http://www.agu.org/pubs/crossref/2009/2008GB003357.shtml

“We show that if the CO2 “fertilization effect” indeed takes place and is maintained in the long term in tropical forests, then it will avoid biome shifts in Amazonia in most of the climate scenarios, even if the effect of CO2 fertilization is halved. However, if CO2 fertilization does not play any important role on tropical forests in the future or if dry season is longer than 4 months (projected by 2/14 GCMs), then there is replacement of large portions of Amazonia by tropical savanna.”

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Can I see the original (peer-reviewed) paper that says this is how it works?

When I say “I assume”, then what follows is from my own sense of common sense, rather than a peer reviewed source.

I would have thought that that was pretty obvious. Are you trying to be obtuse on purpose?

It makes perfect sense to me to assume that “88% of western Amazon rainfall has been transpired twice” means that the third transpiration (on average) reaches the Pacific.

I would assume that the Andes would stop that. Plus the general movement of weather systems is east to west because of the rotation of the earth. What makes you think it would end up in the Pacific instead of the Atlantic (Even without the Andes)?

Compensation point (net photosynthesis = gross-respiration) is lowered with elevated [CO2]. Biomass accumulates and transpiration continues, especially at the NPP limiting end-of-dry season.

Sorry I’m not familiar with your jargon. What is the difference between net and gross photosynthesis, and the difference between net and gross transpiration?

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Plus a rainforest being sunlight limited already has a very thick canopy with close to 100% catchment of sunlight. The benefit of growing more leaves in this situation is not clear.

Compensation point (net photosynthesis = gross-respiration) is lowered with elevated [CO2]. Biomass accumulates and transpiration continues, especially at the NPP limiting end-of-dry season.

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100% 7.5x….Robin: Is that what I claimed?

Yes, you said..

#252 the number of times that the rain has been transpired by the time it falls in the west Amazon basin can be measured by taking a sample of it. The answer is about seven and a half.

#274 The[n] it certainly was a mistake.

Yes it was

So 88% transpired twice implies approximately 94% transpired once, 83% three times, 77% four times, 73% five times, 68% six times, 64% seven times, and 60% eight times. So I figures the average of 7.5 times was less strong than that.

Can I see the original (peer-reviewed) paper that says this is how it works? It makes perfect sense to me to assume that “88% of western Amazon rainfall has been transpired twice” means that the third transpiration (on average) reaches the Pacific.

That’s not the theoretical or experimental findings of the book that you cite above.

Try reading it again. What don’t you get about leaf Et not being the same as canopy Et ? C4 grasses make some savings because they photosynthesize at high rates under high light and temps, but the C3 examples given (cherry trees, soybeans) showed no Et effect with FACE (free air carbon dioxide enrichment) at high temperatures.
Plus a rainforest being sunlight limited already has a very thick canopy with close to 100% catchment of sunlight. The benefit of growing more leaves in this situation is not clear.
Compensation point (net photosynthesis = gross-respiration) is lowered with elevated [CO2]. Biomass accumulates and transpiration continues, especially at the NPP limiting end-of-dry season.

The clouds aren’t reduced at all unless Et is reduced. If, as you claim, Et is overall maintained, so is the water content of the air.

Precisely. Your mechanism is implausible because of feedback effects.

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Robin: “ …[88 % fallen twice]…Which seems a bit stronger than the 7.5 times average figure.” I think you have that back-to-front, ie that your claim of 100% 7.5x is a substantial overestimate.

Is that what I claimed?

The it certainly was a mistake. The figure I heard was the 7.5 times was an average. (And I think that that is reasonably clear from my posts, so I do think that your restatement of my claim to the minimum number of times that any of the water has been transpired is 7.5 is strange. Especially given the fraction.)

Perhaps you are trying to argue by the straw man fallacy rather than being genuinely interested in the facts?

Using your previous guesstimate of 10% less evapotranspiration(Et), then the 88%2x scenario would result in 17% less rainfall (0.9^2*0.88 +0.12 = 0.83) not your 55%.

Well, I make the assumption that the water that has been transpired once is well mixed with the water that has been transpired twice, and so on.

So 88% transpired twice implies approximately 94% transpired once, 83% three times, 77% four times, 73% five times, 68% six times, 64% seven times, and 60% eight times. So I figures the average of 7.5 times was less strong than that.

Obviously your calculation only accounts for the twice transpired water, and assumes that none of it is transpired three times, and also assumes that none of the water that has not been transpired twice has been transpired once. A very contrived and frankly impossible set off assumptions indeed.

Can I be incredulous now?

If you like.

There are too many feedbacks, incl that canopy Et is likely to stay much the same notwithstanding changes in leaf Et (see below).

That’s not the theoretical or experimental findings of the book that you cite above.

Plus a rainforest being sunlight limited already has a very thick canopy with close to 100% catchment of sunlight. The benefit of growing more leaves in this situation is not clear. They will either be in the shade or they will shade other leaves. I’m not sure that the results for crops and grasses (which show reduced Et, despite your claims to the contrary), would hold for a rainforest.

But I am speculating there. Experiments show that Et reduces.

Another homeostatic feedback is that plants which currently grow somewhat less in the wet season because it’s too cloudy, have the opportunity to grow a little more, thus Et overall is maintained, even if timed somewhat differently.

The clouds aren’t reduced at all unless Et is reduced. If, as you claim, Et is overall maintained, so is the water content of the air. But again I digress. Experiments (and theory) shows the Et is reduced.

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Anway I am still very dubious about a drop in annual Et as much as 10%, which you suggest can arise from WUE gains from elevated [CO2]. There are too many feedbacks, incl that canopy Et is likely to stay much the same notwithstanding changes in leaf Et (see below). That’s a restatement of the widely observed fact that NPP for C3 plants is, (with some possible obvious exceptions such as swamp forests), determined and limited by available water. In the western Amazon case, the water limit is the end-of-dry-season soil reserves and NPP is capped by the litterfall that occurs when that soil moisture approaches wilting point. Another homeostatic feedback is that plants which currently grow somewhat less in the wet season because it’s too cloudy, have the opportunity to grow a little more, thus Et overall is maintained, even if timed somewhat differently.

The “Teleconnections” reference uses Hansens 1983 GISS GCM II model (surely there would be something better available now?) to say that if there is a priori no Amazon forest, then in the wettest part of the year the rainfall (and presumably cloudiness) is reduced by perhaps half, ie from 8mm/day to 4mm/day. This follows when LAI in the model’s settings is changed from 6 to 1, meaning substantially lowered Et across the whole region, but particularly in the east from whence moist air currently heads inland. The a priori destruction of the forest in this paper is a very different process to the dieback cycle conjectured by Cox et al 2004 which begins with current forest cover.

Cox et als ‘Amazon dieback’ conclusions arise from runaway feedback, which is highly dependent on the global q10 carbon decay and respiration assumptions, ie that the rate (q) of the chemical process of decompostion/respiration doubles for every +10C change in temp. This one-size-fits-all equation and the coarse geographic grid are necessary for reasons of computational economy, but seriously understate the biological capacity for homeostatic response. W.r.t rainfall and temps, the residuals in their model during training runs to current climate current are large enough to exacerbate the dieback outcome, ie the model has low “skill” and begins with bias towards the negative outcomes. They also assumed decrease in LAI with water stress and thus lower Et, both of which are poor assumptions given what is known about LAI and WUE effects of higher [CO2] and seasonality of growth. Further assumptions are high [CO2] temp sensitivity (not stated in paper but probably your magic 3) and doubling of CO2 by 2050. With those assumptions and biases it was of course no surprise to find runaway feedback in the model’s projections.

Robin : “…On pp73: …. Which if I read correctly …. a significant drop in transpiration.”
You are confusing laboratory plant E with field canopy E. The section you quote from starts by saying “in this section we shall treat the plant as an isolated individual uninfluenced by it’s neighbours” ie a lab rat, not a free range herd. Its also a cherry-pick as you omit the closing sentence of the paragraph which says “This damping effect on plant E operates in addition to [other effects] that elevated [CO2] has on plant growth, of which the most pertinent is leaf area”. Apparently you didn’t read the next parag which says “eight C4 grasses…consumed the same amount of water per plant at ambient and elevated [CO2]”, due to increases in leaf area. It’s a long shot to move from some potted lab grasses having reduced E, to saying the Amazon rainforests is orl gunna die.
You will find on p.75 that canopy E will be invariably less affected than leaf or plant E because of aerodynamic roughness factors and because increases in leaf area index (LAI= m2 leaf/m2 ground) offset reduced stomatal conductance.

Robin #267: “… how you can infer that TRIFFID assumes that leaf area doesn’t increase under increased CO2” TRIFFID does allow expansion to LAI =9 (rainforest LAI is presently ~6), but canopy E is a simple integration of leaf E models (appx A p.11 http://www.metoffice.gov.uk/publications/HCTN/HCTN_24.pdf ) . This is very likely to be an underestimate based on the ref above, and again simplifies the biological response. The Amazon dieback paper is based on TRIFFID outcomes.

And a couple of other things..

#246 George: “Using a neural net model to support AGW is grasping at straws. Using any model to support AGW is irrelevant if that model assumes AGW in the first place”. Robin: “A neural net isn’t a model. You feed in the forcings and the temperatures, and get it to work out how to get from one to the other. It doesn’t assume AGW, it just finds a procedure that will produce the observations, given the observed forcings.” A neural net is not all that different to other ways of finding significant variables and parameterising them. When the modeller supplies the forcings>0, and there are correlated variables like rising CO2 and global temps, of course they will be bundled. It’s still a circular reasoning of cause and effect.

Robin : #237 Also, because the cost of climate change is in the order of ten times the cost of amelioration, it would not be insanity to act if we were only 10% certain. We are about 95% certain. Robin #244 Well, I don’t understand economics, so I only quote Nicholas Stern. ”

I’m happy to take Simonian-Cornucopian view of that. The cost of amelioration is unnecessary if there is an exogenous shift in marginal cost of energy. Lomborg argues (SE 1992 p.133ff) that solar-H costs are dropping so rapidly that it will become a cost-effective alternative in about as much time as would take to put Stern’s wind-down measures into place. I’d rather we earnt and spent trillions in accelerating the science and building the infrastructure for such alternatives, not chopping off trillions and making the poor and hungry more poor and hungry and getting more people to join them.

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I know it’s not accounted for in the model because 1) the paper didn’t say it was and 2) the results obtained indicate that it’s not. The paper only mentioned the effect as potentially offsetting.

Whether leaves increase faster than stomata decreases depends somewhat on what’s limiting growth. However, it will be no worse than break even and the net transpiration will stay about the same as CO2 increases. The only exception might be in a desert, where biomass is water limited. This is certainly not the case in a rain forest.

My point is that the 3-4C per doubling CO2 is so far away from what the data and physics tells us that it’s simply unsupportable. There’s so much uncertainty in the alleged consensus, that it’s unbelievable that any sane person can look at the evidence and conclude the world should spend many trillions of dollars to mitigate CO2 without significantly more due diligence. As far as I’m concerned, even if CO2 did cause a few degrees of excess warming, it would be far more beneficial than harmful. This is despite the fact that I’m an avid skier (50+ days per year), so you can be absolutely sure that if I thought it was a problem I would be on the other side of this issue. I don’t even see enough of a connection to invoke the precautionary principle, even if mitigating CO2 was not a multi trillion dollar expense. If anything, the massive expense would cause me to invoke the precautionary principle in the direction of doing nothing. If CO2 is not near as harmful as the AGW crowd suggests, which is more likely in the face of the data and physics, wasting trillions of dollars is far more harmful than doing nothing at all.

It should be self evident that if a region gets no solar energy for nearly half of the year, ice will form. The average temperature of Antarctica is far below freezing and even the maximum summer temperature is well below freezing (I refer you to Hansen’s satellite data). The North pole average temperature (above the arctic circle) is also well below freezing and the maximum average monthly summer temperature is just about at the freezing point. Both the Antarctic ice cap and the Greenland ice cap are also at a relatively high altitude, which keeps the temperatures down. Absolute minimum ice would be when the N pole ice cap over water completely melts in summer only to reform in the winter. We know from Greenland ice cores that even during the time of the Vikings, when the shores of Greenland were more temperate, the bulk of it’s ice cap was still present.

CO2 feedback was the first hypothesis set forth about how CO2 drives the climate (or have you forgot). This was that increasing CO2 increased the temperature, which caused CO2 to leave the oceans, causing more CO2 related warming. When this was discounted, it moved to CO2 related warming pushed water vapor related feedbacks.

The entire water vapor feedback system must include the effects of clouds. The negative feedback related to water vapor is that evaporating water cools the surface and increases the heat transport from the surface into space. Radiative energy transport from the surface, which is what you are most concerned with, is only applicable for surface not covered by clouds. Convective transport of heat from the surface is via evaporation which moves heat from the surface into the clouds. The cloud tops then radiate this in to space, but this isn’t subject to water vapor absorption as there is little if any water vapor between cloud tops and space.

Regarding my calculations of ocean heat content, it predicts the presence of inflection points at the boundaries of the thermocline. The linear approximations used by the GCM’s do not. My model also only accounts for energy storage above that required to freeze the oceans (i.e. about 273K), not the 0K often used by GCM’s. I do this for the same reasons we talked about earlier. This makes the energy flux in and out of the oceans a much larger fraction of the effective heat content and is why the oceans respond far faster to energy changes than the AGW biased GCM’s predict. Defining the average temperature of the planet as the temperature at the midpoint of the thermocline (which is very close to the average surface temperature) and the average temperature of the cold part of the planet to the temperature at the inflection point at the bottom of the thermocline and the average temperature of the warm part of the planet to the temperature at the inflection point at the top of the thermocline removes much of the uncertainty by providing additional anchor points. I can also set the energy flux through the thermocline as equal and opposite to the heat coming from the Earth under the oceans as the result of a convection current. This establishes the width of the thermocline, relative to the temperatures of the hot and cold energy pools of the planet. I can also set the total energy in the hot pool equal to that of the cold pool (relative to the 0C starting point), which adds an additional constraint.

Regarding 271. AGW ‘theory’ predicts that a forcing power is amplified by a factor of 4.5 (i.e. 3.7 W/m^2 is amplified to 16.5 W/m^2). If we take your 4C number, then the amplification is even larger. Your absolutely right that this is appalling.

George

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the AGW ‘theory’ would predict a surface temperature of over 315K.

What an appalling straw man. No it wouldn’t. AGW theory doesn’t dream up what feedback systems kick in by contemplating the navel and writing something down.

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My point was that the paper mentioned the caveat, but didn’t account for it in the model.

What makes you think that it was not accounted for in the model?

I stand by my assertion that this is a red herring.

Do you stand by your claim that “At higher CO2 levels, the number of leaves will increase faster than the number of stomata per leaf will decrease.”?

Because I’m still not believing that.

This would be very pessimistic since for an average temp of 273K, the max would be 20C warmer, so water vapor feedback would start at a much lower temp.

Not really pessimistic. Cloud albedo feedback would be negative at that time.

The point is that the current climate sensitivity is about 3 or 4°C per doubling.

In addition, cloud related feedbacks would exist even at lower temperatures, except that the clouds would be formed by condensing gases other than water vapor.

Making exactly no difference, because they stop existing by the time the temperature gets near current temperatures, unless you can point me to a non-water cloud.

What’s your point?

Zero ice is not attainable by the system regardless of the GHG concentrations in the atmosphere (the poles have no solar energy for half of the year) and we are pretty close to minimum ice already.

Could you back that up with something?

While you’re there there are a couple of other questions that you missed from my post 246:

1) What is a CO2 feedback? (I thought that CO2 was considered a forcing).

2) I am aware of empirical evidence that shows that the feedback from water vapour is positive, but what is this other empirical evidence that shows that it is negative?

Further in reference to the paper: An Observationally Based Estimate of the Climate Sensitivity, you claimed that it could be dismissed out of hand because ocean heat content is too poorly known. The paper uses the 2 s.d. error. Can you point out why this estimate of error is so much smaller than your own?

Cheers.

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My point was that the paper mentioned the caveat, but didn’t account for it in the model. I stand by my assertion that this is a red herring.
Another red herring is ocean acidification, which is justified by a partial pressure analysis which assumes infinite surface area and fails to account for the high level of buffering in the oceans. As an experiment, take a glass of carbonated water, measure it’s pH and notice it will be rather low. Let it sit uncovered for a few days and go completely flat. Measure the pH again and it will be close to 7.

Regarding amplification, lets assume that only the energy that increases the temperature above 273K gets amplified. This would be very pessimistic since for an average temp of 273K, the max would be 20C warmer, so water vapor feedback would start at a much lower temp.

273K -> 315 W/m^2

341 – 315 = 26 W/m^2

26 * 16.6/3.7 = 166.6

315 + 166.6 = 431.6

431.6 W/m^2 -> 295K

295K is still 6C larger than the average surface temp of 289K. If we start at 263K, which is about halfway between where water vapor feedback starts and an average temp of the freezing point of water, the AGW ‘theory’ would predict a surface temperature of over 315K. Furthermore, CO2 related ‘feedback’ would kick in at about 218K, which is the freezing point of CO2. In addition, cloud related feedbacks would exist even at lower temperatures, except that the clouds would be formed by condensing gases other than water vapor.

On the positive side, at least you now seem to recognize the effects of non linear feedback. Just as water vapor feedback doesn’t kick in until water starts to evaporate, ice feedback stops when there is no ice. Zero ice is not attainable by the system regardless of the GHG concentrations in the atmosphere (the poles have no solar energy for half of the year) and we are pretty close to minimum ice already. Since ice feedback is most of what we see in the ice cores, the amplification attributed to ice, which is often misrepresented as CO2 feedback, is relatively close to zero. In fact, while it’s close to zero relative to increasing temperatures and decreasing ice, it’s much larger relative to decreasing temperatures as ice increases. This can be considered a tipping point, but is more precisely considered a flipping point which is a necessary condition for flipping the climate from a temperate epoch to a glacial epoch. Going the other direction, once ice can grow no more, the climate can flip from a glacial epoch to a temperate epoch.

George

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