vorcil
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42 is the awnser
In fact, greenhouse gases inhibit radiation to such an extent, that convection of heat is the dominate mechanism for transporting energy from the surface to elevations where it can be effectively radiated to outer space.
skypunter said:Why then is convection not addressed further in this thread? Probably because the heat it transports cannot be accurately quantified for modeling purposes.
Due to convection, greenhouse gases appear more like a sieve than a blanket.
skypunter said:It seems that there is a great deal of attention paid to radiational "balance" formulae within the climatological community, but very little toward the acknowledgment of the dynamic nature of the atmosphere. Surely there are many studies of the thermohaline circulation, but so little data which can be applied to a practical global model.
It makes one wonder if the general scientific community is so preoccupied with proving how much it does know, that it has lost sight of how much it does not.
Just a personal observation, perhaps inappropriate here.
Advance apologies if format is breached hereby.
vorcil said:I reckon the temperature will stay at equilibrium,
With the temperature TEMPOARILY RISING it will melt ice
YES
BUT with more water being melted, it's also making it colder simutaneously due to the absorbtion of heat by the water
I would like an expansion on that, if you don't mind terribly. ...if you especially could fit Tim Palmer in the discussion.Sylas said:We've come a heck of along way over recent decades;
bellfreeC said:I would like an expansion on that, if you don't mind terribly. ...if you especially could fit Tim Palmer in the discussion.
MrB.
sylas said:I don't know what you are quoting here, but the various transports can be quantified quite nicely. There are uncertainties, but there is more than enough to establish that actually, convection is the smallest part of heat transport into the atmosphere from the surface.
If we take global averages, over all latitudes, and seasons, and times of day, the net transports work out to about
- Convection: around 17 W/m2. Accuracy not particularly good, but it's around this magnitude.
- Latent heat: around 80 W/m2. Accuracy here is pretty strong; it follows directly from annual precipitation. This is the heat of evaporation which is released into the upper atmosphere as water condenses.
- Radiant heat: around 63 W/m2. Accuracy here is fair; enough to be confident that its rather less than the latent heat, and a lot more than the convection.
skypunter said:It seems to me that radiant heat is the only one of the three which might be accurately estimated. We have plenty of spectral data coming down from satellites on a daily basis.
When I say convection, I mean any transport of heat within a rising air column, including that contained in water vapor. So if you add the latent heat to convection (both being dynamic transport mechanisms which respond to temperature) then this transport mechanism does have a greater total effect than radiant heat. It rapidly by-passes the majority of the "thermal blanket".
How do you substantiate the claim that latent heat accuracy is pretty strong?
It seems to me that radiant heat is the only one of the three which might be accurately estimated.
if you put convection and latent heat together as "special heat", then it is about half as much again as the net upwards radiant heat flux.
The phrase "meteorological butterfly effect" is introduced to illustrate, not the familiar loss of predictability in low-dimensional chaos, but the much less familiar and much more radical paradigm of the finite-time predictability horizon, associated with upscale transfer of uncertainty in certain multi-scale systems.
Yeah, good luck on that! Color me dubious on any efficacy for emergency managment teams.The critical question that climatologists are trying to answer is whether the climate attractor will suffer a minor perturbation (for example, small shift of the whole attractor along one of the axes of phase space), or whether there will be a substantial change in the whole shape and position of the attractor, leading to some possibly devastating weather states not experienced in today's climate.
bellfreeC said:This is Chjoaygame:
"Inside the window, one is interested in separate radiative transfer of heat from the land-sea surface. The mean free path of "single photons", when the air is relatively dry and the CO2 relatively little, can be hundreds of kilometers. The very importantly and greatly variable IR radiative flux through the window, direct from the land-sea surface to space, is on the order of magnitude of 60 W m^-2. In a cloudless sky, the notion of "back-radiation" does not arise here.
sylas said:The latent heat transported up from the surface is given precisely by the mass of water that is evaporated, and that in turn is known from the annual rate of precipitation, for which there is good data available.
skypunter said:Perhaps the rate of past precipitation can be measured, but can it be accurately forecast over the long term?
Surely an estimation of heat transport based upon past precipitation cannot be treated as a constant in climate models.
Xnn said:What has been concluded (TS.4.5 on page 64) is that the Earth's temperature is sensitive to changes of CO2 concentration. In particular, equilibrium change is likely to be in the range 2°C to 4.5°C per doubling of CO2, with a best estimate value of about 3°C.
vanesch said:Just a question, as we are talking about the *physics* of this effect. When you do the calculation with MODTRAN, you find rather 0.9 K per doubling of CO2 if you switch of water vapor feedback (keep same partial pressures for water vapor).
http://geosci.uchicago.edu/~archer/cgimodels/radiation.html
Do the standard calculation (CO2 = 375 ppm) and you find an upward flux of 287.844 W/m^2 (at ground temp 299.7 K).
Now, put CO2 to 750 ppm, and put the ground offset to 0.9 K, then you find an upward flux of 287.875 W/m^2.
So this would mean that in order to put the same heat flux out when we have a CO2 doubling, and we make the assumption of "all else equal", especially water vapor, so no feedback mechanisms or anything, that the *purely optical* effect gives rise to a needed heating of 0.9 K to have again the same outward heat flux.
Is this, according to climatologists, still a correct way of seeing the "primary drive" ? As a physicist, I would say so, in as much as MODTRAN is a correct optical radiation transport model.
(you can of course vary several things, different atmosphere models etc... but you always find values of a bit less than 1 K).
Yes, this has been provided many times. "Figure — Details of Earth's energy balance (source: Kiehl and Trenberth, 1997). Numbers are in watts per square meter of Earth's surface, and some may be uncertain by as much as 20%..." The black and white version that currently brings up the rear of thread id:123613 was by AEBanner, June19-06. Why shouldn't old threads be remembered?Sylas said:The diagram I showed is energy flow in the present based on empirical data for the period March 2000 to May 2004.
Thread id:204120!Sylas said:The statement above seems fine, and you've failed to comprehend what it is about. It is about the thermal radiation in the infrared window,
sylas said:There's one minor complication, because if you look at the literature you'll usually see slightly higher numbers for the Planck response; more like 1.1 or 1.2 K. You can get this with MODTRAN by locating your sensor at about the tropopause, rather than the 70km default. Try getting the radiation at an altitude of 18km with the tropical atmosphere. In this case, you should have something like this:
- 288.378 W/m2 (375ppm CO2, Ground Temp offset 0, tropical atmosphere, 18km sensor looking down)
- 283.856 W/m2 (750ppm CO2, Ground Temp offset 0, tropical atmosphere, 18km sensor looking down)
- 288.378 W/m2 (750ppm CO2, Ground Temp offset 1.225, tropical atmosphere, 18km sensor looking down)
I think I can explain what is going on here. It's a minor additional detail to do with how the stratosphere works.
When you hold surface temperature fixed, MODTRAN will hold the whole temperature profile of the atmosphere fixed.
The cooling of the stratosphere is so immediate that it is not treated as a feedback process at all, but is taken up as part of the definition of a change in energy balance. Hence MODTRAN is not quite giving you what is normally defined as the Planck response. To get that, you would have to drop the stratosphere temperature, which would reduce the thermal emission you are measuring a little bit. By placing the MODTRAN sensor at the tropopause, you are avoiding worrying about the stratosphere at all, and getting a better indication of the no-feedback Planck response.
PS. Just to underline the obvious. The Planck response is a highly simplified construct, and not all like the real climate response. The real climate response is as you quoted from Xnn: somewhere from 2 to 4.5 K/2xCO2. It is the real response that you can try to measure empirically (though it is hard!). You can't measure Planck response empirically, because it is a theoretical convenience.
The full response in reality is just as much physics as the simplified Planck response; real physics deals with the real world in all its complexities, and the climate feedbacks are as much as part of physics as anything else.
vanesch said:OK. I would actually object to doing that, except as a kind of loop-around in a model error in MODTRAN, because what actually counts is of course what escapes at the top of the atmosphere, and not what is somewhere in between. So then this is a kind of "bug fix" for the fact that MODTRAN doesn't apparently do "local thermodynamic equilibrium" (I thought it did) adapting the temperature profile.
vanesch said:Ok. So that's the "bug fix", as normally the upward energy flux has to be conserved all the way up.
vanesch said:Yes. However, the point is that the MODTRAN type of physics response is "obvious" - it is relatively easily modelable, as it is straightforward radiation transport which can be a difficult but tractable problem. So at a certain point you can say that you have your model, based upon elementary measurements (spectra) and "first principles" of radiation transport. You could write MODTRAN with a good measure of confidence, just using "first principles" and some elementary data sets. You wouldn't need any tuning to empirical measurements of it.
vanesch said:However, the global climatic feedback effects are way way more complicated (of course it is "physics" - everything is physics). So it is much more delicate to build models which contain all aspects of those things "from first principles" and "elementary data sets".
vanesch said:And visibly, the *essence* of what I'd call "dramatic AGW" resides in those feedbacks, that turn an initial ~1K signal into the interval you quoted. So the feedback must be important and must be amplifying the initial drive by a factor of something like 3. This is the number we're after.
vanesch said:Now, the problem I have with the "interval of confidence" quoted of the CO2 doubling global temperature rise is that one has to deduce this from what I'd call "toy models". Maybe I'm wrong, but I thought that certain feedback parameters in these models are tuned to empirically measured effects without a full modelisation "from first principles". This is very dangerous, because you could then have included into this fitting parameter, other effects which are not explicitly modeled, and for which this fitting parameter then gives you a different value (trying to accommodate for some other effects you didn't include) than the physical parameter you think it is.
sylas said:The sensitivity value is not simply given by models. It is constrained by empirical measurement. In fact, the range given by Xnn, and myself, of 2 to 4.5 is basically the empirical bounds on sensitivity, obtained by a range of measurements in cases where forcings and responses can be estimated or measured.
You speak of tuning the feedback parameters... but that is not even possible. Climate models don't use feedback parameters. That really would be a toy model.
Climate models just solve large numbers of simultaneous equations, representing the physics of as many processes as possible. The feedback parameters are actually diagnostics, and you try to estimate them by looking at the output of a model, or running it under different conditions, with some variables (like water vapour, perhaps) held fixed. In this way, you can see how sensitive the model is to the water vapour effect. For more on how feedback parameters are estimated, see Bony et al (2006) cited previously. Note that the models do not have such parameters as inputs.
Personally, I am inclined to think that the narrower range of sensitivity obtained by models is a good bet. But I'm aware of gaps in the models and so I still quote the wider range of 2 to 4.5 as what we can reasonably know by science.
I'm not commenting on the rest, as I fear we may end up talking past one another. Models are only a part of the whole story here. Sensitivity values of 2.0 to 4.5 can be estimated from empirical measurements.
vanesch said:Ok, let me try to understand that precisely. Because the way I understood things when I read about it in the 4th assessment report, I was of the opinion that there was what one could eventually call "a methodological error" or at least an error of interpretation of an applied methodology. Now, I can of course be wrong, but I never had any sensible comment on it but have, on the other hand, seen casually other people make similar comments.
I guess so. Uncertainty bounds are estimated on the basis of assumptions that in principle might turn out to be wrong. I think that's the guts of it.vanesch said:I interpret what you say as about what I said above - is that right ?sylas said:The sensitivity value is not simply given by models. It is constrained by empirical measurement. In fact, the range given by Xnn, and myself, of 2 to 4.5 is basically the empirical bounds on sensitivity, obtained by a range of measurements in cases where forcings and responses can be estimated or measured.
Sensitivity is not part of the data used as boundary conditions for climate models. So no, the data are not somehow empirical sensitivity measurements. The free parameters in models, other than boundary conditions, are mainly numbers used to get approximations for things that cannot be calculated directly, either because the model has a limited resolution, or because the phenomenon being modeled is only known empirically.No, but they do contain free parameters, which are fitted to data in order to determine them, no ? And those data are then somehow empirical sensitivity measurements, like with those volcanoes, or am I wrong ? So the free parameters are in a way nothing else but transformations of the empirical measurements using the Bayesian parameter estimation method, no ?
No. We don't have sensitivity measurements. Sensitivity for the real world is something calculated on the basis of other measurements. The calculations presume certain models or theories, which are in turn physically well founded but which in principle are always open to doubt, like anything in science.No, not directly, but they do have free parameters which are fitted to sensitivity measurements, no ?
I don't see how you can measure such a thing "directly" without any model. I thought you always had to use modeling in order to determine the meaning of empirical data like this. Maybe I'm wrong here too.
sylas said:Science doesn't deal in certainty ... not even certainty on the basis for estimating confidence limits.
sylas said:I guess so. Uncertainty bounds are estimated on the basis of assumptions that in principle might turn out to be wrong. I think that's the guts of it.
Then, what is so basic about these calculations? Look at it from the global warming potential point of view. What are the odds of a CO2 molecule staying aloft for a hundred years or more?Sylas said:We don't have sensitivity measurements. Sensitivity for the real world is something calculated on the basis of other measurements. The calculations presume certain models or theories, which are in turn physically well founded but which in principle are always open to doubt,