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I offered you a bottle of wine if you would go through my new article:
http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php

If you had done this, you would certainly not have written as you do.

One more time. Please look at PART 2 of my article, chapter 3.4.
This is where I explain that GISS inlcudes ocean in their station data series, and where I show a graphic of the ocean included.

So if anyone is aware of this, its me. The fact that you and others keep writing that you think im not aware of ocean data in GISS station “land” data might be my fault due to bad communication.

I wrote in my article PART 4:

“I am sure that the algorithm or specific method used by GISS to combine Land temperature and SST explains some of these apparently odd findings. But whatever the “algorithm” used by GISS is, can it be justified that GISS gradually weights the warm NH-Land graph more and more? And ends up with around 67% NH land fraction in 2007 although NH only has 40% land? Maybe, this algorithm or method deserves some attention?
”

And in the WUWT article i write: http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#more-22126

I write:
“In general GISS defends use of larger land fraction due to their 1200km zones around land stations reaching some Ocean areas. But this does obviously not explain a land fraction that appears to go from near zero to around 70% globally during the 20th century.
”

Now, Your article, Bob:
You focus on the similarities between CRU and GISS – i suppose to say that the resulting GISS is ok?
The thing is, CRU and GISS ends up rather alike. But in CRU data i find much more direct land data adjustment than for GISS. On the contrary for GISS, the direct land data adjustments are not so big at all (to my surprice) but in stead the GISS warming trend thats similar to CRU comes when combining the SST and “land”.

SOmething thats messy in al this is, that you seem to trust that CRU land is not ocean while GISS is… Yes yes, GISS has ship and island data included, but a BIG part of the GISS ocean area in their “land” data is obviousy from coastal stations. These stations are exactly the same as for CRU. So its nonsense to say “CRU is just land data”.
Just becasue CRU says that their coastal stations are land while GISS (the same) coastal stations covers huge ocean areas, you cant just treat the same data as if completely different.

I have raised some serious problems in data, and I know you disagree strongly, but i have not seen conving arguments from you, its not bad will.

K.R. Frank

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http://languagelog.ldc.upenn.edu/nll/?p=2290

Which claims that “petitio principii” is itself a poor translation of Aristotle and that it is better to say, either “asking the original point” or “assuming the original point” because these are more faithful to the original Greek.

Also they give OED examples of “beg the question” so it must have been more than just an Americanism at one stage. If you say, “begging the thing in question” it makes a lot more sense as well.

I can see why people avoid this phrase…

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Jo – sorry to nit pick but your Update 2 heading includes a total misuse of the useful phrase “beg the question”. Correctly used, it describes a logical fallacy where an assertion is assumed to be true without evidence other than the assertion itself. It is therefore a misuse, as in your case, to use it as if it meant “to raise the question”.

I believe that to use “beg the question” in a way that implies an unsupported assumption and nothing else is a pure Americanism, the rest of the world expects the word “question” to imply the existence of some actual question or other.

For what it’s worth, if you want formal logic you should say “petitio principii” which means “I demand to know the basis”. To the extent that “begs the question” means the same thing, the question being asked (either explicitly or implicitly) is an explanation as to how some particular factoid was produced (where it came from, what is the origin and methodology, etc). This is indeed the question that Jo is asking above, so I put it that she is using the term in exactly the correct manner.

An example of begging the question would be to say, “We know the IPCC’s view on climate change must be correct because its conclusions follow the science set out in Chapter 9 of WG1 of its 2007 report”.

Although this is a logical fallacy, most people would call it “circular reasoning” and “petitio principii” would not apply to this type of fallacy.

By the way, only Lawyers and Archeologists still practice the sort of formal logic that existed before George Boole. Sadly, no matter how good you logic might be, you still need a basis in some assumptions somewhere, thus “petitio principii” depends on the reasonableness of those assumptions (which cannot be determined by logic).

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The 36/64 ratio: Yes, I´ll change to this ratio that Nick has come up with. I wrote “qualitatively” because I was focussing on the fact that GISS did a down adjustment of the El Nino top while they up adjusted the years 2002-2007. This enables GISS to say that there is no stagnation in temperatures, can you see my point?

Your first question, the data i used: In the buttom of my article:
http://hidethedecline.eu/pages/posts/giss-global-temperature-trend-is-warmed-up-by-weighting-land-data-still-more-186.php
i wrote:

Data sources:
***********
GISS global Land + SST

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt
GISS land temp
http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt
Both HADISST and Reynolds can be seen using:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Last changed: 18th July, 2010 at 01:06:57

***************
These are the numbers officially presented by NASA / GISS.

Are these numnbers not to be used? (if so, why do NASA present them???)

Bob, if you ever have the time i would be very very very greatful and happy if you could go through it.
Not only too “find errors” but I would really be thrilled if you could also say your general opinion of the many topic and issues I raise:

http://hidethedecline.eu/pages/posts/the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-180.php

If you go through this I will send you a bottle of wine

You see, its not all reviewers who has your sharp eye, and neither Joanne nor I have any wish to come up with a “non-sensation”!

Finally: On “the Blackboard” I must say its a very destructive tone, and I mention this because that “mob”-like attitude in writings against Me, Anthony Watts, joanne etc. just has the effect that it takes all the motivation out of digging in to these things. But we really need people to dig into these things. If peoble are scared to be bullied from a mob-crowd like that, it will silence peoble.
You personally has kept a good tone, though.

K.R. Frank Lansner

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So based on that, it’s more of a 64/36 percent split. A quick look at any of the GISTEMP combined maps reveals that about 1% of the globe in recent years has no data, and that’s primarily over the ocean. And then, as Nick Barnes pointed out in his detailed description of GISS methods at Lucia’s, land surface data is extended about 100 miles from all land masses. Bottom line: the relationship is about 60/40, which was also confirmed in the thread at Lucia’s.

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Thankyou very much indeed for your constructive attemps to uncover the issues, its highly appreciated and i will try to answer and considder al your points.

In the mean time I have tried to assume that the GISS LST+SST graph is indeed based on a correct mix of landarea vs. ocean area.
Doing this allows us to retrieve and thus evaluate GISS pure land data:
http://hidethedecline.eu/pages/posts/are-giss-pure-land-data-important-to-understand-the-differences-between-giss-data-and-other-datasets-187.php

When retrieving such a “GISS pure land” data set, it becomes apparant that some known features of the GISS data set seems to originate from this “GISS pure land” dataset.

A dime for your comments!

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I’ve plotted dozens of global temperature anomaly comparison graphs and I don’t recall a divergence of land surface temperatures that you’re showing in the early part of the 20th century. So I attempted to recreate your graph. Unfortunately, I couldn’t duplicate that divergence from 1900 to 1920 or so.

I used GISTEMP combined (LST&SST) and GISTEMP LST data, both with 1200km radius smoothing. I used HADISST, not a combination of HADISST and Reynolds OI.v2 SST data as you had, since I was only interested in the early part of the data, and merging the two datasets adds another couple of steps. All data use 1951 to 1980 as base years for anomalies and are smoothed with a 60-month running-mean filter, centered on month 30. The data cover the entire term of the GISTEMP data, January 1880 to May 2010. And all of the data is from the same source, the KNMI Climate Explorer. Here’s my graph, using the same color coding as yours:
http://i27.tinypic.com/33e3kth.jpg

As you will note, the LST data does not diverge as greatly from the SST and combined data in the early 20th century. This could mean any number of things, but I did double-check the data I used in this graph. A question, what type of smoothing did you use, since it apparently wasn’t a centered 60-month running-mean filter? Otherwise, your data would not have extended for the full term.

I also created a second graph of that data, but in this graph I plotted the difference between the SST data and the two GISTEMP datasets. Note how the two residual curves “overlap” during the base years of 1951 to 1980. This can also be seen in your graph above and my attempt to duplicate it. This means your analysis is skewed by your election to use the standard GISTEMP base years of 1951-1980.
http://i28.tinypic.com/33kuhwl.jpg

So what happens if we use different base years, 1900 to 2000 for example? The next graph is a comparison of GISTEMP Combined (LST&SST), GISTEMP LST, and HADISST, with the base years of 1900 to 2000. Note that there is better agreement during the extended base period. The divergence between the SST data and the two GISTEMP datasets after the mid-1990s is influenced by my not using Reynolds OI.v2 SST data. Reynolds OI.v2 SST anomalies have a higher trend than HADISST. (And my assumption is that GISS uses it because of availability and not the higher trend. Monthly updates for Reynolds OI.v2 are available early in the month, while HADISST updates lag by at least one month.)
http://i30.tinypic.com/212bwxs.jpg

And the last graph is the comparison of the differences between the HADISST and the two GISTEMP datasets, using 1900 to 2000 as base years for anomalies. This graph should better represent the relationships you are expecting from the data.
http://i32.tinypic.com/2m3i7oj.jpg

Look reasonable?

In summary:

1.Please check your data, especially the land surface data.

2.Please check your smoothing to determine if it’s imposing a bias on the ends of your data, or simply use a standard centered x-month running-mean filter. So you lose 36 months of data on the ends–who cares?

3.Please try base years that represent the entire term of the data you’re examining, and:

4.From an earlier comment, you need to mask the land surface data.

Regards

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In any case, why get into this muddle when the perfectly serviceable “raises the question” does the job rather better? Why put a conceptual label of real value to logic and philosophy at risk when there’s nothing to be gained in so doing?

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