The AGW climate feedback discussion

[billiards]

What about the one where all the permafrost melts and loads of greenhouse gases currently trapped are set free?

Or the one where due to increased heat waves we get more forest fires, which then kills a whole load of trees and releases a mass of carbon? (which not only increases greenhouse in the short term but also weakens the planet's ability to capture CO2)

 

[Bored Wombat]

So what looks like a tipping point to WB is in reality the start of the stable process, steered by negative feedback.

Isn't that what a tipping point is? The point between the start of one stable process and the start of a dramatically different one?

 

[vanesch]

Surely, you're not redefining the scientific method? I'd say that a model can be a good tool to shape hypotheses into detailed quantitative prediction, which has to be verified by testing it eventually to the reality.

It's not science, it's engineering. The science was the part where the theory came from on which the model is based. If you do calculations of trajectories of satellites, you also take it on that Newton's laws are valid, and you don't "falsify" the calculated trajectory by sending different satellites and comparing with your calculation. You verify that there aren't bugs in your program, and you are confident that the calculation is going to be right.

Of course, that's a tad too easy, I agree, because you have to make approximations when you do so. You have to decide what's important and what's not if you're modeling things physically. So indeed, it would be better to be able to do some "test casing".

But if you have only one single system (earth's climate), and you don't have a long time (say a few million years of reliable data), then the best you can do is to set up your physical model as best as you can, and take that as the best guess you can make.

Also, you can test subsystems of your calculation. If the main engine is a weather forecast engine that has been tested for several tens of years, this means you master the short-term response well. You can also try to test several other parts, if you have historical data concerning them. And then you have to hope you put it all together correctly.

That's how people build the first atomic bomb too. If you do something totally new, you don't always have the luxury of "prototyping". So you have no choice but to trust your calculations. It's always partly a guess - that you didn't make silly mistakes (but that can be solved by having different independent working groups doing the same thing) - but more importantly that you didn't overlook an important aspect that you thought you could neglect, or that you made a fundamental error somewhere.

Anyway, the thread was about feedback, not models, and I don't think that the discussion about the skill of Karners observations changes from anti-persistent to persistent in this discussion. So if his work suggest anything is that no traces can be found of a dominant positive feedback mechanism, able to push the climate sensitivity for doubling CO2 from the Planck response of 1.1 to 1.2 degrees to some 2 -4.5 degrees.

Feedback is inherently coupled to models. Feedback is a modeling concept. It means constructing a model with a "main" part and a "feedback" part.

You cannot find any "traces of feedback" in pure time series. You don't know if it is inherent dynamics or if the system is structured as a feedback system. What you can do is to try to find/fit a model of the overall system but you never know if that was obtained by a feedback loop or not.

I'll try to explain that later.

 

[vanesch]

To come back to the feedback concept:

In time series analysis and modelling, you have two kinds of linear system descriptions:
"finite impulse response" (FIR) systems, and "infinite impulse response" (IIR) systems.

In fact, one can model almost any (linear) time series systems dynamics both with IIR and FIR systems. Often, IIR systems are more computing-resource-efficient than FIR, but on the other hand, they are a bit harder to "tune".

Well, FIR systems don't contain feedback, and IIR do.

In fact, the definitions are easy:

If x(i) is the input time series (i is an integer indicating "sample number" and represents "time" in most cases) and y(j) is the output time series, then a FIR system is defined by:

y(j) = a0 x(j) + a1 x(j-1) + a2 x(j-2) + ... an x(j-n)

where n is the "order" of the system.

In other words, the output at sample number j is a weighted sum of the n last input samples, and the weighting coefficients are fixed constants which determine the "dynamics" of the system.

For a IIR system, we have:

y(j) = a0 x(j) + a1 x(j-1) + a2 x(j-2) + ... an x(j-n)
- b1 y(j-1) - b2 y(j-2) - ... bm y(j-m).

So an IRR system is a FIR system plus feedback, that is, the output at a certain sample number is composed of, as in the case of a FIR system, a weighted sum of past input samples, but now also a weighted sum of past outputs.

Well, you can approximate any IIR system with a FIR system (of much higher order).

You can't do so exactly, but you can do so within any limit of accuracy. The price to pay is that you will have a very high-order FIR system in some cases to approximate well a rather small-order IIR system.

It is only in the case of unstable IIR systems that you can't build a reliable, long-term FIR system (although you can STILL build a FIR system that approximates the beginning of the divergence). A FIR system can never become unstable. An IIR system can, and that's what makes working with IIR systems somewhat nastier. They are more powerful models, but they are nastier to work with, exactly because of questions of instability.

Andre's simulation was nothing else but an elementary IIR system, something of the kind:

y(j) = G x(j) + F y(j-1)

(so a0=G was the "gain" and b1=-F was the "feedback")

But you can approximate this by a FIR system, by finite substitution:

y(j) = G x(j) + G^2 F x(j-1) + G^3 F^2 x(j-2) + G^4 F^3 x(j-3) + ... + G^(n+1)F^n x(j-n)

In this last system, there is no explicit feedback (the output is not computed using previous outputs).

Note that we see a trace of the feedback loop gain GF :

y(j) = G { x(j) + (GF) x(j-1) + (GF)^2 x(j-2) + ... + (GF)^n x(j-n) }

If GF is smaller than 1 in absolute value, then these coefficients diminish in absolute value as a power series. Hence, the last terms become very small, and truncation is justified. So our FIR system is then a good approximation for the original IIR system.

That's exactly the condition that is necessary for the IIR system to be stable.

And now I come to my original point: if I'm just given time series x and y (inputs and outputs) of the system I'm supposed to model, then I can try to fit a FIR system to it, or I can try to fit an IIR system to it. Now, depending on the quality of the data, that fit will be of good or bad quality. But if the fit is in both cases of good quality, then both system models will reproduce well the behavior of the system, at least for similar signals as the data had.
This is for the very simple case of a *linear* system and one input and output signal.

 

[Andre]

What about the one where all the permafrost melts and loads of greenhouse gases currently trapped are set free?

Or the one where due to increased heat waves we get more forest fires, which then kills a whole load of trees and releases a mass of carbon? (which not only increases greenhouse in the short term but also weakens the planet's ability to capture CO2)

Why would these effects be strong enough to steer climate. Once there was little or no permafrost, when the trees grew at the Arctic coast, http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WPN-45BCR6K-M&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1133189953&_rerunOrigin=google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=0e829aa6f1e183a5e99a5a7d50e8d656, this was close to biggest methane hydrate decompositon event in the Nordic sea (http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V9Y-4FG2XBV-1&_user=10&_coverDate=01%2F01%2F2005&_alid=1133192856&_rdoc=1&_fmt=high&_orig=search&_cdi=5911&_sort=r&_docanchor=&view=c&_ct=27&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=1e072f80837a7092144b4a463d2c4036.

So already in the Holocene, Earth has seen pretty extreme conditions and it only has got colder since then.

More later, I'm maxed out.

 

[Bill Illis]

Actually, my little model runs away in both directions.

Add a little cooling, water freezes to ice and then by albedo changes it runs away to total ice.
Add a little warming, ice melts and albedo runs it away to about 38C. The 38C is just an artifact of how it was tuned.

Albedo changes from Ice/water always re-enforce the initiating forcing (i.e. positive feedback).

Would think that clouds might be a negative feedback at the extremes of warming/cooling.
That is at extreme warming, clouds build up enough to rise albedo.
At extreme cooling, clouds clear enough to counteract the falling albedo.

Problem is that clouds, with some uncertainty, are considered to be net positive feedbacks by conventional climate science. What is supposed to stop run-away global warming in the real world is increased precipitation. From increased weathering this sequesters CO2 and introduces cooling. At the other end of the spectrum, what stops run-away global cooling are volcano's. However, falling CO2 also inhibits plant growth and the lack of plants may halt CO2 levels from falling too much as well.

Xnn, you can constrain your runaway Albedo values to:

- about 0.245 (the lowest level possible in our current atmosphere corresponding to an Earth with no ice, high sea levels and small continental areas concentrated toward the equator, basically clouds will keep it higher than this level) ; to,

- about 0.550 (the highest possible value corresponding to Snowball Earth where all the continents are locked together at one or both of the Poles and ice covers most of the Earth).

The climate history indicates we have come very close to both levels in the past 650 million years.

 

[Skyhunter]

Anyway, the most overlooked feedback factor in my opinion is the latent heat / evaporation. We had a lenghty and difficult discussion about that in this thread in which we dispute whether or not an increased temperature with more of less constant relative humidity would or would not require an additional increase in evaporation rate. If so then the required energy for that would be in the same order of magnitude that the increased greenhouse effect would supply.

Please see the thread you linked for an explanation of why your opinion is wrong.

Your premise that it requires 80 W/m² to support evaporation is over stated by a factor of 1000.

It only requires .08 W/m² to evaporate 1/2 a million cubic kilometers of water per year.

I see what I did. I forgot to convert to grams.

Irregardless, it is still accounted for, witness the IPCC diagram.

 

[Andre]

okay let's try again.

The anual evaporation is 440.10³ km³ per year = 440,000 km³

the Earth surface is 148,300,000 sq km land + 361,800,000 sq km water = 510,100,000 sq km

So the average evaporation for the complete surface = 440,000 km³/510,100,000 km² = 0,000863 km/year = 0.863 meters/year

This is a cube of 0,863 m³ per square meter, which is 863,000 cubic centimeters or grams water per year

So per second per square meter the evaporation is 863000 grams/(365*24*3600)=0.027 gram per square meter per second.

one gram of water requires http://www.usatoday.com/weather/wlatent.htm hence 0.028 gram requires 68.4 joule per second per square meter or 68.4 watt per square meter. Indeed I was off by some 10 watt but as far as I can see not by a factor 1000.

 

[Sorry!]

one gram of water requires http://www.usatoday.com/weather/wlatent.htm hence 0.028 gram requires 68.4 joule per second per square meter or 68.4 watt per square meter. Indeed I was off by some 10 watt but as far as I can see not by a factor 1000.

where did you get that value. one gram of water requiring 2500 joules for evaporation.EDIT: Nvm see where you saw it lol.

it's just that I seen values around 540 cal/g... so about 2260 joules which would bring the value down to what 63?

I am pretty sure there are a lot more factors thuough which effect this value... like pressure, temperature, density etc. etc. it's been awhile since I've taken my physics course though, lol.

 

[Xnn]

The IPCC pegs evapotranspiration at 78 Watts/m^2.
See FAQ 1.1 Figure 1:

http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter1.pdf

Anyhow, this very important mechanism tranports energy within the Earth's atmosphere, its precise value is not a classic feedback.

Feedbacks need to fall into 2 categories:

Albedo
Emissivity

 

[sylas]

okay let's try again.

The anual evaporation is 440.10³ km³ per year = 440,000 km³

the Earth surface is 148,300,000 sq km land + 361,800,000 sq km water = 510,100,000 sq km

So the average evaporation for the complete surface = 440,000 km³/510,100,000 km² = 0,000863 km/year = 0.863 meters/year

This is a cube of 0,863 m³ per square meter, which is 863,000 cubic centimeters or grams water per year

So per second per square meter the evaporation is 863000 grams/(365*24*3600)=0.027 gram per square meter per second.

one gram of water requires http://www.usatoday.com/weather/wlatent.htm hence 0.028 gram requires 68.4 joule per second per square meter or 68.4 watt per square meter. Indeed I was off by some 10 watt but as far as I can see not by a factor 1000.

This is a measure of the latent heat energy flux. Your calculation of this is close, but it is using figures for the ocean only; neglecting evaporation over the land. This makes your result a little too small.

Basically, energy moves up from the surface of the Earth into the atmosphere by three means. Latent heat, convection, and radiation. There is also radiation coming back down from the atmosphere, but we can simply consider the difference between the upwards and downwards flux as the part of the energy moving up from the surface due to radiation.

There has been a fair bit of work on obtaining the various energy fluxes. A major reference is

• Trenberth, K.E., Fasullo, J.T., and Kiehl, J. (2009) http://ams.allenpress.com/archive/1520-0477/90/3/pdf/i1520-0477-90-3-311.pdf , in Bulletin of the AMS, Vol 90, pp 311-323.

The work is summarized with this diagram:

Trenberth et al cites a number of estimates, and the diagram corresponds to 2.76 mm day⁻¹. The surface area of the Earth is 5.1*10⁸ km³. Hence this is using

2.76 *10^-6 * 365 * 5.1*10⁸ km³/year = 5.14*10⁵ km³ per year​

close to Andre's 4.4*10⁵. The difference is the evaporation over the land.

The more serious error is to describe this as feedback, as was explained many times in the other thread.

Consider what happens if we have a temperature rise, for any reason, in the above diagram. The immediate effect is an increase in radiation from the surface. The atmosphere adjusts rapidly to maintain the same lapse rate, so convection remains about the same; and there will be an increase in backradiation from the warmer atmosphere. This is all part of what is normally called the "non-feedback response", which we discussed in the thread already. It is the changes that arise only from temperature change, of the surface and of the atmosphere.

Now consider the knock on changes, which may be part of feedback loops. One effect will be a change in surface cover. Ice melting is the most obvious, but there can be other kinds of effects as well, as vegetation or land cover changes. The ice effect is a significant positive feedback; vegetation cover changes have less dramatic effects but over larger areas; it can be both positive and negative; but overall the surface cover effects are a positive feedback.

More significant, however, is the increased evaporation. This will increase latent heat flux by a small amount, which gives a more effecient transport of heat into the atmosphere. What Andre is missing -- and what he continuously missed in the previous thread as well, is that convection adjusts very rapidly to maintain the lapse rate. So if latent heat effects transport energy more effectively, convection will reduce to compensate. That is why you never find this described as a feedback in any actual scientific literature -- which, I might add, is a requirement for controversial ideas in this forum.

What is a genuine feedback, however, is at least three fold. The increased evaporation corresponds to increased specific humidity... more water in the atmosphere. This leads to:

• More greenhouse effect. Water is a very strong greenhouse gas, and this is a positive feedback.
• Less lapse rate. The moist lapse rate is weaker than a dry lapse rate, and a weaker lapse rate means that the upper atmosphere is warmer; and hence more effective at radiating into space. This is a negative feedback. The combination of lapse rate feedback and humidity feedback is much better constrained than either one individually; the errors tend to cancel. The humidity effect is significantly stronger; so overall this is positive feedback.
• Cloud changes. This one is the hardest to sort out. Cloud can be both a positive and a negative feedback, depending on the nature of the cloud. They are very good reflectors (negative feedback) and also very good greenhouse absorbers (positive feedback). We experience both these effects all the time. In daylight, a cloud shades you and cools. At night, a cloudy sky is invariably much warmer than a clear sky; this is basically a greenhouse effect. There's a lot of work sorting this out, and the effects vary from region to region.

Cheers -- sylas

 

[Andre]

What Andre is missing -- and what he continuously missed in the previous thread as well, is that convection adjusts very rapidly to maintain the lapse rate. So if latent heat effects transport energy more effectively, convection will reduce to compensate. That is why you never find this described as a feedback in any actual scientific literature -- which, I might add, is a requirement for controversial ideas in this forum.

That's a double wrong.

First of all remember that I am not depending on ideas but merely on observations in this thread:

...But what goes up must come down and more evaporation also means necesarily an increase in precipitation when dynamic equilibrium is reached and that is testable, see my last post in that thread linking to http://www.sciencemag.org/cgi/content/abstract/317/5835/233, showing that the observed increase of precipitation is roughly consistent with my assumptions (7% per degree kelvin).

However more studies that suggest various increase rates in precipitation:

http://www.agu.org/pubs/crossref/2009/2009GL040218.shtml

http://www.nasa.gov/centers/goddard/news/topstory/2007/rainfall_increase.html

Secondly, the general idea has been suggested in peer review literature, for instance Chilingar et al 2008

 

[sylas]

Secondly, the general idea has been suggested in peer review literature, for instance Chilingar et al 2008

Gah. Chilingar again.

No, Andre, you're wrong. Chilingar is NOT suggesting a negative feedback effect. He's much MUCH sillier than that.

Before we get stuck into this let me just remind everyone... I do NOT merely dismiss all critics of conventional views of anthrogenic global warming as being cranks. But Chilingar? Complete and utter crank -- except possibly in his own field of petroleum geology; I guess he must be okay at that. But elementary physical thermodynamics of the atmosphere? There's a good reason his paper has zero impact. (Papers, I should say. He published this same nonsense paper in two different journals; which is not kosher. Neither journal is one where you'd expect to see any atmospheric physics being published; but when your paper is this bad...)

Let's review what this thread is meant to be about. It's about feedback. Right at the start, Andre gave the context as follows:

So doesn’t greenhouse effect exist? You bet it does. However the point is, in what extend? And the whole thing can be regressed to two simple questions:

A: What is the basic climate sensitivity (Planck response) of doubling the CO2 concentration?
B: How is that modified by possible feedbacks?
The “IPCC-answer” to the first question seems to be around one degree Celsius. Sylas explains:



I’m perfectly happy with that. And the main dispute is not about A but about B: How is that modified by possible feedbacks? That’s the key. If the overall feedback is positive the sensitivity value would get “amplified”, whereas negative feedback would reduce the sensivity value. This is what the scientific climate dispute boils down to. In this thread I will show why I think that negative feedback prevails.

So this whole thread has been about feedback, which can amplify, or damp, the response of climate to some forcing. We started out with the conventional understanding of greenhouse effects and the forcing from CO₂ of 3.7 W/m² per doubling. This number is not in any real doubt. The calculation is intricate, and depends on knowing the absorption spectra of atmospheric gases; but those ARE known, and the thermodynamic consequences have been known for over a century. Adding CO₂ to the atmosphere gives an additional forcing. This number is used quite conventionally by genuine climate scientists who may be critical of other aspects of the majority view on climate response.

Richard Lindzen, for example, uses that same 3.7 W/m² and argues for a zero or negative feedback effect that would make the temperature response very small. He's not got a lot of support for this argument, but it isn't immediately nonsense on the face of it. I had thought that Lindzen and Choi's recent paper was going to be the focus of the thread. Lindzen, after all, is a climate scientist.

Chillingar, however, is no Richard Lindzen. He's NOT proposing a negative feedback at all. Andre is just wrong about that. Chilligar is proposing a negative BASE EFFECT. He argues that CO₂ leads to cooling. He reverses the effect altogether!

That CAN'T be done with feedback.

It also can't be done without rewriting every introductory textbook on atmospheric physics and radiation.

Cheers -- sylas

 

[Andre]

May I enquire how to fit in that observed global precipitation increase of http://www.sciencemag.org/cgi/content/abstract/317/5835/233, suggesting that it was 7%?

Doesn't that indicate that -assuming dynamic equilibrium- the evaporation rate has to be equal to the precipitation rate? Wouldn't a 7% higher evaporation rate require a 7% higher energy level used? I.E. 86.5 W/m² versus 80 W/m² in the observed period? Now how does this relate to the 3.7 W/m² of doubling CO2?

And we are not talking convection here, just evaporation and precipitation rates

Sure I was keeping Lindzen and Choi as reserve. Just tactics.

 

[sylas]

May I, in between all these smoke screens

I have just pointed out where you are going wrong in the stuff YOU are introducing. Don't blame other people for taking up the various issues you choose to raise.

Doesn't that indicate that -assuming dynamic equilibrium- the evaporation rate has to be equal to the precipitation rate? Wouldn't a 7% higher evaporation rate require a 7% higher energy level used? I.E. 86.5 W/m² versus 80 W/m² in the observed period? Now, how can the 3.7 W/m² of doubling CO2 do that?

And we are not talking convection here, just evaporation and precipitation rates

You can't separate them. Convection is whatever is required to maintain the lapse rate. If there is a flux of latent heat up into the atmosphere, there is that much less heat to carry up by convection. This is the same answer you were given previously, and it won't change if you keep asking it next year.

Sure I was keeping Lindzen and Choi as reserve. Just tactics.

I remain interested to see this actually discussed, as I have recommended now quite a number of times. It would be infinitely better than Chilingar.

Cheers -- sylas

 

[vanesch]

Doesn't that indicate that -assuming dynamic equilibrium- the evaporation rate has to be equal to the precipitation rate? Wouldn't a 7% higher evaporation rate require a 7% higher energy level used? I.E. 86.5 W/m² versus 80 W/m² in the observed period? Now how does this relate to the 3.7 W/m² of doubling CO2?

Honestly, we've been going over this several times now. In this thread, YOU stated that

A: What is the basic climate sensitivity (Planck response) of doubling the CO2 concentration?
B: How is that modified by possible feedbacks?

so we were going to discuss the phenomena of feedback in this thread.

Now you come up again with your evaporation rate, which, as we've explained several times again, has nothing to do with the humidity per se.

But to reiterate the answer you already got, heat transport in the lower troposphere consists of 2 contributions:
- radiative
- convective

Convective itself consists of 2 contributions:
- heat as "warmer gas"
- latent heat

In the lower troposphere, the most important part of heat transport is actually convective.

The TOTAL heat flux has to be so that the lapse rate is re-established, because that's what drives convection. There is a strong negative feedback in the troposphere that restores the lapse rate:

If the lapse rate is softer than the adiabatic lapse rate (that is, if temperature doesn't diminish "fast enough" with altitude), then convection stops, strongly diminishing the total heat transport. That means that lower layers get a lot of extra heat that they cannot get rid of through heat transport, and hence heat up, as such increasing lapse rate (==> negative feedback: initially diminishing lapse rate causes increase in lapse rate).

If the lapse rate is stronger than adiabatic, that means that higher layers are much colder, and hence much denser, than they should be in "equilibrium" (adiabatic) conditions. Hence they "fall down", while lower layers are much hotter (and hence much lighter) than they ought to be ==> very strong drive of convection, increased heat transport and hence tendency to cool down lower layers and heat up higher layers ==> lapse rate diminishes ==> negative feedback again, because initial stronger lapse rate is now diminished.

Convection is hence a very strong feedback mechanism that keeps the lapse rate on the adiabatic lapse rate, no matter what.

Now, what happens when there is more evaporation at the surface, is that the latent heat component increases (that's what you calculate). At identical convection rate, this would mean: more heat transport (that's what you calculate). But then the strong negative feedback sets in: this stronger heat transport would make the lapse rate softer. So convection will "slow down" to restore the lapse rate. You can still have your higher latent heat transport, but it will be compensated by a slower convection and hence less "normal" heat transport.

And that doesn't stop you from having more precipitation, because of course with more evaporation must come also more precipitation. And in fact, you don't even need MORE evaporation, you can have in principle ANY evaporation rate and still have higher humidity levels. Because of the strong negative feedback by convection in the troposphere for every attempt at deviation from the adiabatic lapse rate.

In other words, the humidity in the air determines the ratio of heat transport through convection of latent heat and heat transport through convection of normal heat (warm air). This balance can go one way or another, and is determined by other elements, and has nothing to do with the overall heat transport. More of one will automatically mean less of the other, so that the total sum remains OK, because of the strong convective feedback mechanism in the troposphere.I tried to take opportunity from this "feedback" thread to re-iterate the explanation we've given before already a few times, this time in a "feedback" frame.

 

[Andre]

No matter how many times an explanation is given, it doesn't make it righter or wronger. Maybe I should reiterate the working of the Hadley cell and maybe stress a bit more the diurnal variation, with constant radiative cooling and cyclic solar warming, which makes sure that there is no such thing of keeping the lapse rate adiabatic. The next hour, it is different anyway.

And just about important in transport of water (vapor) is advection which is much more complex.

But I think there is little point in it anyway.

 

[Xnn]

Andre;

I think the best thing to do is to look at the diagram that Sylas posted in message 61.
The evapotranspiration value is the same at the surface as it is in the clouds.
Notice it is a flow of energy within the system.

Now look at what is flowing into the system: 341.3 Wm^2

And what is flowing out at the top of the atmospher: 101.9+238.5 = 340.4 Wm^2

The difference is 0.9 Wm^2. This is global warming.

The 80 or 78 or whatever evapotranspiration itself does not affect the difference between the inputs and outputs at the top of the atmosphere.

 

[Xnn]

Another way to look at Sylas's diagram:

The 341 Wm^2 incoming is solar irradiance
The 102 Wm^2 is a function of albedo
The 239 Wm^2 is a function of emissitivity

The thermals, evapotranspiration and surface radiation may look like feedbacks, but they aren't. Instead they are more like eddy currents.

A feedback would have to be something that affects either albedo or emissitivity.

 

[sylas]

No matter how many times an explanation is given, it doesn't make it righter or wronger. Maybe I should reiterate the working of the Hadley cell and maybe stress a bit more the diurnal variation, with constant radiative cooling and cyclic solar warming, which makes sure that there is no such thing of keeping the lapse rate adiabatic. The next hour, it is different anyway.

The added complexity of divergences of the lapse rate from the adiabatic rate does nothing to address the more fundamental confusions involving the simple case. You are trying to run before you can walk; and the big problem is that you don't recognize the problems you are having with walking.

This is not "AGW" theory; it is simply atmospheric physics, the same as is applied for any planet.

There's a reason that the feedbacks which are considered in all the major references for climate feedback never consider latent heat flax as a feedback; but they do consider lapse rate as a negative feedback and greenhouse effects from humidity as a positive feedback.

Lindzen and Choi's paper is still worth looking at. There's nothing wrong with the notions of feedback in use there; though there are other reasons it has been unpersuasive.

Cheers -- sylas

 

[sylas]

The difference is 0.9 Wm^2. This is global warming.

Or more strictly... it is usually called "warming in the pipeline". Warming is usually simply the temperature difference at the surface, which does not appear in this diagram. The energy flow into the ocean represents a warming that is not yet realized as a temperature difference. This number (which is almost certainly too high) represents energy flowing into the ocean, as it heats up. Once the ocean heats up enough, this flow will be back to balance, and the surface will be a little bit warmer. No additional forcing is required; it is rather the major cause of time delay in the equilibrium climate response to a new forcing. Equilibrium is, by definition, when this flow is on average back to zero, at which point the other upward fluxes will be a bit larger, by this same amount, to maintain the balance.

Cheers -- sylas

 

[mheslep]

[...]This is obvious and important, as the added previous positive feedback steps tends to increase the deviation from to zero persistently (instable), whereas the negative feedbacks tends to pull the process back to the zero mark (stable) anti-persistent. Because of that we also see that the red positive feedback process is smoother and the negative feedback process is more jerky...

A brief comment on stability. In control theory or signal processing stability has a rigorous definition, bounded input - bounded output (http://en.wikipedia.org/wiki/BIBO_stability" ) stability is the common one. In your example you may be using the term differently. If the system input - your random walk in this case - 'walks' away from its initial conditions without bound, then even though the system is BIBO stable, the output is free to behave similarly.

 

[Xnn]

Trying to stay focused on climate feedbacks...

In a simple radiative model of the Earth, surface temperatures are a function of albedo and emissitivity.

Most people understand albedo fairly well.
Rising temperatures, melt ice.
Ice has a lower albedo than water.
Lower albedo results in higher temperatures.
So, ice water albedo has a positive feedback on surface temperatures.

Vegetation also has an affect on albedo.
Lush forest has a lower albedo than seasonal snow/tundra.
So, warmer moister temperatures result in lower vegatation albedo.

Emissitivity on the other hand is not understood as easily.
Emissitivity is the ability of an object to radiate.
Most of Earth's surface has a high albedo.
Water, ice and most vegetation matter is around 0.96.
However, clouds which cover about half of the surface have an emissitivity of about 0.5.
Also, the emissivity of a cloud is a function of it's temperature.
At lower temperatures, clouds do not emit as well as they do at higher temperatures.
Since clouds are usually fairly cold, their emissitivity is <0.5.

Now, it is not totally clear exactly how surface temperatures affect emissitivity.
One might think that rising temperatures could warm up clouds and rise their emissitivity.
However, clouds float and their temperatures probably don't really change all that much.
On the other hand, there will probably be more clouds with warmer temperatures.
Since clouds in general result in a lower planetary emissitivity, this factor would probably drive emissitivty lower. Lower planetary emissitivity results in higher surface temperatures.

So, my suspision is that surface temperature feed back positively by both albedo and emissitivty.

The only negative feedback that I can evision is from the affect of clouds on albedo.
Since I already suspect that rising temperatures will result in more clouds, this would act to rise albedo and thus lower surface temperatures. Maybe this is where the evapotranspiration discussion was heading. More evap = more clouds.

Now, a skeptic might argue that this negative feedback could outweigh or at least equal the positive feedbacks. However, the consensus science is that it doesn't.
More over, I can point to the exaggerated global temperature swings between glacial max and interglacials as an indication that there is an overall amplification (positive feedback) to relatively small forcing of surface temperatures, especially when there is substantial snow and ice on the earth.

 

[mugaliens]

Just to say that I'm also very interested in learning more about the feedback mechanisms.

Ditto. In light of historical data, it's undeniable the Earth's temp oscillates between brief warming peaks and much longer glaciation periods, as well as that there exist built-in mechanisms which moderate both the regular, periodic warming/cooling cycles and the more cataclysmic effects of seriously large and spikes in vocanic activity and meteor impacts which dwarf our nuclear arsenal many times over.

The fact we're still here, and that millions of years of geological records show nothing more than a single blip or two of departure from the bimodal swings tells me that if we believe mankind's efforts will result in runaway global warming, or somehow permanently destabilize Earth's temperature swings, then we know far less about Earth's climate than we think.

This isn't a statement of abandonment of the idea of AGW. Rather, it's a request for caution, not in the light of what we do know, but because there's so much yet that we don't know.

 

[Bored Wombat]

The fact we're still here, and that millions of years of geological records show nothing more than a single blip or two of departure from the bimodal swings tells me that if we believe mankind's efforts will result in runaway global warming, or somehow permanently destabilize Earth's temperature swings, then we know far less about Earth's climate than we think.

If you go back further than the closing of the Panama isthmus, you get a very different climate. (Since that was the start of the ice age).

I think that that shows that the planet can and does go into dramatically different states.

 

[Xnn]

A few more thoughts about feedbacks; especially negative feedbacks.

While melting ice and snow are strong positive feedbacks, if the Earth warms up enough that all of the ice melts than that feedback mechanism disappears. This isn't exactly a negative feedback, but at least there is an upper limit above which it ceases to be as large a factor.

Second, with respect to emissitivity; while most surfaces have very high emissitivities (0.95 to 098) there are some small desert areas that have much lower emissitivities (around 0.6). I believe these are the death valley types which are desicatted.

So, to the extent that warming leads to a growth of these limited deserts, it exerts a negative feedback. This is somewhat counter intuitive, but basically extreme desert areas are better able to radiate heat energy to outer space than most other land areas.

 

[Xnn]

And a little more on negative feedbacks...

In the extreme cases of warming or cooling, plants react to moderate temperature changes if they are from CO2.

At extremely low CO2 levels, plants don't grow as well so they don't remove as much CO2 from the atmosphere and this helps prevent CO2 levels from falling all they way to zero thereby counter acting the cooling trend.

Likewise, as CO2 levels grow, plants grow faster and this helps limit the CO2 thereby putting something of a brake on the warming.

This feedback works in conjunction with precipitation since high precipitation levels accompany warming which wash more carbon plant and animal material into the oceans where it is sequestered.

So, this is a negative feedback, but only applies to CO2.

 

[Bill Illis]

Xnn,

I built an Albedo model based on the 10 degree latitude bands and on the different surface reconstruction maps and continental drift maps that have been made available for the planet through history.

The (simple) model builds in an "heroic assumption" however, that the average cloudiness of the Earth remains constant. Is there a methodology to incorporate changing cloudiness levels which is based on the Earth's average Temperature and Albedo.

This picture was taken by Apollo 17 in mid-December 1972. The white in this real picture (clouds and Antarctica) are reflecting between 40% to 80% of the sunlight while the unclouded ocean in the centre of the picture is only reflecting 5%.

Now take Africa and move it to the South Pole where Antarctica is now (and attach South America, Antarctica, India, and Australia to it) as in 443 million years ago, and how much white would show up.

 

[Xnn]

Bill;

I've looked a little, but can't find a good reference for what the science is for cloud cover as a function of temperature. I'm thinking that it gets more extensive at higher temperatures, but probably not uniformly.

For example, we know that within the past, the Sahara desert was much greener and presumably more cloudy than it is now. But it's not clear to me if this was from a general warming or cooling.

Also, as the continents move around, and larger continental areas are formed, my understanding is that the interiours become deserts. So, I believe the distribution of the continents also plays a role.

 

[Bill Illis]

Here is a screenshot of this 10 degree latitude band Albedo model. The average Earth Albedo according to Trenberth is 0.298 (although I believe the cloud versus surface estimates he uses for Albedo are off since the math doesn't work - its more like 50% each).

Splitting the Earth up into the different latitude bands along with the average Albedo, surface area and weighted-average solar energy received in each band, we can calculate how each latitude band contributes to the global Albedo number. Putting it all together, have exactly the current Earth Albedo.

Now, as we move through different climate epochs, like the ice ages or Gondwana glaciated over at the South Pole, we can estimate how the Albedo would have varied. Without a high Albedo number like 0.333 for the Last Glacial Maximum, you cannot get even close to the estimated temperature of the time. (GHGs only varied enough to account for 1.7C of the 5.0C decline). The Milankovitch Cycles as well, cannot explain the depth and timing of the ice ages (the timelines only match up to a small extent) - The Ice-Albedo feedback or this case the Albedo driver rather than feedback has to be a self-sustaining, overwhelming factor in the ice ages.

The Cloudiness fraction presents a big problem because it will be a make or break factor.

Including the effects of clouds:

• The average Albedo of the Earth is 0.298;

• The average Albedo of the Land is approximately 0.344;
•

​

Snow-covered glaciers are approximately 0.7;
•

​

Non-glaciated Land averages 0.305.

• The average Albedo of the Ocean is 0.283;
•

​

Sea Ice is approximately 0.5 to 0.65; and
•

​

Open Ocean averages 0.267 but is lower at the Equator.

The Albedo is also higher as we move from the Equator to the Poles. The average Albedo at the Poles is 0.685 while the average Albedo at the Equator is 0.240. Take the sea ice and glaciers away from the Poles and replace them with open ocean and the Albedo would drop to about 0.350 (the increased angle means there is more reflection of solar irradiance even in open ocean).

Earth's overall Albedo will not change much at all unless there is a change in cloudiness or more or less ice on the planet (and it only changes by a large amount when the ice and snow moves farther away from the poles like New York). Without ice, the Albedo is going to be between 0.285 and 0.245 (assuming the cloud fraction is constant).

http://img706.imageshack.us/img706/2697/albedomodel.png

I've rebuilt this table for 11 different climate-continental drift scenarios and the values range from 0.252 (Pangea) to 0.517 (Snowball Earth).

 

[Bill Illis]

There is a lot of new material above to absorb, but this method can now also help answer the AGW-Albedo feedback issue.

Say, doubling of CO2 increases temperatures by 1.2C, water vapour increases add another 1.2C and we are at +2.4C by 2100.

How does the Earth's Albedo change.

First, the sea ice in the Arctic is now going to melt out earlier. Between 70N to 80N it is going to melt out now in early June instead of early August. Between 80N to 90N, the sea ice is probably going to completely melt out in early August.

The Albedo between 70N to 90N is going to fall slightly (but because there is so little surface area here and the zenith angle of the Sun is so low) it is not going to make much difference. The average Earth Albedo falls to 0.2965 and the Earth warms by 0.15C.

The Greenland glaciers are going to melt back by at least one-third in the next few hundred years. Sustained over a thousand years, the Greenland glaciers are just in the northern areas. Albedo falls to 0.2955 and temperatures increase another 0.1C.

The snow melts a little earlier in the northen hemisphere. temps increase another 0.13C

The sea ice around Antarctica melts a lot earlier, another 0.12C. There is not much change in Antarctica's glaciers but a small decline adds another 0.008C.

The Earth's Albedo has fallen to 0.293 and temperatures are now up 2.9C (2.4 from GHGs and water vapour; 0.5C from Albedo changes over a few hundred years).

Now just as the Earth's Albedo is lower and temperatures are higher, the Milankovitch Cycles start to kick in again. The Axial Tilt is now 23.3 degrees and the sea ice starts refreezing in the northen latitudes and we are going back into another ice age - (the forecast for summer solar insolation in the high northern latitudes doesn't actually decline very much in the millennia ahead so I can't really say this part is going to happen. Just throwing it out there).

 

[Saul]

Determining whether the planet's feedback response (clouds and related atmospheric responses) is negative or positive is fundamental to all planetary climate research past and future.

It appears the planet's feedback response to a forcing change in the tropics is negative rather than positive.

The recent paper that alleged the planet's feedback response was positive only used the long wave radiation data that is reflected into space. The feedback calculation needs to consider both long wave and short wave radiation. The total sum of long wave and short wave radiation indicates the feedback response is negative rather than positive.

The assumption of positive feedback in the General Climate Models did not make sense based on current and past observations. For example, the planet's response to a step increase such as the cooling associated with a volcanic eruption indicates the feedback it negative rather than positive. (Overdamped response.)

Negative feedback stabilizers systems such that they will naturally resist rather than amplify forcing changes. Almost all physical systems have negative feedback. It seem odd now come to think of it why anyone would assume the planet's response to a forcing change would be to amplify the change. Due to lags in physical systems, a system with positive feedback will be unstable.

If you go the very end of this paper there is a graph that compares the measured feedback response to the feedback response that is used in the climate models.


On the determination of climate feedbacks from ERBE data

By Richard S. Lindzen and Yong-Sang Choi
Program in Atmospheres, Oceans, and Climate
Massachusetts Institute of Technology

Climate feedbacks are estimated from fluctuations in the outgoing radiation budget from the latest version of Earth Radiation Budget Experiment (ERBE) nonscanner data. It appears, for the entire tropics, the observed outgoing radiation fluxes increase with the increase in sea surface temperatures (SSTs). The observed behavior of radiation fluxes implies negative feedback processes associated with relatively low climate sensitivity. This is the opposite of the behavior of 11 atmospheric models forced by the same SSTs.

Therefore, the models display much higher climate sensitivity than is inferred from ERBE, though it is difficult to pin down such high sensitivities with any precision. Results also show, the feedback in ERBE is mostly from shortwave radiation while the feedback in the models is mostly from longwave radiation. Although such a test does not distinguish the mechanisms, this is important since the inconsistency of climate feedbacks constitutes a very fundamental problem in climate prediction.

http://www.leif.org/EOS/2009GL039628-pip.pdf


http://asd-www.larc.nasa.gov/erbe/erbssat.gif

 

[Xnn]

It seem odd now come to think of it why anyone would assume the planet's response to a forcing change would be to amplify the change. Due to lags in physical systems, a system with positive feedback will be unstable.

A positive feedback does not mean that the climate is unstable.

For example, the melting/freezing of ice is a positive feedback mechansim.

As the planet warms, ice melts which reduces the albedo.
Reduced albedo in turn allows more sunlight to be absorbed, which results in more warming.
The additional warming results in more ice melting and so on and so on.
However, at the extreme when all the ice is melted, then that feedback mechanism goes away. Eventually, additional warming will not result in more melting and albedo changes. So, eventually the system will stabilize.

Also, it's not necessary for all the ice to melt in order for the system to stabilize. However, the temperature does have to stabilize before the ice will reach equilibrium.

 

[sylas]

The assumption of positive feedback in the General Climate Models did not make sense based on current and past observations. For example, the planet's response to a step increase such as the cooling associated with a volcanic eruption indicates the feedback it negative rather than positive. (Overdamped response.)

Negative feedback stabilizers systems such that they will naturally resist rather than amplify forcing changes. Almost all physical systems have negative feedback. It seem odd now come to think of it why anyone would assume the planet's response to a forcing change would be to amplify the change. Due to lags in physical systems, a system with positive feedback will be unstable.

There's a minor point of terminology to clear up here.

In climate studies, the term "feedback" is usually used only of processes that modify the underlying "Planck response", which is the base temperature response assuming everything else about a system remains unchanged.

However, in control theory the Planck response itself can also be treated as a feedback... a very strong negative feedback. This is described nicely in Appendix A of Bony et al (2006):

• Bony, S., et al (2006) "ftp://eos.atmos.washington.edu/pub/breth/papers/2006/Bony_etal_feedbacks.pdf"[/URL], in [i]Journal of Climate[/i], Vol 19, 1 Aug 2006, pp 3445-3482.[/list]
  
  It works like this. When you raise the temperature, you start to radiate more energy; and this leads to cooling. Using the notation of Bony et al, appendix A, let ΔR be the change in Earth's energy balance from some given equilibrium condition. Let ΔQ be a "forcing"; an imbalance imposed somehow which leads to a temperature response. Let ΔT[sub]s[/sub] be the change in surface temperature. As a result of the change in temperature, there will be a change in energy balance. Let λ be the amount of energy balance change per unit temperature. This is the climate response.
  [indent]$$\Delta R = \Delta Q + \lambda \Delta T_s$$[/indent]
  Equilibrium is restored once ΔR is back to zero, and the total climate response is the amount of temperature change ΔT[sub]s[/sub] required to compensate for the forcing ΔQ.
  
  The major effect of raising temperature is to emit radiation, in a way that can be estimated from simple radiation physics. This is about -3.2 W/m[sup]2[/sup] per degree, represented as λ[sub]p[/sub]. The negative convention indicates raising temperature let's Earth lose energy; it is a negative feedback and this keeps Earth stable.
  
  There are other factors involved. As temperature increases, so does specific humidity, which gives a positive feedback from the additional greenhouse effect, and a smaller negative feedback from a reduced lapse rate. There is a change in ice cover, which is a positive feedback, as Xnn indicates. There are changes to cloud; which is much harder to determine. Most researchers believe the cloud feedback is a net positive; Lindzen is famous for arguing for a strong negative feedback from cloud responses to temperature. The paper Saul has introduced does not attempt to identify the source of the feedback; it merely attempts to measure it.
  
  The final λ in the energy balance equation can (for small changes, of a few degrees) be approximated quite well as a linear sum
  [indent]$$\lambda = \lambda_P + \lambda_c + \lambda_w + \lambda_i + ...$$[/indent]
  The overall sum is negative; if it was positive then climate would be unstable, just as Saul has said. But when a paper speaks of climate feedback, they invariably mean the sum of all the terms other than the base Planck response. This is what Lindzen and Choi is arguing is negative, and what nearly all other researchers consider to be positive.
  
  Note also; climate models do not make any "assumption" about feedback at all. The feedback is emergent from within the model, as a spontaneous consequence of the interacting processes. This is very clear in Bony et al (2006) which deals with the issue of trying to estimate feedbacks within models. This is quite tricky; because the feedback is not assumed at all.
  
  Lindzen and Choi argue that the models are wrong; which is a point worth considering. But if so, it is because there's some pervasive error in the physics of what they are representing. The most likely candidate for this is cloud effects.
  
  With respect to volcanoes; the response is damped, certainly; that is because the net λ is negative. However, the study of volcanic eruptions indicates that it is not as damped as you would expect from λ[sub]p[/sub] acting alone; this is evidence for positive feedbacks on top of the Planck response. See Wigley et al (2005)
  [list][*]Wigley, T. M. L., C. M. Ammann, B. D. Santer, and S. C. B. Raper (2005), http://www.agu.org/pubs/crossref/2005/2004JD005557.shtml, in [i]J. Geophys. Res.[/i], Vol 110, D09107, doi:10.1029/2004JD005557.
  [PLAIN]http://www.kore-net.com/documents/volc.doc

This is not adequate to refute Lindzen and Choi, of course; neither is Lindzen and Choi adequate to refute Wigley at al. To resolve the discrepancy, one or other of the papers must be fundamentally flawed; and that needs to be identified within the flawed paper itself before the matter can be considered satisfactorily addressed.

Cheers -- sylas

 

[Xnn]

Lindzen and Choi argue that the models are wrong; which is a point worth considering. But if so, it is because there's some pervasive error in the physics of what they are representing. The most likely candidate for this is cloud effects.

I'm not so sure about that, but I'm still trying to figure out exactly what it is that Lindzen and Choi are showing us.

First, their paper is limited to the tropics (20S to 20N) and they are not including any of the land which amounts to about 22% of the tropics.

Second, figure 3 is showing us charts for long wave, short wave and a combination.
Each chart plots Flux/T versus sensitivity and feedback factor.

ERBE data and model results are both plotted along with lines for feedback.

In the LW chart, he shows SW f=0
In the SW chart, he shows LW f=0 and f=1. LW f=1 looks to be a better fit.
In the LW and SW chart, the line isn't labeled, but the ERBE data points to a sensitivty of around 0.5C while the model lines point to around 1.4C.

He also makes the following statement:

Indeed, Fig. 3c suggests that models should have a
range of sensitivities extending from about 1.5°C to infinite sensitivity (rather than
5°C as commonly asserted), given the presence of spurious positive feedback.
However, response time increases with increasing sensitivity [Lindzen and Giannitsis,
1998], and models were probably not run sufficiently long to realize their full
sensitivity. For sensitivities less than 2°C, the data readily distinguish different
sensitivities, and ERBE data appear to demonstrate a climate sensitivity of about
0.5°C which is easily distinguished from sensitivities given by models.

Figure 3C would be the LW + SW chart.

So, is Lindzen suggesting that over the long term there could potentially be an infinite climate sensitivity to CO2 based on ERBE data?


Sylas; your help here would be much appreciated!

 

[sylas]

Sylas; your help here would be much appreciated!

I will be taking a bit of time to look at this one. I want to understand the argument better before I attempt to describe it myself. Interestingly, one of the most specific criticisms seems to have been from Roy Spencer, who is also an advocate for very low sensitivities. When I more of a grip on both sides of that, I'll post again.

Cheers -- sylas

 

[Saul]

I'm not so sure about that, but I'm still trying to figure out exactly what it is that Lindzen and Choi are showing us.



He also makes the following statement:



Figure 3C would be the LW + SW chart.

So, is Lindzen suggesting that over the long term there could potentially be an infinite climate sensitivity to CO2 based on ERBE data?

Xnn,
He is saying that based on the ERBE data there is more SW radiation emitted than LW radiation not emitted when there is an increase in ocean temperature so there is a net reduction of energy top of atmosphere in response to a step change in ocean temperature.

As there is no ice or snow for the tropical case an increase in short wave radiation would indicate that there is either an increase in planetary cloud cover or there is an increase in the albedo of the clouds that do form when the ocean temperature is higher.

Lindzen's comment an infinite response (infinite is too high however his point that positive cloud feedback is not reasonable based on the planet's response to other step changes) is that theoretically if the model feedback is positive that the upper end in the planet's response is likely higher than 5C, if the model is run long term.

Because there are natural lags in all physical systems a system with positive feedback will be unstable.

This is illustrated in Spencer and Braswell's paper. Spencer and Braswell ran multiple model runs using positive feedback for clouds and found the model produced a wide range of responses.

http://www.drroyspencer.com/Spencer-and-Braswell-08.pdf

Potential Biases in Feedback Diagnosis from Observational Data: A Simple Model Demonstration

 

[Xnn]

Spencers paper demonstrates that nonfeedback top-of-atmosphere radiative flux variations can cause temperature variability, which could result in a positive bias in diagnosed feedbacks. That is fine by me... lots of noise = lots of uncertainty.

However, he does not address the positive feedback of lowering albedo from melting ice.

Lindzen stated that if some of the models were run longer, they might show greater sensitivities. However, he also stated that infinity needs to be included as a potentiality. This is the same thing as stating that we need to consider the possibility that all the snow and ice will melt.

This leads us towards an understanding that the tropics and polar regions behave fundamentally different from each other. Negative feedback over the tropical oceans contrasted against a large positive feedback towards the poles.

 

[Saul]

Spencers paper demonstrates that nonfeedback top-of-atmosphere radiative flux variations can cause temperature variability, which could result in a positive bias in diagnosed feedbacks. That is fine by me... lots of noise = lots of uncertainty.

This leads us towards an understanding that the tropics and polar regions behave fundamentally different from each other. Negative feedback over the tropical oceans contrasted against a large positive feedback towards the poles.

If there is less snow and ice in high latitude regions that will reduce the amount of sunlight reflected to space. That is however, a separate issue. The general climate models assumed positive feedback for clouds to amplify forcing changes (warm or cold).

If the total cloud feedback (Short wave and Long wave) is negative rather than positive, the amount of warming due to CO2 increases in the atmosphere will be less planet wide.

The paleoclimatic record seems to support Lindzen and Choi's finding. When the planet was warmer the planet's climate was stable. Cloud cover increases to stop the planet from getting too warm and cloud cover decreases to stop the planet from getting too cold. Cloud cover regulates the planetary temperature.

Changing the cloud feedback in the GCM to negative rather than positive reduces the amount of warming due to a CO2 doubling to a range of 0.75C to 1.8C. (rather than 3C to 5C). I believe the 1.2C is no feedback of any kind. (Clouds, ice, or snow.)

The current planetary temperature increase of 0.7C to 0.5C (Depending on what is assumed for the original base and planetary temperature measurement assumptions.) for a 38% increase in CO2 (0.028% to 0.038%) matches what the models predict with no feedbacks of any kind.

As we know snow cover and ice cover is reduced in the Northern Hemisphere in the last decade, that would support the assertion that there is negative cloud feedback.

To get to 0.75C total increase for a doubling of CO2, a significant portion of the 20th century warming would need to have been due to solar affects on planetary albedo (low and/or high level clouds changes. Say 50%.)

 

[Andre]

However, he does not address the positive feedback of lowering albedo from melting ice.

True, that's outside the scope of his study.

However, maybe it is possible to do a guestimate of the importance of feedback in Arctic areas with ice albedo relative to Lindzens feedback, which is restricted to the tropics. We could for instance compare the surface areas that receive the solar insolation. For that we can simple make the Earth two dimensional, as the area of the solar flux hitting earth:

The colored areas roughly depict arctics above ~67 degrees lattitude versus tropics below ~23 degrees lattitude.

Now the formula's for calculating segment areas is here.

If we use the radius as unit we can simply calculate any segment or area below the segment with this simple spreadsheet:

with the formulas as used in row #9. We see that the arctic segment (cell e4) is about 3% of the half circle surface area, while the tropics (cell f6) are representing 48% of the surface.

It seems that a 'unit' of feedback on insolation in the tropics is about 16 times more effective than a similar feedback in the arctic.

 

[Xnn]

Have found some comment on Lindzen and Choi's paper.

Dr Roy Spencer:

It is not clear to me just what the Lindzen and Choi results mean in the context of long-term feedbacks (and thus climate sensitivity). I’ve been sitting on the above analysis for weeks since (1) I am not completely comfortable with their averaging of the satellite data, (2) I get such different results for feedback parameters than they got; and (3) it is not clear whether their analysis of AMIP model output really does relate to feedbacks in those models, especially since my analysis (as yet unpublished) of the more realistic CMIP models gives very different results.

Chris Colose comments that Lindzen tends to use outdated ERBE data.

So, maybe Lindzen has not found evidence of a negative feedback after all.
It is a very strange paper, especially where he states that the models ought to have higher sensitivities.

Andre;

In the Northern Hemisphere, seasonal snow can cover over half of the land. So, while the Southern Hemisphere has more permanent ice, the albedo feedback is stronger in the Northern Hemisphere. The hemispheres are not symmetrical with respect to snow/ice albedo.

 

[Andre]

http://chriscolose.wordpress.com/2009/03/31/lindzen-on-climate-feedback/#more-429" that Lindzen tends to use outdated ERBE data.

Now Chris states (see link in that post):

This has been documented in Wong et al 2006, Journal of Climate, a paper not even mentioned by Lindzen.

Maybe I am permitted to demonstrate the problems of using non peer reviewed blogs, since http://www.drroyspencer.com/Lindzen-and-Choi-GRL-2009.pdf state:

The observed data used in this study are the 16-year (1985–1999) monthly record of the sea surface temperatures (SSTs) from the National Centers for Environmental Prediction, and the Earth radiation budget from the Earth Radiation Budget Experiment (ERBE) [Barkstrom, 1984] nonscanner edition 3 dataset. Note that this data were recently altitude corrected and are acknowledged to be stable long-term climate dataset based on broadband flux measurements [Wong et al., 2006]....

references:
Wong, T., et al. (2006), Reexamination of the observed decadal variability of the Earth radiation budget using altitude-corrected ERBE/ERBS nonscanner WFOV data, J. Clim., 19, 4028– 4040, doi:10.1175/JCLI3838.1.

 

[Andre]

In the Northern Hemisphere, seasonal snow can cover over half of the land. So, while the Southern Hemisphere has more permanent ice, the albedo feedback is stronger in the Northern Hemisphere. The hemispheres are not symmetrical with respect to snow/ice albedo.

Even if the snow can cover half of the land, -if I interpret that as down to 45 degrees lattitude (halfway the equator) then there is still 82% more area below that lattitude.

Other factors considering snow-ice feedback, of which I don't know, if the models did account for it:

1: Snow usually coincides with winter - low solar angles and Arctic winter, no sun. So there is not a lot of insolation to be albedo-reflected in the first place.

2: Temperature of the surface is also dependent on temperatures subsurface, although the heat tranfer rate due to conduction is low, one can assume that the temperature of the layers of the first few feet of rock/soil, do play a role in the annual cycle. Snow is an excellent isolator (think of iglos) and soil covered with snow is practiclally not losing much more heat, whereas barren soil continues to radiate out and continues to cool. So maybe that the lower atmospheric temperatures above a snow cover due to more reflection is offset partly/substantially by the retention of heat underneath the snow. Note also that this can be considerable comparing the mass of the soil with the mass of the atmosphere. Therefore in the subsequent warming after the winter, a warmer insolated soil may offset the positive feedback to some extend.

 

[Trakar]

Now Chris states (see link in that post):



Maybe I am permitted to demonstrate the problems of using non peer reviewed blogs, since http://www.drroyspencer.com/Lindzen-and-Choi-GRL-2009.pdf state:

Indeed, it would seem, that there are a lot of problems regardless of venue. You refer to the Lindzen Choi paper published in July 2009, Chris's comments were made in March of 2009, and if I'm not mistaken, from the actual wording, appear to be in reference to comments Lindzen made on Anthony Watt's non-peer reviewed blog (http://wattsupwiththat.com/2009/03/30/lindzen-on-negative-climate-feedback/).

So far, I've just been skimming through PF's Climate change discussions, trying to get a feel for where understandings exist and the types of arguments that are prevelent here before deciding whether or not to enjoin such discussions, hopefully, this type of mistake/misrepresentation is not overly rampant!?

 

[Andre]

Note that Xnn stated:

Have found some comment on Lindzen and Choi's paper.

http://www.drroyspencer.com/2009/11/some-comments-on-the-lindzen-and-choi-2009-feedback-study/" :

It is not clear to me just what the Lindzen and Choi results mean in the context of long-term feedbacks (and thus climate sensitivity). I’ve been sitting on the above analysis for weeks since (1) I am not completely comfortable with their averaging of the satellite data, (2) I get such different results for feedback parameters than they got; and (3) it is not clear whether their analysis of AMIP model output really does relate to feedbacks in those models, especially since my analysis (as yet unpublished) of the more realistic CMIP models gives very different results.

http://chriscolose.wordpress.com/2009/03/31/lindzen-on-climate-feedback/#more-429" that Lindzen tends to use outdated ERBE data.

So, maybe Lindzen has not found evidence of a negative feedback after all.
It is a very strange paper, especially where he states that the models ought to have higher sensitivities.

Implying that all comments were on Lindzen and Choi 2009. However we see that this paper does indeed implement the corrections of Wong et al 2006, but moreover the other source which may not be linked to, has implemented these corrections.

Finally note that Spencer in his blog, to which one may not link, may agree with Lindzen and Choi that the climate is much less sensitive than the climate models suggest.

 

[mheslep]

Have found some comment on Lindzen and Choi's paper.

Dr Roy Spencer:

The comment is from Spencer's blog. Even though he's apparently a fine scientist, you might have labeled that comment as such.

 

[sylas]

Implying that all comments were on Lindzen and Choi 2009. However we see that this paper does indeed implement the corrections of Wong et al 2006, but moreover the other source which may not be linked to, has implemented these corrections.

Finally note that Spencer in his blog, to which one may not link, may agree with Lindzen and Choi that the climate is much less sensitive than the climate models suggest.

Quite right. Chris' comments to which Xnn has referred were with respect to an earlier version of Lindzen's work, before it was published. I think you should presume an honest mistake.

Chris' comments were correct at the time, and by the time Lindzen published those particular problems were fixed. So in fact, the problem was not with being a blog per se; it was rather a case of keeping track of what was being referred to.

Dr Spencer, like Lindzen, is one of a very few working climate scientists who argues for a very low climate sensitivity, which makes his criticisms of Lindzen's paper that much more credible. He is evidently basing his criticisms on the real merits of the method itself, without being led into spurious agreement merely because he like the conclusion.

Like Spencer, I want to be completely sure I am being fair to the paper on its own merits, and not merely disagreeing because I don't like the conclusion. I want to understand the paper, and see how it obtains the result and just the method on its own merits.

A comparison paper would be:

• Gregory, J.M. & Forster P.M. de F (2006) The Climate Sensitivity and Its Components Diagnosed from Earth Radiation Budget Data, in J. of Climate Vol 19, Iss 1, pp 39-52

This is a widely cited and much more detailed paper which ALSO uses the ERBE data, and infers a net positive feedback. There are some interesting similarities and differences with the two papers. That Lindzen does not cite this paper is strange; it is very influential and widely cited prior work doing precisely what he has attempted; constrain sensitivity using ERBE data.

I will be posting more on this, but I really want to be sure I understand both papers before I comment further. I want to uphold the high standard shown by Roy Spencer, in sticking to arguments on their own merits and not just because of preconceptions about the right answer.

By the way, the ice feedback matter is not all that fundamental. The expectation of models is of positive feedback in the tropics, so just looking at the tropics is fine. If ERBE really does show a negative feedback in the tropics as Lindzen and Choi suggest, this is revolutionary. Forster has some challenges for the models as well, but not so sweeping; and obtains a positive feedback effect from the same data. I want to understand why the two papers are so different, despite using the same data.

When I post, I will be sticking simply to peer-reviewed sources.

Cheers -- sylas

 

[Xnn]

Finally note that Spencer in his blog, to which one may not link, may agree with Lindzen and Choi that the climate is much less sensitive than the climate models suggest.

Andre;

Thanks for pointing out that Lindzen used the current data in his 2009 paper. At least we can rely on the data. However, I've received another comment regarding the paper at Real Climate.

There is no good reason to expect that tropical oceans are a good proxy for assessing global climate sensitivity. There is already a large amount of water vapor in the tropical atmosphere and no sea ice or seasonal snow. Rising water vapor, melting sea ice and seasonal snow are the primary postive feedbacks of climate models that he compares against.

Next, look at the data charts in the Lindzen paper. SST shows no signficant trend over the period (global warming is most pronounced in the Arctic) So, he picks El Nino/La Nina events as "data points". However, wait a minute, we know that these events are not due to CO2 fluctuations. So, why should we expect climate models to model these as minature global warming/cooling events?

What stands out most prominently in the ERBE data is the Mt Pinatubo erruption of 1992/93. A large fluctuation in SW with a smaller response in the LW. 2 of the models (GDFL CM2.1 and GISS-ER) appear to model that fairly well, but the rest miss it entirely. So, I'm left wondering if the other climate models had the aerosal data for Mt Pinatubo.

Finally, there is a gap in the ERBE SW data in 1993 and a shift thereafter. I'm not sure what that is all about. If it is valid, then there appears to be a trend in the data. If not, then it's just poor data. Confirmation is needed to ensure we understand what is happening since it may be significant.


Conclusion (based on Lindzens data):

None of the models model El Nino/La Nina events very well.
2 models (GDFL CM2.1 and GISS-ER) do a fair job of modeling Mt Pinatubo.
The remaining models either had no Pinatubo data or did a lousy job.
There maybe a trend in SW flux over the tropics.

 

[sylas]

... The expectation of models is of positive feedback in the tropics, so just looking at the tropics is fine. If ERBE really does show a negative feedback in the tropics as Lindzen and Choi suggest, this is revolutionary. Forster has some challenges for the models as well, but not so sweeping; and obtains a positive feedback effect from the same data. I want to understand why the two papers are so different, despite using the same data.

When I post, I will be sticking simply to peer-reviewed sources.

I have been working on this matter, but events have overtaken me. Which is just as well, given as this whole topic is about to be shut down and I am not yet ready to give a proper response of my own.

There has just come out a formal published response to Lindzen and Choi 2009. It is:

• Trenberth, K. E., J. T. Fasullo, Chris O’Dell, and T. Wong, (2010): Relationships between tropical sea surface temperature and top-of-atmosphere radiation, in Geophys. Res. Lett., 37, doi:10.1029/2009GL042314, in press. (Or try this link, which fails now but might work better in future: http://dx.doi.org/10.1029/2009GL042314, I am not sure.)

It will require a subscription to get the paper. The conclusion is concisely summarized:

As shown here, the approach taken by LC09 is flawed, and its results are seriously in error. The LC09 choice of dates has distorted their results and underscores the defective nature of their analysis. Incidentally, LC09 incorrectly computed the climate sensitivity by not allowing for the Planck function in their feedback parameter. For their slope of -4.5 W m^-2 K^-1 and using the correct equations (Section 1), LC09 should obtain a feedback parameter and climate sensitivity of -0.125 and 0.82 K, respectively, rather than their values of -1.1 and 0.5 K. In contrast, the case 4 (Table 1) results yield a positive feedback parameter of 0.6 and a climate sensitivity of 2.3 K. Moreover LC09 failed to account for the forcings in estimating sensitivity.[/color]​

It is worth noting that having errors or defective analysis in a published paper is not particularly unusual. The original paper does have errors, and Lindzen has already acknowledged some of them. He is likely to write a revised paper taking criticism into account, and we shall have to wait and see what he provides... just as we had to wait for a few months to see a formal published paper describing the errors in the original work. This is a normal part of the work of science, and a reminder that one should be very cautious about jumping on a new paper that has just been published as definitive. The discussion will continue.

For all that the paper was well outside the conclusions of the vast majority of work on this subject, and for all that the numbers as in the original 2009 paper are certainly wrong as given, the work itself is not immediately trivially incorrect. It was in some respects rather subtle, and it continues to be useful to have working scientists making unusual proposals, and putting them up for wider consideration by the scientific community.

Note that the corrections to mathematical errors in the original paper restore a positive feedback, in line with all other research, and a feedback value of 2.3 that is low but within the range of the standard IPCC estimates of something from 2 to 4.5. In my own response that I had been working on recently, this was something I had been trying to sort out as well, so it is good to have it confirmed by more expert commenters.

Bottom line... we are right back with positive feedback from the ERBE data, though with some suggestions that the value may be a bit below what is indicated by other methods. This is right back in line with Gregory and Forster (2006) which I had cited previously; they obtained a value of 2.3 +/- 1.4 for climate sensitivity as well.

Cheers -- sylas

 

[mheslep]

as this whole topic is about to be shut down ...

By PF mentors? Why?