http://jhubert.livejournal.com/181274.html?view=844058#t844058

could Basil describe the way he finds the linear regression for his different segments, as I find very different value if I try a linear fit (least square) on the Hadley center since 2002 (up to 2008). I am using monthly means.

Regards.

Here’s MSU Global, Northern Hemisphere, Northern Extratropics, and North Pole temperature anomalies from 1978 to 2007. What diverges and what causes it?

http://tinypic.com/fullsize.php?pic=zswazc&s=3&capwidth=false

Here’s MSU Northern Hemisphere and North Pole temperature anomalies and trends from 1999 to 2007. The North Pole trend is more than double that of the Northern Hemisphere.

http://tinypic.com/fullsize.php?pic=mcb5md&s=3&capwidth=false

Here’s MSU Northern Hemisphere and North Pole temperature anomalies and trends from 1978 to 1997. Prior to 97-98, the North Pole and Northern Hemisphere trends are just about equal.

http://tinypic.com/fullsize.php?pic=2qjvwqw&s=3&capwidth=false

And then the whole overdone “Chow test” when the guy can look at his data and see the random walk in it, yet he insists on looking at 10 year patterns for breaks in a long term pattern. And he doesn’t understand the point about human decision for where to test break points as being a decision point.

It just scares me, when I see my side being so simple-minded.

(No offense.)

The selected base years of NINO3.4 anomaly data dictate the relationship of El Nino and La Nina data. Do they reflect their impact on global temperature? Probably not.

The term step change was used approximately 29 times in this thread. How could the 97-98 El Nino have caused a step change in global temperature if it was followed by a La Nina that lasted longer? Following that line of thought, pick an ENSO SST index (ONI, NCDC NINO3.4). I chose the NCDC data. Multiply the average 97-98 El Nino data by the number of months the anomaly was above 0 deg C. Then multiply the subsequent average La Nina data by the number of months the anomaly was below. The La Nina “deg months” (-33) are greater than the El Nino (25), so if there had been a step change it should have been toward cooling, not a warming.

For example, now shift the base line down 0.6 deg C, making the El Nino data more prominent, and run through the calculations again. The beginning and end shifts forward, too. The “degree months” of the El Nino (39) now exceed the La Nina (10). That would have caused a major positive step change.

Does this prove anything other than anomaly data is impacted by its base? No.

Refer to Trenberth et al (2000) “The Evolution of ENSO and Global Atmospheric Temperatures” if you question the role of the ENSO. Based on his linear trend, El Nino dominance raised global temperature 0.06 deg C from 1950-1998. Add in the immediate effects of the 1950 La Nina and the 97-98 El Nino, and ENSO is responsible for over 0.4 deg C of the rise in global temperature between 1950 and 1998.

Using 1950 as opposed to the mid-to-late 70s for the starting point significantly reduces the positive linear trend, since from 1950 to the 70s, the trend was negative. How much does it reduce it? If I had the statistical capabilities of your guest posters, I’d quantify it. Since I don’t, I won’t.

I agree with Nick Stokes here – you want to do more to justify your selection of change points. For a casual blog post, what you did is probably fine. But really to be persuasive, there’s more needed (perhaps this is coming in part 3?).

In your post above, you mentioned that the major point of your Chow analysis is that the global temperature trend is less than what’s given by a simple linear fit. You may well be correct. But you haven’t yet shown it. Is your significant result special among all the potential change points you could have “Chowed” down on (so to speak)? You seemed to dismiss this in a comment above as “a likely waste of time and resources.” But it’s crucial to establish that the change points you analyzed fit the data especially well – better than some number of other possible sets of change points, particularly if you want to conclude that it’s a better representation of trend than a simple linear fit.

1. It’s post hoc. You postulate a change in 2002 because the temperature then (smoothed) is equal to what it is now in 2008. But suppose, as some assure us, temperatures for the next few years go down. Similar analyses would find break dates right through the 1990’s. But if something really did happen, the timing can’t depend on when future people choose to do their analyses.

2. Discontinuous temperature. Economic analogy – OK you can have a discontinuous interest rate or share price. But suppose you are studying the number of houses. The rate of increase may change, but the actual number of houses can’t suddenly change. Heat is like that. You’ve postulated that in a month in 2002, the temperature rose suddenly by 0.2C. All other months were normal. Now 0.2C is what about a decade of AGW heating is supposed to achieve. Some people find that hard to believe. To expect that such heat would accumulate in a month, then go back to normal, is not plausible. And OK, you could say that the model is idealised, and the heating may have taken longer. But still, it just isn’t physical.

3. Too many degrees of freedom. You’ve compounded this by trying to model the 1998 El Nino rise separately. This creates a justified accusation of bias. But I think it also probably doesn’t make much difference, and just confuses the issue. Just two line segments would do.

4. More on degrees of freedom. With linear regression, you just fit two parameters, and the stat analysis tells you whether the slope is well determined, or whether other slopes might have fitted nearly as well. Only in the former case are you getting a good answer. Here you are introducing a wider group of functions – multiple line segments. You should really test whether your fit is uniquely the best of that class – that other perhaps very different looking models from the same set would not have done almost as well. That is the point of letting the model try to determine the breakpoint, as Menne has done. All your Chow test does is test whether a member of an arbitrary subset the large class is better than a member of another subset (the single line segment).

http://wattsupwiththat.wordpress.com/2008/03/15/sun-still-blank-no-sign-of-cycle-24/

Busy today, moderation may be slow. Don’t fret if comments don’t show up for a few hours.

John West – could not agree more

Anthony – many, many thanks for publishing and maintaining such an informative website. Your’s is one I visit very regularly and take the time to read thoroughly.

As others have pointed out – Sol remains very quiet.

REPLY: Thanks for the kind words. See latest post on “sol” at home page of website

Here’s an opinion piece by Joseph D’Aleo who takes it one step above what I did (includes a correlation with both PDO and AMO). I think this is what Anthony was referring to recently. It’d be nice to see an exposition on the same thing in a refereed journal.

http://www.energytribune.com/articles.cfm?aid=544

As far as going back further, Michaels had a post referencing a peer reviewed paper. The figure looks kind of cartoonish, so it may be for demonstration purposes only. I haven’t read the original paper.

http://www.worldclimatereport.com/index.php/2007/02/13/more-bad-news-about-el-nino/

Obviously, the farther back you go, the less certain the data, so finding a distinct link between PDO and global temperature pre-1900 may be tough.

This is all fascinating stuff. I’m not sure how any card-carrying scientist could let the phrase “settled science” slip through his or her lips when it comes to the global temperature trend and its causes.

Lee has been vague, refused to link to articles explaining how or why 1975 was selected in the graph he posted. Finally, when pressed, suggests we read the paper SteveMoscher selected. That paper may or may not explain any method used to pick the 1975 in the graph Lee linked. Moreover, it suggests that, yes, there is a way to get 1975 as a hinge, but that vanishes if we use the method proposed in the only specific paper Lee proposes. Lee hasn’t explained how this new analysis will affect Basil’s as yet unpublished post.

So what, precisely are we to make of Lee’s immediate accusation of cherry picking?

If he wants to debate whether or not hinge points exist, that’s fine. But, we can’t know what Basil is going to say in part III. Until Basil uses these hinge points to make some sort of conclusions, how can anyone accuse him of any such thing.

works in excell

http://www.beringclimate.noaa.gov/regimes/Red_noise_paper_v3_with_figures.pdf

the author also has an excell plug in which is fun to play with.
I’ll see if I can dig it up.

Also, I’m glad that folks finally got to the end of Menne’s paper. his method
folks will be used to do adjustments for the temperature series of ushcnv2.
so, who knows what that will produce.

Basil keep up the good work i enjoyed your post

A preview feature would be nice. I’ve wished for that myself too, and time or two.

Well, like they say, a picture is worth a thousand words. And now that I can see, visually, what you’ve been trying to say, I see your point.

Now try to see if you can see mine. If we start with your plot, the uninverted 12 month moving average, and start at the most recent point, and work backwards, at a point somewhere in late 2001 (yours is not labeled, but we can work it out from the tic marks, around #70), the 12 month MAV drops back to a point equal to where it is at the end of the graph (i.e. January 2008). Between those two points, there is no “net” cooling or warming. While the anomaly rises and falls between #70 and #144, at #144 it has dropped back to where it was at #70, indicating no net change over that time frame. That’s six years of no “global warming” even by your way of representing the data.

That is all I need to justify what I’ve done. My “scientific curiosity” makes me wonder if the most recent six years are somehow different than the 23 that proceeded. And so I expose my curiosity to the possibility of being wrong by performing a Chow test.

There is no philosophical or scientific basis for contending that what I’ve done is illegitimate. If your point is that the last six years are NOT different, in any meaningful way, than the proceeding 23 years, then state your point in the form of a falsifiable hypothesis and tell us how you would propose testing it.

Basil

Harsh words in a teeth-gritting post, John; a post I wish I could dismiss as a silly rant, if only for my own comfort… but I can’t, because it seems the unbelievable is real and something malignant has taken hold amongst us. The money hunger I can understand; money has always trumped morals amongst some. I can even understand a quest for personal power. I cannot understand the missionary zeal, or the slack-jawed awe, amongst the wider population which is feeding both.

I herewith endorse your concerns; and note to our host I believe your post, John, and my brief response here, is very much on topic and a necessary mix and caution to give urgency to the vital knowledge being generated here, and its dissemination through Watts Up With That?.

This debate and movement is not about the that actual climate, it’s about the take down of the democratic free enterprise societies on planet earth. They mean to replace it with a Marxist-Leninist brand of socialism in a world of serfs under the auspices of the United Nations.

I don’t meant to belittle the work being done to disprove the loons who are selling us this load of crap, but it simply is not the issue. The issue is global slavery vs freedom.

We need to get a lot more political about this war with the Climatites and elect people who will not fall for it. Canada has Stephen Harper who has stated that he knows it’s a lot a crap and that it will destroy our economy if we do what the Kyoto Accord demands. He will have to do something to appease the zealots who insist we ’save the planet’ or he will lost too many votes. My own provincial government in British Colombia has just levied a seven cent per liter on gas to “save the planet”. That would amount to about thirty cents per gallon.

Add to that the diversion of food stuff in favor of growing fuel for cars and trucks and we will have a world wide famine soon. All food will go up exponentially . The poor will starve and the more well off will go broke trying to keep up.

This is a global extortion the likes of which we have never seen before.