I’ve been away from WUWT this weekend for recovery from a cold plus family time as we have visitors, so I’m just now getting back to regular posting. Recently on the web there has been a lot of activity and discussions around the issue of the dropping of climatic weather stations aka “the march of the thermometers” as Joe D’Aleo and I reported in this compendium report on issues with surface temperature records.
Most of the station dropout issue covered in that report is based on the hard work of E. M. Smith, aka “chiefio“, who has been aggressively working through the data bias issues that develop when thermometers have been dropped from the Global Historical Climate Network. My contribution to the study of the dropout issue was essentially zero, as I focused on contributing what I’ve been studying for the past three years, the USHCN. USHCN has had a few station dropout issues, mostly due to closure, but nothing compared to the magnitude of what has happened in the GHCN.
That said, the GHCN station dropout Smith has been working on is a significant event, going from an inventory of 7000 stations worldwide to about 1000 now, and with lopsided spatial coverage of the globe. According to Smith, there’s also been an affinity for retaining airport stations over other kinds of stations. His count shows 92% of GHCN stations in the USA are sited at airports, with about 41% worldwide.
The dropout issue has been known for quite some time. Here’s a video that WUWT contributor John Goetz made in March 2008 that shows the global station dropout issue over time. You might want to hit the pause button at time 1:06 to see what recent global inventory looks like.
The question that is being debated is how that dropout affects the outcome of absolutes, averages, and trends. Some say that while the data bias issues show up in absolutes and averaging, it doesn’t effect trends at all when anomaly methods are applied.
Over at Lucia’s Blackboard blog there have been a couple of posts on the issue that raise some questions on methods. I’d like to thank both Lucia Liljegren and Zeke Hausfather for exploring the issue in an “open source” way. All the methods and code used have been posted there at Lucia’s blog which enables a number of people to have a look at and replicate the issue independently. That’s good.
E.M Smith at “chiefio” has completed a very detailed response to the issues raised there and elsewhere. You can read his essay here.
His essay is lengthy, I recommend giving yourself more than a few minutes to take it all in.
Joe D’Aleo and I will have more to say on this issue also.
Bernard J. (04:52:40) :
I sympathise with what you are trying but it’s not going to be. Not everything the warmists say is wrong some of it is just not relevant. The article of tamino is just a distraction he knows as well as anyone I suppose that 15 0r 30 years is just a blip.
http://www.foresight.org/nanodot/wp-content/uploads/2009/12/histo3.png
Here is 8000 years of Holocene it’s obvious from this perspective that there has been a steady downward trend in temperature that became steeper 3000 years ago and the recent warming just another blip of “noise”. Tamino does not want us thinking of it like that but just for us to look at the past 30 years and get very scared.
Bernard
As a layman, it seems odd to talk about a series of thermometer readings in terms of signal processing.
Firstly, there is an assumption that a ‘signal’ is actually present, which implies an a-priori attitude. OK when you are talking about a deliberate human communication buried in static interference, but otherwise?
We all know that ‘signal’ has all the characteristics of ‘noise’ unless you know in advance what you are looking for, and what form it might take.
So what are the climatologists looking for? Changing climate? Yet, after fifteen years they detect ‘nothing significant’ in these strings of temperature readings.
Hm.
Bernard J. (15:51:56) :
Tamino had this to say on the subject:
Who is Tamino? And why does he hide who he is?
Bernard J. (15:51:56) :
I did answer your question. I just didn’t give the answer you wanted. And that answer isn’t needed. Sorry, I won’t be giving that. I won’t step into your trap. I don’t want to get into arguments over statistics since one can make statistics say anything they want them to.
If 15 years isn’t a good time period for you then let’s make it 1500 years. You won’t have to split hairs then over statistics on a time scale you—or should I say Tamino and not you—say is too short. You’ll find that it was warmer on earth 1000 years ago than now.
I don’t want to play your piddly game. Because no matter what answer I give you’ll go back to manmade co2 is causing dangerous global warming, and you have Tamino’s work to prove it—that is your mantra.
If there is any further problem you have with no statistically significant warming over the last 15 years then please contact Phil Jones about it since he also is saying that.
Bernard J. (04:52:40) :
As AAiM has gone conspicuously quiet on this, could you do this Jan?
Wrong.
I just came here to check tonight. I don’t sit in front of my computer with this page open on it 24 hours a day.
Jan Pompe (05:51:42) :
I have no interest in doing that because I don’t disagree with what Tamino has done.
I DO NOT DISAGREE WITH THIS:
“The simple fact is that short time spans don’t give enough data to establish what the trend is, they just exhibit the behavior of the noise”
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You always have an interesting way of answering.
I am impressed, again.
It really is a simple question: given the noise in the modern temperature record, what is the shortest span of time required where one can say, with at least 95% confidence, that a signal might be expected to rise above said noise?
There has been an awful lot of noise from those who are responding to my question, but thus far there has been no signal at all rising above the clamour.
Let me put it this way: if it emerges at the end of this year that there is “significant” warming since 1995, but not from 1996, what does this mean?
If, for the next 40 years, the same pattern emerges, where warming can be “significantly” identified for any period longer than about the latest 15 years, what does this mean?
Will no-one seriously attempt to answer the question?
Bernard, did you miss Smokey’s good value reply?
“There is no skeptic “cause”. There is scientific skepticism, and it must be kept in mind that skeptics have nothing to prove. Even so, here is a cooling trend of less than 15 years data: click”
Err, Smokey, you do know what statistical signifiance means, right? Sure, there are trends on timescales of less than 15 years, and indeed you’ll be able to find trends over almost all timescales. The question is, if a 15 year trend is not statistically significant, why should that 6 year trend be (the graph ends in 2008)?
If you plotted that graph from 1995, all the lines would be pointing up. Still wouldn’t be a significant trend though.
Besides, I don’t really know what the fuss is about, since ‘statistical significance’ should really read ‘statistical artefact’ in which the 95% level is fairly arbitrarily chosen. Even if a trend were statistically significant at the 95% level, there’s a still a 1 in 20 probability that it’s happened by chance.
What’s more, beyond statistics there must be a physical reason for every fluctuation in the average temperature of the Earth and statistical significance is just a tool for working out whether what you see matters on longer timescales.
Stu (02:06:59) :
“Err, Smokey, you do know what statistical signifiance means, right?”
Ask Phil Jones. He made that statement regarding the flat temperatures over the last fifteen years. Or was Jones wrong?
Bernard J. (22:57:00) :
It really is a simple question:
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It is so simple we have other more interesting things to do.
Bye now.
Smokey (06:32:55) :
What these guys don’t want to say is that if the graph had been more aggressive in in either direction statistical significance would have been found. But since it wasn’t upward enough they can’t claim global warming is happening. But if there had been statistical significance in the last 15 years i think there would be most global warming believers who would be pointing out that warming in the last 15 regardless if it was a long enough time frame or not.
Why do I know this? Experience.
And also, look at how excited some of them are about the fairly high anomaly in UAH for the past 2 months. A 2 month time frame is enough for some of them.
AAIM (06:41:17, 15 Mar 2010).
As I said elsewhere, the magnitude of the signal and the magnitude of the noise operate together to determine the magnitude of the period required for the signal to be statistically discerned over the noise.
It’s a simple relationship, and I am simply asking you to determine what period of time is required in order to be able to say with a degree of statisitcal confidence that a temperature signal is discernable from the noise.
If the signal is such that it takes more than 15 years to pick from noise, this makes no difference to the long term significance if the rise is relatively constant. Indeed, such a rise may still have profound implications for societies and for the biosphere within one human lifetime – but this brings us back to the original question of the noise and the signal, and I really am waiting to see what method the statisticians here believe is appropriate to quantify the time needed to discern one from the other.
To clarify, by “long term significance” I meant “significance” in an implication sense, not a statistical sense.
Smokey said:
“Ask Phil Jones. He made that statement regarding the flat temperatures over the last fifteen years. Or was Jones wrong?”
Phil Jones said:
“I also calculated the trend for the period 1995 to 2009. This trend (0.12C per decade) is positive, but not significant at the 95% significance level.”
Phil Jones said the trend is 0.12C/decade. 0.12C/decade is not flat. Smokey is wrong.
By the way, Smokey also said:
“Tamino cherry-picks 15 years because it supports his CAGW agenda.”
No he didn’t. If you look, you’ll see that he analysed trends for start years going back to 1975, looking for the shortest period that gives statistical significance.
Again, Smokey is wrong. I know I said that already, but it bears repeating.