New research from Stephen Schwartz of Brookhaven National Lab [suggests] that the Earth’s climate is only about one-third as sensitive to carbon dioxide as the IPCC assumes. Schwartz’s study is “in press” at the Journal of Geophysical Research and you can download a preprint of the study here.Got that? If Schwartz's research is correct -- and like other warmists, he's using the deservedly maligned climate models to read this crystal ball -- a doubling of atmospheric carbon dioxide will see temperature increases above natural warming just one-third warmer than warmists insist on. Warmists' crystal balls predict there carbon dioxide levels will be roughly double that of the pre-Industrial Revolution era sometime around 2070; If Schwartz's research is right, we can look forward to a 0.6 degree Celsius surcharge in 2070 due to that doubling.
According to Schwartz’s results, which are based on the empirical relationship between trends in surface temperature and ocean heat content, doubling the CO2 concentration in the atmosphere would result in a 1.1oC increase in average temperature (0.1–2.1oC, two standard deviation uncertainty range).
If he's right, seems a reasonable price to pay for the industry that keeps us all alive.
Joel Schwartz at Planet Gore highlights three more important points of Stephen Schwartz's research:
That last point is important. Although Schwartz is using the same system of climate models as other warmists, unlike those other models Schwartz's is able to explain the rising and falling and rising and falling of temperatures over the twentieth century, and the temperature decline since 1998.Schwartz is careful to include the appropriate caveats to his results. But he also shows that his estimates are consistent with much of the previous literature on the subject.
- Aerosols have a relatively small effect on temperature. A doubling of CO2 has an estimated climate “forcing” of 2.7 watts per square centimeter (W/cm2). In contrast, actual aerosol concentrations during the 20th Century had a forcing of -0.3 W/cm2 with a large uncertainty range that could mean either net cooling or net warming from aerosols.
- The response time, or “time constant”, of the climate to greenhouse gas forcing is relatively small—only five years. In other words, there’s hardly any additional warming “in the pipeline” from previous greenhouse gas emissions. This is in contrast to the IPCC, which predicts that the Earth’s average temperature will rise an additional 0.6oC during the 21st Century even if greenhouse gas concentrations stopped increasing.
Joel Schwartz has the summary at Planet Gore: Overcoming the "Consensus" in One Fell Swoop.
Stephen Schwartz has the full research paper here: Heat Capacity, Time Constant & Sensitivity of Earth's Climate System [pdf].
13 comments:
Schwartz is stepping out of his specialist field. See
http://julesandjames.blogspot.com/2007/08/schwartz-sensitivity-estimate.html
for the take of a scientist who is expert in the field, James Annan.
Annan catches Schwartz making an elementary mathematical mistake, and a more fundamental physics mistake.
As Annan concludes:
It's surprising that Schwartz didn't check his results with anyone working in the field, and disappointing that the editor in charge at JGR apparently couldn't find any competent referees to look at it.
Read the whole thing.
Incidentally, it's odd that you hype up this paper, even though it leans on the climate models you detest so much. Sure, you're careful to note your dislike of them, but why spotlight this paper over other papers that use climate models and arrive at conclusions that don't appeal to your worldview?
It would be like the guy who, caught driving after drinking, launches into a rant about how breathalyzer technology can't be trusted. But when he tests negative for high alcohol, he's happy to take the result and drive off.
It's called situational ethics.
John, you ask "why spotlight this paper over other papers that use climate models and arrive at conclusions that don't appeal to your worldview?"
I spotlight this paper in particular because it's one of the few I've seen that appears to be able to match the actual climate record over the last century, including the pre-war rise in temps without the rise in carbon emission, and the post-war temp decline just as emissions really kicked off.
So that would be like the guy who said, I'll believe a breathalyser when it matches the blood test.
My reservations about the inability of climate models to deal with the complexities of climate science still stand. I was interested to seer reactions from those who do rate the models.
John, you ask "why spotlight this paper over other papers that use climate models and arrive at conclusions that don't appeal to your worldview?"
I spotlight this paper in particular because it's one of the few I've seen that appears to be able to match the actual climate record over the last century, including the pre-war rise in temps without the rise in carbon emission, and the post-war temp decline just as emissions really kicked off.
So that would be like the guy who said, I'll believe a breathalyser when it matches the blood test.
My reservations about the inability of climate models to deal with the complexities of climate science still stand. I was interested to seer reactions from those who do rate the models.
PS: I'll take a look at that link later tonight, when I get a chance.
John a, you think that Anan mathematical model is more correct than Schwartz?
Here is my message that I was gonna post at James Annan's site, but it requires the poster to have Google account. If you believe James, mathematical analysis, then you should read the following analysis, and may be you could see that Annan's analysis is exactly what the following paper suggests that it should be dismissed, because it is inaccurate to use linear models. BTW, Scwartz analysis is still based on linear model where the real climate system is non-linear and multi-coupled feedback.
James have you read the followings:
Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis of feedback processes in a dynamical system: Lorenz model case-study
Appeared in Q. J. Royal Meteorol. Soc., 129, 239-275,
Sensitivity is a non-linear function, and it is pretty much hard to estimate, in current modeling.
Until, this huge barrier in climate numerical modeling is solved or close to being solved, then I think your attack on Dr. Schwartz's work is despicable.
How about you address the science and not the person, and BTW Dr. Schwartz model is a linear one, whether his analysis is correct or not, it won't change the fact that the sensitivity parameter is dynamic, which makes linear feedback climate analysis including those models the IPCC used unreliable.
I recommend that should address the shortfall of numerical modeling rather pushing your religion.
Don't get excited everyone. John A is merely another believer in "climate porn"; a climate pervert in other words!. There is nothing you can say, write or do that'll change his views.
Why?
Because you can't reason with believers such as him. that's just too bad.
LGM
Falafulu: As it happens, I have a Google account, and would be willing to cut and paste your comment into James' blog, since I'm interested to see what he makes of it. OK with you?
John A said...
OK with you?
Go ahead John. I am willing to have a serious debate with Annan about numerical modeling on issues relating to model numerical stability, accuracy, difficulty, inefficiency, etc. This is my specialist area (although I am not a climate scientist) and I have read James Hansen's linear feedback model paper:
CLIMATE SENSITIVITY: ANALYSIS OF FEEDBACK MECHANISMS
which is now regarded as classical outdated method that is very unreliable & inappropriate for modeling climate systems dynamic, exactly as outlined by Rossow & Aires.
PC: See this figure for two models that reproduce the 1940-1970 drop (although not exactly):
http://en.wikipedia.org/wiki/Image:GCM_temp_anomalies_3_2000.jpg
See also IPCC WG1, FAQ 8.1, Fig.1 for a conglomerate of 58 simulation runs based on 14 models.
And here for another graph:
http://environment.newscientist.com/data/images/ns/cms/mg18925431.400/mg18925431.400-2_752.jpg
John A : I've pasted your comment over at James' blog.
Thanks, I will be watching that thread for any reply over there.
I John A./FromNotPC,
I removed your comment because I saw that FF picked it up, and so that the password isn't spread too widely.
Thanks.
PC
Hello, John A,
Could you please email the password and username for Google account that you opened as FromNotPC to Not PC by clicking on the Pay Pal Click Here To Pay link for his tip jar. If yo click on that link, a page comes up, with Not PC's contact email. Just forward the detail to that address. I saved the login detail, but somehow I couldn't find it.
I want to reply to James Anan, since I can see that he has attempted to give an answer, to my post (the one you posted on my behalf).
I noted that you had a post over there today using FromNotPC. So, if I do post over at James site using the same login as you, then I will sign at the end as Falfulu Fisi, so to differentiate between us.
I have read James paper, where he used Bayesian Inference (BI) for sensitivity estimation. I know BI inside out, and it is very good in pattern recognition, but almost useless in terms of dynamical system modeling (DSM). I do use a more advanced variant of BI which is dynamic called Bayesian Belief Network (BBN). I already have software implementation of BBN algorithm for my own use (data-mining).
DSM involves the system process cause-and-effect (time-evolution) , be it climate system, economic system, population system, etc,... Standard BI is not dynamic at all. It is not a function of time. It is widely adopted in anti-spam filter of today, just check your email program because it is highly likely that it uses Bayes antispam filter. The shortfall of statistical inference as BI, is that it has no knowledge about the dynamics of the system. The other word for statistical inference is blind faith.
Once I get the login detail from via Not PC, then I will respond to James latest message.
Cheers,
FF.
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