The Search for a Short Term Marker of Long Term Climate Sensitivity
By Dr. Roy Spencer. October 4th, 2009
[This is an update on research progress we have made into determining just how sensitive the climate system is to increasing atmospheric greenhouse gas concentrations.]
While published studies are beginning to suggest that net feedbacks in the climate system could be negative for year-to-year variations (e.g., our 2007 paper, and the new study by Lindzen and Choi, 2009), there remains the question of whether the same can be said of long-term climate sensitivity (and therefore, of the strength of future global warming).
Even if we find observational evidence of an insensitive climate system for year-to-year fluctuations in the climate system, it could be that the system’s long term response to more carbon dioxide is very sensitive. I’m not saying I believe that is the case – I don’t – but it is possible. This question of a potentially large difference in short-term and long-term responses of the climate system has been bothering me for many months.
Significantly, as far as I know, the climate modelers have not yet demonstrated that there is any short-term behavior in their models which is also a good predictor of how much global warming those models project for our future. It needs to be something we can measure, something we can test with real observations. Just because all of the models behave more-or-less like the real climate system does not mean the range of warming they produce encompasses the truth.
For instance, computing feedback parameters (a measure of how much the radiative balance of the Earth changes in response to a temperature change) would be the most obvious test. But I’ve diagnosed feedback parameters from 7- to 10-year subsets of the models’ long-term global warming simulations, and they have virtually no correlation with those models known long-term feedbacks. (I am quite sure I know the reason for this…which is the subject of our JGR paper now being revised…I just don’t know a good way around it).
But I refuse to give up searching. This is because the most important feedbacks in the climate system – clouds and water vapor – have inherently short time scales…minutes for individual clouds, to days or weeks for large regional cloud systems and changes in free-tropospheric water vapor. So, I still believe that there MUST be one or more short term “markers” of long term climate sensitivity.
Well, this past week I think I finally found one. I’m going to be a little evasive about exactly what that marker is because, in this case, the finding is too important to give away to another researcher who will beat me to publishing it (insert smiley here).
What I will say is that the marker ‘index’ is related to how the climate models behave during sudden warming events and the cooling that follows them. In the IPCC climate models, these warming/cooling events typically have time scales of several months, and are self-generated as ‘natural variability’ within the models. (I’m not concerned that I’ve given it away, since the marker is not obvious…as my associate Danny Braswell asked, “What made you think of that?”)
The following plot shows how this ‘mystery index’ is related to the net feedback parameters diagnosed in those 18 climate models by Forster and Taylor (2006). As can be seen, it explains 50% of the variance among the different models. The best I have been able to do up to this point is less than 10% explained variance, which for a sample size of 18 models might as well be zero.
Also plotted is the range of values of this index from 9 years of CERES satellite measurements computed in the same manner as with the models’ output. As can be seen, the satellite data support lower climate sensitivity (larger feedback parameter) than any of the climate models…but not nearly as low as the 6 Watts per sq. meter per degree found for tropical climate variations by us and others.
For a doubling of atmospheric carbon dioxide, the satellite measurements would correspond to about 1.6 to 2.0 deg. C of warming, compared to the 18 IPCC models’ range shown, which corresponds to warming of from about 2.0 to 4.2 deg. C.
The relatively short length of record of our best satellite data (9 years) appears to be the limiting factor in this analysis. The model results shown in the above figure come from 50 years of output from each of the 18 models, while the satellite range of results comes from only 9 years of CERES data (March 2000 through December 2008). The index needs to be computed from as many strong warming events as can be found, because the marker only emerges when a number of them are averaged together.
Despite this drawback, the finding of this short-term marker of long-term climate sensitivity is at least a step in the right direction. I will post progress on this issue as the evidence unfolds. Hopefully, more robust markers can be found that show even a stronger relationship to long-term warming in the models, and which will produce greater confidence when tested with relatively short periods of satellite data.
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Parroting two links that also do not have quantitation of the subject under discussion (Arctic sea ice volume) doesn’t cut it either at this level.
What are you talking about… you asked for data, I show it, you call me a parrot, and then deny there is quantitative data? If you want more specifics, go look up the journal articles cited.
Anthony… I am not sure what you are getting at… NASA doesn’t count as a name? Scientists always put their names or identify their organization during the peer review process. You must be talking about blogs… which are not capable of scientific review.
The AGW crowd are hiding? How are the researchers, data collectors, etc hiding when they publish their findings?
REPLY: What’s your name?
“1930s were the warmest decade for the US. It clearly shows no massive warming problem”
I stopped reading there.
OK. Seriously… using 10 years of data (is it even a full 10?) to criticize theory on climate… Am I eating crazy pills?
I have been trying to find a generally accepted time scale of climate that distinguishes it from weather.
This is basic, but close: Read “How does climate differ from weather? ”
http://www.ucar.edu/learn/1_2_1.htm
NOAA uses 30 years of data to define an average temperature.
The number 30 is also found in statistics for being able to approximate the mean and SD of samples to populations. Usually when n-1>30; s->S.
I don’t know what else to say…
I see this same lack of understanding on weather and climate from AGW skeptics and no one ever corrects them. It drives me insane when AGW supports try to do it because it makes everyone look uneducated.
danappaloupe (19:08:59) :
Parroting two links that also do not have quantitation of the subject under discussion (Arctic sea ice volume) doesn’t cut it either at this level.
What are you talking about… you asked for data, I show it, you call me a parrot, and then deny there is quantitative data? If you want more specifics, go look up the journal articles cited.
———–
Just give me one number that has Arctic sea ice volume in cubic meters, or cubic kilometers. Just one.
I’d prefer two, but at this point I’ll take one.
Don’t change the subject by running off to square meters (x,y). I’m asking for x, y and z. Just post a number with a verifiable reference.
Just give me one number that has Arctic sea ice volume in cubic meters, or cubic kilometers. Just one.
Do you want the volume of the entire ice sheet? Obviously we can’t know that exactly and it would be useless because we want to know if it is getting thicker or thinner. The mean thickness tells us a lot about what is going on. We know that on sites that have been repeatedly measured the mean thickness has decreased. I believe I already cited that. Submarines have been measuring mean thickness since before the Cold War.
You could read this though
http://psc.apl.washington.edu/publications/pubs/Rothrock2007JC004252.pdf
and this
http://ams.allenpress.com/perlserv/?doi=10.1175%2F1520-0442%282004%29017%3C3623%3AAMFTHR%3E2.0.CO%3B2&request=get-document&ct=1
All you need to do is read the Abstract ( I read it all and don’t pretend to understand most of it)… 2200+ data points etc etc… they conclude that sea ice thickness is decreasing.
If we are arguing over if the volume of the Arctic ice is increasing or decreasing (which I believe is the whole point of this exchange, knowing the mass of ice for a year is pointless)… area has decreased (cited earlier) and mean sea ice thickness has decreased….
That is probably not good enough though. Why do I waste my time.
I actually did just learn a bunch of new information though. Thanks.
What, no number ??
If you don’t want to waste any more time, admit that there is no number.
Phil you are wrong to think that the exact volume of an ice sheet is essential to this debate, climatology, or even studying ice sheets in general. We don’t know the exact volume of the oceans, but we can measure if they are increasing or decreasing.
You are demanding an impossible and pointless number when what we are debating is change not size, demonstrating that you are unwilling to approach this scientifically or even participate in a reasonable discussion. Much like how creationists demand frame questions about proving evolution, demanding to see the exact fossil that shows our transition from a lower species.
The beauty of statistics is that we don’t need to measure the entire sheet of ice to know with certainty if it is increasing or decreasing or not changing.
You did at least take a basic stats class, and gone on to apply it to sciences in some way right?
No, you are wrong. If you say that the Arctic sea ice volume is decreasing or increasing then you need to show two numbers at least (with error bars preferably). I would even accept two numbers from a model at this point.
The current Arctic sea ice extent is not a fossil. It has an exact number as I type.
I’ll take a number (or two) from “the beauty of statistics”, with “it” being volume. Area is one click away on the right hand side of this blog page.
Please, if you don’t have a number in your next post, will you admit that the number is not available, through direct measurement, modeling or beautiful statistics ??
PS substitute “extent” with “volume”, in the second paragraph, so there is no confusion.
I will participate in a reasonable discussion on Arctic sea ice volume when we establish what the available data (i.e. numbers in cubic kilometers) tells us.
The point of all of this is that the volume of ice may be changing, correct?
Yes.
If area is decreasing (x, y), and mean thickness (z) is decreasing and Volume = x*y*z, then Volume is decreasing.
We do not need to know the total exact volume of ice to know this.
I am not even going to say it is or is not decreasing at this point… but I bet if it was increasing you would conveniently accept it.
Not to mention that the exact volume of arctic ice at any given moment in time is irrelevant because it is constantly changing (in motion) with time (seasons).
The Heisenberg Uncertainty Principle may apply here. At this exact moment can you recite what that is? Look it up.
“You changed the outcome by measuring it!!!” -Hubert J. Farnsworth from Futurama
You need to go talk to a student of the philosophy of science about this. They can clear this up for you. Don’t even mention climate, or ice, use something neutral like an alpine lake that fluctuates with seasonal snow melt.
Demand that you must know the exact volume to know if it is changing (say that you cant measure surface input, all water seeps in through an immeasurable number of subsurface seeps, to eliminate conversation about measuring variables).
Even set up in this way, they can tell you exactly what I am telling you.
Peace
danappaloupe (21:56:43) :
The point of all of this is that the volume of ice may be changing, correct?
Yes.
If area is decreasing (x, y), and mean thickness (z) is decreasing and Volume = x*y*z, then Volume is decreasing.
________________________________________
Correct, and since x and y are pretty well established on a daily basis, now you just need to to give a number for z at time t and we can calculate volume at time t. Simple isn’t it ??
So what’s z then ??
“and since x and y are pretty well established on a daily basis”
Awesome!!!, now we are even more certain that we know if V is changing, even with a weaker confidence in the change in Z!!! A decrease in the propagation of error, due to a dramatic increase in the certainty in 2 of 3 variables, may even lead to an exponential enhancement of our confidence interval! Wow.
Its true, the stats that is. You really just shot yourself in the foot.
Data from over 2000 naval survey points shows a decrease in mean thickness over time, with high certainty.
Data from the ice satellite project, though not as accurate as we want, shows a decrease in ice thickness. Thanks to statistics this data can be used to draw meaningful conclusions about ice thickness. We might not be able to say with certainty that we know the rate of change but I am pretty sure we can test a null hypothesis that the mean of Z from a few years of data is moving in some direction away from Zero.
I don’t even want to go into your concept of what t (time) means and why it is completely wrong in this scenario. But I can’t resist.
you say “at time t”
Wrong. Ice, is measured as a mean, even in area using X and Y, OVER A PERIOD OF TIME. Furthermore the measurements used for analysis do not happen at a specific moment in time at all, but at an event, either the minimum or maximum of the measurements. The time at which that event happens can be used, for completely different reasons.
I actually collect data this way frequently during stream sampling. We estimate peak run off from snow melt and sample vigorously before and after that point to make sure we catch it. The same thing happens during precipitation events in the spring and fall. Everyone else I know and every paper I have read says to do it the same way.
Enough numbers available:
5.
Hadow and his scientific advisor erroneously believed that their expedition was the only way ice thickness measurements could be done, and they seemed oblivious to other efforts and systems. While this was obviously a selling point to sponsors and an ego boost for the team, it was flat wrong. For example, there’s a bouy network that provides ice thickness data,. Then there’s ICEsat which provides mass and balance measurements, as well as ice thickness maps,…
(from http://wattsupwiththat.com/2009/10/15/top-ten-reasons-why-i-think-catlin-arctic-ice-survey-data-cant-be-trusted/ ).
So who needs expeditions to gain even more numbers? They’re there in abundance!
RR Kampen (02:41:43) :
Enough numbers available:
So who needs expeditions to gain even more numbers? They’re there in abundance!
—————–
So why are you and danappaloupe having such difficulty in typing one ??
Re: philincalifornia (04:18:09) :
So why are you and danappaloupe having such difficulty in typing one ??
Won’t speak for danappaloupe, but I am paralyzed from my surprise you seem unable to type them.
danappaloupe
RR Kampen
Show us the data from over 2000 naval survey points and the decrease.
And read this,
The Ice in the arctic is two times thicker than expected:
http://www.radiobremen.de/wissen/nachrichten/wissenawipolararktis100.html
Pi Pi
Hi Carlo, is this your son of seven posting? O well. As you know the Arctic ice melts and gets thinner every year, so even you can understand there must be something amiss in that article.
You can find the data for yourself. I will not do it for you, because you will accuse me of cherry picking or so.
Oh come on RR, type just one from the state-of-the-art study that is all over the news today.
Thank you, philincalifornia, for doing that.
http://www.ens-newswire.com/ens/jul2009/2009-07-08-03.asp
Using ICESat measurements, scientists found that overall Arctic sea ice thinned about seven inches a year, for a total of 2.2 feet over four winters….
Between 2004 and 2008, multi-year ice cover shrank 595,000 square miles – nearly the size of Alaska’s land area. ….
“One of the main things that has been missing from information about what is happening with sea ice is comprehensive data about ice thickness,” said Jay Zwally, study co-author and ICESat project scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland.
“U.S. Navy submarines provide a long-term, high-resolution record of ice thickness over only parts of the Arctic. The submarine data agree with the ICESat measurements, giving us great confidence in satellites as a way of monitoring thickness across the whole Arctic Basin,” said Zwally.
philincalifornia (09:26:00) :
Yes, That state-of-the-art, peer reviewed study, from the Catlin Arctic Ice expedition.
As I’m sure you are aware Vangel, I wasn’t just arguing about sea ice volume. I was trying to point out that if someone makes a statement of quantitation it is a necessity to have numbers. Parroting two links that also do not have quantitation of the subject under discussion (Arctic sea ice volume) doesn’t cut it either at this level.
This argument could be about the number of coins in danappaloupe’s pocket yesterday versus today.
I agree with your statement but point out that accuracy and relevance also matter. In the case of the AGW proponents, they are unable to show that their global average has either accuracy or meaning. And when I look to their ice data I see very similar problems. For one, they seem to forget that the planet has two polar regions. For another, they quote thickness data even though it doesn’t seem to be very accurate and cannot be independently verified by other means.
Anthony… I am not sure what you are getting at… NASA doesn’t count as a name? Scientists always put their names or identify their organization during the peer review process. You must be talking about blogs… which are not capable of scientific review.
The AGW crowd are hiding? How are the researchers, data collectors, etc hiding when they publish their findings
I think that he is referring to many of the anti-SM people who take shots by using others and do not respond directly to the issues that are being debated. Mann is a clasic example of someone who has been running from debate. The same is true of Phil Jones, Briffa, and others that refuse to show the data they use in their papers even though the journals have strict rules about transparency.
I also think that it is very revealing to see so many former NASA employees step up in the debate after they retire. They seem to have been unwilling to risk their positions and funding by speaking out against the warmers while they were employed and could only say what they believed after they were no longer employed by the agency and were assured of receiving the pensions they were entitled to. If you have paid attention you should have noticed that the warmers have been very careful to avoid actual debates because they could not really defend their claims with anything other than predictions coming from unverified models.
“1930s were the warmest decade for the US. It clearly shows no massive warming problem”
I stopped reading there.
OK. Seriously… using 10 years of data (is it even a full 10?) to criticize theory on climate… Am I eating crazy pills?
Where did you get 10 years of data out of the statement? I am talking about all of the American data set. If you look at the instrumental record you find that, “the U.S. has warmed during the past century, but the warming hardly exceeds year-to-year variability. Indeed, in the U.S. the warmest decade was the 1930s and the warmest year was 1934.” If the warmest decade in the US was the 1930s and 1934 was the warmest year, then where do you get off arguing that the data is showing dangerous warming? (I guess that your conclusion comes from the crazy pills you seem to be eating.)
I have been trying to find a generally accepted time scale of climate that distinguishes it from weather.
This is basic, but close: Read “How does climate differ from weather? ”
http://www.ucar.edu/learn/1_2_1.htm
NOAA uses 30 years of data to define an average temperature.
The number 30 is also found in statistics for being able to approximate the mean and SD of samples to populations. Usually when n-1>30; s->S.
I don’t know what else to say…
I see this same lack of understanding on weather and climate from AGW skeptics and no one ever corrects them. It drives me insane when AGW supports try to do it because it makes everyone look uneducated.
How convenient that we use a 30 year period when that is the length of a PDO cycle and you are at the end of a warm phase. And how convenient to make ‘adjustments’ to the raw data that add about 0.6C to current temperatures when compared to the last warm cycle. Of course, when we look at the actual data we don’t see any warming.
That is the problem with your side of the argument. The only way to get warming is to ‘adjust’ the data by adding a signal that is about the same size as the claimed warming. But fudging data is hardly the way of science and claiming that original data and the methods used to change it are unavailable does little for your side’s credibility. The latest Yamal chronology fiasco is the latest of a series of blunders that have cost your side credibility. Briffa’s use of such a limited set in violation of his own stated principles and the use of a single tree that provides most of the warming signal is a disgrace to both the authors of the articles that used the chronology, the reviewers that missed the problems in the articles, and the journals that published them. The previous fiasco was the dropping of the Polar Urals chronology when the updated set showed that there was no warming signal in the data. That was preceded by the revelation that researchers were unable to replicate Graybill’s Sheep Mountain results. Add to that the use of the upside down Tiljander proxies and the use of inappropriate bristlecone and foxtail pine proxies that ignored the effects of changes in precipitation and CO2 fertilization and the whole dendro community has been totally discredited.
So where exactly does that leave you? For one, you do not have complete, reliable and accurate surface records that can be independently reviewed and verified as required for the results to be scientifically acceptable. For another, we have an independent audit by Anthony that shows that around 90% of the US surface stations are biased by 2C or more, a fact that was missed by NASA/GISS. That is a serious problem because the claimed global warming is only 0.6C and that is equivalent to the adjustment made to the raw data. That leaves you with warming that comes from data that is biased to the high side AND gets an adjustment that makes it warmer by the amount claimed by the AGW proponents.
How are any of the adjustments scientific? How can we trust people that were incapable of spotting that the warming bias from the stations was around three times higher than the claimed warming? And where is the credibility in hiding the surface data when every time other data sets were allowed to be examined the reviewers find no warming signatures and improper methodologies?
[REPLY – Note the NOAA adjustment graph is in °F, not °C. Even so, the adjustment almost doubles the warming trend. ~ Evan]
Excellent Vangel !! 😀
“and the whole dendro community has been totally discredited.”
Dendrochronology for dating is unquestioned, it’s just the idea that trees are a temperature proxy which is silly.
The beauty of statistics is that we don’t need to measure the entire sheet of ice to know with certainty if it is increasing or decreasing or not changing.
You did at least take a basic stats class, and gone on to apply it to sciences in some way right?
You might want to reconsider this last statement. For one, duration matters a great deal. A reduction of thickness in one short period of time in one part of the sheet is meaningless just as an increase in thickness is meaningless because an ice sheet may be far more complex than the people studying it realize and because there are natural variations that tell us very little about the trend.
For example, we know that parts of the Greenland ice sheet increased by 50 feet over 50 years. We know this because the Greenland Society of Atlanta found two B-17 Flying Fortresses and several P-38 fighters 250 feet below the surface on which they landed during WWII. Does this mean that there was a massive build-up of ice across the entire region? Perhaps, but we do not have enough data to make a claim one way or another. But the event should clearly make us question the alarmist claims made by the warmers, particularly when the measurements they come up with come from questionable methods that are not supported by other means.
As far as I am concerned, the ice volume data is even less reliable than the global temperature data. It is made up of splices from different sensors and compilation algorithms and has yet to be shown to be accurate enough to tell us anything about the long term trends. Of course, even if it were accurate we would still need to go through several cycles to ensure that the long term trend is visible.