Guest Post by Willis Eschenbach
There seem to be a host of people out there who want to discuss whether humanoids are responsible for the post ~1850 rise in the amount of CO2. People seem madly passionate about this question. So I figure I’ll deal with it by employing the method I used in the 1960s to fire off dynamite shots when I was in the road-building game … light the fuse, and run like hell …
First, the data, as far as it is known. What we have to play with are several lines of evidence, some of which are solid, and some not so solid. These break into three groups: data about the atmospheric levels, data about the emissions, and data about the isotopes.
The most solid of the atmospheric data, as we have been discussing, is the Mauna Loa CO2 data. This in turn is well supported by the ice core data. Here’s what they look like for the last thousand years:
Figure 1. Mauna Loa CO2 data (orange circles), and CO2 data from 8 separate ice cores. Fuji ice core data is analyzed by two methods (wet and dry). Siple ice core data is analyzed by two different groups (Friedli et al., and Neftel et al.). You can see why Michael Mann is madly desirous of establishing the temperature hockeystick … otherwise, he has to explain the Medieval Warm Period without recourse to CO2. Photo shows the outside of the WAIS ice core drilling shed.
So here’s the battle plan:
I’m going to lay out and discuss the data and the major issues as I understand them, and tell you what I think. Then y’all can pick it all apart. Let me preface this by saying that I do think that the recent increase in CO2 levels is due to human activities.
Issue 1. The shape of the historical record.
I will start with Figure 1. As you can see, there is excellent agreement between the eight different ice cores, including the different methods and different analysts for two of the cores. There is also excellent agreement between the ice cores and the Mauna Loa data. Perhaps the agreement is coincidence. Perhaps it is conspiracy. Perhaps it is simple error. Me, I think it represents a good estimate of the historical background CO2 record.
So if you are going to believe that this is not a result of human activities, it would help to answer the question of what else might have that effect. It is not necessary to provide an alternative hypothesis if you disbelieve that humans are the cause … but it would help your case. Me, I can’t think of any obvious other explanation for that precipitous recent rise.
Issue 2. Emissions versus Atmospheric Levels and Sequestration
There are a couple of datasets that give us amounts of CO2 emissions from human activities. The first is the CDIAC emissions dataset. This gives the annual emissions (as tonnes of carbon, not CO2) separately for fossil fuel gas, liquids, and solids. It also gives the amounts for cement production and gas flaring.
The second dataset is much less accurate. It is an estimate of the emissions from changes in land use and land cover, or “LU/LC” as it is known … what is a science if it doesn’t have acronyms? The most comprehensive dataset I’ve found for this is the Houghton dataset. Here are the emissions as shown by those two datasets:
Figure 2. Anthropogenic (human-caused) emissions from fossil fuel burning and cement manufacture (blue line), land use/land cover (LU/LC) changes (white line), and the total of the two (red line).
While this is informative, and looks somewhat like the change in atmospheric CO2, we need something to compare the two directly. The magic number to do this is the number of gigatonnes (billions of tonnes, 1 * 10^9) of carbon that it takes to change the atmospheric CO2 concentration by 1 ppmv. This turns out to be 2.13 gigatonnes of carbon (C) per 1 ppmv.
Using that relationship, we can compare emissions and atmospheric CO2 directly. Figure 3 looks at the cumulative emissions since 1850, along with the atmospheric changes (converted from ppmv to gigatonnes C). When we do so, we see an interesting relationship. Not all of the emitted CO2 ends up in the atmosphere. Some is sequestered (absorbed) by the natural systems of the earth.
Figure 3. Total emissions (fossil, cement, & LU/LC), amount remaining in the atmosphere, and amount sequestered.
Here we see that not all of the carbon that is emitted (in the form of CO2) remains in the atmosphere. Some is absorbed by some combination of the ocean, the biosphere, and the land. How are we to understand this?
To do so, we need to consider a couple of often conflated measurements. One is the residence time of CO2. This is the amount of time that the average CO2 molecule stays in the atmosphere. It can be calculated in a couple of ways, and is likely about 6–8 years.
The other measure, often confused with the first, is the half-life, or alternately the e-folding time of CO2. Suppose we put a pulse of CO2 into an atmospheric system which is at some kind of equilibrium. The pulse will slowly decay, and after a certain time, the system will return to equilibrium. This is called “exponential decay”, since a certain percentage of the excess is removed each year. The strength of the exponential decay is usually measured as the amount of time it takes for the pulse to decay to half its original value (half-life) or to 1/e (0.37) of its original value (e-folding time). The length of this decay (half-life or e-folding time) is much more difficult to calculate than the residence time. The IPCC says it is somewhere between 90 and 200 years. I say it is much less, as does Jacobson.
Now, how can we determine if it is actually the case that we are looking at exponential decay of the added CO2? One way is to compare it to what a calculated exponential decay would look like. Here’s the result, using an e-folding time of 31 years:
Figure 4. Total cumulative emissions (fossil, cement, & LU/LC), cumulative amount remaining in the atmosphere, and cumulative amount sequestered. Calculated sequestered amount (yellow line) and calculated airborne amount (black) are shown as well.
As you can see, the assumption of exponential decay fits the observed data quite well, supporting the idea that the excess atmospheric carbon is indeed from human activities.
Issue 3. 12C and 13C carbon isotopes
Carbon has a couple of natural isotopes, 12C and 13C. 12C is lighter than 13C. Plants preferentially use the lighter isotope (12C). As a result, plant derived materials (including fossil fuels) have a lower amount of 13C with respect to 12C (a lower 13C/12C ratio).
It is claimed (I have not looked very deeply into this) that since about 1850 the amount of 12C in the atmosphere has been increasing. There are several lines of evidence for this: 13C/12C ratios in tree rings, 13C/12C ratios in the ocean, and 13C/12C ratios in sponges. Together, they suggest that the cause of the post 1850 CO2 rise is fossil fuel burning.
However, there are problems with this. For example, here is a Nature article called “Problems in interpreting tree-ring δ 13C records”. The abstract says (emphasis mine):
THE stable carbon isotopic (13C/12C) record of twentieth-century tree rings has been examined1-3 for evidence of the effects of the input of isotopically lighter fossil fuel CO2 (δ 13C~-25‰ relative to the primary PDB standard4), since the onset of major fossil fuel combustion during the mid-nineteenth century, on the 13C/12C ratio of atmospheric CO2(δ 13C~-7‰), which is assimilated by trees by photosynthesis. The decline in δ13C up to 1930 observed in several series of tree-ring measurements has exceeded that anticipated from the input of fossil fuel CO2 to the atmosphere, leading to suggestions of an additional input ‰) during the late nineteenth/early twentieth century. Stuiver has suggested that a lowering of atmospheric δ 13C of 0.7‰, from 1860 to 1930 over and above that due to fossil fuel CO2 can be attributed to a net biospheric CO2 (δ 13C~-25‰) release comparable, in fact, to the total fossil fuel CO2 flux from 1850 to 1970. If information about the role of the biosphere as a source of or a sink for CO2 in the recent past can be derived from tree-ring 13C/12C data it could prove useful in evaluating the response of the whole dynamic carbon cycle to increasing input of fossil fuel CO2 and thus in predicting potential climatic change through the greenhouse effect of resultant atmospheric CO2 concentrations. I report here the trend (Fig. 1a) in whole wood δ 13C from 1883 to 1968 for tree rings of an American elm, grown in a non-forest environment at sea level in Falmouth, Cape Cod, Massachusetts (41°34’N, 70°38’W) on the northeastern coast of the US. Examination of the δ 13C trends in the light of various potential influences demonstrates the difficulty of attributing fluctuations in 13C/12C ratios to a unique cause and suggests that comparison of pre-1850 ratios with temperature records could aid resolution of perturbatory parameters in the twentieth century.
This isotopic line of argument seems like the weakest one to me. The total flux of carbon through the atmosphere is about 211 gigtonnes plus the human contribution. This means that the human contribution to the atmospheric flux ranged from ~2.7% in 1978 to 4% in 2008. During that time, the average of the 11 NOAA measuring stations value for the 13C/12C ratio decreased by -0.7 per mil.
Now, the atmosphere has ~ -7 per mil 13C/12C. Given that, for the amount of CO2 added to the atmosphere to cause a 0.7 mil drop, the added CO2 would need to have had a 13C/12C of around -60 per mil.
But fossil fuels in the current mix have a 13C/12C ration of ~ -28 per mil, only about half of that requried to make such a change. So it is clear that the fossil fuel burning is not the sole cause of the change in the atmospheric 13C/12C ratio. Note that this is the same finding as in the Nature article.
In addition, from an examination of the year-by-year changes it is obvious that there are other large scale effects on the global 13C/12C ratio. From 1984 to 1986, it increased by 0.03 per mil. From ’86 to ’89, it decreased by -0.2. And from ’89 to ’92, it didn’t change at all. Why?
However, at least the sign of the change in atmospheric 13C/12C ratio (decreasing) is in agreement with with theory that at least part of it is from anthropogenic CO2 production from fossil fuel burning.
CONCLUSION
As I said, I think that the preponderance of evidence shows that humans are the main cause of the increase in atmospheric CO2. It is unlikely that the change in CO2 is from the overall temperature increase. During the ice age to interglacial transitions, on average a change of 7°C led to a doubling of CO2. We have seen about a tenth of that change (0.7°C) since 1850, so we’d expect a CO2 change from temperature alone of only about 20 ppmv.
Given all of the issues discussed above, I say humans are responsible for the change in atmospheric CO2 … but obviously, for lots of people, YMMV. Also, please be aware that I don’t think that the change in CO2 will make any meaningful difference to the temperature, for reasons that I explain here.
So having taken a look at the data, we have finally arrived at …
RULES FOR THE DISCUSSION OF ATTRIBUTION OF THE CO2 RISE
1. Numbers trump assertions. If you don’t provide numbers, you won’t get much traction.
2. Ad hominems are meaningless. Saying that some scientist is funded by big oil, or is a member of Greenpeace, or is a geologist rather than an atmospheric physicist, is meaningless. What is important is whether what they say is true or not. Focus on the claims and their veracity, not on the sources of the claims. Sources mean nothing.
3. Appeals to authority are equally meaningless. Who cares what the 12-member Board of the National Academy of Sciences says? Science isn’t run by a vote … thank goodness.
4. Make your cites specific. “The IPCC says …” is useless. “Chapter 7 of the IPCC AR4 says …” is useless. Cite us chapter and verse, specify page and paragraph. I don’t want to have to dig through an entire paper or an IPCC chapter to guess at which one line you are talking about.
5. QUOTE WHAT YOU DISAGREE WITH!!! I can’t stress this enough. Far too often, people attack something that another person hasn’t said. Quote their words, the exact words you think are mistaken, so we can all see if you have understood what they are saying.
6. NO PERSONAL ATTACKS!!! Repeat after me. No personal attacks. No “only a fool would believe …”. No “Are you crazy?”. No speculation about a person’s motives. No “deniers”, no “warmists”, no “econazis”, none of the above. Play nice.
OK, countdown to mayhem in 3, 2, 1 … I’m outta here.
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Hi Ferdinand.
I asked you this question way back in the thread but cannot trace an answer.
You make an eloquent case that man is responsible for the increase in co2 over the last 150 years. However I believe that you do not think that increased CO2 has any particular impact on the slight temperature rise we can observe over the last 350 years (CET)
Can you point me to a paper whereby you set out your case that whilst we are responsible for increased CO2 concentration this has limited impact on temperatures?
thanks
Tonyb
Hi Tony,
As an aside, the films of Iain Stewart were broadcasted here on Flemish television last month… Had some comment on their website, like the “hide the decline” as discussed in Portsmouth. Now after Climategate did break out, the truth is emerging and I wonder if Iain will remember our discussion…
About the effect of a CO2 doubling:
– The physics of increased CO2 on IR absorption is quite solidly established. The effect is logarithmic, which means that each doubling has about the same effect. The effect of CO2 increase, water and other gases was measured in lab circumstances, leading to the Hitran calculations, the transmission of IR through the atmosphere for different wavelengths. That shows a reasonable agreement with real life measurements done by satellites. The effect of increasing CO2 until now is marginal and at the edge of the satellites detection system.
Nevertheless, the effect of only a CO2 doubling, without feedbacks, is limited to about 0.9 C. Including water vapor feedback, which is reasonably anticipated for higher seawater temperature, that gets to 1.3 C. Still a benign warming.
The other feedbacks which brings the IPCC estimate to 1.5-4.5 C, or an average of 3 C for 2xCO2 is where the discussion starts. That is based on two items: the negative forcing caused by human induced aerosols and the influence of clouds.
The first item is quite interesting: the cooler 1945-1975 period coudn’t be reproduced by the earlier models, as CO2 was steadily increasing. Therefore they needed a cooling support, which was found in human made sulfate aerosols. In that period these were increasing. Now if one calculates the effect of human sulfate aerosols (average lifetime in the troposphere of about 4 days) back from the natural sulfate aerosols by the Pinatubo eruption (average lifetime in the stratosphere about 3 years), then the net effect of human aerosols is less than 0.1 C cooling and since 1990 about steady (less in the Western world, more in SE Asia).
That was reflected in one of the shortest discussions at RealClimate:
http://www.realclimate.org/?comments_popup=245
Where a lot of links can be found.
In summary: the effect of cooling aerosols is largely overestimated (and of warming aerosols like soot underestimated), which has as consequence that the effect of GHGs is largely overestimated too, as both are in counterbalance for the 1945-1975 cooler period.
The second – even worse – problem in the climate models is the effect of clouds. These represent the largest factor in the width of the range of estimates. But the strange point is that all models include clouds as a positive feedback, while all specialists in cloud cover see clouds as a negative feedback. Clouds even may be part of internal earth cyclic behaviour (PDO, NAO,…) and may be a forcing for temperature, leading to temperature changes, instead of reverse.
All together in summary:
I do think that increasing of CO2 will have some effect, but at the low side or lower than the range the IPCC/models use. Thus in general a benign effect…
Hi Ferdinand
I rather liked Iain Stewart although he was not able to answer our questions very well. He had a big following of groupies though didn’t he? 🙂
Driving that huge billboard around the city showing the Hockey stick made for great TV but poor science.
Ok, I understand your position now on warming. I don’t really disagree with you-I think the Misclowski theory appears to work through the physics quite well and he reckons a theoretical 0.7C rise on doubling, although a real world situation will almost certainly mitigate the actual rise. In this connection the positive feedbacks are rather fanciful I always feel. They have never happened in the past with this sort of gentle temperature increase so why should they happen now?
Why do you think that temperatures started rising hundreds of years before (possible) man made increases in CO2.
It is shown in numerous instrumental datasets such as CET
http://c3headlines.typepad.com/.a/6a010536b58035970c0120a7c87805970b-pi
By the way this has been a very interesting discussion with Jeff Glassman. I would score you 3 goals each and you are now in the last phase of extra time before the penalty shoot out. 🙂
I was rooting for Holland in the final but didn’t feel they played as well as they could and resorted to a lot of brutal football and on balance deserved to lose. A lesson for you and Jeff here, keep it clean!
best personal regards
Tonyb.
Re Ferdinand Engelbeen, 7/12/10 at 5:18 pm
1. Re Second Law & Dynamic Equilibrium
The Second Law eats Dynamic Equilibrium for breakfast. The Second Law tells us that systems spontaneously maximize their entropy, and that reversible processes do not exist in the real world. Without a definition for Dynamic Equilibrium, the notion remains too vague to even rank as a model. You use it is a universal substitute for thermodynamic equilibrium, When the latter is required for an à priori model but does not exist in the real world application, you insert dynamic equilibrium. As used by Wikipedia, Dynamic Equilibrium applies only to reversible processes, which violate the Second Law.
2. Re gain factor
Cited in full, you relied on this description of SPO CO2 data:
>>Monthly values are expressed in parts per million (ppm) and reported in the 2003A SIO manometric mole fraction scale. The monthly values have been adjusted to the 15th of each month. Missing values are denoted by -99.99. The “annual” average is the arithmetic mean of the twelve monthly values. In years with one or two missing monthly values, annual values were calculated by substituting a fit value (4-harmonics with gain factor and spline) for that month and then averaging the twelve monthly values. CDIAC, Keeling, C.D., et al., May, 2005.
As I previously reported to you, that citation is out of date. The new version is materially different, and constitutes a correction:
>>Values above are taken from a curve consisting of 4 harmonics plus a stiff spline and a linear gain factor, fit to monthly concentration values adjusted to represent 2400 hours on the 15th day of each month. Data used to derive this curve are shown in the accompanying graph. Units are parts per million by volume (ppmv) expressed in the 2003A SIO manometric mole fraction scale. The “annual average” is the arithmetic mean of the twelve monthly values. CDIAC, Keeling, R. F., et al., May 2008.
http://cdiac.ornl.gov/trends/co2/sio-spl.html
The ambiguous phrase “4-harmonics WITH gain factor and spline” (CAPS added) no longer can be read to connect just to missing data. It now clearly applies to the entire curve, as it probably did in the first instance. As I explained previously, a gain factor is not an appropriate name for extrapolation or interpolation.
The CO2 data are generally worthless when published only with secret gain factors or smoothing filters with secret forms or secret parameter values.
3. IPCC data smoothing
You provided links to two curves on your website. Neither even slightly resembles the records provided by IPCC in time span, variability, or data presentation. Compare with MLO v. SPO, TAR, Figure 3.2, p. 201, and MLO v. Baring Head, AR4 Figure 2.3, p. 138. The problem lies in those IPCC figures, and not some vague laboratory data. The fact that your curves might agree within 0.1 ppmv is irrelevant to the problem IPCC creates. IPCC’s smoothing appears in two ways. (1) The variabilities of both the trend and the seasonal variance of each record, considered separately, are too small compared with real data. And (2), the records considered pairwise agree too closely. You say that IPCC applied “no additional smoothing”. However, the smoothing was applied SOMEWHERE prior to publication in IPCC reports. Looking back just one level and according to IPCC authors, the smoothing included “4 harmonics plus a stiff spline and a linear gain factor” for SPO and Baring Head, at least, but not for MLO.
You insist,
>>In fact, if you take MLO’s data for convenience (the longest continuous record), or South Pole data or more or less “global” data (the average of several ocean level stations), it hardly matters as the difference in trend over the past 50+ years is less than 5 ppmv, while the level increased some 70 ppmv over the same period.
This is after filtering, smoothing, and a gain factor adjustment, all intended to make divergent data agree. If you find that the records agree at some level lower than the final, publication level, then you should work to discover how the data were manipulated to make that happen.
4. IPCC’s doubling error.
You say,
>>The point was that the current small deviations of CO2 levels around the world have no importance for the IPCC at all, as their models are based on a doubling and more in the future.
You left out important words. IPCC models climate sensitivity as a constant increase for each doubling of CO2 concentration. That is a logarithmic relationship. As a result, the effects of CO2 never saturate. The total RF for CO2 can quickly exceed the limits of its absorption bands. This model violates the Beer-Lambert Law. IPCC is enamored with the logarithmic model because (1) it exaggerates the effect of CO2 and (2) it doesn’t require the determination of the present day operating point for the climate with respect to CO2 concentration. The data to make that determination do not exist.
Since composing this response, you provided additional beliefs with respect to the logarithmic relationship, saying on 7/13/10 at 5:52 am
>>The physics of increased CO2 on IR absorption is quite solidly established. The effect is logarithmic, which means that each doubling has about the same effect.
This might be a belief in some circles, but it remains a violation of physics and even reason. For an à priori model, the logarithm function is easily fit to any concave (i.e., “concave down”) segment of specified curve in a region. That limited application of curve fitting is not sufficient to proclaim the specified curve to be logarithmic. As far as an à posteriori model is concerned, the experiment by which IPCC claims the sensitivity to the logarithm of CO2 concentration is linear has not been conducted. The Beer-Lambert Law provides instead that the response to the logarithm of increasing CO2 is an S-curve, concave up at first, then concave down.
Also you use expressions like “solidly established” and other references to wide spread practices. This may be the reason you subscribed to the belief system, but it is no part of science. A belief or a conjecture held by a petagaggle of climatologists is, alas, just a belief or a conjecture.
5. DIC measurements
You wrote,
>>Both DIC and CO2(g) were measured at Bermuda and show that DIC increases with less than 10% of the increase of CO2(g), which shows that the ocean’s mixed layer doesn’t absorb extra CO2 in the atmosphere that well.
I don’t understand what you have written. If I could see the data, I would have a chance. I exhausted myself searching through your citation plus its embedded citations through three or four levels, which came to nothing but calculations based on the hypothetical equilibrium model. Where exactly does the 10% number appear? With that information, I might understand the implied experiment and how you came to your conclusion that the ocean doesn’t absorb CO2 “that well” when CO2 is highly soluble in water.
6. Non-responsive answers.
I asked you where are the data supporting “a few tenths of a ppmv”, and you answer that I can make the calculations.
I asked why IPCC didn’t exploit what you assert: that the raw data match. You answer IPCC didn’t need to.
7. Basis for mass balance analysis
You claim,
>>The total mass balance of CO2 in the atmosphere is NOT based on the in/outflows of the atmosphere with the oceans and vegetation, it is based on the inventories of fossil fuel use and the measured increase in the atmosphere. CAPS replacing bold in original.
Previously, you wrote,
>>There are several mass balances in use, including by the IPCC. The IPCC doesn’t assume a separate aCO2 cycle (as MASS, but they do for isotope changes), as all emissions simply are mixed into the natural CO2 cycle. CAPS added.
And I responded,
>>Contrary to your assertion, IPCC does have separate ACO2 and nCO2 cycles. These it details in its carbon cycle figure. The ACO2 values are in red, the nCO2 values are in black. AR4, Figure 7.3, p. 515.
and you answered,
>>OK, this is the first time that I have looked at that graph. It looks identical to the NASA graph (which I thought it was), except that these make no differentiation between nCO2 and aCO2. It looks like a best guess of the partitioning between aCO2 and nCO2 in the total flows not as really separate cycles (except for the emissions of course). I suppose that the IPCC tried to show how much CO2 has increased (as mass) in different compartments as result of the emissions, but there is certainly not that much aCO2 in the atmosphere (at maximum some 8%) and I don’t think that the flows between oceans and atmosphere increased with 20 GtC/yr due to the emissions… This is simply bad work. Engelbeen, 6/25/10, 3:10 pm.
So you previously recognized and wrote about IPCC reporting on the mass of CO2 and “the flows between oceans and atmospheres”. Just to be perfectly clear, Figure 7.3 which we discussed included the mass of CO2 in the reservoirs of the Atmosphere, Fossil Fuels, and Vegetation, Soil & Detritus. It included four exchange fluxes, in and out, between the atmosphere and the Vegetation parts, and it included four exchange fluxes, in and out, between the ocean and the atmosphere. The caption of Figure 7.3 includes,
>>Gross fluxes generally have uncertainties of more than ±20% but fractional amounts have been retained to achieve overall BALANCE when including estimates in fractions of GtC yr–1 for riverine transport, weathering, deep ocean burial, etc. CAPS added.
Now you say, with emphasis,
>>The total mass BALANCE of CO2 in the atmosphere is NOT based on the in/outflows of the atmosphere with the oceans and vegetation, it is based on the inventories of fossil fuel use and the measured increase in the atmosphere. CAPS added.
Ignoring the logical disconnect between the total mass balance compared with the fossil fuel use in your claim, it is nonetheless false. You appear not to be following the dialog on this thread. You are hip shooting – going for volume over substance.
You say,
>>As repeatedly said and shown with references to the (inter)calibration procedures, which you obviously choose to ignore, intercalibration is common practice in any type of laboratory to assure the correct operation of equipment and the correct value of calibration gases. This has nothing to do with bringing the observations into agreement. The observations are what they are, if you like them or not. And the IPCC has no business with the calibration and techniques used.
I have ignored none of it, and your accusation is baseless. You are wasting space by endlessly repeating the same irrelevant information about the quality of laboratory data. The fraud is manifest in the IPCC reports. The clues are the various inter and intra network calibrations admitted by IPCC, and the fact of the secret linear gain factors. IPCC applied those gain factors to the monthly data from stations other than MLO, and then provided graphs to show monthly MLO data tightly overlapping SPO and Baring Head data. You seem unable to discuss this matter and to stay on subject.
8. Analysis by partial derivatives
In case you weren’t conversant with partial derivatives, I laboriously laid out my analysis for you, saying,
>>This analysis is by the partial derivative with respect to temperature, keeping the responses to pressure constant. It shows why a more complete mass balance treatment is necessary.
You responded,
>>That is only one part of the equation (and not inversely, it is a ratio coefficient), the other part is the effective concentrations on both sides.
Of course! That is what I was trying to show you. That is what a partial derivative analysis means. Only one variable is to change at a time. The others are temporarily kept constant. I also told you what the next step is, and you repeat what the next step is.
9. pCO2(aq), the imaginary number.
I’ve lost count of the number of times you’ve tried to make this point:
>>If these are equal (including Henry’s Law) at the temperature of the tropical waters, the outgas will be zero. Thus the delta between pCO2(aq) and pCO2(g) is what drives the flux.
Henry’s Law does not involve the pCO2(aq). Henry was not so foolish. If pCO2(aq) existed, we might be able to measure it. If such things existed, we might be able to build a theory for the rate of flux between a gas and its solvent. Henry’s Law might be a lot easier to express, even limited to ideal gases. We might not need the condition of thermodynamic equilibrium.
On the other hand, the following equation is relevant:
F = ks(pCO2(aq) – pCO2(g))
It is discussed in the Rocket Scientist’s Journal, “On Why CO2 Is Known Not To Have Accumulated in the Atmosphere, etc.”, Eq. (1). However, pCO2(aq) is actually the pCO2(g) in the air above a sample of the water after the system has reached some approximation equilibrium. It does not exist in the water to resist the flux, F, though the equation treats it that way. It is a scientific conjecture, set forth in a number of papers as if it were a validated model, i.e., a theory. The parameter k is the gas exchange relationship, usually attributed to Wanninkhof, an IPCC contributing author, for his extensive writings trying to establish a meaningful value based on wind speed and a viscosity factor for the water known as the Schmidt number. Wanninkhof, 1992, 1999, 2003. Wanninkhof says,
>>While it is doubtful that a single, simple parameterization with wind speed can cover all spatial scales and environmental conditions, wind is currently the most robust parameter available to estimate global exchange. Wanninkhof, R., et al., “A Cubic Relationship between Air-Sea CO2 Exchange and Wind Speed”, Geo.Phys.Res.Ltr., vol. 26, No. 13, 1889-1892, 7/1/99.
In other words, he’s looking for his keys where the light is good.
The gas exchange parameter has grave problems. Wanninkhof provides estimates for it from various investigators. See RSJ, “On Why CO2, etc.”, id., Figure 2. In this figure, most of the estimators go to zero at zero wind speed, meaning Henry’s Law ceases in zero wind. The disparity at high wind velocity on that chart is 8:1 between investigators. In Wanninkhof’s presentation to the Joint Global Ocean Flux Study Committee on 5/5/03 on his work, he provides a chart showing an estimate attributed to “Weseley et al, 1982” that is 16 times as great as an estimator fit to bomb-14C. Id., Slide 13 of 41. On Slide 15 he says, “Cross (1-way fluxes are about 50 times greater than net fluxes”. The meaning of net in this statement is unclear, due in part to the PowerPoint presentation having no accompanying text. Also, the meaning of net remains hidden within the several papers available on this subject, including Takahashi, “Global sea-air CO2 flux based on climatological surface ocean pCO2, etc.”, Deep-Sea Research II 49 (2002) 1601-1622. Is the k parameter calibrated to produce a net flux, or do the investigators do the subtraction after calculating the flux? Any measurements used to extract the k parameter would necessarily be a net amount, but what is the duration of the individual flux measurements?
Wanninkhof early worried:
>>It is not clear whether wind speed can be used by itself to estimate gas transfer velocities. Wanninkhof, R., “Relationship Between Wind Speed and Gas Exchange Over the Ocean”, J. Geophs.Res., vol. 97, No. C5, 7373-7382, 5/15/1992.
In the abstract, Wanninkhof says,
>>Some of the variability between different data sets can be accounted for by the suggested mechanisms, but MUCH OF THE VARIATION APPEARS DUE TO OTHER CAUSES. CAPS added, id.
The situation seems to have improved little over the ensuing two decades, although the writings and reliance on a spooky k parameter have proceeded as if the model had been validated. Seeing the actual flux data to which the coefficient was fit could have provided insight into the problem. And indeed, the problem should have been posed as a scientific model to predict air-sea CO2 flux, with the prediction tested against field data. That is not evident. Without such validation, the model could be no more than a hypothesis. Moreover, considering the fact that the crucial parameter of pCO2(aq) does not exist, ever — but certainly not simultaneously with pCO2(g) – reduces the model to a mere conjecture.
The fact that the Takahashi diagram, which is calculated from the Wanninkhof k parameter, results in a coherent picture lends no weight to the conjecture. The same observation applies to the Revelle factor. See RSJ, “On Why CO2, etc.”, Figures 3 and 4. The fact that something can be measured validates no model. Without the model and an explicit prediction, we can’t say what was actually measured. The Takahashi diagram and the Revelle chart appear to be SST plots and consequences of ordinary solubility, not flux.
10. The resurrection of dynamic equilibrium
You say,
>>>>Why would that happen? Are you claiming Le Chatelier’s principle applies to your dynamic equilibrium?
>>Of course that applies, as that is the case for every dynamic equilibrium. And the whole carbon cycle behaves like a simple process in dynamic equilibrium.
Where is you support for these claims? You weaken all your arguments by laying down naked claims for some.
11. AIRS data
The AIRS data confound my model and IPCC’s. The Equatorial outgassing recognized by IPCC and relied upon in my ocean macromodel, while visible in the Takahashi diagram is not visible in the AIRS data. Of course, the AIRS observations are well up into the troposphere, and my model in which the outgassing affects the MLO record need not rise to the AIRS altitudes. The AIRS data are sure to improve modeling. However, the new data tend strongly to invalidate IPCC’s critical well-mixed assumption.
For Tonyb, 7/13/10 at 7:46 am:
3 – 3? I demand a recount. Let’s invoke instant replay, goal by goal.
Jeff Glassman says:
July 14, 2010 at 8:47 am
1. Re Second Law & Dynamic Equilibrium
The Second Law eats Dynamic Equilibrium for breakfast. The Second Law tells us that systems spontaneously maximize their entropy, and that reversible processes do not exist in the real world. Without a definition for Dynamic Equilibrium, the notion remains too vague to even rank as a model. You use it is a universal substitute for thermodynamic equilibrium, When the latter is required for an à priori model but does not exist in the real world application, you insert dynamic equilibrium. As used by Wikipedia, Dynamic Equilibrium applies only to reversible processes, which violate the Second Law.
I don’t think that we ever will agree on this, but the natural world is full of processes which are in dynamic equilibrium, which obey the second law of thermodynamics by going into chemical, mass and thermal dynamic equilibrium with maximum enthropy when in isolation. The difference is that you make an absolute condition of non-reversibility (which exists for the enthropy), while the maximum enthropy may include any dynamical chemical equilibrium where the net (mass, energy) transfer is zero.
See http://en.wikipedia.org/wiki/Chemical_equilibrium
Some nice discussion about the many interpretations of the second law:
http://www.phys.uu.nl/igg/jos/publications/dresden.pdf
2. Re gain factor
If Keeling Sr. only used the “gain factor” if 1-2 months were missing, and IF Keeling Jr. used a “gain factor” to fit the South Pole data to the Mauna Loa data, that would give a hell of a jump between 2005 and 2006, as the first gain factor didn’t change the curve at all (other than for maximum 2 months), while the second gain factor must have a profound effect, according to you.
Further, as already said but which again is ignored, the second procedure applies not to the continuous measurements at the South Pole or any other station, but to biweekly flask samples as clearly is indicated in your reference:
Precise measurements of atmospheric CO2 at the South Pole have been obtained by Scripps Institution of Oceanography (SIO) researchers since 1957. This record is based primarily on biweekly flask sampling.
Then the whole curve is made to make a nice plot from noisy data.
The IPCC in its graph only used the “cleaned” monthly averaged continuous measurements of the different stations, without any “gain factor” (except for missing months), and compared the curve of Mauna Loa as delivered by NOAA, with that of Baring head, delivered by the National Institute of Water and Atmospheric Research of New Zealand. The “cleaned” monthly averages from Baring Head can be found here:
http://cdiac.ornl.gov/trends/co2/baring.html or directly from:
http://cdiac.ornl.gov/ftp/trends/co2/baring.177
This includes the notes (besides instrument malfunction to reject data):
Baseline data are selected from the remaining data based on steadiness of the CO2 concentration and on wind direction. At Baring Head maritime well mixed air masses come from the Southerly direction, and a baseline event is normally defined as one in which the local wind direction is from the South and the standard deviation of minute-by-minute CO2 concentrations is much smaller than 0.1 ppmv for 6 or more hours.
and
Annual means are simply the arithmetic mean of the monthly values calculated by CDIAC. Annual means are provided only for years with complete monthly records.
No curve fitting, no “linear gain” included at all…
But the raw flask data from different stations are available too: Keeling Sr. has plotted a few of them here:
http://cdiac.ornl.gov/ftp/ndp001a/ndp001a.pdf
The raw flask data for the different stations are here:
http://cdiac.ornl.gov/ftp/trends/co2/sio-keel-flask/
3. IPCC data smoothing
Was explained in item 2.
The IPCC doesn’t smooth, only used the “cleaned” monthly averages delivered by others. The rules for excluding outliers are pre-defined and the results with or without outliers are equal for any practical purpose.
You provided links to two curves on your website. Neither even slightly resembles the records provided by IPCC in time span, variability, or data presentation.
I have done my homework: if the raw and smoothed data for a few years resemble each other within the measurement error, I don’t see any reason to assume that the data for the rest of the years is manipulated to prove any preconceived theory. I have more interesting work to do than recalculate every single bit of information, but I like to check some random samples to see if what they say is true.
IPCC’s smoothing appears in two ways. (1) The variabilities of both the trend and the seasonal variance of each record, considered separately, are too small compared with real data. And (2), the records considered pairwise agree too closely.
Sorry, but that is your problem, not that of the IPCC, neither mine. Both the raw data (continuous and flasks) and the “cleaned” data are very close to each other for all “base level” stations over the world. That is probably because CO2 in general is well mixed. Which is what you don’t like to accept. Alternatively, you can measure the CO2 levels yourself. Hawaii is a nice spot to start with. The South Pole a little harsh, but Antarctica still is on my wish list of things to do before I die…
Final note on this: If you accuse someone or some organisation of huge manipulation of data, as you do, please check the facts thoroughly before you put that accusation online…
4. IPCC’s doubling error.
Sorry, no discussion on that point. I have given my opinion for Tony, and that is it.
5. DIC measurements
You wrote,
>>Both DIC and CO2(g) were measured at Bermuda and show that DIC increases with less than 10% of the increase of CO2(g), which shows that the ocean’s mixed layer doesn’t absorb extra CO2 in the atmosphere that well.
I don’t understand what you have written. If I could see the data, I would have a chance. I exhausted myself searching through your citation plus its embedded citations through three or four levels, which came to nothing but calculations based on the hypothetical equilibrium model.
You are looking too far: the Bermuda plot shows the nDIC, which is measured (but normalized to standard conditions of salinity) and the (not shown, but measured) CO2 levels in the atmosphere. I have taken the CO2 levels from Mauna Loa as base, but as the trend in the NH is the same for all stations, that makes no difference. While pCO2(g) increased 10%, nDIC (in micromoles/kg) increased 0.8% in the same period. See:
http://www.bios.edu/Labs/co2lab/research/IntDecVar_OCC.html
6. Non-responsive answers.
I asked you where are the data supporting “a few tenths of a ppmv”, and you answer that I can make the calculations.
As can be seen in the different plots I already sent in, where raw and “cleaned” data were compared in the same plot, there is no visible difference in seasonal amplitude, average or trend. Based on the scale of the plots, that are differences less than o.2 ppmv. But I have calculated the averages too, which was added in the same message:
The 2008 average for the raw hourly data of Samoa is 384.00 ppmv, for the selected daily data it is 393.91. For Mauna Loa: raw 385.34, selected 385.49.
I suppose that I may say that at least for Mauna Loa and Samoa (but also for all other baseline stations) the atmosphere is very well mixed…
Thus I supplied the differences in average for including and excluding the outliers. The non-excluded data are used for daily, monthly and yearly averages. The monthly averages is what the IPCC plotted. I have done that for a few years. If you don’t trust my calculations, then please help yourself…
I asked why IPCC didn’t exploit what you assert: that the raw data match. You answer IPCC didn’t need to.
Why should the IPCC have a look at the raw data at all, they are interested in background CO2 increase, not the marginal noise around the trend. And they trust NOAA to deliver the best data availbale. Even valued skeptics like Dr. Spencer, Lindzen and many others accept the (cleaned) Mauna Loa data as presented by NOAA.
7. Basis for mass balance analysis
So you previously recognized and wrote about IPCC reporting on the mass of CO2 and “the flows between oceans and atmospheres”. Just to be perfectly clear, Figure 7.3 which we discussed included the mass of CO2 in the reservoirs of the Atmosphere, Fossil Fuels, and Vegetation, Soil & Detritus. It included four exchange fluxes, in and out, between the atmosphere and the Vegetation parts, and it included four exchange fluxes, in and out, between the ocean and the atmosphere.
OK, as a starter, let’s forget the flux estimates for aCO2/nCO2 as what was plotted by the IPCC. There are too many errors in it. For the total mass of CO2 in the atmosphere, the total CO2 flows are of interest, not the partitioning between aCO2 and nCO2. NASA made the original plot:
http://earthobservatory.nasa.gov/Features/CarbonCycle/Images/carbon_cycle_diagram.jpg
Thus what is change in mass of CO2 in the atmosphere after a year? That is the difference of all ins and outs (seen from the atmosphere):
dCO2(atm) = CO2(in1 + in2 + in3 + …) – CO2(out1 + out2 + out3) + aCO2
4 GtC = CO2(90 + 121 + …) – CO2(92 + 122 + …) + 8 GtC
or
CO2(in) – CO2(out) = – 4 GtC
With other words, without knowing any individual flux or change in fluxes or direction of fluxes or total influxes or total outfluxes, the net result of one year carbon exchanges in all directions is that the sum of all outflows during one year is 4 GtC larger than the sum of all inflows. For another year that may be 3 GtC or 5 GtC, but in the past 50+ years always more outflow than inflow.
You seem somewhat disconnected with the principles of a bank account: while a huge amount of money flows back and forth between many contributors and many loaners, want counts is what the net result is off all those transactions is at the end of the year. If your contribution is larger than the gain, better look for another bank…
If you have a bussiness you don’t need a detailed record of all transactions during a day (you better do, but that is a different story), to count what is in your cash register and know what your gain or loss was for that day.
Thus while the detailed fluxes and inventories of the different compartiments are of interest for the details of the carbon cycle, they are not needed to know the net result. And as the increase in the atmosphere is less than the emissions, and the laws of non-destruction of mass still hold, the cause of the increase is perfectly known.
The clues are the various inter and intra network calibrations admitted by IPCC, and the fact of the secret linear gain factors. IPCC applied those gain factors to the monthly data from stations other than MLO, and then provided graphs to show monthly MLO data tightly overlapping SPO and Baring Head data. You seem unable to discuss this matter and to stay on subject.
You can endlessly repeat your accusations, but you have not a shred of evidence except your own misinterpretations of normal calibration procedures for calibration gases and equipment, not of the data) and the fact that the “gain” is the difference with last year needed for curve fitting of noisy flask data, not the continuous measurements.
8. Analysis by partial derivatives
Maybe my misinterpretation then, but need to look into the details. My interpretation was that in your calculation the outflow was constant over time, which can’t be the case if CO2(g) increases and temperature at the equator remains equal.
9. pCO2(aq), the imaginary number.
I’ve lost count of the number of times you’ve tried to make this point:
>>If these are equal (including Henry’s Law) at the temperature of the tropical waters, the outgas will be zero. Thus the delta between pCO2(aq) and pCO2(g) is what drives the flux.
Henry’s Law does not involve the pCO2(aq). Henry was not so foolish. If pCO2(aq) existed, we might be able to measure it.
Well, they are going to measure it (some do already in real life tests), liquid-liquid without any air involved:
http://bibapp.mbl.edu/works/18724
In any case, pCO2(aq) is the tendency of CO2 in solution to escape and proportional to the concentration of CO2 in the water phase, independent of the gas phase above it.
Moreover, considering the fact that the crucial parameter of pCO2(aq) does not exist, ever — but certainly not simultaneously with pCO2(g) – reduces the model to a mere conjecture.
The fact that pCO2(aq) is measured by seaships and other means for over 80 years and the database now contains many millions of such data, simultaneously with pCO2(g) of the same places, which shows huge differences from the equator (positive) to the poles (negative) is of course some trivial aside…
While I agree that the atmosphere – ocean flux is far from settled, if there is little to no wind, the flux of CO2 in/out the oceans depends largely on diffusion of CO2 through the water phase + the water-gas transfer, which are extremely slow. Whatever the pCO2(g)-pCO2(aq) difference. Or whatever Henry’s Law predicts. What you still not accept is that getting an equilibrium between what Henry’s Law dictates in the water phase from the gas phase concentration is not instantaneous and needs a lot of time, much more time than the changes in chemical equilibria which result from the changes in increasing or decreasing [CO2] in the water mass.
The Takahashi diagram and the Revelle chart appear to be SST plots and consequences of ordinary solubility, not flux.
Of course they appear like SST plots, as temperature is one of the main factors, but it is not the only factor.
10. The resurrection of dynamic equilibrium
You say,
>>>>Why would that happen? Are you claiming Le Chatelier’s principle applies to your dynamic equilibrium?
>>Of course that applies, as that is the case for every dynamic equilibrium. And the whole carbon cycle behaves like a simple process in dynamic equilibrium.
Where is you support for these claims? You weaken all your arguments by laying down naked claims for some.
According to Wiki, Le Chatelier’s principle:
Any change in status quo prompts an opposing reaction in the responding system.
If the temperature of seawater at the equator increases, more CO2 will build up in the atmosphere and that counteracts the release of CO2, at the same time increasing the uptake at the poles, even at constant temperature (you know Henry’s Law)…
If humans release CO2 into the atmosphere, that will increase the CO2 level of the atmosphere, which will reduce the release of CO2 at the equator and increase the uptake near the poles…
The CO2 response to temperature changes is remarkably linear over the past 420,000 years.
The CO2 response to human emissions is remarkably linear over the past 100+ years:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_co2_1900_2004.jpg
Thus the whole CO2 cycle behaves as a simple linear, first order process where the dynamic equilibrium is disturbed by temperature and the emissions.
11. AIRS data
Of course, the AIRS observations are well up into the troposphere, and my model in which the outgassing affects the MLO record need not rise to the AIRS altitudes. The AIRS data are sure to improve modeling. However, the new data tend strongly to invalidate IPCC’s critical well-mixed assumption.
There are no practical differences between measurements taken at sealevel at Hawaii and Mauna Loa at 3,400 m. There are no practical differences between AIRS data at the latitude of Mauna Loa (with peak at 6,000 m) and the data of Mauna Loa. The AIRS data show maximum CO2 levels in the mid-latitudes, ground and altitude stations show maxima in the mid and more nordic latitudes…
And again, if a monthly variation of only 2% of the range (of which most is due to the seasonal changes and the SH lag) is not well-mixed what on earth is then well-mixed?
This is very dangerous, this is the first step down the road of believing the socialist hoax. Next is the idea that CO2, *OUR* CO2, could contribute heat to the atmosphere that wouldn’t otherwise be there. Now, we have to follow your Gaia equilibrium hypothesis that the earth will naturally (and quickly) bounce the heat credit back out into space. It is easier if we can just believe that CO2 isn’t increasing because of man, that CO2 doesn’t heat the atmosphere anyway, and that higher global average temps are good. (Those things are contradictory, but you only have to believe them one at a time, as the argument calls for.)
Thanks for the CO2 data; specially for the ice cores Willis.
Now let me see how many of your roolz I can break.
First question would be; for those of us that are largely onlookers, can you tell us approximately where these various ice cores hail from (pun intended) For example is Fuji actually an ice core off Mt Fuji; or am I jumping to an erroneous conclusion. Not that it’s a big deal just an approximate “west Antarctica” , “Central Greenland” , whatever will do.
First observation would be; that 280 ppm over all that pre-modern period is remarkably flat data. How could that possibly jibe with global temperature fluctuations over the same time frame given that Schneider’s law says:-
T2 – T1 = (cs). logbase2(CO2,2/CO2,1) thereby defining “Climate Sensitivity” (cs) as the mean global surface Temperature rise for any CO2 doubling; which I presume is the “Climate Science” equivalent to the velocity of light (c) in “Optical Science”.
Second observation:- I don’t see any relevence or meaning to the term “Residence Time” when it comes to CO2 in the atmosphere. As far as I can tell, CO2 like H2O is; and always has been, (since humans) a permanent component of the earth’s atmosphere; so it is NOT decaying.
I’m also puzzled by the term “e-folding time” since I can not distinguish it (as described) from the “Time Constant” (tau) of ordinary exponential decay. Do Climatologists have some special drive to make up their own terms, and ignore the vast body of previous Physics research and Literature.
I’m happy with : CO2,2 = CO2,1. e^(-t/tau) Which is still silly since CO2 is not decaying away. Now the advabtage of the standard time constant form is that the initial rate of decay is such as to decay to zero in one time constant (at that constant rate).
So for example, let us imagine that 280 ppm is the baseline to which CO2 wants to “decay” and we have a transient excess of 110 ppm giving us 390 ppm.
The annual peak to peak cycling of CO2 at the north Pole, and in fact of the whole >80 deg Arctic is 18 ppm versus 6 ppm for Mauna Loa.
And that 18 ppm drop occurs every year in just five months; and I believe is largely due to the arctic ice melt which then takes up CO2 from the atmosphere into all that melt water from which CO2 was excluded (segregated out) during the previous freeze.
So that 18 ppm drop in five months appears almost a straight line; and if we assume that left running the mechanism would run all the way down from 390 to 280 ppm, then the Time constant must be 110/18 * 5 months or 30.55 months.
That means a decay to 1% residual (excess over 280) would take five time constants or 53 months or 12.7 years.
But as I said; it isn’t really decaying anyway; since the amount is maintained by continuous emission. It is quite irrelevent that one CO2 molecule is being replaced by another; they do the same thing.
Willis you say the isotope argument is a weak one; and I agree; though I do not dismiss it.
Assuming it is true that C12 abundance has been increasing; or rather C13 isotope is decreasing; that is a plausible argument that a source of C13 depleted carbon is being released to the atmosphere. It is not such a good argument to say that the INCREASE in atmospheric CO2 is ALL from that source.
If somebody pumped oil from an oil field that for some reason contained a lot of Argon which we just vented to the atmosphere; then of course we would expect atmospheric Argon to increase. So I agree with you that the isotope argument is not definitive. I am also given to understand from some of the Botanical visitors to WUWT, that there are several kinds of botanical metabolisms depending on plant species, and that they behave quite differently as regards C12/C13.
But bottom line is; I’m not quite daft enough to claim that man is not the source of the CO2 increase; we certainly are emitting plenty; but I am curious that it is just 800 years or so since the missing or suppressed MWP so per Al Gore’s graphs we should be due for a CO2 goosing round about now; due to that warming period.
But I really like your ice cores; although I wonder how they relate to global CO2 since the antarctic at least is quite atypical when it comes to CO2; whcih despite glib claims by Climatologists; is anything but well mixed in the atmosphere. I didn’t know there could be anything on earth that was as hemispherically assymmetrical as the global distribution of CO2.
We have an 18 ppm p-p cycle north of 80 deg, falling to 6 ppm p-p at Mauna Loa, and then reversing to -1 ppm at the south pole.
So much for “well mixed”.
“Well mixed” to me, means that I can take a sample of atmospehre from anywhere on earth say near the surface, and not immediately adjacent to some hot CO2 source; and upon assay obtain the same species relative abundance everywhere.
And why is it that people use ppmv; when the material is not all at some standard condition; when it is so much easier to talk about mole abundance since we can actually count molecules.
But thanks again Willis for an enlightening post. I’m totally dependent on folks like you and Steve and others who have real data available and know how to get it.
George
As to “Reversible Processes” and the Second Law which is mashing around in the Englebeen et al discussion.
I’m a fan of Rudolph Clausius expostition of the second law; if only for its arcane, definitely non-Churchillian English exposition; to whit:-
” No CYCLIC machine can have no other effect than to transport “heat” from a source at one Temperature to a sink at a higher Temperarture. ”
And note that the process is to be cyclic but that does not imply reversibility.
We teach in Optics that Light is reversible. That is not even approximately true except in the most degenerate of cases involving no change in medium.
We could say that the rays of geometric optics are reversible.
But Physically, if you have a boundary between two media; there is always a ray split, and you get a reflected beam and a refracted beam typically both partially plane polarised.
If you reverse the reflected and refracted output beams they do not reform the original input beam and you still end up with multiple beams.
And true reversibility of a heat engine; would certainly seem to be prohibited.
As for clouds being a positive feedback in models; that is completely laughable. It always gets cooler in the shadow zone when a cloud passes in front of the sun, and the surface is typically illuminated by a nearly colimated beam from the sun (1/2 degree divergence) whereas the surface emitted LWIR from the shadow zone is at least Lambertian if the surface is optical, and more likely isotropic for a rough surface; so the cloud forming the shadow, can intercept only a small fraction of the LWIR fromt he shadow zone; and upon re-radiation from the cloud as an LWIR spectrum even less of it arives back at the shadow zone so there is no way the LWIR emissions make up for the loss of direct solar insolation.
And please remeber weather is NOT climate; so don’t tell me about last night’s weather with a high wispy cloud. When we talk about cloud effects we mean the effect of a change in global cloud cover that persists over some climatically significant time interval like say 30 years. It is ALWAYS negative feedback; NEVER positive.
And see Wentz et al SCIENCE for July 7 2007, “How Much More Rain will Global Warming Bring ?” The only thing Wentz does NOT say is that it is fashinable in most science circles to have more clouds of precipitating density when you have more rain.
The resulting negative feedback is huge compared to any possible CO2 effect.