global warming: salvaging fact from heaps of BS

SkepticLance · May 12, 2008

So far, temperature rise, measured as global average, is only 0.8 Celsius. We can live with that, and quite a bit more. Sea level rise has been a fraction of a metre, and we can live with that, also, plus quite a bit more.

The time for drastic and reckless action is still way over the horizon. We need to address the cause, as swansont said. The real problem is that governments are still fooling around, when there are real things they can do now. As I have said before, the world needs about 1000 extra nuclear power plants, since electricity is going to supplant fossil fuels as a resource in lots of areas. The important thing is to get under way the things that we can do, and develop new alternatives where such are not yet available.

Bio-fuels are a case in point. Mostly biofuels consist of ethanol from corn, or biodiesel from such things as palm oil. Both have been utter disasters so far, and both should be curtailed. If the world is to use biofuels on a large scale, we need new technologies, such as whole plant conversion to ethanol - not just the edible part.

pioneer · May 13, 2008

What most of the models don't take into account, is the #1 greenhouse gas which is H2O. For example, in the fall if there is a frost warning, if clouds move in to prevent the radiational cooling, the surface stays warmer because the heat is reflected back to the ground to prevent frost. In the summer when getting a tan, a bunch of clouds can work the other way and reduce the amount of solar energy reaching the surface. I would also expect at least some of the solar energy will be reflected back upward into space because of clouds, especially the high attitude ones that contain lots of tiny shiny ice crystals.

On relative scale of 1-10, water is up there at 10 and the rest are closer to 1-2 which why we need the best and brightest to help quantify these. The water is obvious enough to ask uncle Joe to act as expert. The water, since it is not included as a dynamic variable in many models, may be treated as a constant. If CO2 works like it is suppose too, then the heating affect will put more water in the air. There will be make more cloud cover, higher cloud tops for reflection, etc. One may even expect more high altitude clouds as the percentage of water gets higher and higher. There is also more water falling from high altitude which cools earth, etc. The projected numbers may be biased high.

This is not intentional oversight, just the water is very complicated to model because it affect is as dynamic as the weather itself. Maybe at least a study of solar reflection as a function of atmospheric water, such as cloud cover, cloud type and cloud height. For example, if one cloud type is better than another and the earth is producing more or less, this could have an impact. Even if heat is bouncing between the upper level greenhouse gases and increasing cloud tops, each bounce back and forth means some extra heat is able to escape the greenhouse gases.

The simplified diagrams show heating coming off the surface with one bounce against the greenhouse giving 35% return yield. After two bounces that may drop to 30%, just to use a number. The more cloud cover means more average bounces. The more clouds also means a cooler surface since clouds give shade. What is also happening, is some of the surface heat doesn't reach the other greenhouse gases because it bounces back off the clouds. The result may be the projections biased high. Once the water is included we can trust the results more.

iNow · May 13, 2008

What most of the models don't take into account, is the #1 greenhouse gas which is H2O. [/qUOTE]
I'm sorry, Pioneer, but pretty much all of the conclusions in your post are false since you began with such an inaccurate and invalid premise.

You are enormously mistaken to believe (and suggest) that "most models" don't take water vapor into account. That statement is laughable in the magnitude of it's error.

(emphasis mine):

http://en.wikipedia.org/wiki/Global_climate_model

Atmospheric GCMs (AGCMs) model the atmosphere (and typically contain a land-surface model as well) and impose sea surface temperatures (SSTs). A large amount of information including model documentation is available from AMIP [4]. They may include atmospheric chemistry.

AGCMs consist of a dynamical core which integrates the equations of fluid motion, typically for:
surface pressure

horizontal components of velocity in layers

temperature and water vapor in layers

[*]There is generally a radiation code, split into solar/short wave and terrestrial/infra-red/long wave

[*]Parametrizations are used to include the effects of various processes. All modern AGCMs include parameterizations for:

convection

land surface processes, albedo and hydrology

cloud cover

A GCM contains a number of prognostic equations that are stepped forward in time (typically winds, temperature, moisture, and surface pressure) together with a number of diagnostic equations that are evaluated from the simultaneous values of the variables. As an example, pressure at any height can be diagnosed by applying the hydrostatic equation to the predicted surface pressure and the predicted values of temperature between the surface and the height of interest. The pressure diagnosed in this way then is used to compute the pressure gradient force in the time-dependent equation for the winds.

Oceanic GCMs (OGCMs) model the ocean (with fluxes from the atmosphere imposed) and may or may not contain a sea ice model. For example, the standard resolution of HadOM3 is 1.25 degrees in latitude and longitude, with 20 vertical levels, leading to approximately 1,500,000 variables.

Coupled atmosphere-ocean GCMs (AOGCMs) (e.g. HadCM3, GFDL CM2.X) combine the two models. They thus have the advantage of removing the need to specify fluxes across the interface of the ocean surface. These models are the basis for sophisticated model predictions of future climate, such as are discussed by the IPCC.

AOGCMs represent the pinnacle of complexity in climate models and internalise as many processes as possible.

If you'd like to support your contention with anything more than personal opinion, I'd welcome that.

JohnB · May 13, 2008

Chris,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is the uncertainty in the determination of the mean of the model projections rather than the spread.

Since the model spread is rarely mentioned, in fact probably all model projections I've read refer to using the mean of ensemble runs, I don't see the problem. Even the IPCC (SEction 8.3) says

The multi-model averaging serves to filter out biases
of individual models and only retains errors that are generally

pervasive. There is some evidence that the multi-model mean

field is often in better agreement with observations than any of the

fields simulated by the individual models

Why do you object to comparing the mean to observations when the IPCC obviously doesn't? Is it because you don't like the answer?

Using older data without justification

Yes he did justify it, an Addendum was sent explaining the choice on Jan 3, 2008. Douglass quotes the relevent section in response to Gavin in the Briggs thread you contributed to.

looking at time periods of high internal variability doesn't help either.

The ROABCORE data covers the satellite period 1979-2004. How do you suggest getting accurate tropospheric temperature readings without using satellites? Or are you suggesting that due to "internal variability" records from the satellites should not be used? AGW theory requires accelerated heating in the trop, the models predict accelerated heating in the trop, the observations show the model predictions to be wrong.

Now I don't have a scientific background, however in my time here I've found that those who do, espouse (and have to repeat it endlessly to posters in the pseudoscience subforum:D) a simple step process to check a theory.

1. Formulate theory. (Check.)

2. Make testable predictions. (Check.)

3. Compare to observations. (Che......Oops.)

As a point of interest,

Gavin Schmidt said,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is instead the uncertainty in the determination of the mean of the model projections rather than the spread. It is exactly equivalent to throwing a dice 100 times and calculating the the mean throw to be 3.5 +/- 0.1 and than claiming that a throw of a 2 is a mismatch.

Chris C said,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is the uncertainty in the determination of the mean of the model projections rather than the spread. It's like saying the mean of rolling a dice 100 times is 3.5 +/- 0.1 and claiming that one throw of 2 is a mismatch.

And people on my side of the fence get accused of "Parroting"?

This seems to be a distraction though.

It is a bit. Since reading the original comment I've had these funny pictures running through my mind. (They always run, as it's not a safe place to be.) Like I said earlier, some sort of arcane ritual, a Climatologist having an epiphany on the road to Damascus, a large, forboding, leather bound book the "Climatomnicon" kept in secret places. Taking the comment at face value, you can have a ball imagining how this "unspoken" knowledge is passed on.

Chris C · May 14, 2008

My apologies on the quote w/o credit.

AGW theory does not "require" extra tropical heating; this is a principle of moist convection that is expected from any cause. In fact, the greenhouse effect requires a temperature decline with altitude, so if observations showed less atmospheric warming than models show, then that would mean climate sensitivity was *underestimated* because of less negative feedback from the lapse rate response. Not overly reassuring that the models could be wrong. The models are in fact not right with the sea ice decline either, but not on the conservative end (Rahmstorf 2007).

The weather noise over the interval looked at is very important, and because of that, the spread of the runs due to weather is important. An ensemble is a collection of simulations run by one model, for one experiment, and is good for a set of possible trajectories for some forcing x. It's fine if you use data, but make sure you understand that there is noise, and not just the forcing from some external perturbation. It's like "global warming stopped in 1998 while ghg's have increased." Silly.

Because there is an incorrect treatment of the model uncertainty, and no discussion on the data choices (the original paper would have been nice, rather than being lost in blog comments), it seems that the other analysis which show no difference between models and observations are worth looking at, no?

...................................

Now I don't have a scientific background, however in my time here I've found that those who do, espouse (and have to repeat it endlessly to posters in the pseudoscience subforum) a simple step process to check a theory.

1. Formulate theory. (Check.)

-- Based on a centuries+ work of radiative physics, fluid dynamics, etc

2. Make testable predictions. (Check.)

--Like the temperature rise over the last century, strat cooling, increased ocean heat content, sea level rise, polar amplification, increased NH response, trop warming a bit more than surface, ice declines, species response, etc

3. Compare to observations. (Che......Oops.)

--Like the temperature rise over the last century, strat cooling, increased ocean heat content, sea level rise, polar amplification, increased NH response, trop warming a bit more than surface, ice declines, species response, etc. Now models aren't perfect, but when comparing them to observations, maybe a correct analysis would be good. Right now, the main and "broad" predictions are being borne out.

JohnB · May 14, 2008

My apologies on the quote w/o credit.

No sweat, my comment was meant in a friendly fashion, hence the . You gave me a great straight line and I wasn't big enough to pass it up. Just because we are on opposing sides doesn't mean we can't have levity or respect for each other.

Like the temperature rise over the last century