[JP]

I don't usually weigh in on these threads since most contributors seem to have a horse in this race and use the thread to promote their particular viewpoint on climate change.  It's also outside of my area of expertise (physics).  However, as I posted in one of yor_on's other threads, there was an interesting article in The Economist last week that discussed the lack of warming in the past decade and cited some recent studies.  It does appear to be a real effect, although it doesn't negate the fact that there is overwhelming evidence that greenhouse gasses, including CO₂ do cause average temperatures to rise. 

What I can comment on is the proper way to deal with this data, which is basic science.  All decent models should include an analysis of uncertainties and include error bars.  Those that predicted a temperature rise over this past decade include error bars, and the lack of temperature rise does fit within those error bars, although if it continues it will fall outside the error bars of the model.  What this means is that the past decade is interesting, but not confirmation that the model is wrong. 

We also know that current models are not exhaustive: it's impossible to model every aspect of the earth's climate and all models make a lot of simplifying assumptions.  If these assumptions are wrong, the models will be off.  From what I remember from the article, two effects might be important: clouds and deep ocean warming.  Both need to be studied in more detail. 

I can also finally comment on the wrong way to do science, as I'm a scientist and this is a science forum.  It's bad science to come in with an agenda and cherry pick a few data points to "prove" you're correct--especially if you ignore the fact that the past decade is within bounds of current models.  Sure, more research is probably needed to figure out if the past decade indicates the models are wrong, but telling us you're correct because you can draw a sine wave through some cherry-picked data has little to do with the scientific method.  Similarly, arguing away the past decade as a meaningless hiccup in the data is also bad science.  Checking it against the error bounds in models is the proper way to do things--to see just how much meaning there is in the lack of warming. 

The Economist article is linked below, which includes references to the various studies involved.  Given the way such threads tend to go on the internet, I'm not holding my breath for a scientific discussion.

http://www.economist.com/news/science-and-technology/21574461-climate-may-be-heating-up-less-response-greenhouse-gas-emissions

[yor_on]

There are some interesting ideas.
http://www.spaceref.com/news/viewnews.html?id=673
http://physicsworld.com/cws/article/news/2010/jan/29/drop-in-warming-linked-to-water-vapour-decrease
http://www.realclimate.org/index.php/archives/2010/08/the-key-to-the-secrets-of-the-troposphere/

When it comes to both the atmosphere and the ocean it's really difficult to make those extensive studies. Before all they need to be funded. And considering how NASA:s budget looks those days, and what satellites etc, they plan to shoot up?

[imatfaal]

JP - stats isnt my strong point although I am now trying to set that straight, could you help me out a bit. 

If you have a mathematical model of a physical process ie given x1, x2,x3.... , y1,y2,y3 & z1,z2,z3 etc. we can predict a1,a2,a3 - I presume all of your input data has an observational error and uncertainty.   I would think that for an iterated process with high dependence on initial variation there is a methodological uncertainty introduced by your processing.   Both of these will be translated through to the prediction which will have confidence ranges and error bars etc.  Now your actual observations that you test against your predictions - in this case the global mean temperature, this will also have empirical error and uncertainty.   So to test your model you can plot observed against predicted - and hope that the observed falls within your error bars.    I hope this is right so far cos this is the bit I think I am sure about. 


1.  is there a single descriptive statistic that gives the probability that model gives results a1,a2,a3 and observation A1,A2,A3 - each numbered pair being temporally seperated and a new test.  the famous 5 sigma is your choice in physics - but isn't this for multiple observations of similar but unconnected events rather a single entity being observed over time?    (homespun example of what I am getting at - if I predict 3.5 for the roll of a die I will never be correct; however if the results are judged cumulatively rather than individually after a few rolls I will start to look pretty spot on)

2.  The article shows 5-95% and 25-75% percent confidence intervals - they look more like error bars to me.  And whilst I don't fully understand this page on wikipedia http://en.wikipedia.org/wiki/Confidence_interval it doesnt seem to be talking about the same thing.  It looks from the graph as they are saying that of the models we have run only the top 5% and the bottom 5% are outside this coloured band - or is it saying that only if the error is in the 5% that would maximise or minimise the prediction would it be outside this coloured band. 

sorry that I could not provide a science response on the issue.  But i loved your post and felt it deserved a response. 

[yor_on]

Not too happy about this conclusion. "if, however, temperatures are likely to rise by only 2°C in response to a doubling of carbon emissions (and if the likelihood of a 6°C increase is trivial), the calculation might change. Perhaps the world should seek to adjust to (rather than stop) the greenhouse-gas splurge. There is no point buying earthquake insurance if you do not live in an earthquake zone. In this case more adaptation rather than more mitigation might be the right policy at the margin. But that would be good advice only if these new estimates really were more reliable than the old ones. And different results come from different models."

First of all, adjust is what we will do. The CO2 concentrations are not going down, they are raising.
Secondly, what it bears down too is an assumption of 'business as usual', with all that this will bring with it in forms of exploitation and a poorer Earth. It's like the id**s finding it good that the Arctic melts, because we can then prolong our usage of oil, methane, coal etc. It's not good, whatever makes you think that it is?

Greed?

And then using papers that's not been peer reviewed supporting such an assumption?

[yor_on]

Are you thinking of how climate scientists define a Standard deviation Imatfaal? Same as everyone else I would say?

"Standard deviation - A measure of the spread or dispersion of a set of data. The more widely the values are spread out, the larger the standard deviation. It is calculated by taking the square root of the variance."

Variance - A measure of the average distance between each data point and the data mean value; equal to the sum of the squares of the difference between each point value and the data mean." From National Oceanic and Atmospheric Administration's (NOAA)

Look here The Science and Practice of Seasonal Climate Forecasting at the IRI for some of the complexity of the task.
And here is a preliminary prediction 2012 Updates to model-observation comparisons. And if you check the sources there you will see 'Skill and uncertainty in climate models.'

"Abstract

Analyses of skill are widely used for assessing weather predictions, but the time scale and lack of validation data mean that it is not generally possible to investigate the predictive skill of today's climate models on the multidecadal time scale. The predictions made with early climate models can, however, be analyzed, and here we show that one such forecast did have skill. It seems reasonable to expect that predictions based on today's more advanced models will be at least as skillful. In general, assessments of predictions based on today's climate models should use Bayesian methods, in which the inevitable subjective decisions are made explicit. For the AR4, the Intergovernmental Panel on Climate Change (IPCC) recommended the Bayesian paradigm for making estimates of uncertainty and probabilistic statements, and here we analyze the way in which uncertainty was actually addressed in the report. Analysis of the ensemble of general circulation models (GCMs) used in the last IPCC report suggests there is little evidence to support the popular notion that the multimodel ensemble is underdispersive, which would imply that the spread of the ensemble may be a reasonable starting point for estimating uncertainty. It is important that the field of uncertainty estimation is developed in order that the best use is made of current scientific knowledge in making predictions of future climate. At the same time, it is only by better understanding the processes and inclusion of these processes in the models, the best estimates of future climate will be closer to the truth."

[JP]

Not too happy about this conclusion. "if, however, temperatures are likely to rise by only 2°C in response to a doubling of carbon emissions (and if the likelihood of a 6°C increase is trivial), the calculation might change. Perhaps the world should seek to adjust to (rather than stop) the greenhouse-gas splurge. There is no point buying earthquake insurance if you do not live in an earthquake zone. In this case more adaptation rather than more mitigation might be the right policy at the margin. But that would be good advice only if these new estimates really were more reliable than the old ones. And different results come from different models."

That's a question of policy, not science, though and The Economist tends to be pragmatic about policy. 

[JP]

Mattew,

From what I understand of climate science, the confidence interval takes into account uncertainties in the model and predicts the results of measurements at different points in time (and potentially space).  Since any single measurement can't be predicted with certainty, the confidence interval simply says that X% of measurements should fall within this range if the model is correct.  Usually due to the law of large numbers, the confidence interval is a Gaussian distribution about the mean, and you can measure it in terms of # of standard deviation.  A measured data point that falls outside the 95% confidence interval would be only 5% likely to be due to random chance.  This might seem meaningful, but if you've taken 20 measurements, one of them is likely to fall there just due to random chance. 

Your example of a die is a bit tough, since the die is equally likely to come up 1-6, but you could always say that it will average a 3.5 with a 1/3 chance of being 3-4 and a 2/3 chance of being 2-5 (those would be your confidence intervals).  If you rolled a single 6, it wouldn't tell you much--only that it's outside the 66% confidence interval.  But if you rolled 20 6's in a row, then you could look at the data, find that such a result is incredibly unlikely, and start to question your model (maybe your die is loaded).

I'm not an expert on complex time-dependent processes, and haven't had to do any probabilistic analysis of them.  I assume the scientists developing climate models are experts and that they've rolled their model uncertainties as well as past measurements into the predictive powers of the model to correctly compute confidence intervals.  Then, like your die, you can count measurements and use statistics to quantify how likely your model is to be wrong based on those measurements.  (Remember, in science you don't prove a model correct--you can only say how consistent or inconsistent it is with data.)  I'm assuming climate scientists also do this, and that's what the article I linked hints at.  I haven't gone to the other analyses they speak of, but then I'm not the one trying to show that climate scientists are wrong. 

[JP]

I guess my take-home point is that it's insufficient to draw a line through existing data to "prove" your model.  That's not proof: that's developing a model to fit data.  "Proof" involves testing the model with new measurements that weren't already used to develop it in the first place!  More importantly, you can't prove a hypothesis, you can only disprove it, so most scientific advances happen when a new model is proposed and then scientists go out and collect data that disprove an existing model.  In the case of climate change, this would involve figuring out how likely our measurements of temperature are in light of existing models, and if they are exceedingly unlikely this would be grounds to accept a new model. 

I'm a physicist, and making the argument that the past decade disproves climate models is a bit like particle physicists taking a handful of measurement on the LHC and saying "we didn't see the Higgs, therefore it doesn't exist" without doing any statistical analysis of the results.  It turns out that if the Higgs existed, those measurements would be EXTREMELY LIKELY anyway because it shows up so rarely. 

Saying that the past decade "proves" cooling is like if I looked at those LHC measurements and came up with a theory for a JPoson particle that just happens to have the exact signatures of those measurements.  Of course it would 100% match those measurements by design so appealing to them as proof is absurd.  I'd have to make predictions (including confidence intervals) based on my theory and then gather more data before I could discuss how well it fits with data.

[yor_on]

Yeah, pragmatism cements. But we're getting a new climate, and we really should try to adapt. Although pragmatically seen, I don't either expect that to happen, ahem, which is why I don't (normally) bother writing about this any longer. I find us very stuck in our ways, human momentum, whatever A little like a big ship, meeting the opposite of a iceberg? ah well, we live in interesting times, and our offspring will live in even more interesting. I would give a great deal to be here in fifty years, cause I'm terribly curious about what we will say then.

Physics is easier

[yor_on]

And beautifully explained JP, you have a way of breaking it down into understandable words. And that's also why we need more data, we all want to know how well the models will fit the future, don't we? And to know it well, we need as many measurements over time we can get, at as many locations as is possible. So we really need those satellites, and we really need those weather stations, and we need them to monitor continually over those fifty years. But amazingly NASA don't get the money, and then we have Canada who don't seem to 'believe' in using weather stations anymore. A Canadian climate scientist wrote that to get a really good weather report today (a year or so ago) she had to tune in to American weather

Isn't that slightly weird?

and I have more examples of the same type of behavior. So yeah, considering it all, I can't help but wonder what our offspring's judgment will be of how we handled the situation.
'

[imatfaal]

Thanks JP. 

The more I read (and with your added explanation) the more errors I see in media presentation of facts.  And this is a problem - the science is robust and the scientific presentation correct, however the newspapers feel they have to simplify but then they lace the article and diagrams with buzzwords and jargon - often quite wrongly.  It is this that leads many honest (non-climate) scientists to look at the argument presented in the press and say "that's rubbish" - their error is to assume that the scientific argument presented in the journals suffers from the same problem.

With the Higg's / LHC in the press so much I spent some time reading up on the statistics that physicist used - and it blew my mind the complexity and subtlety of it; this is why I am on a course to start afresh from the very beginning.  I have no doubt that the climate scientists - who deal with a unimaginably complex system that is prototypically chaotic and  highly reliant on small variation initial conditions, and are under greater and harsher scrutiny than any other group of researchers - must use powerful and rigorously tested statistical methods.

I am sorry there will be no JPoson - I will certainly back your claim for precedence.  But as Peter Higgs and his colleagues postulated the breaking of electroweak symmetry before I (and I think you) were born, we might have a struggle convincing the rest of the world.  However I do know some pretty high ranking oilco executives  and if we can get them on board, well you never know - shamefully it has worked before in challenging and casting doubt on perfectly good scientific knowledge....

[MoreCarbonOK (OP)]

JP says
 (the cooling)  does appear to be a real effect , although it doesn't negate the fact that there is overwhelming evidence that greenhouse gasses, including CO2 do cause average temperatures to rise.

henry@jp

there is NO real evidence for this. Everything is based on what was presented 100 years or so ago,
i.e. the so-called closed box experiments. For example, there is the cooling effect of GHG's that has never been accounted for.
I have tried to explain this here:
http://blogs.24.com/henryp/2011/08/11/the-greenhouse-effect-and-the-principle-of-re-radiation-11-aug-2011/


CO2 also causes cooling by taking part in the life cycle. Plants and trees need both warmth and CO2 to grow – which is why you don’t see trees at high latitudes and – altitudes. It appears no one has any figures on how much this cooling effect might be. There is clear evidence that there has been a big increase in greenery on earth in the past 4 decades.

http://wattsupwiththat.com/2011/03/24/the-earths-biosphere-is-booming-data-suggests-that-co2-is-the-cause-part-2/

From all of this, you should have figured out by now that any study implying that the net effect of more CO2 in the atmosphere is that of warming, must exhibit a balance sheet in the right dimensions showing us exactly how much radiative warming and how much radiative cooling is caused by an increase of  0.01% of CO2  that occurred in the past 50 years in the atmosphere. It must also tell us the amount of cooling caused by the increase in photosynthesis that has occurred during the past 50 years.

There are no such results in any study, in the correct ranges, let alone in the right dimensions. For example, consider the fact that time must be in the dimensions (of the test results).

If you claim that more CO2 causes more warming rather than cooling, you have to come up with that balance sheet....

[JP]

Henry,

From what you keep posting, I can see two possibilities.  Either you don't understand the scientific method or you're trolling us.  In either case, there isn't much point in arguing your ideas on climate change, since this is a science forum and you're not discussing science. 

If you're posting in good faith and don't understand the scientific method, I've tried to explain it in the posts above.  You can also check out wikipedia articles on the scientific method and hypothesis testing as good places to start.  Though I'd recommend using their links to more rigorous sources to really understand the methodology of science.  That will give us good common ground to have a scientific debate on the matter.  Until then I won't be responding to your posts since you keep repeating the same arguments and ignoring science and this is a science forum.

If you're trolling, then obviously taking the bait would just give you more ground to post links to your blog (promoting your own blog, by the way, a major no-no on this forum). 

If others want to continue debating, that's their prerogative.

[MoreCarbonOK (OP)]

Henry@jp
I believe you are one of the intelligent people here on this blog and I am hoping to get your ideas straight so that ultimately we can get the whole of Europe thinking straight.
Please look at my tables here:
http://blogs.24.com/henryp/2013/02/21/henrys-pool-tables-on-global-warmingcooling/
(sorry for the reference but I don't know how to upload those tables here - anyway it is not like I am not advertising or selling anything)
If you take a careful look: these tables prove in a very simple way that there has been no warming due to the increase in CO2 or other GHG's.
Namely, if a manmade GH effect were real, we should see minima rising, pushing up means. Namely the GH effect theory (if you understand it) proposes that cooling (down of earth) becomes slower, as GHG % increases. Naturally, this should cause minima to rise faster. What I can see from the RATIO in my tables is that it was the maxima that were increasing (until around 1998-2000), pushing up means and minima at a ratio of about 6:3:1
So I have proven to you that there has been no manmade GH warming effect. The warming from 1973/4 was natural. Maximum temps. rising pushing up means.
Now, how and where is that not a logical procedure of investigation and where did I not use scientific method?
I  put it to you that you don't understand the scientific method or that you do not want to understand it.

[MoreCarbonOK (OP)]

henry@jp
I figure you got that story from the Economist just about right....you are so near and yet so far from the right track...
http://wattsupwiththat.com/2013/04/05/warming-and-worry-go-awol/
one step for one man
a whole step for Europe and humankind
for you to become a skeptic (of man made climate change)
like I did
5 years ago.
God will bless you if you keep following the Truth, and nothing but the truth.

[MoreCarbonOK (OP)]

here is something to think about

http://www.youtube.com/watch?feature=player_detailpage&v=_ZHI0INAHsc

[imatfaal]

MoreCarbonOK

This is a text-based forum and argument and points of interest should be made if at all possible in writing.  Unadorned videos and bare links to your blog are not in keeping with the spirit of the site as a Science Question and Answer Forum.  Many of the members will not have the time, inclination, or ability to view a 10+minute video by an unknown amateur commentator.

In future, links may be deleted and videos removed unless they are entirely pertinent to the discussion and the points they raise or refute could not have been made in a more traditional manner

Thanks

imatfaal - moderator

[MoreCarbonOK (OP)]

Everything I say or quote is clearly on topic and on target. There has been no "man made"  global warming for at least 16 years. Live with it. I wonder why you keep chasing away the real scientists on this site, i.e. those seeking the truth. Truth is important, you know. In fact your whole life (and after life) depends on it....

[damocles]

From your post #7:

I happen to be familiar with spectrophotometry. You have to understand what actually happens when we put a beam of light of certain wavelength on a sample of liquid or gas. We have various spectrophotometers that can measure the various ranges of UV-visible -IR etc. Usually you have the option to vary the wavelength of the beam of light, either manually or automatically. If the gas or liquid is completely transparent, we will measure 100% of the light that we put through the sample coming through on the other side. If there is “absorption” of light at that specific wavelength that we put through the sample, we only measure a certain % on the other side. The term “extinction” was originally used but later “absorption” was used to describe this phenomenon, meaning the light that we put on was somehow “absorbed”. I think this was a rather unfortunate description as it has caused a lot of confusion since. Many people think that what it means is that the light of that wavelength is continually “absorbed” by the molecules in the sample and converted to heat. If that were true, you would not be able to stop the meter at a certain wavelength without over-heating the sample, and eventually it should explode, if the sample is contained in a sealed container. Of the many measurements that I performed, this has never ever happened. Note that in the case of CO2, when measuring concentrations, we leave the wavelength always at 4.26 um. Because the “absorption” is so strong here, we can use it to compare and evaluate concentrations of CO2.

I was fairly sure that I had signed off from this forum and that I would have no further input, but this has really provoked me! Let me explain what really happens when light is absorbed:

• it is true that light energy is converted to heat energy, and in the case of CO₂ absorption at 4.25 µm this means an excitation of the O=C=O asymmetric stretch from the zero vibrational level to the first excited state vibrational level.

• This energy can be re-radiated, but the equation for rate of spontaneous emission goes as the inverse fourth power of the wavelength, which would mean a time of the order of seconds for the carbon dioxide to re-radiate.

• Is there an alternative? Well, yes there is. Our excited state molecule is suffering about 10⁹ collisions per second if in the gas phase or 10¹² "jostlings" per second if in the liquid phase. About 1 in 1000 of these interactions will be super-elastic -- that is, the excess vibrational energy of the carbon dioxide will be lost in the interaction and turn into translational energy of the solvent or other gases in the gas mixture.

• Once the excess energy is in the form of translational energy it will be conducted or convected away, eventually being transformed into heating of the cuvette and then of the laboratory generally. This is why you do not see your cuvettes warming and then exploding.

• In the atmosphere, and especially in the outer atmosphere, there are no "walls" and it is very likely that a stationary equilibrium will be set up, albeit at a slightly higher temperature, and this is what is being described when a respectable article talks about re-emission. You need to remember that in between the initial absorption and then re-emission, there will be a lot of nitrogen and oxygen molecules moving faster, and even being excited collisionally into vibrational states that can only be collisionally relaxed.

[yor_on]

Sweet explanation Damocles