from the same Rogelj et al. 2014, modified to include rows for this “case k,” would be helpful.
Environ. Res. Lett. 9 (2014) 031003 (7pp)
doi:10.1088/1748-9326/9/3/031003
http://iopscience.iop.org/1748-9326/9/3/031003/pdf/1748-9326_9_3_031003.pdf http://iopscience.iop.org/1748-9326/9/3/031003/media/erl492804suppdata.pdf
Thank you.
Hi Nic and Richard,
Ocean heat uptake for 1995-2011 is indeed correct based on Box 3.1 in AR5 (@Christian: You’ve got to scale the heat uptake to the entire Earth’s surface, not only the ocean surface, which brings your 0.8W/m2 down to 0.5W/m2 … as Paul S has kindly pointed out already).
However, the 1859-1882 heat uptake estimate is based on a multitude of assumptions, all of which are essentially independent of AR5. Arguably, the estimated difference in system heat uptake between base and final period (0.36W/m2 as of Table 3) is hence also not a “true” AR5 estimate. There are several reasons why this might pose a problem, but given that non-linearity is a much more severe issue in the first place, it isn’t really something which bothers me. Trumpeting such results as if they present something particularly meaningful certainly is (particularly when considered in the light of more recent work, which would alter the conclusions of the paper substantially).
Regarding the much more relevant forcing assumptions, I am pleased to see that you, Nic, eventually used the AR5 aerosol ERF (rather than your adjusted number) for the central estimate. One issue which we (i.e. Tom Curtis and I) couldn’t resolve over at ATTP was that the AR5 forcing given in Annex II points towards 1.93W/m2 forcing increase (between the 1859-1882 and 1995-2011 periods), compared to 1.98W/m2 shown in Table 3 in the paper. Doesn’t sound like much, but given that the combination of more recent HadSST and Cowtan&Way temperature data brings the TCR estimate up to 1.5K already (let alone problems related to hemispheric forcing differences), it might well be of relevance. Perhaps you can briefly clarify what might be the cause for this rather small discrepancy. Thanks!
Hi Richard,
I’m not sure I fully understand what you are saying about ocean heat uptake (OHU) data. As I said, for the final periods Lewis & Curry (2014) uses the latest IPCC AR5 data, as used for Box 3.1, Figure 1. The paper states this at the start of section 3.2. The data used in Otto et al (2013) is an earlier, slightly different, version of the Box 3.1, Figure 1 data.
For the base period, Otto et al (2013) followed what I did in a 2012 blog-published energy budget study based on the AR5 second order draft (SOD) forcing data (http://wattsupwiththat.com/2012/12/19/why-doesnt-the-ar5-sods-climate-sensitivity-range-reflect-its-new-aerosol-estimates/). I adopted the OHU estimate given in Gregory et al (2002) for the 1861–1900 period of 0.16 W/m², but deducted only 50% of it to compensate for the Levitus et al. (2012) regression trend that I used for the final period implying a somewhat lower 2002-2011 OHU than is given in the SOD. I also trebled the Gregory et al (2002) uncertainty estimate. Otto et al did exactly the same, although it did use the AR5 OHU data.
The Lewis & Curry base period OHU estimates were instead derived from Gregory et al (2013); the resulting 1861-1900 estimate agrees to that from Gregory et al (2002), as stated in section 3.2. The information given in Gregory et al (2013) permitted separate estimates to be made for OHU in the three base periods used. Only 60% of the estimated OHU values were used, on account of the model used by Gregory et al having (like most AOGCMs) fairly high climate sensitivity.
” As to the source of the estimated 5-95% range for TCR from the CMIP5 models (1.2-2.4K), it is taken directly from the range stated on page 84 (TFE.6) in the AR5 technical summary. ” Yes; we are not disagreeing on the source. As TFE6 Figure 2 says, that range comes from Table 9.5.
” The bars are added to reflect the style of the original figure in AR5.” Understood, but the TCR figure in AR5 also gave probability density functions for studies and a histogram for CMIP5 models, which much more clearly revealed the difference between the oppositely skewed Otto et al and CMIP5 probability distributions.
[Response: Note that CMIP5 model results are not a proper probability distribution, therefore the skewness of the histogram is not indicative of anything much. – gavin]
> Figure 1 does not reveal that the Otto et al (dark green) and
> Lewis and Curry TCR distributions are much more heavily skewed
> … the bulk of their probability is concentrated towards the
> lower end of the 5-95% range. –
https://www.realclimate.org/index.php/archives/2014/10/climate-response-estimates-from-lewis-curry/comment-page-1/#comment-607025
Anyone have a pointer to something like those comparisons, but showing each as a probability distribution curve rather than a rectangular bar?
Found one chart showing the probability distributions I was asking for:
Posted on June 23, 2014 by Jim Bouldin at:
Global temperature change computations using transient sensitivity, in comparison to AR5
Rocketeer quote:
Whether the new work is sloppy or brilliant, this is just another paper published in a prestigious journal s – See more at: https://www.realclimate.org/index.php/archives/2014/10/climate-response-estimates-from-lewis-curry/#sthash.wuBETkG5.dpuf
My comment: I suspect the problem you face isn’t whether the green house effect exists or not, or whether humanity issues more or less CO2. The problem, I believe, is the disagreement over parameters such as TCR and ECS, and what portion of the temperature increase from 1973 to 1998 can be attributed to Anthropogenic emissions…..by insisting the issue is only a debate over global warming you got stuck in first gear. And maybe this is the reason the problem gets a low priority in people’s minds. You are using a very simple and easily defeated idea.
re #18
CO2 Law dome, last 1000 years.
We are in the mid-Pliocene at 400-ppm CO2 waiting for natural systems to catch up so it’ll be at least 2C warmer and sea-level 25m/82ft higher when that happens, how fast is the only question as long as greenhouse & waste-heat emissions continue unabated.
To frame reality in terms of the gain in CO2, that was 1-ppm/180-years at the highest rate-of-change at the end of the Wisconsin ice-age, we’re at 3-ppm/year, 540-times faster than recent geologic history.
Using the worst-case scenario seem valid the way Greenland & Antarctica’s ice-sheets are going, nothing less is gambling.
For PJ
Are you willing to say where you got the mistaken information you relied on?
Many people repeat opinions without citing sources.
If you’re willing to say where you got that opinion, and why you considered it a reliable source that you could repeat without citing a source, “we can figure out why … your conclusion does not follow.”
As John Mashey points out, facts citing good information will help you reach conclusions.
We’ve all been fooled by opinions posing as facts, they come from all sides of the issue.
Pushing hard for cites is one way to test sources.
@ Robert Way (#7):
The reference is Simmons & Poli (authors’ names are misspelled in your comment)
http://onlinelibrary.wiley.com/doi/10.1002/qj.2422/abstract
Re: #19
Your link doesn’t address the point made. CO2 forcing in the mid 20th century relative to ~1800 was ~0.6 w/m2 – or about one third of the forcing in 2014.
This is interesting timing, as today Durak & others have come out with a paper claiming the warming in the southern oceans has likely been underestimated. So perhaps, after the paper can be digested and the results confirmed (or not) it would make sense to insert a new number for the OHC update rate.
John Finn says: “… CO2 forcing” (ignoring all else).
It would be rather a distraction to invite people to retype everything yet another time again, eh?
You can look this stuff up. He could give you pointers to sources, as can anyone who’s read the science. Trust those who do at least enough to read for yourself about the material and think.
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/tssts-2-5.html
“the effect of human activities since 1750 has been a net positive forcing … Improved understanding and better quantification of the forcing mechanisms since the TAR make it possible to derive a combined net anthropogenic radiative forcing for the first time….”
And, of course, there are feedbacks. But John Finn has been here a long time and knows all this.
> Thomas … Durak
Durack; see http://www-pcmdi.llnl.gov/about/staff/Durack/dump/oceanwarming/
“Quantifying Underestimates of Long-term Upper-Ocean Warming” by Paul J. Durack, Peter J. Gleckler, Felix W. Landerer and Karl E. Taylor –
Nature Climate Change 5th October 2014. DOI: 10.1038/nclimate2389
It’s a study of the studies.
This paper won’t give you “a new number”– that’s not what they’re doing there at all.
The supplementary material may be more readable for amateurs like us than the terse Nature text:
http://www.nature.com/nclimate/journal/vaop/ncurrent/extref/nclimate2389-s1.pdf
Re: #22
Strange that you fail to mention the other recently released paper relating to Ocean Heat. That would be the Llovel et al paper which is discussed here
http://www.jpl.nasa.gov/news/news.php?feature=4321
From a policy perspective (I work in a Government. Or perhaps for a Government) this is all interesting, but largely irrelevant, given that CO2 emissions are still rising (IPCC suggests at 10Gt per annum increase in the last decade)
If we are extremely lucky, TCR will be towards the bottom end of the range. But even if everyone here were to suddenly and unexpectedly agree that TCR were 1.3K +/- 0.1K, the need for urgent action, internationally, to reduce emissions would not be weakened one iota. No country in the world has been able to reduce its emissions at 2% per annum over any extended period, with some notable exceptions where the economy crashed (former USSR is a good example). In part this is due to a lack of effort but even in the UK where there has been effort, emissions only fell by ~14% between 2000 and 2012 (see https://www.gov.uk/government/statistics/final-uk-emissions-estimates)
The USA has achieved some notable emissions reductions through shale gas, but those are inherently limited by the relative carbon intensities of gas and coal.
So, to be short, given full political commitment to emissions reduction, globally, I reckon we could do about 2% per annum, if lucky. A few more years of inaction and that 2% per annum reduction rate isn’t going to keep us inside a carbon budget, even for 1 TCR of 1.3K, let alone 1.8K, or worse.
We need a binding, ambitious deal at Paris. Nothing written above changes that in the slightest.
Re: #25,
The study concludes:
“The net warming of the ocean implies an energy imbalance for the Earth of 0.64 ± 0.44 W m−2 from 2005 to 2013.”
This is consistent with other estimates and inconsistent with various spin in media outlets, or a global warming “pause”.
http://skepticalscience.com/print.php?n=2383
Note that the study has large error estimates, which is what you’d expect given it relies on little direct measurement and infers from other data (such as sea level).
“−0.08 ± 0.43 W m−2 ”
Durak et al. clearly imply climate sensitivity estimates using this data would be adjusted higher. Not sure what Llovel et al. imply, given their estimates are consistent with others. Their 0-2000 m estimate is quite large. I’ll let our experts here comment on that.
Silk writes
“…the need for urgent action, internationally, to reduce emissions would not be weakened one iota.” Wrong. The imperative for urgent action has been the enemy of the need for smart, sustained action and has fueled the climate war mentality and resulting policy dysfunction. The lowered climate sensitivity estimates are good news; they allow a little more time to allow an improved climate science inform policy and for the open-minded, climate moderates to reclaim the ground lost to extremists (on both sides) with their bunker mentality. I try to show (to a general audience) the important difference climate sensitivity makes here- http://climatesensitivity.blogspot.com/
#25
strange that you fail to quote more of that press release (actually, I’m kidding — quote-mining is exactly the sort of thing I expect pseudo-skeptics to do)
“Scientists at NASA’s Jet Propulsion Laboratory in Pasadena, California, analyzed satellite and direct ocean temperature data from 2005 to 2013 and found the ocean abyss below 1.24 miles (1,995 meters) has not warmed measurably. Study coauthor Josh Willis of JPL said these findings do not throw suspicion on climate change itself.
“The sea level is still rising,” Willis noted. “We’re just trying to understand the nitty-gritty details.””
“Coauthor Felix Landerer of JPL noted that during the same period, warming in the top half of the ocean continued unabated, an unequivocal sign that our planet is heating up. Some recent studies reporting deep-ocean warming were, in fact, referring to the warming in the upper half of the ocean but below the topmost layer, which ends about 0.4 mile (700 meters) down.”
“Landerer also is a coauthor of another paper in the same Nature Climate Change journal issue on ocean warming in the Southern Hemisphere from 1970 to 2005. Before Argo floats were deployed, temperature measurements in the Southern Ocean were spotty, at best. Using satellite measurements and climate simulations of sea level changes around the world, the new study found the global ocean absorbed far more heat in those 35 years than previously thought — a whopping 24 to 58 percent more than early estimates.”
They should perform a more comprehensive research then. I don’t really trust the validity of Lewis and Curry climate estimation.
Here’s another source — aside from Durack, et al. above — that alludes to ocean heat capacity having an impact on atmospheric temps:
J. Hansen, et al. 1981. “Climate Impact of Increasing Atmospheric Carbon Dioxide,” Science, 213(4511)957-966, at http://pubs.giss.nasa.gov/docs/1981/1981_Hansen_etal_1.pdf
See fig. 1 on pg. 960 showing most likely temps 19 years later in 2000 just about where they were in 2000: “Fig. 1. Dependence of CO2 warming on ocean heat capacity. Heat is rapidly mixed in the upper 100 m of the ocean and diffused to 1000 m with diffusion coefficient k. The CO2 abundance, from (25), is 293 ppm in 1980, and 373 ppm in 2000. Climate model equilibrium sensitivity is 2.8C for doubled CO2.”
Pretty much on the mark re projected temps with 2.8C for doubled CO2.
I like to show this to skeptics who say models can’t predict anything correctly and where was the prediction that the oceans would be a factor (they think climate scientists are just making stuff up post hoc.
Current #31 (Lynn Vincentnathan)–Also Barton Levenson’s useful (though now, alas, a bit dated) summary:
http://bartonpaullevenson.com/ModelsReliable.html
slightly delayed comment re #27 (gmb92):
Some caution re Llovel et al. Their energy imbalance estimate of +0.64 W/m2 is ocean only, which could very easily be misinterpreted the way it’s written in their abstact. For the entire planet (which would be the Earth’s or planetary energy imbalance) their actual value is +0.45 W/m2! Would also be consistent with their estimates of the change in sea level height. Given that ocean heat uptake between 2004 and 2013 was indeed a bit smaller than before (at least in some OHC dataset), it’s perhaps not too surprising that their number is lower than previous estimates that had years before 2004 included.
It’s also worth noting that the slight deep ocean cooling found in Llovel et al. is an inverse estimate only, derived by comparing trends of upper level OHC and sea level height measurements (from satellite altimetry, GRACE and in situ observations) and then closing the full ocean heat content budget. The comparably low imbalance number doesn’t contradict the potentially higher ocean heat uptake before 2004 as of Durack et al. After all, everything seems to add up very neatly.
re #12
Yes, but was another error, what cause are wrong heat-uptake Value (time period length). To get sure about, i used estimates of Levitus (2012), estimate from this, how much Forcing is equal to 1*10^22 Joule or 10 ZJoule and then can also reproduce LC14-Value.
I am soory about getting wrong about heat-uptake, but the most of errors are the simple ones, you never have thought to make a mistake about.
IPCC and the other climate models do not consider nonlinear feedbacks, as you pointed out.
The reason for this is that it is impossible to model or predict the occurrence or rate of feedbacks such as albedo flips, methane releases, accelerated destruction of carbon sinks, etc.
The wish to avoid mathematical embarrassment at some point in the future tells us that scientists have been so intimidated that they are reluctant to even discuss scenarios that are inherently unpredictable with respect to numerical precision.
This flaw is not acceptable, in my opinion, and should drive an attempt to work with modern probability and chaos theory professionals.
I’ve recently completed a pretty serious blog post dealing with climate change, with reference especially to the new NASA report on deep ocean (non) warming, which as I see it, could make a huge difference to the debate. And no, I’m not a “denier,” but a card carrying lifelong Democrat, liberal to the gills. I’d appreciate feedback from anyone reading here in the form of comments, positive or negative. http://amoleintheground.blogspot.com/2014/10/common-sense-on-climate-change.html
Mike Roddy:
We look forward to the publication of your groundbreaking paper, Mike.
You really don’t understand the culture and practice of Science, you know.
Victor wrote: “And no, I’m not a ‘denier,’ but a card carrying lifelong Democrat, liberal to the gills.”
So what?
There are radical leftists who deny the overwhelming scientific evidence that anthropogenic global warming is both very real and very dangerous. And they are just as wrong as the right-wingers, conservatives, centrists and liberals and others of various political persuasions who deny the science.
Do you suppose that branding yourself “liberal” will make your claims more persuasive?
“Do you suppose that branding yourself “liberal” will make your claims more persuasive?”
Do you suppose that ad hominem attacks will make YOUR claims more persuasive?
It’s well known that most “deniers” have a political agenda. I just wanted to make it clear that I don’t. As for the rest, I invite you read what I have to say before forming a judgment.
Victor @36.
Having read through your blog post, it would be incredibly charitable to tell you that there are very big gaps in your understanding of climatology, far too big for you to be tapping out arguments on the reality of AGW with any shread of credibility.
Less charitably, I would be more inclined to ask why you don’t see yourself as a climate denier. Whatever your background, you still manage to conclude “I see no point, therefore, in diverting vast amounts of money and resource in a quixotic attempt to reverse global warming by seriously undermining one of the most precious resources we have: fossil fuels.” But of course, deniers are in denial about being deniers, aren’t they.
But I am an incredibly charitable sort. So I will tell you that the main point you make in your blog beyond the usual denialist nonsensical blather concerns SLR (which you appear to be taking as a proxy for OHC). You present a graphic of ‘robust’ SLR happening since 1870 and global temperature since 1880. Here you see a mismatch. In your words, “global warming didn’t really take off until somewhere around 1910.”
Did you not think to look at all the data available? Did you go no further than eyeball a couple of graphs before coming to such controversial conclusions? Temperature records did exist prior to 1880. (Global land temperatures back into the 1700s are graphed 2 clicks down here). Nor is SL prior to 1870 a complete blank. (See fig 1 here.)
Climatology has no problem linking OHC to AGW. That is not to say that there are no issues with “trying to understand the nitty-gritty details,” but such issues “do not throw suspicion on climate change itself.” Yet, even though you took these quotes on board, you still manage to deny AGW.
The problem, as you say Victor, is that “the cart’s before the horse.” That is, you put your bloggy cart before the know-what-you’re-talking-about horse
Victor, your post simply rehashes tired cherry picks. The date is cherry-picked, the data is cherry-picked (RSS is the only data set that yields this result), and the concept is flawed: the ‘hiatus’ is nothing unusual, given the nature of the observed data set.
For instance, Santer et al (2010):
“Our results show that temperature records of at least 17 years in length
are required for identifying human effects on global-mean tropospheric
temperature.”
http://muenchow.cms.udel.edu/classes/MAST811/Santer2011.pdf
I should add that using RSS also has the effect of lengthening the necessary period for reliably detecting the anthropogenic signal because (like the other main satellite data analysis, UAH) it refers not to surface temperatures but to lower troposphere temperatures generally. Those temperatures are considerably more variable than surface temps–‘noisier’, if you will. So the signal takes longer to emerge from the higher noise levels in those data sets.
You can see that quite clearly using a tool like woodfortrees. Here, I’ve plotted RSS data in red and GIS in blue:
http://www.woodfortrees.org/plot/rss/from:1998/plot/rss-land/from:1998/trend/plot/gistemp/from:1998/plot/gistemp/from:1998/trend
You can see that the red plot ‘swings’ a lot further than the blue–and you can also see the cool ‘bias’ since 1998.
And finally, dealing with the fallacy at some length from an article about 5 years old:
http://hubpages.com/hub/When-Did-Global-Warming-Stop
As noted therein, if you look for global warming since 2000 you will (if sufficiently naive) reach quite a different conclusion.
Victor@36,
Your politics are irrelevant. What matters is that you are wrong. It is simply flat-assed wrong to cherrypick 1998–the biggest El Nino in memory–as a starting point. This one mistake invalidates everything you say in your post. Might I recommend a course in elementary statistics?
Mike Roddy,
Do you realize that the real scientists are not intimidated by words like “nonlinear”? If there were significant benefit from introducing additional feedbacks–be they linear or nonlinear–scientists would be all over it. How about leaving science to the scientists?
Curry had an op-ed in teh WSJ yesterday touting her paper with Lewis.
http://online.wsj.com/articles/judith-curry-the-global-warming-statistical-meltdown-1412901060
Looks to me like many posting here are in denial about the hiatus. As I understand it, most climate scientists agree on that score. The NASA scientists whose paper I quoted clearly accept the reality of the hiatus, referring to it as an ongoing “mystery.” As far as cherry picking is concerned my intention was not to present a comprehensive review of all the research, but simply to display graphs that most clearly illustrated the problems I see. If certain details were thereby exaggerated, I apologize. But you can’t simply dismiss a graph as cherry picked simply because it doesn’t suit you, I’m sorry. My point was not that the hiatus began in any particular year, nor that it followed any particular trajectory. My point was that, at a certain point roughly within the last 18 years or so, the correlation between warming and CO2 emission seems to have broken down. If you prefer 15 years to 18 years fine — it doesn’t really matter.
I also pointed out the lack of correlation prior to 1975. Sure, we see a situation where both warming and CO2 emissions have clearly risen over the past 100 years or so. But if one were the cause of the other there would be a clear correlation between them at all, or almost all, points. There is not. What I see is a steady increase in CO2 output accompanied by a highly varied series of warming trends — until 1975 when the two do finally seem to correlate — until somewhere around 1998, or later if you prefer, when the correlation again breaks down. That is NOT consistent with causation. As the folks from NASA said, it’s a “mystery.” Either that or a flawed hypothesis.
Victor wrote: “Do you suppose that ad hominem attacks will make YOUR claims more persuasive?”
An ad hominem is not an “attack”, it is a fallacy.
And in fact, it is YOU who have engaged in an ad hominem fallacy, when you asserted that your argument should be accepted, not on its scientific merit (or lack thereof), but because you are a “liberal”.
After all, that’s really the exact same fallacy as asserting that someone’s argument should not be accepted because he or she is a “liberal” — which is of course one of the most popular rhetorical fallacies among deniers.
All you have done is turn it around.
MARodger quoted Victor’s blog post:
“I see no point, therefore, in diverting vast amounts of money and resource in a quixotic attempt to reverse global warming by seriously undermining one of the most precious resources we have: fossil fuels.”
And that is, of course, ALWAYS the fundamental message of the deniers:
We must do nothing that would reduce consumption of fossil fuels, and we must do nothing that would “divert vast amounts of money and resources” from the fossil fuel corporations to other sectors of the industrial economy.
Kevin McKinney,
I totally missed that he switched from GISS to RSS for the moneyshot. That is clearly a denialist tactic–indicative of motivated reasoning at the least if not dishonesty! RSS is highly questionable at this point.