It looks like I’m going to blog the Heartland ICCC conference! With this in mind, I’m going to try to practice using my camera for video so I can capture interviews and post them on YouTube. If nothing else, we’ll hear everyone’s accent. (I have an unlovely nasal midwestern chicago area accent. )
So, with this in mind, I’m inviting people to suggest questions I can ask. Rules for questions:
- The questions must be questions. I don’t want long winded talking points masquerading as questions. We can leave that to US Senators ‘questioning’ people during Senate hearings.
- The questions should avoid being obviously argumentative. I’m not planning to ask any “What would it take to make you you stop beating your wife”, type questions.
- Trivial is ok. Neven wants to know how many people are less than 50 years old. I can ask that.
Ideally, I’d like to have 5 basic questions for everyone I corner and 5 alternate questions. I’m sure all of you can suggest questions, and I can make a nice list. You can also suggest which 5 people I should try hardest to corner. (I know. Everyone will want me to interview Monckton! We’ll see if he’s game.)
How ’bout give 5 best reasons why AGW is a fraud? Should be good for the Learned Lord Monckton.
My list:
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1. Do you agree that increasing GHG concentration in the atmosphere must cause some (even if modest) increase in average surface temperature?
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2. Do you think that publicly funded research on climate models is a worthwhile activity, or should public funding for modeling be stopped?
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3. Independent of global warming, would it be prudent to reduce consumption of petroleum and natural gas to conserve these resources so that they are available for more valuable future use than combustion (petrochemical feed stocks, etc.)?
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4. Many well known climate scientists support immediate public action to reduce CO2 emissions. Do you think this is the case due to the political/philosophical views held by those scientists, due to their understanding of the Earths climate, or perhaps both?
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5. Do you believe that a ‘grand compromise’ is possible in public policy related to global warming? For example, rapid and large increases in the use of nuclear power linked to taxes levied on CO2 emissions?
Here are three:
1. What would improve the vetting of scientific research publications?
2. What can be done to build a wall of separation between Science and Politics?
3. What is your opinion of the Precautionary Principle?
List of people to talk with:
Anthony Watts
Steve M
Spencer
Any other climate scientists who attend.
No pols.
Flash memory is cheap; 8 GB will give you about 2.5 hours of video capacity at very good resolution; but you’ll need spare batteries! A mini-tripod would also help.
Lots of good questions. Maybe I’ll have such a long list I have to pull questions out of a hat!
1) What should be done to improve the peer review process?
For Roy Spencer:
1) When will you complete your latest research and submit for publication?
2) When will the daily satellite data website be updated for inclusion of AQUA TLT so we don’t have to guess each month? 🙂
1. Do you think humans can control the natural climate and on what scale?
2. Where do you think the temperature is being accurately measured and truthfully recorded and reported?
3. If you could summarize the state of climate science generally in one sentence, what would that sentence be?
4. Who in the climate science community should we “trust”?
5. Why are the Cubs Such Losers? 😉
Andrew
1. As I said before I want to know if Douglass ever checks his email. He doesn’t seem to be presenting (He did in New York, but he isn’t on the speaker list this time)-but if anyone happens to see him…
2. Ask them if they think that climate is predictable in principle over a period of say thirty years. This has got to be asked right because there is a difference between this question as regards principle and practice. Mainly what I want to know is who thinks that the “unpredictable”-chaotic-factors matter in the long term and who thinks that climate is pseudo-deterministic.
3. Has the community become more or less tolerant of your views over time, in your opinion?
4. What can/should be done make research more “open” in light of climategate?
5. What areas of research are the most important to focus on to improve our understanding of climate?
DG (Comment#40062)-You might still end up guessing, UAH has now added in NOAA-18.
Lord Monkton – should climate science be proved faulty, what repercussions do you expect for the manufacturers of waterproof underblankets? Isn’t it true your whole campaign is funded and orchestrated by the global mattress manufacturers association? Can you cite ANY peer reviewed studies showing correlation of nighttime incontinence and obfuscation? Who funded the studies? Isn’t this the same organisation that has been blocking the talking pillow community from accessing bedtime reading lists?…. or something like that! Have fun…. 🙂
Ones for everyone could be:
1) what do you consider the most appropriate metrics for evaluating global climate and why?
2) using those metrics on 100year timescales what bounds do you think global climate would lie between without man made “greenhouse gas” emmissions? and on 500year timescales? and then with mmgge?
3!) what shortcomings would you like to see improved in the evaluation of your chosen metrics?
4) how confident are you you’ll hold the same views on climate in 5 years time? 10 years time?
5!) how does that effect your outlook on future funding, policy and practice of climate research?
1.) Do you accept or reject the proposition that the earth is currently warming?
2.) Do you agree that the urban heat island effect is evidence that humans can change their local climate?
Unfortunately, those are closed questions. 🙁 I will try to think of some more open ones.
3.) What do you think is the most plausible explanation for the insistence by some scientists that the earth’s climate is warming due to CO2 emissions from human activity, that this warming will continue and that this warming will in general have negative consequences?
A bit convoluted, and maybe SteveF’s question above covered it better.
1) For Roy Spencer: What would the trend be if you adjusted for Pinatubo and El Chichon?
2) For Anthony Watts: How does the USHCN v2 homoginization algorithm work?
… and for the old guys…drum roll please…
3) Is that a wig or Rogaine?
4) Is that a bottle of viagra in your pocket or are you just glad to see me?
5) When a preetty gorl walks down the street, does your pacemaker open the garrage door?
1. If you could implement one policy mechanism today to help strengthen our environment, what would it be?
2. Do you see any chance of adopting policies with pay-offs that stretch beyond the political lifespans of those in office?
3. What areas do you see as offering the greatest chance for cooperation between those holding differing views on climate change?
4. What type of climate conversation do you think you will be having in five years? 10?
5. Considering the level of rhetoric involved in the climate debate, how relevant is what you hear to you personally? Do you eat it all up? Tune it out? How made up is your mind on these issues?
Can the noise be removed from the temperature record sufficiently to make confident observations?
Has AGW become primarily a social movement using a veneer of science to advance its agendas?
Has the climate behavior of the last ~100 years been markedly different from other periods, and with what confidence can this be answered?
How much opportunity cost has focus on CO2 as a means of controlling the climate imposed on the world?
What can be done to destroy the global carbon market?
the only question needed:
Please summarise your paper in 1 haiku.
1. Since the earth-ocean-atmosphere system can only lose
significant energy through longwave radiation, is some
energy gain inevitable?
2. Given that AGW theory is based on gases emitting from
the stratosphere at a temperature lower than the surface,
do places which experience surface temperatures which
are colder than the stratosphere ( Antarctica and Greenland in winter ) mean cooling in those areas?
3. What is the significance of the failure to verify of the
tropical upper tropospheric ‘hot spot’?
4. Is the steepening of the water vapor lapse rate from the
reanalysis data valid? Does this mean a negative water vapor feedback?
5. Why isn’t more made of the fact that thirty year trends
in all global data sets (SST, surface index, satellite) are all below the IPCC best estimate for a ‘Low Scenario’?
For Dr. Spencer:
1. When will the code you use to process satellite data for UAH temperature anomalies be placed in the public domain?
2. When will the data and source code NASA uses to artificially create Aqua MASU Channel 4 readings be placed in the public domain?
3. What are the scan depths for each footprint for channel 5 on the Aqua satellite? (Alternately, where is this information made available to the public).
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For any scientific figure there:
1. Do you support placing in the public domain all raw data and computer source code used to produce scientific papers ?
2. What is your favorite color? (just to bring the question total up to 5).
Sorry, typo. Question 2 for Dr. Spencer should be:
.
2. When will the data and source code NASA uses to artificially create Aqua AMSU Channel 4 readings be placed in the public domain?
1. What is your best guess for May UAH Temperature Anomaly?
2. Have you ever used Grecian formula?
3. What is your best guess for Arctic ice minimum this summer?
4. What years/procedures should be used to calculate global temperature anomalies?
5. What’s for lunch?
If all the external long-term variable factors were constant: no more anthropogenic CO2, constant land use, no major volcanic eruptions, Solar cycle exactly 22y with constant amplitude, no asteroid impacts, no precession etc. – would that lead to a stationary climate on Earth? If not, what kind of changes (timescales, amplitudes) one could expect?
Is it a good idea to become more dependent on weather (e.g. wind power) in the hope of limiting climate change?
Q: Would you reduce speed when driving in a snowstorm? Why (not)?
@ Bart Verheggen (Comment#40097)
Why do you ask? Are snowstorms steadily increasing over time? How much taxpayer money should we spend mitigating snowstorms?
ClimateWatcher (Comment#40081) April 6th, 2010 at 9:06 pm
No, otherwise you will be breaking the laws of thermodynamics.*
* There being no ‘forcings’ changing the state of the climate.
Sera (Comment#40100) April 7th, 2010 at 4:30 am
You missed his point entirely.
@ bugs (Comment#40102)
Lucia made three rules- Bart missed #2, entirely.
Bart is trying to pretend the conference is a waste of time and does not have the professionalism to resist a dig or three.
Yet it is the AGW promotion events, like Rio, Kyoto, Bali and Copenhagen, etc. etc. etc. etc. that require huge public support receive great hype and accomplish nothing.
Question: What do you think the chances are that the increase in CO2 is due to human influences?
The reason I’m curious: I’m always surprised when I see Pielke Sr., Spencer, Watts, Id, and a number of other luminaries all either state or host musings about other possible sources of the CO2 rise on their sites, when the source of the majority of the recent rise in CO2 is about as well understood as the fact that the earth revolves around the sun because of gravity. So, I’d like to know if these people are just musing about alternate, weird explanations for well known phenomena because they think its fun, but they don’t really believe that its plausible… or, are they so skeptical about anything to do with AGW that they’ve blinded themselves to reality.
I think Bart’s point was: would you be more cautious when conditions warrent it. the follow-up would be do you believe the current warming warrents caution?
Is there or is there not a such a thing as a greenhouse effect. I’m betting a sizable proportion of the people attending won’t think there is.
Tim W:
Which then leads to, if you accept the need for caution, what policy path would you recommend for amelioration? (adaptation, reduction in dependence on fossil fuels, government control of emissions).
For many on both sides, this is as much a referendum on socialism versus free market solutions as it is on climate science.
Mainstream reporters should be interesting subjects, and in this post November 17 (19?), 2009 era there may be more of them than in prior years.
1) China is building a coal-fired electrictity generating plant weekly. Should we start a trade war, or if it should be the ordinary kind of war, nuclear or conventional weapons?
2) (Followup) Since China is building so many plants, and by buying so many coal reserves globally indicating that they will not go Green, why should slow-growth developed nations concern themselves with CO2?
3) On April 8, 2010, the UK voted to approve/reject the World Bank loan to build a coal fired electricity generating facility in South Africa. The decision was highly controversial, with Greens opposed and the World Bank claiming southern Africa desperately needed the electricity. What is your position?
4) Have recent revelations about temperature proxy reconstructions, such as in The Hockey Stick Illusion, changed your mind about whether or not current temperatures are unprecedented?
5) My allergies are horrendous this morning, and if I am alive after lunch I will try for questions which don’t break the rules, Sera. 😉
Marcus (Comment#40107)-To my knowledge Roger has never said or given space to any such claims. Where exactly do you get that from?
[quote bugs (Comment#40109) April 7th, 2010 at 7:33 am]
Is there or is there not a such a thing as a greenhouse effect. I’m betting a sizable proportion of the people attending won’t think there is.
[/quote]
I don’t think you’ll find too many skeptics who doubt there’s a greenhouse effect, Bugs.
.
It’s the magnitude, and even the sign, of that effect as concentrations of greenhouse gasses change that’s the question.
bugs-
How many quatloos do you want to bet?
Or would you like something more interesting/ Perhaps a charity to receive a donation?
If Bart’s question is interpretted as a question about caution, would the answer not depend entirely on the quality of the storm and the road involved?
1) What do you think of Demetris Koutsoyiannis’ notion that climate is inherently uncertain and thus not reducible to a set of identifiable exogenous causes no matter the detail or quality of such information?
2) What areas of emerging research are most likely to impact understanding of climate in the next decade?
3) If you could be any kind of tree, what would you think of the whole Ricky Martin thing?
If you believed it was going to snow would you.
a. drive faster.
b. use a snowmobile instead.
c. study why it snows and spends years and countless dollars
trying to write a global treaty with people who dont live in the snow to prevent future snowstorms that your grandkids might
encounter.
d. tell scary blizzard stories to children
e. Make up silly analogies
f. Call people who questioned your forecast evil.
g. Invest in technology to clear roads of snow.
h. Sell igloo making devices.
i. buy a dog sled.
j: be happy for polar bears.
Analogies are always frames. Frames get you to focus your attention on the details the framer is interested in, while ignoring other details. It’s the highest form of scientific dishonesty. When you see a scientist use a frame, understand that he is trying to practice rhetoric. Typically, he is not trained in rhetoric. Typically he is trained in avoiding metaphorical thought. For the most part scientists make bad marketeers, bad rhetoricians, and lousy poets. bart is no exception. he should start with Haiku. Its easy, just count syllables.
But to return to Bart’s question:
Q: Would you reduce speed when driving in a snowstorm? Why (not)?
Well, How fast do you assume that I am driving? has the road been cleared? am I on the way to the emergency room? what’s the exact visibility, how far do I have to go? Do I have chains on? is it just snow or ice and snow. But, generally, depending on the conditions, one would slow down from a normal speed, as conditions warrant. Now, this is based on our individual experience and expertise in driving. And we can point to a clear history of what happens when people dont slow down. So, the question ( which is a frame ) really Smuggles in assumptions. The assumption is that we know the cost of changing our driving speed and we know the cost of NOT changing it. In Global warming, none of us have much experience with the effects of global warming, why? because it’s argued that the warming is unprecedented. The other thing the analogy smuggles in is a “free lunch” There is no real cost to slowing down. And the last thing it smuggles in is the idea the driver is saving himself. In global warming, its largely a question of international and intergenerational transfers. So basically, people should just be aware that ANY frame that personalizes the situation ( its like buying insurance ) ANY frame that compares Global warming to a situation faced by individuals is a false frame. People engage in these false frames because they dont want to ask the questions directly. Like so:
1. In a world of warmer temperatures and rising sea levels and increased hurricanes, the future citizens of New Orleans will
face some environmental challenges.
A. What can and should the people living there today do
to make a kinder future for the people who choose to live
there?
B. What can and should the people living in the US do to
help their fellow citizens prepare for this potential
hazard
C. What can and should we ask the rest of the world to do?
You don’t even have to believe in global warming to answer such questions. What most people miss is that at the FOUNDING of the IPCC the frame of “global action” was forced on the problem.
And that precondition actually stalls effective local action.
And now, while driving in the snow, the people telling scary blizzard stories have not slowed down themselves ( see Al gores energy consumption ) They have rather tried to negotiate treaties to get everyone to agree to slow down.
Andrew_FL, Marcus is correct that Pielke has reviewed articles on the sources of the atmospheric CO2.
However, part of the CO2 in the atmosphere is in response to the previous temperature rise (CO2 as a feedback rather than a forcing), part is due to changes in land usages and so forth.
Anyway I think we probably understand the inverse square law of gravity to a few more decimal places (according to these guys, we know it to a few parts in 10^7 over Earth-size dimensions) than we do climate.
There’s a lot that hasn’t been fully fleshed out wrt the carbon cycle. There are missing carbon sinks for example. People can get back to us with lectures on how well the climate science is nailed when they can do “simple things” like balance the carbon sources and sinks.
Re: steven mosher (Apr 7 10:57),
I think you just showed why questions like the one Bart suggested are to be avoid. If I do ask people whether they would reduce speed when driving in a snowstorm, I’ll probably get answers like, “Whoa! Snow in Chicago on May 20? Let’s all go look!” or “If it’s a bright sunny clear day, would you drive at 20mph on the Ryan just because the weatherman predicted snow?”
The second sort of response could trigger a battle of stupid ‘rhetorical’ questions. People asking these rhetorical questions always seem to think the question itself makes some obvious point they think everyone should believe, but rhetorical questions almost never make the point the questioner thinks they make.
With respect to Bart’s blizzard question: No one disagrees we should drive cautiously during a blizzard, or that it’s advantageous to equip your car with snow tires icy, blizzard prone areas. But if we try to force the discussion of global warming into the frame of driving during a blizzard, we’ll soon be arguing about whether Bart’s metaphor is suggesting that everyone in El Salvador needs to use snow tires just in case. ‘Cuz you can never be tooooo cautious! And snow tires are free– right?
The whole discussion just becomes confusing and stupid.
I’m going to be going through these, adding clarifying words, and picking the ones that seem of greatest general interest. I kind of hope Lindzen is there. That would be fun.
[quote steven mosher (Comment#40124) April 7th, 2010 at 10:57 am]
And now, while driving in the snow, the people telling scary blizzard stories have not slowed down themselves ( see Al gores energy consumption ) They have rather tried to negotiate treaties to get everyone to agree to slow down.
[/quote]
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You are correct, of course, but I don’t think this captures the scope of the problem.
.
The real concern with so-called “the precautionary principle” is that the precautions are worse than the danger they attempt to solve. See this video for an example: http://www.youtube.com/watch?v=d24b56MmIts
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Additionally, the dangers from these “precautions” are demonstrable, as that video shows, whereas the dangers from CO2 are not.
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So forget analogies. If you see dozens of species being wiped out in a generation, would you try to stop it?
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Because that’s what’s happening now. And organizations like the UN are promoting the cause of the slaughter.
Bart’s question is the ultimate question, just look at Mosher’s detailed reply running off beyond the weeds and down the scree slope…
My answer to Bart’s question is to turn on my headlamps and be more observant and respond to the changing conditions as needed. Most highways are designed to allow for speed limit driving in snow and rain. If the snow continues to build up on the roadway, then a gradual decline in speed is warranted. The last thing I would do is slam the brake to the point of causing a backup and potential rear-ending chain reaction.
* Where can I find a Unit Root?
* Whoz VS?
* Wherez the toilet?
Q: Would you reduce speed when driving in a snowstorm? Why (not)?
Answer: use snow tires and watch out for straw men.
Would you mind operating my camera so I can get in the video too?
Bob-
How do I operate your camera?
Bart,
I don’t drive so the question is irrelevant!
Lucia,
You wanted questions YOU could ask. That question is meant to be quoted exactly by you.
Bob—
Yes. But how do I use your camera? Are you offering to lend it? That’s what’s confusing me. (Right now, I plan to bring my camera, which has video ability… but small!)
Lucia: I believe that Bob is saying that you should ask person X at the conference “please take my camera and video tape me with it”, where “my camera” means “Lucia’s camera” and “me” means “Lucia”.
Andrew_Fl: http://pielkeclimatesci.wordpress.com/2010/03/25/guest-post-a-simple-tool-to-detect-co2-background-levels-by-francis-massen/
Carrick: Well, I meant to include the word “mostly” in my original question, don’t know how it dropped out. Yes, a few ppm of the 100 ppm or so of CO2 increase is a result of increased ocean temperatures. A larger percentage can be attributed to land use change. There is uncertainty about the exact allocation of carbon sinks geographically. Having said that: I would say, with 100% certainty, that the dominant cause of the recent CO2 increase is fossil fuel burning (and to a lesser extent, other human influences).
Honestly, we don’t have gravity nailed down yet either (how goes gravity wave detection? General relativity-quantum reconciliation? Do we even know if gravitons exist?), and yet no one goes around musing that since we don’t understand everything about gravity that we can’t attribute certain things like orbits to it. Why aren’t the anthropogenic CO2 doubters that seem to be all over the place wandering about doubting gravity?
-Marcus
Carrick (Comment#40126)-I was think more along the lines of any instance suggesting that the rise in CO2 is anything but almost entirely man made. In fact, I’m sure he has specifically said he believes the evidence that the CO2 increase is man made is very strong.
To everyone-what would I do in a snow storm? Well, given that I 1. Don’t drive and 2. Have never been in a snow storm, I probably wouldn’t know what to do. However the AGW situation is more along the lines of seeing storm clouds and hearing your TV Meteorologist going on overly enthusiastically that white stuff is going to fall like crazy ANY SECOND! But it isn’t snowing now so you’re driving home and maybe it’s coming down a little by the time you get there, so anticipating tomorrow’s drive you put on your snow tires and check that you have enough food etc. stocked up in case you get stuck in your house.
Marcus (Comment#40175)-Huh? All I see is a post about determining CO2 levels. I see nothing saying that the increase that’s been measured isn’t man-made. Did you just read “Ernst Beck” and pop a vein?
Lucia, yes the discussion becomes confusing and stupid. Metaphors or frames are supposed to take us from the known to the unknown, that is they are supposed to help us navigate unfamiliar territory by appealing to things we “all” understand. It’s also their weakness, because they can often go awry and miss salient aspects of the unknown.
magic java,
yes when I first read the PP my reaction was .. Pascal’s wager
how utterly quaint. What most people don’t realize is that the arguments we are having today are all simple recapitulations of arguments we have had for a very long time. Nothing much new under the sun.
Marcus, you specified gravity and the Earth around the Sun. Quite obviously this is well known and understood compared to climate, where 50% errors are common and predictions that fall outside of the 95% CI are considered acceptable.
Gravity waves, certainly a “moving target here, are a second order effect… parts in 10^15 and smaller. You just wish there was something in climate that was so precisely “not measured.” And quantum gravity is second order in G/m_p c^2 (m_p = mass of the proton), which works out to a (10^-38)^2 effect.
Does Marcus suffer from physics envy?
magic java and mosh,
I think the PP pushers need to learn something from the medical profession: http://en.wikipedia.org/wiki/Primum_non_nocere
@ Don B (Comment#40116)
The pollen count has me in tears right now- I guess that makes us brothers in arms…
@ George Tobin (Comment#40123)
I agree with all of these.
Barts’ question was a ‘loaded’ question- forcing the subject to answer a specific way, which then leads to the ‘gotcha’. The correct answer to his question is one that he will likely not approve of: Adapt. If Bart is a smart guy (and I’m betting he is), then he will return with a good/solid/short question for Lucia to ask. And no one loses face.
FWIW- I could only come up with three.
steven mosher (Comment#40184) April 7th, 2010 at 10:06 pm
There is one significant difference between PP and Pascal, with Pascal, there is no evidence for god, it is purely a matter of chance. With AGW there are copious amounts of evidence, based on scientific research. Apples Oranges.
Should I laugh, or cry?
Is their actually any physical real world evidence of any human signature in the climate, now and the last 50 years
Is there any evidence that anything occuring in the climate now and the past 50 years cannot be explained by natural variability.
is it not entriely possible that the human race is panicking because it got warm over a period of time, and is merely extrapolating it linearlly into the future ever higher so that the planets fries..
Just following, a period of panicking as the planet cooled, extrapolating ‘cooling’ predicting a new ice age (1970’s)
Are we condemned as a race to repeat this cycle, like so many disciples of canutes.. (if only King Canute, had made his courtiers stand on the shoreline, whilst he stood high and dry, commanding the sea – to make his point to the sycophants)
AGW is a popular delusion, no conspiracies required.
The carbon credit/tax economy is as doomed as the ‘tulip’ economies, and the ‘south sea’ bubble.. History lessons should be compulsary for all economists/scientists/polticians..
‘Popular delusions and the madness of crowds’ published 1841 – shows us nothing new under the sun, with repect to inteligent peoples cababilities to delude themselves.
http://en.wikipedia.org/wiki/Extraordinary_Popular_Delusions_and_the_Madness_of_Crowds
Has the ‘AGW consensus’ been created via groupthink?
Agw theory would appear to ALL the symptoms, and all the criteria to allow it to develop..
http://en.wikipedia.org/wiki/Groupthink
bugs – “With AGW there are copious amounts of evidence, based on scientific research.”
Please can you list your top five pieces of evidence from most persuasive at number one down?
Barry Woods (Comment#40192) April 8th, 2010 at 3:10 am
yes.
yes
no.
No.
No.
No
yes
yes
curious (Comment#40196) April 8th, 2010 at 5:00 am
I don’t tend to think of it as a popularity contest. Like much science that deals with complex problems that span many disciplines, it’s more a matter of building up the supporting evidence. It gets to a point where there is so much evidence it’s hard to see that there is any alternative.
However, in some sort of order that is not a top five.
Fingerprints.
http://www.pewclimate.org/docUploads/Pew%20Center_Global%20Fingerprints_3.06.pdf
http://www.nature.com/nature/links/030102/030102-3.html
http://www.skepticalscience.com/human-fingerprint-in-global-warming.html
The physical basis.
http://www.pewclimate.org/global-warming-basics/facts_and_figures/climate_science_basics
Obervations.
http://rankexploits.com/musings/2010/march-uah-temperature-anomaly-0-653c/
http://www.guardian.co.uk/environment/2007/feb/02/climatechange.climatechange
Peak science bodies.
http://www.abc.net.au/news/stories/2010/03/15/2845519.htm
The pathetic level of evidence against AGW
http://arxiv.org/abs/0707.1161
Re: Marcus (Apr 7 20:38),
Thanks! D’oh.
Now I’ll have to dress well….
Andrew’s Three Favorite Evidences For AGW:
1. Squiggly Lines
2. Ice Melting
3. Squiggly Lines That Convincingly Represent Ice Melting 😉
Andrew
actual evidence please not just a supposed correlation..
ie evidence of a human signature, with the natural climate fully accounted for and understood..
just becaus eyou have a study that the ice IS melting, does not explain WHY the ice is melting..
evidence/experimentation to prove the link..
As far as i understnd it, simple physics may allow a small allow a small amount of man made warming, but the feedabck may reduce it to nothing, and the natural variability just swamps any detectable human signature..
If you look at the group think link..
agw theory, ipcc/cru, show ALL the suggested symptoms and causes. It will be THE textbook description in ten years.
In 2 hundred years our descendants will be thinking how could they have been so stupid. Whilst superiously going about their own populr delusion of their time.
bugs,
None of your links have any evidence that supports the claim that human CO2 emission are the primary cause of the most recent warming and further emission will lead to catastrophic consequences.
bugs – “It gets to a point where there is so much evidence it’s hard to see that there is any alternative.”
Sorry bugs, I’m a bit dim. Please can you just give me five sentences in your own words which summarize the strongest (not most popular) evidence in support of AGW. Thanks.
I have a few questions, but I don’t know who one would ask at the ICCC. Maybe it would be better asked the IPCC?
Q. 1)
Why don’t we see more regression analysis, with in-depth discussion, for estimating climate sensitivity?
For example, using the models:
[1] temp = a * ln(co2) + b
[2] temp = a * ln(co2) + b * enso + c
Actually, perhaps you can ask Anthony why his widget plots temp vs. co2 instead of temp vs. ln(co2)?
Even though I’m a lukewarmer, I hate the temp vs. co2 plots.
Q. 2)
Why don’t we see a more discussion on year 2100 co2 projections?
Q. 3)
Do you believe it is a “fool’s errand” to estimate UHI trends by solely using temperature data? After all, if we knew which sites represented the “truth”, wouldn’t we just use those? Isn’t it better to regress temp data vs. socio-economic data?
Q. 4)
Do you believe it is a fair statement to say “the models are trending towards rejection?”
Q. 5)
Ask Lucia if I should be asking the above questions to her? 🙂
AJ
I think I know the answer the IPCC types would give to (1). The reason is that those sorts of fits don’t take into account heat capacity. In other words: Fits based on that form violate known physical principles. No one should do that sort of fit; they are only modestly less bad than fitting Temp = a * co2 +b. But if you want me to ask Anthony about his widgets, I can.
I can ask Roy Q3. (I think he’s going to answer that he’s working on using population data.)
Thanks Lucia,
Re: 1)
I’ve regressed sensitivity using model [1] using a 30 year sliding window for the period 1950-2008 and found sensitivity to have an upward slope, which I believe would support the heat capacity argument.
I’ve also done the same regression using model [2] (and amo) and found the slope to be flat. Does that weaken the heat capacity argument?
Re: 3)
I think the problem that Roy is going to have is that he will have to decide which population density represents the “truth”. He has already shown that rural area’s UHI is very sensitive to small population density changes. So does he go with the less sensitive urban areas as the “truth”? Does he go with data from areas with zero population density? If so, why not just use those in the first place? Is my thinking “whacked”? Maybe I need a toy model?
Another issue is that he has already shown significant year to year and region to region (USA vs. ROW) variability in his charts. With that variabilility, I doubt if he can produce significant findings.
AJ
AJ
Do you mean you regressed
Temp(time) = a * ln(co2)(time) +b and found 0<a?
Using something like GISSTemp?
The coefficient ‘a’ is not the sensitivity because your temperatures are not the value achieved after co2 is set to a constant value for a long, long, long time. Also, your regression is neglecting other factors known to affect Temperature. However, the main thing is if you just provided a step function of CO2, temperature would slowly rise over time. So, during the transient, Temp(time) is not a function of CO2. If you did an analysis during this period, you would find no correlation between temperature and time.
I don’t know what we might learn by finding how the parameter “a” varies as you slide the window over 30 years.
There isn’t any argument over heat capacity. Heat capacity exists. The heat capacity of the earth’s climate system must be pretty large– larger than say a huge stone cathedral. If you devise a curve fitting to CO2 and Time that ignores heat capacity, the results are likely to be unenlightening.
I think Roy is currently exploring about these sorts of questions. I don’t know what he thinks or what he’s figured out.
Thanks again Lucia,
In my spreadsheet I had columns for monthly temp (repeated using gisstemp, hadcrut, ncdc) and ln(co2). I then did “linest(ln(co2) column,temp column)” for *all* thirty year periods between 1950-2008 (periods centered from 1965 to 1993). I then charted how sensitivity (a*ln(2)) progressed over this period. IIRC, the there was a downward slope in the very early period, but was strongly upward thereafter.
When I regressed temp vs. ln(co2), enso, and amo (a la Bill Illis), the slope was flat over time. It remained fairly constant with a value ~ 2.
I could send you my spreadsheets if you would like?
I thought that if the calculated sensitivity slopes upward, then there is “heat in the pipeline”. If it is flat, then there isn’t.
AJ
AJ, Lucia,
Some time ago I figured the combined IPCC estimated forcings for CO2, methane, N2O, halocarbons, and my best guess at solar cycle forcings, with the total forcing expressed as two “independent” versions: the immediate total forcing (1 year) and a lagged version of the same forcing; I tried everything from 3 years to 40 years lag constant. These two forcings (immediate and lagged), Nino 3.4, and AMO were then regressed against the Hadley global mean temperature history. The fit was quite good (R^2 of >0.86 in the best case), but the quality of fit was not terribly sensitive to the assumed lag period. The best fit came at short lags (~3 years), but the fit wasn’t bad even at 35 years lag constant. The diagnosed sensitivity (degrees C per watt) changed only slightly until the lag constant reached about 10 years, then increased more rapidly with increasing assumed lag (no surprise there).
.
My conclusion was that it is difficult to learn anything about heat capacity/lag or climate sensitivity based on a best least-squares fit to the temperature data. No matter what you assume, the fit will probably turn out pretty good. It is indeed a fool’s errand.
Why are comments showing up in italic font?
Someone should try . Did that work? No. A puzzle.
Re: lucia (Comment#40235)
I do not quite agree with that. Sure, if you start driving a system you are not going to get a very good idea of its sensitivity from a linear fit to the transient response (the early stages of the response), but if you drive it continuously and steadily, for a time longer than its natural “response time”, most driven, damped systems eventually settle to a pattern from which you can derive some useful conclusions. Basically, you get the response to a time-averaged version of the forcing, which for many kinds of forcings is approximately just a time-shifted version of the same.
So I would say that all those lagged regressions that AJ and SteveF were doing are at least as meaningful as anything else in this field. They will tell you what the effective climate sensitivity is right now, that is, how the system has responded to the forcings over the past many decades, and therefore how it is likely to respond over the next few decades as well, assuming the forcings continue to be described by reasonably smooth, slowly varying functions.
Re: AJ (Apr 8 13:22),
Why do you think this? It’s not obvious to me how the results of your procedure relates to “heat in the pipeline”. If you have an explanation involving a simple physical model, you might be able to show me.
julio
Sure. I’m not saying there is zero information obtained from a fit under all circumstances and all times. If the response time of the climate system was very rapid, we could learn something from that fit. But is it that rapid?
But the difficulty is that, in the abstract, you need to have a lot of information about the full time history of the forcing and to take limiting cases, you need to have an idea of the response time of the object being driven.
Given an arbitrary history of forcing, you can’t automatically tell anything from fits of the sort AJ suggest.
Re: SteveF (Apr 8 14:18),
The italics resulted from my using a real < instead of html.
Andrew_KY (Comment#40202) April 8th, 2010 at 6:45 am
You’re not going to like the evidence for sub atomic particles, either, I guess.
Re: lucia (Comment#40262)
I’m sure there are several relevant timescales, but many are certainly very fast. You can spot Pinatubo in all those time series!
We have a very detailed record of the CO2 concentration for a very long time, and it is probably not a bad first approximation to assume that everything else, over the past 160 years, averages to zero. So I still think the exercise is meaningful. If there is a steadily growing signal, it should be possible to see it through the noise, and it should correlate to the forcing, possibly with some lagging.
More importantly, I have not looked at the IPCC models, but I am pretty sure that they are not much more sophisticated than this in the way they handle latency. They are just differential equations. If they were linear, one could just derive the various relevant timescales from the eigenvalues of a matrix. Even if they are nonlinear, one could still do the same by linearizing around a steady state. As long as the time scales that pop out in this way are in the months to years range, a 160-year fit should not have to worry about transients at all…
The convection is inherently non-linear. Nevertheless, it’s possible to estimate time scales for a variety of sub-process. Non-linearity doesn’t really make that difficult. There are multiple time scales.
Well… expect the forcing function isn’t linearly increasing. So, it’s not clear what you get.
AJ,
I think the problem with Q. 3) is that we don’t know which sites represent the “truthâ€, as none of our urbanity proxies are perfect. That said, GISSTemp effectively tries to do what you suggest by pretty much throwing out all bright nightlight stations and replacing them with the trend from nearby dark stations.
Re: lucia (Apr 8 12:00),
No linear correlation anyway.
Mildly OT rambling:
Kinetics is all about the transient response. My dissertation work involved fitting charge vs. time curves from potential step electrochemical experiments to obtain the rate constant of the charge transfer reaction as a function of potential. Of course, I had a model. Mass transport was controlled only by diffusion and there was a closed form solution of the behavior with time for a charge transfer rate that was less than the diffusion rate. Back then, though, I had to write my own subroutine to calculate the complement of the error function (erfc). The convergence of the algorithm was very slow and the intermediate calculations required very high precision. Having a 60 bit CPU mainframe was a big help. But only the initial part of the curve was controlled by the rate of charge transfer. At long times, it was purely diffusion controlled and varied as the sqrt(t). I’m not at all sure that one or two time constants is sufficient to characterize the climate response (assuming always that there is such a thing) when there are potentially diffusion controlled (eddy or not) processes in the heat transfer to and from the ocean. The Bode and Nyquist impedance plots of a diffusion controlled process as a function of frequency look very different from those for an RC circuit.
Opps… I meant Temperature and CO2. In the hypothetical, CO2 doesn’t vary, but temperature does. That’s the difficulty.
(My not writing what I meant surely lead to confusion. . .)
How many of your papers showing flaws in the AGW theory have you been unable to publish in the peer reviewed literature?
“You’re not going to like the evidence for sub atomic particles, either, I guess.”
bugs,
Then again, no criminals are perpetuating a Global Sub Atomic Particle Scare, are they? 😉
Andrew
Boris (Comment#40296)-Do you mean how many have been deliberately kept out?
It’s the quality not the quantity, incidentally.
Another point-it’s usually possible to get published somewhere (although Ross McKitrick will find himself going to applied Stats journals where people have some clue what he’s talking about).
Hello Lucia,
Here are my five…oops, six and a half questions.
I hope they meet your parameters.
1 – Do the problems with the IPCC stem from its being rigged from the start to declare “manmade activities” the problem?
2 – Are we still, officially, in an ice age?
3 – Is the greater and more likely threat to humanity global cooling since so much of our food supply depends on the length of the growing season?
4 – In the long history of Earth, CO2 levels are near historic lows. Is there a genuine reason to panic over a modest increase in CO2 levels, whatever the source?
The AGW theory is that CO2 increase leads temperature increase.
5a Doesn’t the AGW theory automatically fail based on the Vostok ice cores?
5b Doesn’t the AGW theory automatically fail based on how little correlation there is between temperature and CO2 levels over the last 110 years?
6 – Which is the better investment? Spending money battling “climate change” and reducing CO2 which is a minor greenhouse gas, or spending money to provide rechargeable LED lighting and access to clean water to people who need one or both?
http://www.lutw.org
http://www.samaritanspurse.ca/ourwork/water/Default.aspx
lucia (Comment#40276)
A simple physical model? Oh, great! Now I have to construct a model in excel and simplify the series into a formula. And here I was just about to submit my findings to Nature 🙂 SteveF is right! This is a fool’s errand!
Intuitively I think the lags are short. I base this on how the seasons progress up here in Nova Scotia (~45N lat). If you compare our mean temps with the equator, we make up 2/3rds of the difference between January and July. A month after the summer solstice, the temps start heading south again. In the summer the lakes, bays, and the Gulf of St. Lawrence warm up nicely, although jumping into the open ocean is still a kamikaze thing to do.
That’s why I believe the lags are short and the flat slope of the co2 sensitivity calculation over time is meaningful. Turning this belief into math, however, would take some effort. But thanks for the critique 🙂
Zeke (Comment#40277)
I think the bright/dark lights method of GISSTEMP is suspect. Given that rural areas are more sensitive to population density changes, they could easily be effected by moderate mega-trends.
In my neck of the woods, one might argue that given the depopulation of the rural areas, there is a negative UHI. Also one could compare a shapshot of a typical rural community from today to one from 50 years ago. On the UHI+ side, more pavement and air-conditioners. On the UHI- side more energy efficient heating and better insulated structures. However this plays out at a global level, I can’t pretend to know. It just demonstrates how difficult it is to determine which stations represent the “truth”.
I think there are at least 3 dominant time scales for the simplest possible problems. One is short, and can be thought of as being for the “air”. Another one must be for warming the deep ocean– and must be fairly long. What’s worse, is some of these time scales must describe diffission problems, which means the response is more complicated than for simpler systems.
Re: lucia (Comment#40276)
For a nonlinear system, no, but for a linear system, as long as the forcing is “slow” enough, you will get, after the transients have died, pretty much a straight line, if you plot the response versus the forcing.
Here’s the simplest possible example: I have integrated numerically, from t=1850 to t= 2009, the equation
dT/dt = -r*(T-T0) + f*log[CO2(t)/CO2(1850)]
This is just a damped driven system, which has a stable steady state at T = T0 in the absence of driving. For the forcing I have used the actual CO2 record, beginning with the year 1850, normalized so that the actual forcing builds slowly from zero (it makes the transient a lot less dramatic).
As you correctly pointed out, CO2(t) is definitely not a linear function of time, but if I plot T vs log[CO2], this is what I get:
http://comp.uark.edu/~jgeabana/linear.png
The red line is for r = 0.2 (a “response time” of about 5 years), and the black one for r = 1 (a response time of about 1 year).
This is in fact a fairly general result for linear systems. It does not matter if you have one equation or a thousand, as long as the driving is slow enough. Note that the red line is a little bumpier; this is because in that case the system is a bit more sluggish and does not keep up with the forcing as well as the faster system does.
Note also that the slower system has a bigger response. This, I believe, may be the best way to think about those legendary “positive feedbacks”. Clearly the overall temperature of the Earth is fairly stable, so the overall feedback has to be negative, but the “positive feedbacks” could make it, overall, “less negative” (as in this example, -0.2 vs. -1), in which case the effective response to the forcing is larger.
Which brings me back to the topic of this thread in a roundabout way. First off, congratulations, and I hope you enjoy the conference! Second, if nobody has suggested this yet, why don’t you ask everybody “what do you think is the effective value of the climate sensitivity in degrees per CO2 doubling, and on what do you base your belief?”
(I’ll discuss nonlinear systems a bit in another post, if I have time)
Julio (Comment#40325)-It would be insufficient to look at the CO2 forcing alone, one also has to consider other greenhouse gases and aerosols. GHG’s are well determined, but aerosol forcing is a crap shoot.
I think everyone is admitting that the twentieth century is not a good place to constrain the climate sensitivity. Some believe that they can use paleoclimate to do it, but I think that’s not feasible, either. That naturally makes me an extremist, since the “mainstream” view is that paleoclimate “proves” the models are right.
Julio
and if r=0.05 for a response time of 200 years? Some estimate this for the oceans, meanwhile it’s thought to be fast for the air.
Can you put data on your plot?
BTW: I discussed some of the response issues in a different way here:
![]()
Yes. For a simple, purely linear system, we get stuff like this:
http://rankexploits.com/musings/2008/linear-thinking-can-we-fit-a-line-to-figure-out-climate-sensitivity/
Good question!
Here’s my brand new/innovative physical model for modelling energy absorbtion 🙂 I call it the “bouncing ball” model. Each time a ball bounces it loses x% of it’s kenetic energy to heat energy. Because of this loss of kenetic energy, each successive bounce is lower, but also faster. Eventually the compression of the bounce is no longer enough to lift it off the floor, but it is still oscillating. Very quickly these oscillations deminish to the atomic level and effectively all kenetic energy has been lost.
Now think of the air as a nerf ball, which loses it bounce quickly and the ocean as a rubber ball which retains it’s bounce for longer. I think the air loses it’s bounce within days and the oceans within months. After the oceans have absorbed this energy, any downwelling of warm water is offset by an equal upwelling of cood water. This could explain the flatness of the Argo and sea level data for the few years leading up to the latest El Nino.
Far from a perfect analogy, but you asked for a simple physical model and here it is! 🙂 I’d have to take Physics 101 again to come up with a better one. Is global warming all about converting lw energy to sw? Is there an exponential characteristic in this process similar to the bounces coming quicker and quicker? If so, then maybe the analogy isn’t that bad?
P.S. I also think Julio’s question is a good one.
Re: lucia (Comment#40329)
I wasn’t sure if you meant r=0.05 for a response time of 20 years or r=0.005 for a response time of 200 years, so I did them both 🙂
I was surprised by how straight the r=0.005 case turned out, after all, since it is really pushing the envelope (linear regressions are the black dashed lines; incidentally, in my formula above I forgot to mention that I picked f=0.5 for all the calculations, rather arbitrarily).
http://comp.uark.edu/~jgeabana/linear3.png
I’m not sure what you mean by putting data on the plot. If you mean sharing the code, sure, but it is a Mathematica file…
The post you quoted was indeed a good cautionary tale about what will usually not work. My comments here are about what will often be useful, instead (even for nonlinear systems)–namely, look (well) beyond the response time, and plot response as a function of forcing, not time.
Re: nonlinear, I pretty much agree with your comments regarding chaotic dynamics on that other thread. I may add a little of may own over here later today.
Re: Andrew_FL (Comment#40327)
I do not think leaving out methane and ozone is a big deal, since these things are a small contribution to the overall greenhouse effect anyway, and probably more trouble than they are worth (but I stand ready to be corrected).
Aerosols are, as you say, a problem, so lacking any reliable information to the contrary, I would take the default position that either (a) they fluctuate over short time scales and average to some kind of constant background over the time scales I am interested in, or (b) if they do contribute a nonvanishing trend, it mostly cancels out with other equally obscure and incalculable contributions, such as solar variation (that’s more or less what I got from the paper by Stott, but I may have misinterpreted it).
CO2, on the other hand, is a steady forcing; it does not go up, down and sideways; it just keeps going up and up, relentlessly. It would take a massive conspiracy of noise to hide such a signal in the temperature record, unless it happened to be a truly insignificant player. The fits I posted the other day suggest to me that the signal is, indeed, very clearly there.
Contrariwise, it would take a massive conspiracy of aerosols to disguise a climate sensitivity of 3 or higher so as to make it look so much like the climate sensitivity of 1.9 that I see in the temperature record. So my conclusion is that the climate sensitivity is probably what it appears to be (1.9 C per CO2 doubling), which puts me, I think, squarely in the lukewarmist camp.
I do agree with you re: paeoclimate. If somebody thinks they cannot tell what the climate sensitivity is from the recent instrumental record, which is full of all kinds of data obtained by direct observation, and yet they think they can get it from some conjecture about what the climate was like tens or hundreds of thousands of years ago, there is something seriously wrong with their heads.
Julio–
I mean put something like
(Observed surface temperature – reference temperature) and (ln Co2) on the plot. Currently, you just have theory plots.. right? (Or did you use a line rather than discrete points for data?)
Basically, does your theory explain data?
Great!
Maybe you, Tom Vonk and I can have a ridiculously long “chaos” thread.
Tom knows a lot more about chaos than I do because I’ve never used chaos to do anything practical. But my thinking is “stochastic”, “descriptive statistics” and “chaos” are not “either /or” ideas.
Re: lucia (Comment#40351)
I do use the real-world 1850-2009 CO2 data (via an “interpolating function object” that Mathematica builds for me), but it is just a toy model. I could try to turn it into a fit to the real temperature data, but I’m not sure one could learn much from it. Basically, I just wanted to make a mathematical point, and using real-world data for the CO2 forcing was easier than making something up 🙂
I’ll see if I can say anything intelligent about chaos. It has been a while! If nothing else, I can always quote Bob Dylan:
“I accept chaos. I am not sure whether it accepts me.”
Lucia,
As a companion to the “effective sensitivity” question, I would like the next question to be:
“What will be the atmospheric co2 concentration in the year 2100? And why?
Thanks, AJ
P.S. I liked my “bouncing ball” model. After all, nothing is more “toyish” than a nerf and rubber ball, eh?
P.S.S. Am I the only one left in the room?
With kindest regards, AJ 🙂
ok, I’m leaving and turning out the lights. Good-night Johnboy.
AJ – just saw your ball comments. One thing that I think is worth bearing in mind is that the solar energy supply to any locality on earth is effectively pulsing on a daily basis with an annual signal on top. Apologies if that is stating the obvious – I haven’t been following the detailed comments.
Good morning AJ,
We had beautiful weather Friday night. I suspect no one sat at their computers here in the midwest.
Bad idea, Lucia:
-It’s not a serious conference with people doing good work (like ACS, MRS, APS, AGU, ASME, etc.)
-There’s are a fair amount of cranks there and some of the worst ones.
-Already too much emphasis on socializing and “let’s put on a show” amateurism, that generally is not good work.
-People in these groups tend to “allie” with each other and don’t really push THINKING when it involves calling out their own allies. (and yes, you do a little, but IMHO insufficient, especially wrt Watts…and instead too much chummyness with a real duffer and a dishonest one.)
—————————
If you wanted to interview people, you could grill Watts for a bunch of his silliness and why he hasn’t finished (or repudiated his preliminary publishing) on things like the Basil solar silliness, march of the Thermometers, paint screen work, site surveys, etc. (fill in more)
Julio-the other GHG’s contribute significant forcing increases:
http://www.esrl.noaa.gov/gmd/aggi/
Re: Andrew_FL (Comment#40423)
Andrew,
Thanks! I’ll admit I’m surprised: from their figure 4, it looks like CO2 is only responsible for about 60% of all the GHG-forcing increase since 1979.
I find it amusing that 60% of the 1.9 C “climate sensitivity” which I quoted yesterday is precisely 1.14, or just about the “bare” radiative CO2 climate sensitivity, without any feedbacks at all!
But, of course, that’s not fair. If I’m going to include other GHG’s, then I really should make an effort to include aerosols, etc. Presumably the two errors of omission will tend to cancel each other out.
I may *try* and redo my fits, at least for the 1979–2009 period, especially if I can find a reliable (ha, ha) resource on aerosols. The paper by Stott that I quoted the other day has the change in T due to sulfate and volcanic aerosols pretty negligible for the 1970-1999 period, so maybe ignoring them would be OK….
In any case, I think this only reassures me in my belief that an “effective climate sensitivity” of 1.9 C per CO2 doubling is a good *upper* limit, and the “real” number may actually be rather smaller….
Julio:
Here are the GISS Model E forcings
Annotated text file is found here.
I’d use something like Lucia’s two-box model to model the effect of the forcings on climate. Let me know if you want an R-source link for that.
Julio, you brought up eigenvalues, they do study the eigenvalue problem in ocean dynamics.
For example, Meridional oscillations in an idealized ocean-atmosphere system, Part I: uncoupled modes by Vikram M Mehta, Climate Dynamics 6, Number 1 / July, 1991, pages 49-65.
Re: Carrick (Comment#40450)
Oboy.
OK. I’ll play with this (I can’t resist the temptation!). You’ll hear back from me in a week or two. 🙂
Thanks also for the link to the oceans paper. I admit those century-long timescales worry me a bit.
I remember seeing Lucia’s two-box model before, but a direct link would save me a bit of searching, so, if it’s not too much bother…
Marcus should apologize:
http://www.marshall.org/pdf/materials/656.pdf
“It is unambiguous that this increase in CO2 that we see is predominantly man-made.”
But my thinking is “stochasticâ€, “descriptive statistics†and “chaos†are not “either /or†ideas.
.
That’s my thinking too .
“Chaos” is a property of (some) solutions of differential equations both partial and ordinary .
This is an either/or issue with no wiggle room .
F.ex chaos is a property of N-S in the PED domain and of the Lorentz system in the ODE domain .
Stochastic is something else altogether which is not really related to the chaotic or non chaotic features of some natural law expressed by PDE or ODE .
A chaotic solution can sometimes be studied with statistical tools in which case stochastic and chaotic march hand in hand .
Incidentally 99,99% of people think that this is ALWAYS the case .
Well sometimes it is impossible – qualitatively the chance to have a a measure (probability) left invariant by the evolution is better for temporal than for spatio-temporal chaos .
This is just a result from experience so don’t quote me on that 🙂
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… because I’ve never used chaos to do anything practical.
It’s generally the case .
I have had the opportunity to work on problems of stability in electrical grids a long time ago .
This is a very practical problem that is governed by temporal chaos and that’s why I was lead to expand my knowledge of non linear dynamics . In biology and medical sciences chaos is omnipresent too – f.ex your and my future heart failure will be a result of a purely chaotic system (I didn’t look closely at those issues but my father , a medecine doctor , did) .
.
That leads me to propose questions for your trip :
1) Is the climate spatio-temporal chaos ?
2) If yes , what feature are conserved (if any) by spatial averaging ?
3) If the spatial coupling is weak , is the spatially local trajectory in the phase space ergodic ?
Tom–
Good questions. It sounds like we are closer on our views of chaos than I suspected!
I would never go so far as to claim that a stochastic point of view is useful for all chaotic systems. I’d need to understand more than I do about chaos. I’d probably go as far as suggesting that when it doubt about nature of a chaotic system treating it as a stochastic system is worth a shot. Sure, the attempt might fail. But, depending on the goal, it’s also often worth a shot to linearize, extrapolate, do an experiment, make approximations etc.
BTW: I think I saw something about chaos and heart disease on television. Discovery? NOVA? One of those science for the masses type shows.
Lucia
.
Good questions. It sounds like we are closer on our views of chaos than I suspected!
Just for my general education , what was it that you “suspected” ?
.
I’d probably go as far as suggesting that when it doubt about nature of a chaotic system treating it as a stochastic system is worth a shot.
Yes that’s what people generally do .
Actually if one has not a closed set of equations this is the natural thing to do .
Problem is that even if there is an invariant PDF , it generally doesn’t look like anything you are familiar with .
It looks more like a spectrum with large holes (states where the system never is) and sharp peaks grouped in clusters .
And of course the invariant PDF (in N dimensions of the attractor)and its projection on an axis don’t look similar either .
As for spatially correlated systems (systems where things flow) , there is a formal duality between their dynamics and the hamiltonian dynamics . As we know that the hamiltonian systems are not ergodic , spatially correlated systems shouldn’t be ergodic either .
This can be intuitively understood when looking at the shape of cigarette smoke in a room where air doesn’t move and perturbing it (initial conditions) by moving a finger through the smoke near the cigarette tip .
.
I think I saw something about chaos and heart disease on television.
Yes it is a very studied domain . And when one connects the mysterious sounding “chaos” and the scary “heart failure” it surely raises enthousiasm in the mass media .
As I said , I didn’t look at it closely but the short of it is that your heart follows the deterministic chaos . But the nature has been kind enough so that the governing parameter (like the Reynolds for FD) stays in a range where the solution is quasi periodical . But the threshold value is not far and when the parameter crosses it , the solution becomes chaotic and you die .
Re: TomVonk (Apr 13 04:42),
I thought you thought discussing averages, st. devs etc. was utterly useless!
The whole point of my question -apparently missed by most- is to question the role of uncertainty.
The question is about how you would respond to a credible, yet uncertain, threat.
Uncertainty cuts both ways: Things could be less bad or worse than predicted.
If you’d argue that the GW threat is not credible, then in addition you’d have to argue for a high degree of certainty regarding your position (analogously, in a snowstorm you’d want to be sure that you’re driving on an extremely wide road without any other traffic). Just saying “there’s too much uncertainty in the science” (analogously, “my view of the road is not good”) doesn’t cut it. That was the point of my (one liner) question.
I think how people deal with uncertainty is a very central theme to the issue of how to deal with GW. And as with any analogy, it of course breaks down at some point, and can be twisted in all kinds of ways. Perhaps the question wasn’t “well posed” in that sense.
Bart
Everyone gets that this is your point.
Twisted?
You are missing everyone else’s point which is: The sort of question you are asking is counterproductive to meaningful dialog. Worse, putting questions to people you want to strike out that is like lobbing a softball right into the strike zone. I could take a camera and film everyone as I ask that question. Some would just walk away. Others will just hit that one out of the park and score a home run.
Uncertainty cuts more than two ways. The effect of attempts to mitigate could be less bad or worse than predicted. Some well meaning mitigation attempts could backfire and result in more ghg’s. Geo-engineering could have problems. Turning corn into fuel could have problems. Heavy investments in solar, wind or other technologies, done poorly could have unintended negative consequences.
If I ask a ‘driving in snow storm’ question, which is both open ended and obscure, I could get answers that go in all sorts of directions, none of which answer the question you think you are asking. One couldn’t even accuse the person answering of twisting because everyone knows you didn’t literally want to know if they slow down their speed when driving in a snowstorm.
I can certainly ask a direct question about responding to uncertainty. But asking one that is cloaked in a hypothetical about driving in a snowstorm is not useful. That’s the point everyone else seems to get, and is trying to communicate to you.
Bart Verheggen,
Yes, of course uncertainty ‘cuts both ways’. But I think the problem is a bit more complex. There is uncertainty in the sensitivity of course, but there is also a lot of uncertainty in the consequences of any specific temperature rise. What will be the long term (century or more) consequences of a 2C rise in average temperatures? How about 3C? Or 4C? How about rainfall in the central USA or the south of Brazil? Sea level rise in 75 years? Nobody really knows. I think it is the multiple layers of uncertainty which give many people pause. The multiplied uncertainties reduce the ‘credibility’ of the threat of warming.
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As I commented to Eduardo at your now famous ‘unit root’ thread, I think better definition of ocean heat uptake and aerosol effects will be needed to constrain the range of climate sensitivity (and so reduce the first layer of uncertainty) before there will exist a political consensus in most countries to make large public investments to reduce CO2 emissions. 10 years of Argo data and Glory Mission aerosol data will probably be enough.
Lucia,
You’re right, and I did get that. That’s why I ended with: “Perhaps the question wasn’t “well posed†in that sense.”
Perhaps a drier though hopefully clearer version of the question could be: How do you deal with uncertainty in the face of a threat deemed credible by most (though not all) experts? Are you certain enough that the threat is *not* credible so as to rule out the chance of it being very bad indeed?
SteveF,
You wrote: “The multiplied uncertainties reduce the ‘credibility’ of the threat of warming.”
That to me is a very strange proposition, and seems based on discounting the chance of things being even worse than expected (i.e. you’re only taking into account the uncertainty meaning that things could be not quite as bad as expected, and forgetting about the other direction uncertainty goes).
An example may be sea level rise. It’s very uncertain how fast sea level rise will proceed. But past analogues hint at a very steep relation between global avg temp and sea level, if the climate has been at said temp at a long enough time (see e.g. http://www.glaciology.net/Home/Miscellaneous-Debris/relationshipbetweensealevelriseandglobaltemperature) How long is enough? We don’t know. Is that uncertainty comforting? I don’t think so. Sea levels were approx 6 metres higher than today in the previous interglacial, whereas global avg temp was only a few (1-3) degrees higher (different estimates going around).
Re: Bart Verheggen (Apr 13 06:59),
Your question is weighted to obtain the answer you want. If the solution were as easy as you make it out to be by the construction of your question, we wouldn’t be having this discussion. Suppose you’re driving because you need to be somewhere by a certain time or something very bad will happen. If you slow down, you won’t get there in time. Slowing down or wrecking the car produce equivalent outcomes. Now do you slow down? We’re simply not going back to a late 19th century economy and leave the rest of the world even worse off, which is the only thing we could do right now to keep delta T below 2 C if the climate sensitivity is indeed 3C/doubling or higher.
Bart Verheggen,
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People have very different views of risk, and very different philosophies about what ‘moral responsibilities’ humanity has to avoid changes in Earth’s environment.
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Suppose we knew exactly the response of the average temperature to a doubling of CO2 (say 3.5 C), and we knew the exact response of the Greenland ice sheet to 3.5C warmer temperatures: a ‘catastrophic’ melting of the ice sheet over 1,750 years, with a resulting sea level rise of 7.5 meters during that 1,750 years. With this information we could make a rational evaluation of the costs versus benefits of the changes needed today to change that outcome 1,750 years hence. Under this ‘catastrophic scenario’, people could determine that substantial investment is warranted today. But they could also determine that the current cost is too high, and that accepting a 7.5 meter rise in sea level rise over 1,750 years is preferable, and make investments in other things (like planning for a the sea level rise!). With reliable projections of the future, the decision becomes easier to make, but will inevitably be a decision that is political; a decision based on philosophy, values, and economics.
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However, with less than certainty of a ‘catostrophic’ outcome, convincing people to make substantial sacrifices today will be much more difficult (approaching impossible, I think).
Re: TomVonk (Comment#40595)
Just a quick comment on this: I do not think it is a matter of nature being kind, but of life exploiting an “island of stability”.
There is a more general anthropic argument one can make. Chaotic systems may be generic in a mathematical sense, but most of the things we encounter and depend on in everyday life have already been selected (by “evolution”, in the most general sense of the word) for durability and stability, so they will typically be very weakly chaotic if at all (like, say, the solar system).
That is why I do not believe the climate of the Earth (as opposed to the weather) could be chaotic to a significant degree. There might be planets where the climate is wildly chaotic, but they would almost certainly not have evolved intelligent life!
(Carrick: I know, I’m supposed to be doing another calculation right now with those GISS forcings you pointed out to me. I’ll report in a few days.)
How about some questions about the EPA and the endangerment finding? I am curious about whether the technical and scientific points of contention would ever find their way into a courtroom. As I recall, more than one justice remarked in the Mass. vs EPA decision or the oral arguments that there was no scientific evidence presented to the court from the skeptical side of the argument. Personally I don’t see why a court shouldn’t be able to see an honest disagreement about the science and pronounce the whole thing as uncertain. They won’t do that though if only one side is ever presented at court.
This is a much better question. 🙂
I should note, the answers are going to branch a lot. Most people’s response to a threat deemed credible will depend on the magnitude of the threat, the definition of “credible” and other factors. One might ask me to define credible. Is something credible if there is a 0.1% chance of occurring in 100 years? Or is the credible threshold at “more likely than not”.
Also, in terms of leaving stuff out, it’s true that some people discount hypothetical low probability catastrophe far in the future. But other seem to ignore the fact that some of the insurance to avoid these remote possibilities come at the expense of almost certainly increasing suffering in developing nations immediately.
I have no idea how to balance these things, but it seems to me that they do need to be balanced.
“How do you deal with uncertainty in the face of a threat deemed credible by most (though not all) experts? Are you certain enough that the threat is *not* credible so as to rule out the chance of it being very bad indeed?
This is a much better question.”
It’s a (two) terrible question(s). OMG, where do I start? :wink”
“very bad” What is this, Kindergarten?
Andrew
Something tells me Heartland doesn’t get into lawsuits. I may be thinking of the Competitive Enterprise Institute.
Andrew_KY
““very bad†What is this, Kindergarten?”
I suggest you consider that English is Bart’s second language (or perhaps third or fourth language… he is Dutch after all). His English is of course excellent, but it is not native English, and we should not expect it to be. How is your Dutch, by the way?
DeWitt Payne wrote:
“We’re simply not going back to a late 19th century economy and leave the rest of the world even worse off, which is the only thing we could do right now to keep delta T below 2 C if the climate sensitivity is indeed 3C/doubling or higher.”
Others also echoe the sentiment that stringent mitigation will wreck the economy (having to make big sacrifices, increasing poverty, etc). I’m not an economist, but I am skeptical of such claims and think they are overblown.
I’ve seen many studies claiming that for about 1% of global GDP the most dramatic consequences of climate change can be prevented (some ref’s collected here: http://ourchangingclimate.wordpress.com/2009/09/14/bjorn-lomborgs-eternal-postponement/). That has no resemblance whatsoever with the 19th century economy. The costs of unrestrained global warming are likely much greater. Climate effects are expected to hit poorest nations the hardest, so poverty is hardly a reason to *not* mitigate climate change.
These cost estimates are of course inherently uncertain, pointing again to the central role of the concepts of uncertainty and its evil twin, risk.
Krugman discusses these issues in his NYT article (http://www.nytimes.com/2010/04/11/magazine/11Economy-t.html?pagewanted=all and discussed eg at http://hot-topic.co.nz/krugman-on-climate-economics-uncertainty-makes-the-case-for-action-stronger/)
How to deal with risk of the only partially known, that’s the ultimate question. And I think that is also the core of the disagreement between different climate ‘factions’.
Lucia
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I thought you thought discussing averages, st. devs etc. was utterly useless!
Oh no 🙂
The central limit theorem is a theorem after all and a fundamental one .
But what might have come across in some posts is that I am not very interested by averages and sigmas applied to a PARTICULAR case which is the surface temperature field of the Earth .
That’s why I don’t comment about this issue but I read with interest most analytic posts here . And let me tell you that I found that there were some remarkable pieces like the 2 box model analysis .
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Julio
Chaotic systems may be generic in a mathematical sense, but most of the things we encounter and depend on in everyday life have already been selected (by “evolutionâ€, in the most general sense of the word) for durability and stability, so they will typically be very weakly chaotic if at all (like, say, the solar system).
That is why I do not believe the climate of the Earth (as opposed to the weather) could be chaotic to a significant degree. There might be planets where the climate is wildly chaotic, but they would almost certainly not have evolved intelligent life!
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The problem is that there are too many misconceptions about what “chaos” (btw I don’t like this misleading denomination) really means .
Without meaning any disrespect , you seem to share some of these misconceptions .
Some examples :
– Chaos is not opposed to stability . It has been demonstrated already 100 years ago that the system of 3 bodies is chaotic . The solar system appears stable not because it is not chaotic but because the space is basically empty and the probability to have a body large enough meeting the Earth (or another planet) near enough is negligible . And even without that it is impossible to predict accurately the Earth’s orbital parameters beyond some 10 millions years .
– There is no such thing like “weak chaos” . It would translate like saying that a Lyapounov coefficient is “weakly positive” . Along the same line there is also no “wild chaos” or “degrees of chaos” .
I agree these expressions are often used especially in climate science but almost never in papers about non linear dynamics .
– Contrary to the popular belief , chaotic solutions behave in a more stable way that many non chaotic solutions . This is due to the fact that the attractor allows only a very small portion of the phase space compared to all energetically allowed states .
A chaotic solution is by definition bounded and extremely constrained . Especially chaotic ergodic systems are stochastically remarkably stable . The success of statistical thermodynamics is due to this property . Chaotic solutions cannot “diverge” else they are no more chaotic . I would say that life on Earth was possible precisely because the climate system is locked in a remarkably constrained chaotic attractor .
– Weather is chaotic while climate is not . This is a really mysterious belief . It amounts to believe that those objects are described by completely different physics . But if weather is really chaotic then it is chaotic on all time scales (proven property of any chaotic solution) . If one takes 1000 year averages of the Lorenz system they are exactly as chaotic as the original instantaneous ODEs .
What happens in reality is that by going to large time scales , the high frequency components are filtered out and the low frequency components become visible . But once a system is in a chaotic regime (because it is dissipative and out of equilibrium) there is no special frequency that would separate the trajectory in chaotic and non chaotic “parts” .
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Unfortunately few physicist trained in non linear dynamics are interested by the climate and even less really work in this domain .
I am convinced that progress would be achieved if people like Ruelle&Co contributed to look at the system with another paradigm than equilibrium thermodynamics .
“Andrew_KY
““very bad†What is this, Kindergarten?â€
I suggest you consider that English is Bart’s second language (or perhaps third or fourth language… he is Dutch after all). His English is of course excellent, but it is not native English, and we should not expect it to be. How is your Dutch, by the way?”
SteveF,
I’m not on the intrawebs propagandizing about Global Warming. I’m trying to respond to people propagandizing about Global Warming. If Global Warming is Global Problem and Everybody Should Believe In It, then it’s proponents need to communicate in a meaningful way. Grade-School Level “very bads” with no explanation are not very useful in conveying meaningful information to someone trying to address the issue seriously, no matter what country somebody is from.
Very Bad how? In what way? This is really basic stuff.
Andrew
If the sun doubles it’s insolation, will that change the climate. If it halves, and the earth turns into a snowball, will that change the climate? The chaotic system has external forcings that are going to change the fundamental state it is in.
Bugs–
The chaotic system has external forcings that are going to change the fundamental state it is in.
Sure, but that doesn’t mean the system is not chaotic.
The difficulty is that I think some people think saying “chaos” means that the state of the system can’t be characterized. That’s not true. (What’s true is that we can’t make long term predictions– that’s a different thing.)
When the system with defined properties is chaotic, an attractor exists. We know the state will fall on that attractor. So, if climate (or weather) is chaotic, then given a known level of insolation, rate of rotation of the earth etc., both weather and climate will fall on a particular attractor.
If you did change insolation dramatically and let the earth sit at this new state, the weather and climate would fall on a different attractor. That new attractor would correspond to higher insolation; I think it would almost certainly have higher average temperatures. But the both weather and climate would still be chaotic.
What you and Tom are saying are not contradictory.
Now, if we move to empiricism and we observed a rise in temperature, the question is: How do we know that temperature rise corresponds to a shift in the location of the attractor for the current forcing? How do we know it’s not just the sort of thing we expect to see even if we stay on the same attractor?
Or than the whole use of “chaos” language, this isn’t much different from more traditional statistical approaches where we ask whether we can detect a trend in a noisy signal.
Bart,
“How to deal with risk of the only partially known, that’s the ultimate question. And I think that is also the core of the disagreement between different climate ‘factions’.”
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Yes, that is the ultimate question. How someone answers that question depends on a lot of factors. But the level of perceived risk is certainly very important. I believe that high levels of uncertainty reduce the perception of risk for most people, and this currently blocks the formation of a consensus for significant public action to reduce CO2 emissions. I doubt this will change until uncertainty about climate sensitivity is substantially reduced and the risks/benefits of no action/action are much better defined. The science just needs to be a lot better to reduce the uncertainty.
Lucia,
I remember (year ago) reading that the observed patterns in chaotic systems tend to repeat at different scales of time and size. Do I remember this correctly? If so, then might it be productive to look for similar patterns of temperature variation at different time scales?
SteveF–
It might be if
a) we had data over a longer period of time,
b) the data was as clean as might be hoped for in a laboratory experiment and
c) we could be confident we were not fiddling with the forcings.
The difficulty is that we have a-c all present in the thermometer record, and paleo isn’t going to be very good.
That said, anyone can create graphs of T(i+1) vs. T(i) etc. Also, anyone can start data mining for other types of graphs to find the attractors.
I think the reason people working in chaos prefer lab experiments is they would like to link the mathematics to cleaner data initially. They also would like cleaner problems.
Re: TomVonk (Comment#40646)
I concede all the technical points and plead guilty to using informal language such as “chaotic to a significant degree”–although I think that in context it should have been obvious what I meant.
But I don’t think the “belief” you question is really mysterious at all. The point is that, in physics, everything is an approximation from the beginning. I cannot even write down equations to describe the experiments in the lab downstairs if I have to include in them everything in the universe–to which it is undoubtedly coupled “to some degree”. I can only make some progress if I start throwing away things whose effects I can estimate are going to be negligible (that is, below the experimental resolution) over the time scales of interest to my experimentalist colleague. And in the process of doing this, it may well be that “weather” and “climate”, even if they arise, in a very general sense, from “the same physics”, may end up being described by different equations.
Here’s a dumb example. Suppose I am interested in a variable Y = x + X, where the dynamical equations for x are approximately decoupled from those of X. Let us say that x is slowly varying and obeys regular dynamics, and X varies fast and obeys chaotic dynamics. Also assume that the standard deviation of X is very large compared to x, but that it averages to nearly zero over, say, any 12-month period.
Then on the “weather” timescale x can be treated as a constant or even neglected entirely, and the weather equations are chaotic. On the other hand, if I write “climate” equations for av(Y), where av(Y) is the 12-month running average of Y, etc., I may very well neglect av(X), and just get a non-chaotic equation involving av(x).
Your point is only that, if X is chaotic, then so is av(X), and hence I cannot assume that it is strictly constant, and equal to zero. But nothing prevents it from being negligibly small for practical purposes, which is all the modeler cares about.
Now, do I believe that this is the real state of affairs as regards the Earth’s climate? I don’t know. But it is possible, and this is the sort of thing we are trying to figure out. Are there significant secular effects on av(x) due to X? Again, I don’t know. I just don’t think anything can be dismissed beforehand–including the possibility that climate might end up being very nearly deterministic, over an appropriate timescale, “for all practical purposes.”
Julio,
I think I created a cartoon of what you are describing:
In this cartoon, I took the Lorentz butterfly equations, and set the three parameters to … (something, something, RA), but in one case I set the Rayleigh number to Ra=50 for one process and the other Ra25. Then, I decided the “process” we are examining is “F=y+RA”. I plogged (Y(t), Y(t+t_lag)) for each process.
Obviously, this is a “cartoon” process because the physics correspond to nothing. But what I have is 1 attractor for the RA=25 case and a different one for RA=50. The two are sufficiently far from each other that someone looking at the statistics of the two processes a person studying the process might decide that to leading order, we can treat the difference between the value of F in one process and the others as deterministic. Another might insist we need to remember the processes are chaotic because for each process, the value of F is chaotic. Of course, the way I drew the cartoon, both points of view could have utility.
Given this picture, I suppose when people say that climate is deterministic and weather chaotic, they may merely be thinking that climate is a long term average. If we start averaging over time and make similar plots, I’ll probably see smaller and smaller spreads in values of “F” for the attractor. So, at a certain point, many people are going to think it’s better to treat the attractor as a point instead of a complicated looking thing.
Re: lucia (Comment#40694)
Yes, in the language of your cartoon, what I was saying would be like assuming that RA is a slowly-varying function of time controlled by its own (non-chaotic) differential equation….
The difficulty is that I think some people think saying “chaos†means that the state of the system can’t be characterized. That’s not true. (What’s true is that we can’t make long term predictions– that’s a different thing.)
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Yes !
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I think the reason people working in chaos prefer lab experiments is they would like to link the mathematics to cleaner data initially. They also would like cleaner problems.
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Yes !
There are many demonstrated mathematical theorems concerning non linear dynamics .
Using the celebrated Takens embedding theorem it is easy (well relatively) to reconstruct the attractor properties from a single variable time series . It is also easy to clearly distinguish theoretical linear stochastical processes (ARMA type) from non linear deteministic processes (chaos type) .
The problem being that the Takens theorem is valid in the infinite time limit (like the ergodic theorem too) and for a mathematical theorem it is unacceptable to say that when the assumption is “approximately” realised , the theorem is “approximately” true .
In a kind of paradox , chaos researchers are much more rigorous than researchers in classical deterministic domains where such statements are bread and butter but …. 🙂
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Suppose I am interested in a variable Y = x + X, where the dynamical equations for x are approximately decoupled from those of X. Let us say that x is slowly varying and obeys regular dynamics, and X varies fast and obeys chaotic dynamics. Also assume that the standard deviation of X is very large compared to x, but that it averages to nearly zero over, say, any 12-month period.
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Yes that is the classical slightly more formalised assumption that a process is described by a sum “clean deterministic classical signal” + “noise” .
I will spare Lucia an Nth comment about Reynolds averaging 🙂
But what you assume is that your process Y is linear . It is trivially non chaotic . So what you say amounts to saying “If I assume that a process is non chaotic then it is non chaotic .” This statement is of course tautologically true .
I am saying something completely different and it has nothing to do with assumptions about X and its averages not even whether they are invariant .
I am saying that Y=[x(X(t)) , X(t) , t] . x may be fast or slow or constant this doesn’t matter . In this case Y may be chaotic even if it looks like x + X on some finite time scales .
So how to decide what is the true dynamics of Y ?
The obvious answer is to write the equations for Y . They will be N-S type PED what doesn’t really look linear like x + X . But this is hard for probably the most complicated non linear system we know in physics .
An empirical answer by f.ex time series study is per definition impossible . The reason is the same as the one I mentioned above for the Takens embedding theorem . However with the increasing observation time and progress in spatiotemporal chaos theory it will be possible .
The last way is to disconnect from physics and go over to mathematics . Like T.Schneider a leading expert in non linear dynamics said about ARMA models “Nobody really believes that non linear physical processes can be described by linear combinations of stationary random variables . But the latter are easy to use and stand on sound mathematically theoretical foundations .”
And as there indeed is a complex connection between purely stochastical systems and purely chaotic systems via ergodicity , such approaches may very well work (statistically) untill they stop to work one day .
Obviously, this is a “cartoon†process because the physics correspond to nothing.
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Yes .
It doesn’t even look like the Lorentz attractor – in reality it is rather stable and the difference between Ra 25 and Ra 50 could not be seen on a low resolution plot .
Also what do you mean by the denomination of the coordinates ?
Your Y is the Y from the Lorentz ODE ?
If yes , what is supposed to mean plotting Y(t+1) or F(t+1) (I suppose the “1” means 1 LTU) , next point on the Lorentz solution as function of the previous point Y(t) ?
With only 60 LTU you wouldn’t even cross the transitory .
I admit that it is very unclear to me what you plotted even if I can see that the global idea which amounts to translate a Lorentz system in the phase space with a HUGE translation vector is approximately similar to Julio’s assumption .
If I take a chaotic climate system and heat it, the whole chaotic system rises in temperature. Rambling on about chaos is just using it as a comfort blanket.
Tom-
Unless I miscoded (which is possible), that’s a lorentz attractor. I used
Pr (i.e. σ)=10
Ra (i.e. ρ)= 50 or 25
β=8/3.
I used an integration time of 0.0025, and ran 10,800 time steps.
However, I don’t really display [y(t+1), y(t)] (meaning a separation of 1 time step), I display [y(t+10), y(t)].
(For the cartoon, I shlepped this up in EXCEL. Otherwise, I’d pick an even smaller integration time. My choice time step at least makes the attractors look similar to each other as I decrease time step. Much larger time steps can do weird things, so that could be an issue.)
F=(Y+ Ra). So, it’s Y but shifted by Ra. (The shift is done to create a cartoon that I think is the point Julio is trying to make.)
That was the point the cartoon is supposed to make. Something deterministic changed (here RA). In my weird system, this changes the ‘centroid’ (if that’s a concept) of the attractor. The system is still totally chaotic, but the change in RA did change system properties.
I’m not sufficiently familiar with Lorentz attractors to know whether the change in Ra should, or should not have changed the spread of the attractor. Maybe I have a bug? It doesn’t look like a time step issue. ….
bugs (Comment#40748) April 15th, 2010 at 6:12 am
Right bugs and melting ice doesn’t add fresh water to the ocean that changes currents and causing some places on Earth to be cooler then they were; and the full moon doesn’t change tides to break up ice at the North Pole making the weather there cooler too either…And never ever in the vast geological record did the climate on earth go from very warm to very cold and visa versa despite the greenhouse gas concentrations in the atmosphere; or a volcano erupted…on infinity.
bugs
I agree with you. That’s the ‘point’ of the shift in the cartoon. The blue attractor is supposed to represent a system at higher forcing; the red at lower. If “F” is temperature, the blue attractor represents a system that is chaotic, but overall hotter than the system represented by the red attractor. (I guess I should have switched colors?)
I’m not sure what you mean, but I suspect you are 1/2 right and 1/2 wrong on this.
I do think some people want to suggest if the system is chaotic, it can’t be characterized, or that everything that can happen is unbounded or something. But chaos doesn’t mean either. The trajectories of chaotic events are difficult to forecast– but that’s not the same as saying they are difficult to predict.
Hmm… I wonder if anyone has plotted an attractor for monthly temperatures [T(t), T(t+1)] for a control run of a model? That might be interesting.
Lucia,
“The trajectories of chaotic events are difficult to forecast– but that’s not the same as saying they are difficult to predict.”
For sure, if the chaotic system is well characterized/described mathematically. But when it’s not well characterized, it seems to me that the range of “normal” chaotic variation is not known, which makes it very difficult to quantify any deterministic shifts (the change from one attractor to the other in your cartoon system), and assign causation to those shifts. Do I have this wrong?
BTW, I see the hours of your posts and I wonder “Does this person never sleep?”
SteveF–
I think you are correct. That’s why I said I think bugs is 1/2 right and 1/2 wrong. In comments at any blog, we get a range of claims. So, I think some people cry “Chaos!” to mean unpredictability in every possible sense of the word. Others understand what it means, and recognizing the complexities argue:
1) The system is chaotic but
2) We don’t much of an idea what the attractors might look like and
3) We know changes in deterministic forcings could do something like the cartoon lucia showed above but
4) How in the world do we distinguish between temperature changes associated with that big shift she shoved in the cartoon vs. an alternate cartoon where there is no shift, but we just moved into a different lobe on a strange attractor?
(I could make cartoons to explain Q4 better. If we were at a real blackboard, I could make all sorts of cartoons for each issue.)
The answer to (4) is, it’s difficult to distinguish.
On the time stamps: I sleep. I work part time, so I have lots of time.
Lucia,
OK. Thanks.
I think I like cartoons on white boards better… no chalk dust.
Glad to hear that you sleep.
1) It’s been more than 20 years since the IPCC came into existence to evaluate the risk of climate change caused by human activity. What do you think the two or three most important things are that we have learned about the climate system in that time?
2) Do you feel that we are more or less certain about a causal relationship between human activity and observed climate change and why?
3) In what areas do you feel our understanding is best and/or our certainty highest with respect to changes in the climate system?
4) The least certainty and/or understanding?
5) Which areas do you think are the most important to our understanding of the climate system and the possible effects of human activity?
Lucia
I used an integration time of 0.0025, and ran 10,800 time steps.
However, I don’t really display [y(t+1), y(t)] (meaning a separation of 1 time step), I display [y(t+10), y(t)].
.
That’s what is puzzling .
Normally if you display that , you get something that looks like a random series . It looks stationary or non stationary depending on luck . So it shouldn’t look like what is on your plot (attractor shape) . Besides , indeed the number of steps is low and the step is high but that is just a technicality .
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3) We know changes in deterministic forcings could do something like the cartoon lucia showed above but
4) How in the world do we distinguish between temperature changes associated with that big shift she shoved in the cartoon vs. an alternate cartoon where there is no shift, but we just moved into a different lobe on a strange attractor?
(I could make cartoons to explain Q4 better. If we were at a real blackboard, I could make all sorts of cartoons for each issue.)
The answer to (4) is, it’s difficult to distinguish.
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Indeed correct questions but not so difficult .
I already gave a fast answer to Julio – it lies in the dimension of the phase space .
As we are just trying to eliminate some misconceptions about what chaotic solution mean and what they don’t mean , we’ll forget for the moment that weather is spatio-temporal chaos and NOT temporal chaos .
Of course this difference is conceptually huge but we can’t write posts a size of text books either 🙂
OK so our system’s dynamics are described by a trajectory in a phase space of dimension N .
N is unique and invariant .
The attractor will be some manifold in the phase space of dimension M < N . F.ex for the classical Lorenz system N = 3 and M = 2.06 .
This shows btw how dramatically a chaotic system constrains the allowable states – we loose almost a whole dimension and the system is constrained to stay forever only on a fractal quasi surface in a 3D volume .
But the main point is that there is already EVERYTHING about the dynamics of the system in N .
You can’t simply add new K independent degrees of freedom (which is what the “translation vector” in the phase space would do) because then the phase space would be of dimension N + K and not N and the attractor > M .
It’s here that Takens embedding theorem kicks in (with the caveat about the infinite time limit) – whatever time series you observe with whatever parameter , you will always obtain the same attractor dimension which is M .
So it is excluded that unknown degrees of freedom exist on top of those already explictely observed in the equations describing the dynamics of the system .
Unless , as I wrote , one supposes that there is a completely new (unknown) physics that somehow appears above some time scale and that has not been accounted for in the physics we used to describe the system first place . And by new physics I don’t mean values of parameters or time constants (slow , fast etc) , I really mean new equations with new degrees of freedom .
A qualitative argument that such new physics doesn’t exist is the observation that during 4 billions years the system stayed unusually stable what suggests that the attractor is extremely constrained and stable .
All this is of course only valid for temporal chaos and it is not clear if such results transport to spatiotemporal domain whose theory is still in infancy .
Personnaly I am convinced that in 90% they don’t .
Nice questions Schnoerkelman, perhaps we could add:
‘Are we getting value for our money, if so, how would we know, and what do we have to show for it?’
SteveF
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But when it’s not well characterized, it seems to me that the range of “normal†chaotic variation is not known, which makes it very difficult to quantify any deterministic shifts (the change from one attractor to the other in your cartoon system), and assign causation to those shifts. Do I have this wrong?
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Yes .
Such a “shift” is impossible in a temporally chaotic system for reasons explained above .
An attractor is (by definition) a dynamical invariant . It can’t “shift” unless you missed something huge in its dynamics and even in this case the word “deformation” would be better than “shift” .
TomVonk (Comment#40834),
Well, thanks for the response, but honestly, it looks like I would need a course (or two or three!) in chaos theory to even understand what you are saying.
My doubt remains: how can you tell in a chaotic system like Earth’s climate (with a poorly or completely unknown mathematical description of it’s chaotic behavior) if a temporal change in a measured variable is simply due to the chaotic nature of the system, independent of any external forcing, or if that measured change is the result of an external forcing? Isn’t this the key question WRT assigning global temperature increases to GHG forcing?
TomV–
If I plot (X vs Z) from my excel spread sheet using Lorenz values, my attactor looks just like his and I have plenty of loops. I’m having fun with this discussion so I may create a sort of “open thread- chaos ramblings” post so we can iron out what we all mean. I’ll show my various graphs.
I think that we aren’t all understanding each other, because I’m pretty sure that in the Lorenz problem, we could postulate the following problem:
1) Some one is running a system with Lorenz dynamics. In that system, the temperature difference across two planes is imposed (δT); other things come from the properties of the fluid. We let that run a long time; we measure temperature as a function of time T(t). We make pretty plots. We compute metrics like average temperature <T>, stdevT etc. The graduate students are thrilled to bits! Wow!
2) At night, the janitor comes along. He bumps the system and changes the temperature of both plates. Each plate warmed by 3C– oddly (δT) stayed constant.
3) The graduate students return the next morning and start taking more data. They notice that the average temperature <T> increased. However, other than the shift, the data all look the same. Wow!
Now, because they are literally looking at T, they will notice the system shifted. In contrast, if they had been plotting the lorenz variables, they would see the system was “the same”.
I suspect some in comments (like me, julio etc.) are thinking of the literal temperature when we say things shifted. I suspect you are thinking of the lorenz variables. But monitoring climate, we see things like Temperature, not a heavily transformed lorenz variable.
Lucia thanks for doing this. A chaos thread would be great. especially with toy problems.
SteveF :
My doubt remains: how can you tell in a chaotic system like Earth’s climate (with a poorly or completely unknown mathematical description of it’s chaotic behavior) if a temporal change in a measured variable is simply due to the chaotic nature of the system, independent of any external forcing, or if that measured change is the result of an external forcing? Isn’t this the key question WRT assigning global temperature increases to GHG forcing?
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Steve the problem is already in the question .
You seem to want to distinguish “internal” variations and “forcings” by causality .
That is not how it works .
In the study of dynamical systems the “forcings” are explicitely part of the system .
Write the equations for the Earth in the gravitational field .
What is the “forcing” and what is the “internal variability” ?
Chaotic system have ALWAYS 2 necessary features :
1) they receive energy
2) they dissipate energy
Then it is in the how they do both that defines their dynamics (= trajectory in the phase space) .
The how are the dynamical equations that you solve .
So when something , anything , changes in their state , it is a result of interaction of everything . You can’t say that it is more this or less that . Of course it is not independent of the energy supply or the way energy is dissipated (if you call that “forcing”) .
But the question of assignement of changes to one particular parameter doesn’t make much sense and is actually misleading if you deal with a chaotic solution .
The variables simply don’t separate in non linear ODEs .
Lucia :
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I called it puzzling because you said that :
However, I don’t really display [y(t+1), y(t)] (meaning a separation of 1 time step), I display [y(t+10), y(t)].
And then you said that :
If I plot (X vs Z) from my excel spread sheet using Lorenz values, my attactor looks just like his and I have plenty of loops.
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As your plot coordinates are called y(t) and y(t+1) so the first statement would be true but then the plot would look like a random series .
If the second is true then you get something that looks like a projection of the attractor on a plane (spagetti plate) but then the coordinates should be called X (t) and Z(t) .
So I still don’t know what are the 2 coordinate axis and what the plot actually represents .
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I suspect some in comments (like me, julio etc.) are thinking of the literal temperature when we say things shifted. I suspect you are thinking of the lorenz variables. But monitoring climate, we see things like Temperature, not a heavily transformed lorenz variable.
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Well I can not tell for sure what others are thinking .
But I am pretty sure that I don’t think what you suspect me thinking 🙂
First the Lorenz system is just an example so I don’t think in terms of Lorenz variables in particular .
Second , I think (and probably didn’t express it clear enough) in very general terms of dimensionality of the phase space and constraints on the topology of the trajectories .
Of course it applies to the Lorenz system as an example but it also applies on any other chaotic solution of any arbitrary non linear dynamical system .
What you call “litteral” temperature is just one coordinate of the phase space .
Like is “litteral” pressure , “litteral” density and even “litteral” CO2 concentration if you wish .
I can use them under their “litteral” form or make any kind of simplifying transformations (normalize , scale etc) .
So , clearly , once I have the phase space of the system I study and the corresponding dynamical laws , there is no room for anything else unless I badly missed one or several dimensions .
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Even if what I say is quite general , I’ll use the Lorenz example for simplicity – it has a 2.06D attractor in a 3D space .
I don’t need to characterize the coordinates – knowing that there are exactly 3 is necessary and sufficient .
It can’t “shift” , it can only “deform” .
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Now somebody comes and says that I horribly forgot W(t) to describe the dynamics 🙂
This W is per definition different from X, Y and Z .
And he also kindly supplies me with 4 non linear ODE’s featuring X, Y , Z and W .
3 look vaguely like the original I used but with W inside .
The 4th is new physics .
In other words he tells me that I got the dimensionality of the system wrong , it is 4 and not 3 .
OK so I solve it , find chaotic solutions and the attractor is f.ex 2.89 D .
And it is precisely at THIS point that I say that it is not very difficult to distinguish which of both ideas is right .
As I can reconstruct the attractor with any variable (Takens theorem) I take X , measure it and compute the attractor dimension .
If I find 2.06 (what is the case in reality) , I know that there is no independent W and that the system is fully and completely described in a 3D space with X, Y and Z only .
At the same time I discover that the 4D system is wrong and could deduce that W is some (unknown) combination of X , Y and Z .
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Now replace Lorenz by climate and the argument goes the same way (always must add the spatiotemporal caveat !)
Tom,
I don’t understand why you think it doesn’t make sense to try to identify or assign the cause of some sorts of changes even if a system is chaotic.
In the Lorenz system, you set up your little box with the top plane cooled so it stayed at Tc and the bottom heated so it stayed at Th, you could establish some sort of flow system. You could watch it. Maybe you monitor some feature– temperature 1/2 way between the top and bottom but 1/2 way from the center of the box. You monitor for 3 weeks. You created nifty temperature plots. Maybe you plot [T(t), T(t+τ)] and find an attractor for this. You also find an average temperature. All this happened at Tc and Th with pure helium box.
Then, you go on vacation. When you come back, the attractor looks different. The average temperature looks different.
Why would it not make sense to suspect someone fiddled with your test rig? Why would it not make sense to check the temperature of the top plate and the lower plate were set at the values you’d kept them at before you went on vacation? Maybe someone came in and fiddled with the setting? Why would it not make sense to test whether the box is still full of pure helium? Maybe someone changed the fluid– thereby changing the viscosity, density and coefficient of thermal expansion?
Why does it not make sense to figure out why the properties of the system changed?
Conversely, if you knew in advance someone was going to slowly increase the temperature of the lower (hot) surface, why would it not make sense to try to assign the cause of change to changing the temperature of the lower surface?
Then, you go on vacation. When you come back, the attractor looks different. The average temperature looks different.
Why would it not make sense to suspect someone fiddled with your test rig?
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Oh that makes great sense . And I wouldn’t only suspect , I would know .
As an attractor is (by definition) a topological invariant , if it changes it means that the constants of the system itself changed and probably in a dramatic way .
Actually as in your scenario I am an expert in a chaos research lab , I know my chaotic threshold parameters by heart and go immediately to check the one of the 3 constants that has moved .
Perhaps all 3 moved .
Or worse , somebody put the box upside down 🙂
What I meant as not making much sense is to ascribe causes for the trajectory inside the attractor , not the attractor itself .
Because we can only observe during finite times , what we observe in practice is the former not the latter .
Tom
That’s what I think people mean by detecting the attractor “shifted”, or if you prefer “deformed”.
Using the Lorenz attrator in the lab, it’s easier to specify how we would know something changed. After all, there are only 3 parameters, we know what they are, and we can watch it long enough to know what the attractor looks like.
But switch to climate. We know it’s chaotic. The average temperature changes. We have a finite sample of data from [T1,T3]
How do we know whether apparent differences from [T1,T2] and [T2,T3] are due to motions along a trajectory inside the same attractor? As opposed to a change in the system parameter which changed the attractor?
That’s the question people are asking. I think the answer is: using the tools of chaos, so far, no one has provided any answer to that question.
(This is why people use statistics instead. Sure, they may have problems too. But, that’s the tool people turn too.)
Tom–
We cross posted!
To facilitate further discussion, I posted a bunch of images, and write a chaos post.
But my question for this is:
How do we know that, owing to finite times for observations of the earth’s surface that what we observed in practice is the former not the latter?
I’m closing comments. Please go to the
chaos post for further discussion.