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General Global Warming / Climate Change Discussion
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| midtskogen | Date: Saturday, 04.01.2014, 19:43 | Message # 106 |
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| Quote Watsisname (  ) Yes, it's called atmospheric chemistry.
Chemical experiments are mostly performed in a lab. The total effect, including indirect effects and feedback issues at an entirely different scale and environment in the real world may be different. Cf Svensmark's experiments, perhaps.
How shall we then explain Einbu's results in the 40's? Of course, we can be so sure about the chemistry that finding observations in agreement with theory must mean that there were no other variations in the observing period, but in that case the observations serve as no confirmation of theory at all.
Quote Watsisname ( ) Increase in high-latitude cloud coverage is not efficient at decreasing outgoing thermal radiation, because the surface temperature and cloud top temperature are at similarly cold temperature.
Sounds reasonable for much of Antarctica, but much less so for the Arctic. Expect typical midwinter temperatures for the North Pole to be in the -20 - -40C range, not much colder than the South Pole at midsummer. From the Atlantic side weather can cause thaw beyond 80 degree latitude in midwinter (7.7C has been measured at 78N in January).
Of course, the Arctic only makes up a small part of the Earth's total surface, but on the other hand, variation is much greater in the Arctic, so the contribution is much greater than the area would suggest.
NIL DIFFICILE VOLENTI
Edited by midtskogen - Saturday, 04.01.2014, 20:01 |
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| Watsisname | Date: Sunday, 05.01.2014, 04:39 | Message # 107 |
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| Midtskogen, I have to be frank with you here and say that you are speaking way outside of your depth and apparently not realizing it. I’d like to help you out, but you have to understand first what your limits of knowledge are so that you can then work to broaden them.
I am not interested in debating about CFCs with you, but I’ll be happy to help you find the resources so that you can educate yourself. Start by learning what Atmospheric Chemistry means and its central pillars of methodology. Then compare this with how scientists actually figured out the CFC-ozone matter, perhaps by reading the press release for the Nobel Prize awarded for this work. Then read some of their papers.
As to Einbu's results, I think you should first try to find a journal article of his work or someone who examines it; there could be useful insight there. The second thing to note is that there are many atmospheric processes that affect ozone concentration. You can find much research on processes that affect ozone column density on regional scales if you take the time to look. The unique radiative and atmospheric processes over Antarctica, leading to the Antarctic Ozone Hole, were what most influenced research in this field and the effect of CFC's. It is a very complex and fascinating sequence of events.
Quote Sounds reasonable for much of Antarctica, but much less so for the Arctic. Expect typical midwinter temperatures for the North Pole to be in the -20 - -40C range, not much colder than the South Pole at midsummer. From the Atlantic side weather can cause thaw beyond 80 degree latitude in midwinter (7.7C has been measured at 78N in January).
Sorry, you did not understand it correctly, or maybe I was unclear. If surface and cloud temperature are similar and cold, with respect to other latitudes, then covering more surface with cloud does not appreciably change the outward flux, and other effects end up being more important, in this case the negative optical depth feedback. This is of course a very simplified description and I left a lot of details out. I'm not writing a research paper here; I'm trying to explain why various cloud feedbacks are the way there are in a short and simple way. If you need sources, then here's one.
http://adsabs.harvard.edu/abs/2011AGUFMGC41A0778Z
Quote Of course, the Arctic only makes up a small part of the Earth's total surface, but on the other hand, variation is much greater in the Arctic, so the contribution is much greater than the area would suggest.
Variation of what? What is its role on global cloud feedbacks? Make sure you really know what you’re talking about, form a coherent thesis, and then see if the scientific literature says the same. What I have been describing with low-latitude convective clouds being the dominant contributor to global cloud feedback, and by extension, climate sensitivity, is verified in this Nature article, and I can cite dozens of previous papers which show the same.
I look forward to your next post, but try to critically review your ideas before presenting them.
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| midtskogen | Date: Sunday, 05.01.2014, 21:35 | Message # 108 |
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| Quote Watsisname ( ) As to Einbu's results, I think you should first try to find a journal article of his work or someone who examines it; there could be useful insight there.
One of the links that I gave gives an easy-to-read yet nuanced presentation, but in Norwegian. The chemistry is well understood, yet it points out that the Arctic natural variation is large. So who's that guy openly saying that we know there is natural variation in the Arctic likely more rapid than the changes caused by humans, supplying nuances as fuel to sceptics? Surely in the pocket of Big Fridge drawing spiritual inspiration from the tobacco industry? You decide. And Einbu? He was a teacher, otherwise fully self-learned. Yet he was an extremly diligent observer, which was early recognised earning him state pay for the rest of his career. There is little reason to doubt what he observed. Any errors would rather be in the interpretation of his data.
Note that I'm not discussing with you whether CFC affects the atmosphere or not, but whether the natural variation significantly affects what we observe. If different assessments of natural variation causes the time to doom to vary by a factor of 2, from a political point of view, it doesn't matter much. Action is needed anyway. However, in my book it matters a great deal in science. We don't like inaccuracies in science, nor half truths.
I'll turn the challenge back to you. If you were unaware of the low ozone level in the 40's, and of Einbu, dig up some papers on the topic, and perhaps you learn something.
Quote Watsisname ( ) maybe I was unclear.
Are you saying that circulation not changing overall global cloudiness, just where they appear, does not matter, or are you only saying that cloud change in the Arctic does not matter?
Quote Watsisname ( ) Variation of what?
I meant surface temperature. In winter clouds can quickly raise the surface temperature by 10 - 20C. You don't see that in the tropics.
NIL DIFFICILE VOLENTI
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| Watsisname | Date: Monday, 06.01.2014, 05:33 | Message # 109 |
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| When someone who actually studies the topic you're arguing about tells you that you do not understand it sufficiently, and provides you with methods for educating yourself so that an intelligent discussion can be had, then you should probably take that a little bit seriously. I know you are smart, and as I’ve said before I have a great deal of respect for you, but you do not understand atmospheric sciences, or how scientists figured this stuff out, well enough to make the kinds of arguments that you have been making. Again, I’d like to try to help you out, but you have to put in some effort yourself.
You made no indication that you did what I asked by learning about atmospheric chemistry and the methods by which scientists figured this stuff out. I would like for you to do so and then reflect on your statement "Chemical experiments are mostly performed in a lab. The total effect, including indirect effects and feedback issues at an entirely different scale and environment in the real world may be different." This statement is a extremely gross mischaracterization. It's effectively completely wrong. I would like for you to learn why. Put in the effort. 
Quote midtskogen ( ) I'll turn the challenge back to you. If you were unaware of the low ozone level in the 40's, and of Einbu, dig up some papers on the topic, and perhaps you learn something.
Data and re-analysis:
Source for above, including historical context, methodology, and analysis, with discussion of relevant atmospheric dynamics:
http://onlinelibrary.wiley.com/doi/10.1029/2003JD003963/abstract
Additional reference detailing these dynamics
And another.
Einbu & son's data are good, though calculated ozone column densities are systematically too low. But that’s not what is interesting, nor is the negative trend. It was a return to typical stratospheric ozone values for those locations. What is interesting is that the ozone levels at the start of the period are anomalously high; the highest in the whole interval, and this is established even in other northern-European datasets including records from previous years. These changes were due to a unique meteorological condition involving atmospheric flow patterns.
All you have found here is a case of regional variation due to understood atmospheric processes, just as I had previously suggested would be the case. This is why I suggested you do this kind of critical research yourself. Atmospheric scientists understand this stuff pretty well. They know that stratospheric ozone is not a constant. They understand the things that affect it. They also understand how CFCs affect it, and determined that it was a very serious problem that needed to be dealt with. This knowledge is extremely robust. It is time for you to accept this and to move on.
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Quote midtskogen ( ) Are you saying that circulation not changing overall global cloudiness, just where they appear, does not matter, or are you only saying that cloud change in the Arctic does not matter?
None of the above. I have no idea where you got any of those ideas; they're all incorrect.
Remember, your suggestion was “It makes we wonder if not the circulation part and regional variations need better understanding. Temperatures vary the most in polar regions. If cloud cover increases here, reflected incoming radiation will not increase much (winter darkness and high albedo in the first place), but it will decrease outward radiation and greatly influence winter temperature.”
I explained to you that the feedback from arctic clouds is negative, not positive as your reasoning would suggest. I gave you a source for this info. I then briefly described why the surface-cloud radiation balance is not an important factor here. In fact it is not important in any season. (Wang & Key, 2004). You should read this paper, it is a free-text.
The situation in the arctic is well understood and you are severely out of your depth in arguing about it. Atmospheric scientists are smart people. You seem to think that you’re coming up with ideas that they haven’t thought of or researched yet. They have.
Quote midtskogen ( ) I meant surface temperature. In winter clouds can quickly raise the surface temperature by 10 - 20C. You don't see that in the tropics.
Okay, now do what I asked and critically review your idea. Find a source for this information, with this source showing that it invalidates the information I have been providing you with on arctic or global cloud feedbacks.
Edit: Fixed incorrect links.
Edited by Watsisname - Monday, 06.01.2014, 05:57 |
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| midtskogen | Date: Monday, 06.01.2014, 22:42 | Message # 110 |
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| I think we're mutually beginning lose track here.
Lab vs real world: All I'm saying is that what you see in the calm lab might blow away in the real world, so you don't measure what you intend to measure. I'm not saying that chemistry of the laws of physics are different in a lab and in the big world.
Ozone and natural variation: I'm saying that natural variation, which is a part of the total that you measure, such as caused by atmospheric flows, seems to affect measured levels significantly. Then you go on pointing out meteorological events. Uhm, yes, exactly. I'm not arguing that chemistry and physical laws have natural variation, like two substances reacting one day, but not the next or another place or at another scale, or the speed of light undergoing an oscillating quasi-cycle, or the kind.
In most cases, when you do a measurement in the physical world, what you measure doesn't come with a memory which will give you a breakdown of all the contributions that affected the value that you read. You measure some total, not some long term average where natural variation is gone plus the human influence.
Quote Watsisname ( ) None of the above. I have no idea where you got any of those ideas; they're all incorrect.
Good. I was pondering that the distribution of clouds could affect the global radiation balance [in a measurable degree], assuming that some regions can act better as heat sinks than others. In which case changes in global cloudiness doesn't tell the full story. Where and whether positive or negative in the example doesn't really matter, but as a separate topic the effect in the Arctic is interesting nevertheless.
Thanks for the paper. It provided many numbers. It gives 10C as the cloud-top surface difference for the Arctic Ocean (I'm generally equalling the Arctic as the Arctic Ocean + coastlines unless otherwise stated, which I should be clearer about). I have been unable to find the global average for that as a comparison, though.
Before going on, an important clarification, saying that Arctic clouds have a negative feedback, fed back from what?
Not really related to this debate, Wang & Key had some interesting cloud cover data showing the seasonal variation, and ten years ago I built some simple instruments to determine cloud cover. One is a light meter which determines whether there is sunshine or not when the sun is above the horizon based on whether the light is above a threshold defined by the sun's altitude. The other is a crude device measuring the outward radiation, simply a well ventilated accurate thermometer next to a similar thermometer in a closed box and I assume that the outward radiation proportional to the temperature difference. It works surprisingly well for the purpose, though it tends to take very cold high altitude clouds as clear sky (but these conditions are rare).
Anyway, I now have ten years of data, and I hadn't thought of plotting the seasonal means for the entire period. Until now. So here goes:
Night time data for June are missing for obvious reasons. I should have averaged the night and day data, but to get the weighting correct due to the day length requires some work, so I didn't bother.
Like in Wang & Key, the least clouds are in spring.
NIL DIFFICILE VOLENTI
Edited by midtskogen - Monday, 06.01.2014, 22:45 |
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| Watsisname | Date: Monday, 06.01.2014, 23:57 | Message # 111 |
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| Quote midtskogen ( ) Lab vs real world: All I'm saying is that what you see in the calm lab might blow away in the real world, so you don't measure what you intend to measure. I'm not saying that chemistry of the laws of physics are different in a lab and in the big world.
List and describe the three pillars of methodology of the field of atmospheric chemistry.
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| midtskogen | Date: Tuesday, 07.01.2014, 06:52 | Message # 112 |
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| Quote Watsisname ( ) List and describe the three pillars of methodology of the field of atmospheric chemistry.
I can't know if there's something very specific that you have in mind - there are a few ways to cut this, but my recipe for methodology would be: First you obviously need to do some observations and measurements in the big world to know what you're dealing with. That knowledge you take to the lab where you can study the fundamental processes in detail and in a controlled environment. Then you generalise, i.e. do your math and make your models. Now you must test your modelling by more observation, and repeat the process as needed. That's 4 + 2n steps, where n is the number of extra iterations before you're happy, but we can speak of three distinct actions: observation, experimentation and generalisation (if we chose to exclude iteration as a separate action, though it's important, but you wanted three). This is quite common for all disciplines. You do observation while you experiment too, so the two first blend. Insisting on "trice slice" we can also say: observation (either lab or field), generalisation, iteration. The beginning is quite inductive, opposed to deductive, Newton vs Decartes. The former: "In [experimentali] philosophia propositiones deducuntur ex phænomenis, & redduntur generales per inductionem". It's over 20 years since I studies philosophy and scientific methodology as separate subjects, so I should probably stop there with the historical context. I recognise the value of both top-down and bottom-up approaches; I believe in intuition, but stronger in observation.
EDITS: Various minor refinements. I tend to post without much polish and edit iteratively, especially in the morning whilst getting three kids ready for kindergarten/school in case I can't get back to post.
NIL DIFFICILE VOLENTI
Edited by midtskogen - Tuesday, 07.01.2014, 11:47 |
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| Watsisname | Date: Thursday, 09.01.2014, 03:26 | Message # 113 |
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| Excellent job, you clued in on all three pillars. Put simply, they are:
-laboratory experimentation
-modelling
-observation
There is a strong interplay between these.
Laboratory experiments are used to study the chemical processes of interest under controlled conditions and determine their reaction rates. Models take in this information and use it to simulate what happens in the real atmosphere. To do this requires interdisciplinary knowledge from fields such as atmospheric physics, dynamics, biology, geology, and climate. Observation is used to verify if the models are correctly representing reality, improve our understanding where they don't, and gain new insights for further research.
Now, with this understanding of methodology, let us reflect on your previous statements,
"Lab vs real world: All I'm saying is that what you see in the calm lab might blow away in the real world, so you don't measure what you intend to measure. I'm not saying that chemistry of the laws of physics are different in a lab and in the big world."
and
"Chemical experiments are mostly performed in a lab. The total effect, including indirect effects and feedback issues at an entirely different scale and environment in the real world may be different."
Are you able to see now the flaws in both of these statements?
P.S. I haven't forgotten about your earlier questions. We'll get to them but I thought resolving this issue first would help make for a more productive discussion as well as keeping posts from getting ridiculously long.
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| Trulskij | Date: Thursday, 09.01.2014, 04:04 | Message # 114 |
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| Lol i live in germany today was +15C sun and... at 8.01.2014 never saw snow in germany winter 2013/14 i mean wtf ^^ used only pullover to wear ^^ this is funny somehow (its Frankfurt Hessen)
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| Watsisname | Date: Thursday, 09.01.2014, 04:30 | Message # 115 |
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| That's good Unusual Weather thread material. 
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| midtskogen | Date: Thursday, 09.01.2014, 22:03 | Message # 116 |
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| Quote Watsisname ( ) -laboratory experimentation
-modelling
-observation
Ok, perfectly fine. Every discipline can cut the cake and label the pieces in ways that fit best.
Quote Watsisname ( ) Are you able to see now the flaws in both of these statements?
It would be simpler if you said in direct words what you think the flaws are rather than to ask to have your mind read.
We can likely agree on the part that laboratory experiments with oxygen, UV, CFC etc found in the atmosphere by observation, give a observational basis good enough to conclude by induction that the processes in the lab must also take place in the atmosphere, only also interacting with things that you didn't add in the lab. And we can agree on the part on atmospheric physics, dynamics, biology, geology and climate. It also means, however, that one single imperfection in the model of either atmospheric physics, dynamics, biology, geology or climate will affect your observation from which the conclusion is that either you did something wrong in the lab or more likely that one or more of you models of atmospheric physics, etc, have flaws or significant limitations but you don't even know which. You'll end up refining your models until you end up with something matching the observations, but since so many models are involved you can't really know independently whether they're perfect or you incorrectly "corrected" the wrong model so the errors happen to cancel each other out. To sum it up in one word: attribution.
I think all this boils down to how we view uncertainty and how the methodology should deal with it. Strict Newtonian methodology forbids you from making hypotheses: You make a lot of observations and either you have enough to make a theory which matches the observations without exceptions or you have nothing but bare observations. This is probably impossible to follow in practise, but approaching this methodology is a very good defence against confirmation bias, which appears to have become increasingly relevant in for instance climate science - in both camps but of course mainly in the other camp. Remember that before Newton science was mostly done through reason only and was indistinguishable from philosophy. It was believed that everything could be deduced and explained from reason alone. Which makes perfectly sense together with the concept of God's image, inherent knowledge, etc. When this methodology was abandoned around the 17th century and the focus shifted from reasoning to observation, science began making rapid progress. Now I fear that the respect for a proper scientific method might be in decline. That scientists have become so eager to publish before they have sufficient data, to publish what they have even if they're stuck. Quantity in scientific production has been allowed to compensate for quality. You'll find articles using "could" in their main conclusions, i.e. they're merely proposing a hypothesis, but is that good science? Which revolutionary articles in science used the world "could"? By all means, I think it is important to publish observations, but I fear that the additional hypothesising attracting more attention is a step back towards mediaeval methodology.
While you're likely to protest wildly against such criticism of methodology, I hope it can explain some of our differences. Feel free to explain why your standards of methodology are superior.
In the case of CFC, I think the lab experiments and the confirmation that CFC makes it to the upper atmosphere form a sufficient basis upon which to make political decisions unless there are any known significant and uncertain feedback mechanisms at play.
NIL DIFFICILE VOLENTI
Edited by midtskogen - Thursday, 09.01.2014, 22:05 |
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| Watsisname | Date: Friday, 10.01.2014, 02:19 | Message # 117 |
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| Quote midtskogen ( ) It would be simpler if you said in direct words what you think the flaws are rather than to ask to have your mind read.
You do not have to read anyone's mind, you just have to read the text and use some critical reasoning. If you have difficulty grasping it, then by all means ask for additional help.
Your comments portray knowledge in atmospheric chemistry as being determined by laboratory experiment, such that the results may be invalid when applied to the real atmosphere with its formidable complexity. The flaw is that this is not how the field works.
Atmospheric chemists know that in order to understand how chemical processes work in the atmosphere, an understanding of how the atmosphere and associated systems work and interrelate is prerequisite. Thus, this is a major component of methodology, drawing upon interdisciplinary knowledge to form models. These models simulate the atmospheric dynamics, sources and sinks of chemical species, their transport, their reactions, etc. Laboratory experiment is used to determine those reactions and their rates, so that models can determine how the chemical processes unfold in reality.
Has this information helped you?
Quote You'll end up refining your models until you end up with something matching the observations, but since so many models are involved you can't really know independently whether they're perfect or you incorrectly "corrected" the wrong model so the errors happen to cancel each other out. To sum it up in one word: attribution.
This would be a reasonable critique if there were a severe lack of understanding of the components being studied, the interdisciplinary knowledge thereof, and an inability to validate them. Absolutely no. Your reasoning is equally applicable to other fields of science such as meteorology (or atmospheric dynamics in general), geology, cosmology, and astrophysics. You could argue that our understanding of stellar structure is flawed by the same approach.
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| midtskogen | Date: Friday, 10.01.2014, 09:58 | Message # 118 |
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| Quote Watsisname ( ) Your comments portray knowledge in atmospheric chemistry as being determined by laboratory experimen
Not only. We know better that the sun emits UV from field observation than lab experiments, for instance.
Quote Watsisname ( ) such that the results may be invalid when applied to the real atmosphere with its formidable complexity
The lab results are not being invalidated by that complexity. It's rather the question whether we are really validating (or invalidating) the lab results accurately.
The attribution problem increases with the complexity and variability. The variability can be addressed by observing patiently. Don't you think future scientists will rather find our observations more valuable than our current conclusions based on what will appear as a snapshot of the longer term variation? We can't always model our way out of a lack of observations catching long term variability, since we can't feed model output back to itself for verification. You say that we have all attributing factors under firm control (in which case generalisation is fine), I say let's still make observations.
Quote Watsisname ( ) Your reasoning is equally applicable to other fields of science
Absolutely!
Quote Watsisname ( ) You could argue that our understanding of stellar structure is flawed by the same approach
"Flawed" might not be the right word, or all understanding will be flawed owing to the falsiability criterion. The attribution problem exists everywhere, even in your lab. How big the problem is varies.
What happened to the Arctic clouds and their effects on temperature/radiation balance?
NIL DIFFICILE VOLENTI
Edited by midtskogen - Friday, 10.01.2014, 10:12 |
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| Watsisname | Date: Sunday, 12.01.2014, 05:58 | Message # 119 |
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| I am sorry, but you are not grasping the conversation properly; you are responding by quote fragment and missing the context.
This is the first argument you presented:
(a) Conclusions in atmospheric chemistry are mostly based on lab experiment. These conclusions may be incorrect when applied to the real atmosphere.
This argument is based on a severe misconception and I would like for you to understand what it is. I've explained it for you, and instead of acknowledging the error, you have modified the argument to this:
(b) There is an attribution problem. So many models are involved that we can't independently verify if models produce observed behavior because they are actually correct or not.
This is a new and equally severe misconception. The flaw is that the argument assumes that validation is only done, or able to be done, between real-world observation and the final model output. This assumption is wrong. Validation is done on all of the components and intermediary steps of the process.
The root cause of the flaws in your arguments so far has been an inadequate understanding or familiarity with the field being discussed. The sooner you can recognize this, the sooner this conversation can proceed to more interesting topics, or return to the questions on cloud feedbacks that you have posted. I am hopeful that we can do this, and I am willing to continue helping you or provide additional reading material when needed.
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| midtskogen | Date: Monday, 03.02.2014, 13:42 | Message # 120 |
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| Quote Watsisname ( ) Conclusions in atmospheric chemistry are mostly based on lab experiment. These conclusions may be incorrect when applied to the real atmosphere.
I've already tried to explain to you that I haven't said that. On the contrary I wrote things like "the lab results are not being invalidated by that complexity".
Quote Watsisname ( ) The flaw is that the argument assumes that validation is only done, or able to be done, between real-world observation and the final model output. This assumption is wrong. Validation is done on all of the components and intermediary steps of the process.
It sounds like you've solved the attribution problem! I look forward to read the paper. By what year and month will the ozone layer have fully recovered? Seriously, I have no problems grasping the idea that you can address the attribution problem by looking for "fingerprints". One cause often have several effects, and these can independently be quantified in controlled experiments extended to models, and in the end, unless you end up with an endless cascade of variables that you have to take into consideration, your equation might add up. This really just strengthens my mantra: observations, observations and observations. In the case of ozone, the case should be obvious. Few observations existed in the 80's and still we could wish for more data.
EDIT: Something relevant for my general comments previously on publishing too much too soon: In the age of speed science (try Google translate), referring I wouldn't be productive enough. and Why most published research findings are wrong (a potentially self-prophetic title for a published research paper...?) (rebuttal).Added (03.02.2014, 16:42)
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Shortly after the last time the AMO peaked: Scientists believe that the melting of ice in the polar regions indicate a radical change in climatic conditions.
NIL DIFFICILE VOLENTI
Edited by midtskogen - Monday, 13.01.2014, 06:58 |
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