In a new GRL paper, Svensmark et al., claim that liquid water content in low clouds is reduced after Forbush decreases (FD), and for the most influential FD events, the liquid water content in the oceanic atmosphere can diminish by as much as 7%. In particular, they argue that there is a substantial decline in liquid water clouds, apparently tracking a declining flux of galactic cosmic rays (GCR), reaching a minimum days after the drop in GCR levels. The implication would be that GCR can affect climate through modulating the low-level cloudiness. The analysis is based on various remote sensing products.
The hypothesis is this: a rapid reduction in GCR, due to FD, results in reduced ionization of the atmosphere, and hence less cloud drops and liquid water in low clouds. Their analysis of various remote sensing products suggest that the opacitiy (measured in terms of the Angstrom exponent) due to aerosols reaches a minimum ~5 days after FD, and that there is a minimum in the cloud liquid water content (CWC) minimum occurring ~7 days later than the FD. They also observe that the CWC minimum takes place ~4 days after the fine aerosol minimum (the numbers here don’t seem to add up).
The paper is based on a small selection of events and specific choice of events and bandwidths. The paper doesn’t provide any proof that GCR affect the low clouds– at best -, but can at most only give support to this hypothesis. There are still a lot of hurdles that remain before one can call it a proof.
One requirement for successful scientific progress in general, is that new explanations or proposed mechanisms must fit within the big picture, as well as being consistent with other observations. They must also be able to explain other relevant aspects. A thorough understanding of the broader subject is therefore often necessary to put the new pieces in the larger context. It’s typical of non-experts not to place their ideas in the context of the bigger picture.
If we look at the big picture, one immediate question is why it should take days for the alleged minimum in CWC to be visible? The lifetime of clouds is usually thought to be on the order of hours, and it is likely that most of the CWC has precipitated out or re-evaporated within a day after the cloud has formed.
In this context, the FD is supposed to suppress the formation of new cloud condensation nuclei (CCN), and the time lag of the response must reflect the life time of the clouds and the time it takes for new ultra-fine molecule clusters (tiny aerosols) to grow to CCN.
Next question is then, why the process, through which ultra-fine molecule clusters grow by an order of ~1000 to become CCN, takes place over several days while the clouds themselves have a shorter life time?
There is also a recent study in GRL (also a comment on May 1st, 2009 in Science) by Pierce and Adams on modeling CCN, which is directly relevant to Svensmark et al.‘s hypothesis, but not cited in their paper.
Pierce and Adams argue that the theory is not able to explain the growth from tiny molecule clusters to CCN. Thus, the work by Svensmark et al. is not very convincing if they do not discuss these issues, on which their hypothesis hinges, even if the paper by Pierce and Adams was too recent for being included in this paper.
But Svensmark et al. also fail to make reference to another relevant paper by Erlykin et al. (published January 2009), which argues that any effect on climate is more likely to be directly from solar activity rather than GCR, because the variations in GCR lag variations in temperature.
Furthermore, there are two recent papers in the Philosophical Transactions A of the Royal Society, ‘Enhancement of cloud formation by droplet charging‘ and ‘Discrimination between cosmic ray and solar irradiance effects on clouds, and evidence for geophysical modulation of cloud thickness‘, that are relevant for this study. Both support the notion that GCR may affect the cloudiness, but in different aspects to the way Svensmark et al. propose. The first of these studies focuses on time scales on the order of minutes and hours, rather than days. It is difficult to explain how the changes in the current densities taking place minutes to hours after solar storms may have a lasting effect of 4-9 days.
There are many micro-physical processes known to be involved in the low clouds, each affecting the cloud droplet spectra, CWC and the cloud life times. Such processes include collision & coalescence, mixing processes, winds, phase changes, heat transfer (e.g., diffusive and radiative), chemical reactions, precipitation, and effects from temperature. The ambient temperature determines the balance between the amount of liquid water and that of water vapour.
On a more technical side, the paper did not communicate well why 340 nm and 440 nm should the magic numbers for the remote sensing data and the Angstrom exponents, calculated from the Aerosol Robotic Network (AERONET). There are also measurements for other wavelengths, and Svensmark et al. do not explain why these particular choices are best for the type of aerosols they want to study.
For a real effect, one would expect to see a response in the whole chain of the CCN-formation, from the smallest to the largest aerosols. So, what about the particles of other sizes (or different Angstrom exponents) than those Svensmark et al. have examined? Are they affected in the same way, or is there a reason to believe that the particles grow in jumps and spurts?
If one looks long enough at a large set of data, it is often possible to discern patterns just by chance. For instance, ancient scholars thought they found meaningful patterns in the constellations of the stars on the sky. Svensmark et al. selected a smaller number of FDs than Kristjansson et al. (published in 2008) who found no clear effect of GCR on cloudiness.
Also, statistics based on only 26 data points or only 5 events as presented in the paper is bound to involve a great deal of uncertainty, especially in a noisy environment such as the atmosphere. It is important to ask: Could the similarities arise from pure coincidence?
Applying filtering to the data can sometimes bias the results. Svensmark et al. applied a Gaussian smooth with a width of 2 days and max 10 days to reduce fluctuations. But did it reduce the ‘right’ fluctuations? If the aerosols need days to form CCNs and hence clouds, wouldn’t there be an inherent time scale of several days? And is this accounted for in the Monte-Carlo simulations they carried out to investigate the confidence limits? By limiting the minimum to take place in the interval 0-20 days after FD, and defining the base reference to 15 to 5 days before FD, a lot is already given. How sensitive are the results to these choices? The paper does not explore this.
For a claimed ‘FD strength of 100 %’ (whatever that means) the change in cloud fraction was found to be on the order 4% +-2% which, they argue, is ‘slightly larger than the changes observed during a solar cycle’ of ~2%. This is not a very precise statement. And when the FD only is given in percentage, it’s difficult to check the consistency of the numbers. E.g. is there any consistency between the changes in the level of GCR between solar min and max and cloud fraction and during FD? And how does cloud fraction relate with CWC?
Svensmark et al. used the south pole neutron monitor to define the FD, with a cut-off rigidity at 0.06GV that also is sensitive to the low-energy particles from space. Higher energies are necessary for GCR to reach the lower latitudes on Earth, and the flux tends to diminish with higher energy. Hence, the south pole monitor is not necessarily a good indicator for higher-energy GCR that potentially may influence stratiform clouds in the low latitudes.
In their first figure, they show a composite of the 5 strongest FD events. But how robust are these results? Does an inclusion of the 13 strongest FD events or only the 3 leading events alter the picture?
Svensmark et al. claim that the results are statistically significant at the 5%-level, but for the quantitative comparison (their 2nd figure) of effect of the FD magnitude in each of the four data sets studied, it is clear that there is a strong scatter and that the data points do not lie neatly on a line. Thus, it looks as if the statistical test was biased, because the fit is not very impressive.
The GRL paper claims to focus on maritime clouds, but it is reasonable to question if this is true as the air moves some distance in 4-9 days (the time between the FD and the minimum in CWC) due to the winds. This may suggest that the initial ionization probably takes place over other regions than where the CWC minima are located 4—9 days afterward. It would be more convincing if the study accounted for the geographical patterns and the advection by the winds.
Does the width of the minimum peak reveal time scales associated with the clouds? The shape of the minimum suggests that some reduction starts shortly after the FD, which then reaches a minimum after several days. For some data, however, the reduction phase is slower, for others the recovery phase is slower. The width of the minimum is 7-12 days. Do these variations exhibit part of the uncertainty of the analysis, or is there some real information there?
The paper does not discuss the lack of trend in the GCR of moderate energy levels or which role GCR plays for climate change. They have done that before (see previous posts here, here, and here), and it’s wise to leave out statements which do not have scientific support. But it seems they look for ways to back up their older claim, and news report and the press release on their paper make the outrageous claim that GCR have been demonstrated to play an important role in recent global warming.
A recent analysis carried out by myself and Gavin, and published in JGR, compares the response to solar forcing between the GISS GCM (ER) and the observations. Our analysis suggests that the GCM provides a realistic response in terms of the global mean temperature – well within the bounds of uncertainty, as uncertainties are large when applying linear methods to analyse chaotic systems. The model does not include the GCR mechanism, and the general agreement between model and observations therefore is consistent with the effect of GCR on clouds being minor in terms of global warming.
As an aside to this issue, there has been some new developements regarding GCR, galaxy dynamics and our climate (see the commentary environmentalresearchweb.org) – discussed previously here.
(Note: There are some infelicities in phrasing above, e.g. “proof… that GCR affect [sic] the low clouds” and “only give support this hypothesis” — have somebody proofread. Don’t mean to nitpick, this is a good, comprehensive review of the paper.)
I’m thinking these guys must have tried a number of correlations and picked out the ones with the highest R^2; the fact that the different effects all happen at different times makes this look an awful lot like cherry-picking.
Gee, if there was a nova in the galactic neighboroughood, we could shoot dry ice or silver iodine to the sky. But maybe I got this wrong. I just had to begin the thread.
Is this commentary longer than the GRL paper itself?
Only marginally on topic, but I was interested in the author’s rather high-handed and self-satisfied assertion that “It’s typical of non-experts not to place their ideas in the context of the bigger picture.” So, experts automatically have access to the Big Picture?
Well, that’s definitely not my experience. I was a not-very-successful scientist who moved into a different field because I lacked my colleagues’ ability to completely ignore the bigger picture and focus on a very small problem area. As my old biology teacher used to say decades ago, “an expert is someone who knows more and more about less and less until he knows everything about nothing.” And I can sort-of see what he means in today’s climate science.
As an example of a “bigger picture” guy, can I respecfully offer the example of a “climate scientist”? Not a qualification from any of the well-known universities (as far as I know), the climate scientist is a jack of all trades, with all that implies, who maybe knows a bit about modeling and computer programming too. The true scientist is maybe flattered that his or her area of expertise is being acknowledged in climate science, but do they have the context, the bigger picture, to know how it interrelates with a myriad of other areas of expertise? I very much doubt it.
Are CWC (or CLW), cloud liquid water content, and LWCF, liquid water cloud fraction, the same or similar quantities?
Regarding CWC or CLW:
http://www.ncdc.noaa.gov/oa/satellite/ssmi/ssmiclw.html
“Use of the 85 GHz measurements allows for the retrieval of extremely low amounts of CLW. It should be noted that there is considerable uncertainty in the retrieved amounts of CLW due to the lack of ground truth. However, the CLW product clearly indicates cloudiness patterns and relative magnitudes.”
Regarding LWCF, it would be nice to know which one of the many MODIS
atmospheric data products was used. See:
http://modis.gsfc.nasa.gov/data/dataprod/index.php
Are apples being compared to apples? Are there other studies that use these two (MODIS & SSM/I) data sets? In general, do we know how well correlated MODIS and SSM/I data are with AERONET data?
I’m a bit confused by this – could the lags come from some sort of feedback process, like the CO2/temperature lag in ice cores?
Sorry, I just can’t help myself. Following BPL-
“the paper did not communicated (communicate?) well why 340 nm and 440 nm should (be?) the magic numbers…”
Also “And is this accounted for in the Monte-Caro (Carlo?) simulations…”
Otherwise a great analysis! Steve
BPL: “proof… that GCR affect [sic] the low clouds”
Affect here looks right to me, as in the GCRs change the clouds. Effect, as in creates the clouds, doesn’t seem as apt to me.
I agree with Steve Fish about “communicated”.
Well one thing is for sure, the authors of the reviewed paper a least bothered to do a proper proof read. [an attempt at irony? -moderator]
From Webster
usage Effect and affect are often confused because of their similar spelling and pronunciation. The verb 2affect usually has to do with pretense . The more common 3affect denotes having an effect or influence . The verb effect goes beyond mere influence; it refers to actual achievement of a final result . The uncommon noun affect, which has a meaning relating to psychology, is also sometimes mistakenly used for the very common effect. In ordinary use, the noun you will want is effect .
perhaps the CLOUD9 at CERN will shed some light.
If one compares the sunspot number (as a proxy for GCR) to global temperature(HadCRUT3 global mean) by Fourier analysis, there is no “bump” in the temperature spectrum that corresponds to the solar cycle.
http://www.woodfortrees.org/plot/sidc-ssn/from:1900/mean:20/scale:0.002/fourier/magnitude/to:50/plot/hadcrut3vgl/from:1900/mean:20/scale:1/fourier/magnitude/to:50
Since Svensmark sees clouds respond rapidly (~1 week lag) to GCR changes, and clouds influence radiation budgets & temperature over even shorter timescales (diurnal or less), it’s hard to imagine a process that would suppress GCR influence on an eleven year timescale, and yet amplify their effect to a level that would influence climate on 50+ year timescales.
I would also like to point out that the notion of a static, unchanging cloud cover is foreign to the history of the earth or any other planet with a fluid envelope. A cloud is an observable manifestation of part of the the continuous process of water evaporation, condensation into clouds, re-evaporation, and precipitation. Condensation nuclei(CN) aren’t always the limiting process in the hydrological cycle. The large spatial variations in temperature; humidity; other competing sources of CN besides GCRs; winds, turbulence and convection which participate in the transport of water and energy that are integral parts of the hydrological cycle; and variations in the regions where GCRs create CNs will limit the global extent of and mask the visibility of the effects of GCRs on clouds and the climate. Only if you look really hard, as Svensmark or Kristjansson did, can you even find statistically robust evidence for even limited, local effects.
I would speculate that when GCR CN aren’t the rate controlling part of the hydrological cycle/cloud formation, a hypothetical step change in GCR that lasted many months (a “Dodge Event” &;>) might result in a transient effect at the beginning that had a time course similar to that seen by Svensmark with Forbush Events.
It is also possible that the Lindzen Iris Effect, which is postulated to increase clouds with increased forcing like increased solar output, combined with the Svensmark GCR effect, which increases clouds with decreases in solar output, would cancel each other out, so that the Lindzen-Svensmark net effect is zero.
The point is that forming ions is the easy part, it’s growing them to CCNs that is limiting.
“For a claimed ‘FD strength of 100 %’ (whatever that means) the change in cloud fraction was found to be of the order 4% +-2% which they argue that is ’slightly larger than the changes observed during a solar cycle’ of ~2%.”
Does the cloud cover uncertainty in this paper overlap the uncertainty in measurements obtained over the solar cycle? Elsewhere Svensmark has attributed a 3-4% change in cloud cover to the solar cycle, here 2%.
FredB,
The difference is we expect changes in climate (and therefore biogeophysical boundary conditions) to affect CO2 levels, but we don’t expect changes in climate to affect the sun or cosmic rays.
I still wonder how well we really understand the fate of these “pre-CCN” and where they go, mostly on longer timescales.
“proof… that GCR affect the low clouds” is correct in this instance, because GCR is plural – Galactic Cosmic Rays. If GCR were singular, then it would be “GCR affects the low clouds”. In both cases, the use of the verb affect is correct.
I’m not sure how constructive it is to criticise someone whose first language is not English, though.
4 Alex says: I was interested in the author’s rather high-handed and self-satisfied assertion that “It’s typical of non-experts not to place their ideas in the context of the bigger picture.” So, experts automatically have access to the Big Picture?
A little basic logic would help here. Alex complains about the author’s “high-handed” tone while engaging in high-handed rhetoric himself. And the Ignoratio Elenchi and Strawman of his conclusion could scarcely be more bald-faced. Indeed, it is unclear to me in what respect it could be more obvious that that conclusion does not follow from the premises.
RE: Time delay between arrival of the cosmic rays and the formation of clouds. If most of the cosmic rays penetrate the Van Allen belt, but a few spawn secondary, tertiary, etc. ion showers from the belt, these would perhaps be much more slow moving than the original cosmic particles. Perhaps the delay could be accounted for in this manner?
RE: Long term variations in cosmic rays: The solar system moves in relationship to other bodies in the galaxy, and this might cause variations in cosmic radiation that we have not even begin to measure and understand because of the short length of time during which we’ve even known such particles exist. Of course, that leads to the observation that NO ONE yet has enough data on this to draw any conclusions with much confidence.
I’ve updated my page on Svensmark with a bit (just above the summary) about this new item.
http://www.ossfoundation.us/projects/environment/global-warming/myths/henrik-svensmark
I highlighted the lack of connection between clouds that live (typically) in spans of hours, in relation to the considerations of days as pointed out so well by Rasmus.
As always, if anyone spots relevant inaccuracies or context problems, please let me know through the contact link on the site.
17 Gary Herstein:
Gosh, high-handedness seems to be endemic around here! Motes and eyes ….
The physics of the GCR hypothesis is interesting–but it’s interesting as physics. There is simply no way it could account for very much of the warming we have seen over the past 40 years. The rather ad hoc nature of the delays, offsets, etc. in the analysis merely highlights the primitive nature of our understanding of the role of cosmic rays. In contrast, the basics of the role of CO2 have been known for over a century. Which you gonna believe?
#13 Eli,
good to see you posting again… and absolutely succinct, on topic and even more important: right!
When the mainstream is attacked, a common mantra is “correlation is not causation” – when we have an established theory of GHG warming behind the correlation that’s under attack. Here we have a much more tenuous link between temperature and an physical effect (GCR), with a significantly less robust statistical basis for claiming a link. Does “correlation is not causation” apply here?
I tried to post this earlier, but some sort of SW glitch just gave me a waiting for ever signal.
Even if GCRs have a real (and large enough to matter) effect, if they are modulated on a time scale much longer than the silicate weathering thermostat operates, shouldn’t any signal be damped out. Assuming the thermostat works efficiently one wouldn’t expect to be able to find a signal.
From memory I recall that maritime air contains about 1 million CCN per liter, land-based air 5 to 6 millions per liter. How many CCN per liter can GCRs generate? Aren’t there many factors that can limit or promote cloud formations that are much more significant?
Chris #20, thanks for this – I was thinking of feedbacks within the supposed nucleation mechanism. But my real point was simply that a lag is not necessarily a problem, although it would require investigation. Obviously a lead would be far more problematic.
I wasn’t talking about affect versus effect! “GCR affect” should be either “GCRs affect” or “GCR affects.” Singular versus plural!
” Does “correlation is not causation” apply here?
Comment by Philip Machanick ”
The answer to that may be found here:
http://scienceblogs.com/deltoid/2009/07/the_agw_denialists_rules_for_d.php
“but a few spawn secondary, tertiary, etc. ion showers from the belt, these would perhaps be much more slow moving than the original cosmic particles.”
Which will still have lots of energy and therefore be moving quite fast and they don’t have very far to go.
And if they decay, moving slower than near-lightspeed means they decay to something else.
“The solar system moves in relationship to other bodies in the galaxy, and this might cause variations in cosmic radiation that we have not even begin to measure and understand”
But then these movements must be far too slow to cause the changes we CAN see, measure and understand.
#18, how would you get a lag of several days from any speed differences between particles that move at relativistic speeds, across a distance of considerably less than one light second?
If GCR is short for galactic cosmic rays, then affect is correct.
Rasmus raises a lot of questions about this paper. A few of them are easy to answer from a better knowledge about Svensmarks research, like:
”why 340 nm and 440 nm should the magic numbers for the remote sensing data and the Angstrom exponents “ The reason for choosing these wavelengths are that small aerosols scatter violet light. Screening the sky for a reduction of these wavelengths = screening for a reduction in small aerosols.
For a claimed ‘FD strength of 100 %’ (whatever that means) The percentage refers to the modulation of a full solar cycle. Thus 120% should be understood as a 20% bigger change in cosmic rays than you would see in a full solar cycle.
Svensmark discussed these findings in a debate arranged by the Swedish Research Council in May this year. If you can cope with Svensmarks appearance and accent you get a lot of information about this paper by watching the presentation (in English of course!) here:
http://www.vr.se/webdav/files/Webbtv/VET0010/Player/default.htm?http://www.vr.se/webdav/files/Webbtv/VET0010/Ondemand/090511/cue_0004.asx&http://www.vr.se/webdav/files/Webbtv/VET0010/Ondemand/090511/
Well, if nothing else, this article and its reply thread prove that scientists today are no more curious and open-minded than they were 100 or 200 years ago. I can see you guys in prior lives vigorously defending Phlogiston and Ether. If you have cognitive dissonance, please deal with it constructively. The truth always comes out in the end.
Wow, a self described “not very successful” science student decides this failure/ignorance is bliss and goes and joins the denialosphere. There the solid rubber brain can bounce continuously between assertion and self-satisfaction, fueled by extensive materials from the ever-evolving industry and political PR and well financed pseudo think tanks.
No amount of wide-ranging multidisciplinary work by thousands (millions?) of scientists over many decades will ever make a dent in this kind of smugness. The big picture they have access to is ever so much more reliable than that of those who do the work to gain and enlarge knowledge.
—
I probably should have resisted the temptation to pen this, but it makes me so angry because it endangers not only their posterity but ours.
Re 33 – but should we be so open-minded to devote much time to reconsidering Phlogiston and Ether?
Search on chuck+cardiff+climate
Postings debunking climatology on blogs dedicated to astrology, freakonomics … my, there certainly are a lot of postings under this name about climate.
[Response:avoid double quotes – gavin]
> avoid double quotes
This might help. I won’t bug you further about it.
http://coffee2code.com/wp-plugins/wpuntexturize/
Last update:04 April 2008
“Description: Prevent WordPress from displaying single and double quotation marks as their curly alternatives…. does NOT prevent wptexturize() from making any other character and string substitutions.”
PS, paste into Google: “chuck cardiff” +climate (about 136 hits)
for future benifit: What about double quotes? What happens?
Re “The paper doesn’t provide any proof – at best – that GCR affect the low clouds, but can at most only give support to this hypothesis”
couldn’t the same be said about any paper on climate? What would constitute a “proof” of this or any other climate hypothesis?
I firmly believe the evidence in support of AGW is overwhelming, but I have never seen a formal “proof” of it (and never expect to). It seems a little strange (and hypocritical) to be asking for “proof” of (potentially) competing hypotheses.
Chuck Cardiff August 2009 at 12:15 PM
That was a remarkably opaque comment. I -think- what you’re trying to say is, Rasmus’ article is part of an unwarranted pile-on?
It might help you to understand that Svensmark has volunteered to publicly overstate the power of cosmic ray induced cloud nucleation to explain certain features of our climate.
While so doing, Svensmark did not just stick to making apparently exaggerated claims about the predictive power of his research output but also has taken the opportunity to assert that his work nullifies the findings of a considerable number of other scientists.
By not only inflating the importance of his own work but in so doing putting an unwarranted boot in the faces of his colleagues, Svensmark’s credibility has been somewhat damaged in the scientific community. This means that everything he now publishes is going to be scrutinized with extra diligence so as to make sure whatever claims he’s making are grounded in fact.
It’s probably also true that Svenmark has aroused sheer ire; many of his critics are likely now taking a simple kind of delight in poking holes in his arguments. Human nature says that if you’re going to be needlessly combative you’d better gird yourself with good armor because you’re going to find a lot of arrows headed in your direction. That’s especially true if you mount an attack for specious reasons. Fortunately for Svensmark he seems to have a very thick skin indeed.
Review of Svensmark’s book for the layperson, with some specific collegial complaints laid at his feet:
http://physicsworld.com/cws/article/print/30103
JT – I too cringed a bit with the “The paper doesn’t provide any proof” line. Except for mathematical proofs, surely support for a hypothesis is all a scientific paper can ever hope to achieve. Some better than others obviously and some not at all. I also will provide the disclaimer that I genuinely respect and accept the massive body of evidence supporting the theory of AGW and the expertise behind it. It’s just that ‘proof’ word kinda freaked me out a bit as I normally only encounter it in arguments made by denialists who don’t even know what science is.
The physics seems rather dubious. Has anyone ever seen particle tracks in clouds? I think not. Particle tracks are only seen in human-made cloud chambers. Charged particle interactions with ordinary clouds are hard to believe. We should be seeing lines appearing suddenly in fog if it really is happening.
A mass ejection from our sun’s corona usually causes an aurora if it hits Earth, which is a lot more than the usual number of particles hitting our upper atmosphere. The only interaction between cosmic rays and a coronal mass ejection would be an electromagnetic one, the gas densities being about the same as vacuum in outer space, as usual. A frozen-in magnetic field would make charged particles spin around and apparently follow the larger mass of the coronal mass that was ejected. Gamma rays and uncharged particles would not be affected.
Please run both the physics and the astrophysics by your local department of physics and astronomy. This whole thing could be cleared up there.
“couldn’t the same be said about any paper on climate? What would constitute a “proof” of this or any other climate hypothesis? ”
It could. But it would be wrong.
The GCR paper fails to show how it does what it needs to do to have the effect required.
It just says that it waits X days to form clouds. The only reason why it waits X days is because without that, it doesn’t work. No proof as to what scientific fact demonstrable in the lab or repeatable in the real world makes it do so.
Unlike CO2 as a GG: it shows a warming based on the basic science. That it interrupts IR passage through it can be demonstrated. The effec of adding more CO2 to our atmopshere can be shown by mathematics based on the model of the atmosphere being a continuous fluid, which model can be tested to see how close it is to reality.
“Evidence” would be a better choice…
Mark,
You would be wrong as well.
AGW has not passed your own test.
There’s no proof as to what scientific fact demonstrable in the lab or repeatable in the real world makes elevated CO2 cause the needed increase in water vapor neccessary for AGW to be valid.
CO2 can only be shown to be a minor GG. The alarming levels of human caused warming can only be shown based on the presumption that levels of water vapor are increased enough to do the real warming and without the negative effects of additional cloud cover.
Are you really claiming this CO2 up=water vapor up=alarming climate warming theory has been proven?
Because that would be headline news.
People are cringing at “The paper doesn’t provide any proof” line for good reasons.
The hypocricy is freaking them out. Especially after dismissing the denialists scientists who know what science is and how it does not prove the AGW warming theory that relies upon the water vapor component.
Mark,
You would be wrong as well.
AGW has not passed your own test.
There’s no proof as to what scientific fact demonstrable in the lab or repeatable in the real world makes elevated CO2 cause the needed increase in water vapor neccessary for AGW to be valid.
Nonsense, the mechanism for CO2 to raise temperature has been adequately demonstrated in the laboratory as has the increase in water vapor pressure with increasing temperature (Clausius-Clapeyron). In contrast Svenmark has failed to show why there should be a delay in the action of CCN following CR.
On a first glimpse i can think of cosmic weather, but nevertheless this makes it even more importend in the prospects of the contribution to climate forcings we have under control.
You are wrong Howard.
“There’s no proof as to what scientific fact demonstrable ”
Stream-of-consciousness babbling shows you have no clue what you’re saying.
Here’s how it goes:
The absorption spectra of CO2 can be found in a lab.
The IR from the earth at ~300K can be set against that absorption spectra and the dimming for a given amount of CO2 can be calculated. A lab experiment can prove your calculations correct.
You seem to want to include H2O and the increase of saturation content of air with increasing temperature can be ascertained and its absorptive effects likewise calculated.
“CO2 can only be shown to be a minor GG.”
It’s the second biggest GG.
Minor????
“based on the presumption that levels of water vapor are increased enough to do the real warming”
And such effect can be worked out in the equations of radiative balance and tested against lab experiments.
“and without the negative effects of additional cloud cover.”
Incorrect. The “alarming levels” are calculated WITH cloud cover.
Remember: cloud cover can increase warming or reduce it, depending on whether it is low or high cloud.
“Are you really claiming this CO2 up=water vapor up=alarming climate warming theory has been proven?”
Yes.
Are you saying it hasn’t? Oh, of course you are, but it’s easy to say that, rather harder to prove it, which is what you HAVEN’T done.
“The hypocricy is freaking them out.”
Them? Who is “them”?
“Especially after dismissing the denialists scientists who know what science is ”
No, they don’t. Or if they do, they are ignoring it in return for mucho din ero.
http://www.agu.org/pubs/crossref/2008/2008GL035333.shtml
http://geotest.tamu.edu/userfiles/216/dessler09.pdf
See the author’s blogging report on it at:
http://www.grist.org/member/view-all/posts/1595
—-excerpt—-
I have a paper [PDF] in this week’s Science discussing the water vapor feedback. … Interestingly, it seems that just about everybody now agrees water vapor provides a robustly strong and positive feedback. Roy Spencer even sent me email saying that he agrees.
What I want to focus on here is model verification. If you read the blogs, you’ll often see people say things like “the models are completely unvalidated.” What they mean is that no one has produced a 100-year climate run with a model, then waited a hundred years, and evaluated how the model did. There are many practical problems with doing this, but the biggest is that by the time you determine if your model was right or not, it would be too late to take any meaningful action to head off the problem….