## Steig’s “Corrections”

Roman M has already done one post on the impact of the Harry error. Ryan O has also done so [see comment here]. As has Steig.

I show below some graphics that I’ve just done on AWS recon trends.

At Steig’s website, he now states:

awsreconcorrected.txt is a correction to the above file, using corrected AWS data at two AWS stations. See the note under “Raw Data”, below. [Note that corrections have been made to AWS stations “Harry” and “Racer Rock”. See the READER web site for details. ] The resulting differences in the reconstruction are too small to be discernable in Figure S3, or in the trends for individual stations given in Table S1 in the Supplementary Information that accompanies the paper in Nature. (Corrections for all stations in the Table S1 are in the third decimal place (that is <0.01 degrees C/decade)). The mean trend for Antarctica changes by less than 0.004 degrees C/decade. The mean trend for West Antarctica changes by less than 0.02 degrees C/decade. Note also there is a typo in Table S2. The correct coordinates for station ‘Harry’ are 83.0 S 238.6 E. Note that none of these corrections have any impact on the satellite-based reconstructions; no AWS data were used in those reconstructions.

Several different trend period are used in the article. In the main text, Figure 4 uses a period of 1979-2003 as shown below (for AVHRR data.)

Steig Figure 4e. Comparison of reconstructed and modelled mean annual temperature trends (degrees Celsius per decade) for the periods; e–h, 1979–2003.

Figure S3 referred to above shows trends for AWS stations, but for incompatible periods: left – 1957-2006 and right 1969-2000.

Figure 2. Steig Figure S3 excerpt.

To “facilitate comparison” with Steig et al Figure 4, I calculated trends for the 1979-2003 period for the AWS reconstruction, with trends being illustrated more or less emulating the style of Figure S3 (I’ll post scripts up in the comments.) I’ve labeled some of the stations in play.

Harry is the station with the largest 1979-2003 trend in the entire reconstruction, as you can readily see below. Harry, Racer Rock, Clean Air, Elaine and Butler Island, have all been mentioned in recent comments with amendments of one type or another being required to the first four stations (though only Racer Rock and Harry changes are incorporated in the present update.)

The Harry trend (the one with the screwed up data) is a very distinct feature in West Antarctica.

Figure S3. Spatial pattern of temperature trends (°C/decade) from reconstruction using AWS data. a) Mean annual trends for 1957-2006. b) Mean annual trends for 1969-2000, to facilitate comparison with ref. (2).

I just downloaded the “corrected” versions from Steig’s website, yielding the plot below. In this period, I submit that it is clearly not the case that the “resulting differences in the reconstruction are too small to be discernable”.

Figure 4. 1979-2003 trends in Steig AWS reconstruction (corrected).

I’ll experiment a bit tomorrow to see why there are such differences in results for the 1979-2003 period and the 1969-2000 period that Steig discusses.

1. Tom Gray
Posted Feb 6, 2009 at 5:20 PM | Permalink

It seems to be very strange that the large result at Harry in the original reconstruction did not draw interest in obtaining an explanation.

2. Stuart Harmon
Posted Feb 6, 2009 at 5:23 PM | Permalink

once upon a time you dressed so fine
now you don’t talk so loud
how does it feel to be on your own.

Sorry watching BD at Newport

So your are a statistician I am an engineer so please give me a chance:-

Lets say the spread between the maximum and minimum temperature in the Antarctica is 55 degrees in one year?

From the analysis you have provided above the trend/ is o.o2 degrees per decade.

Lets say the maximum spread one day is, my guess 20 degrees.

Assume there are 10 temperature measuring stations.

My guess is the error would be 1 degree ie 5%

So this is not testing the strength of steel the variables are huge.

So my guess is that Professor Steig could be wrong by a factor of 50 plus or minus.

Sorry about the guesswork but Mr GS thinks guessing is good.

If the above is total garbage please don’t post.

3. Steve McIntyre
Posted Feb 6, 2009 at 5:28 PM | Permalink

For CA readers who are looking at individual stations – could I put Uranus Glacier, Ferrell, Limbert on your radar screens.

• Gary A.
Posted Feb 6, 2009 at 5:52 PM | Permalink

Re: Steve McIntyre (#3),
All three of the stations Uranus Glacier, Ferrel, Limbert do not have data for the periods 2003, 2004, 2005, 2006. For what it is worth.

• SidViscous
Posted Feb 6, 2009 at 5:54 PM | Permalink

Interesting the kind of things you can find with a google search.

http://www.mmm.ucar.edu/events/antarctic06/presentations/colwell.ppt#325,23,Questions

Always neet to see soome of the campbell stuff as I have experience with them in other fields.

Also interesting seeing people doing the same things we are, upgrading from the CR-10X to the CR1000. In case anyone cares, shouldn’t be to bad as far as data continuity. The same sensors and related electronics (Multiplexers, signal conditioners) are used in the same way. I’ve done some work in transitioning between the two and don’t see any major disontinuity in the data, well rather if there is any it’s HUGE, which immediately tells you you’ve done something wrong so you fix it.

• Jeremy
Posted Feb 6, 2009 at 8:05 PM | Permalink

Re: SidViscous (#7),

Bizarre presentation there. The second-to-last frame is a jpeg of a google search for IGRA, which they take to mean Integrated Global Radiosonde Archive

• Jeremy
Posted Feb 6, 2009 at 8:10 PM | Permalink

Re: SidViscous (#7),

Bizarre presentation there. The second-to-last frame is a screenshot of a google search for IGRA, which they take to mean Integrated Global Radiosonde Archive… but the first result is “International Gay Rodeo Association”. Why they felt the need to include a screencap of that is bizarre.

There seems to be no mention of the station Ferrell in that presentation. However, it was interesting to note that Uranus Glacier and Limbert both had to be dug out of the snow, and they’re both near the ocean on the “warming” peninsula.

• Tolz
Posted Feb 6, 2009 at 6:38 PM | Permalink

Hmm. Are you supposed to notify BAS and RC to put those on their radar screens as well, just in case?

• mugwump
Posted Feb 7, 2009 at 5:48 PM | Permalink

Re: Steve McIntyre (#3), from the revised Fig 4 above, Ferrell looks very suspicious, as does the big red unlabeled station next to it. All around is blue.

4. Joel
Posted Feb 6, 2009 at 5:28 PM | Permalink

Why? It showed exactly what they expected. I wouldn’t doubt that someone looked at Harry, said “Eureka!” and proceeded to build a paper around it.

5. Joel
Posted Feb 6, 2009 at 5:29 PM | Permalink

Sorry, “4” is relying to “1”.

6. Alan S. Blue
Posted Feb 6, 2009 at 6:06 PM | Permalink

There’s a station named Doug that’s practically on top of Harry since ’94.

Are all of these newer stations failing to meet muster due to being more recent additions?

7. Posted Feb 6, 2009 at 7:06 PM | Permalink

According to Gavin: “The trends come primarily from the long-term manned stations. The spatial pattern comes from the satellites”.

However significant emphasis was placed in Steig et al on “Independent data” from two AWS stations. So how robust are the trends from the examples provided. Lets have a look at Siple and Byrd mentioned on page 461.
Steig et al indicate trends of 1.1+-/- 0.8 degrees Celcius per decade for Siple, and 0.45+/- 1.3 degrees C per decade for Byrd stations (wow a 1.3 degree C error!) which feature prominently in figure 3b of the paper.

Byrd and Siple trends were constructed by splicing short intervals of AWS data with 37-GHz satellite observations.

See GISS charts HERE for Byrd and HERE for Siple.

Information on Byrd is available from University of Wisconsin HERE. Of note in the photos is the variable tower height above the snow surface over the years and that Byrd station is powered by an “RTG”: radioactive thermo-electric generator rather than batteries. I was unable to access the field reports links so could not look at the station history in detail.

There appear to be problems with the links at the University of Wisconsin website for Siple. I have passed on an email on this to their staff. (Perhaps Super Grover has been there already and they are busy updating).

Given the size of the errors and patchiness of data from these AWS stations along with the data problems arising from variations in snow depth and other problems, I can only conclude that the trends are not very robust at all and they do not provide any evidence for significant warming.

• JS
Posted Feb 6, 2009 at 7:28 PM | Permalink

Re: MarcH (#10), are those error bands the standard error? If so then you are actually looking at a 95% confidence interval of (-0.5, 2.7) for Siple and (-2.15,3.05) for Byrd. Does anyone know how they calculate the error bounds for the RegEM method?

• Posted Feb 7, 2009 at 2:38 PM | Permalink

Re: JS (#11),
These errors ranges are taken directly from the paper. P 461

8. Hugo M
Posted Feb 6, 2009 at 8:36 PM | Permalink

Within “ftp://amrc.ssec.wisc.edu/pub/aws/10min/rdr”, you will find a file “readme.updates”. Looking there for Byrd reveals:

04/02/03 — Data for Byrd (8903) were replaced for March, April, November and December, 2002. The wind direction was corrected.

03/28/03 — Data for Byrd (8903) were replaced for November and December, 1999 and January – September, 2000. The wind speed and direction were not correct and were eliminated.

Concerning Harry:

02/19/04 — Data for Harry (8900) have been added for July, 2000. The file for July actually contained August data.

After some date, some stations, apparently including Byrd have been equipped with a dT sensor. This could be the third temperature sensor sometimes visible on some of the photographed stations, mounted below the big electronic box. “readme.format” says, that the dT signal, if present, is in the 8th column in raw data files

Besides low temperature variance, this could give another hint to stations buried in snow. At least it will clearly mark the periods, when the dT sensor had been buried. Probably there is distinct pattern.

“Readme.format” also contains hints on data erroneously attributed to two stations. If detected, they provided two files with correct station ids, both containing an “x” somewhere in the filename. Possibly the guys condensing these raw data files into antarctic READER monthly means simply missed some of these?

10/01/02 — The data labelled 89110799.r (Gill) is actually for 89120799.r (D-57). The labels have been corrected and Gill for July will be added.

9. Mike Smith
Posted Feb 6, 2009 at 8:54 PM | Permalink

Ferrell Station (ARGOS ID 8929)

WMO Number: 89872
Latitude: 77.860 degrees South
Longitude: 170.819 degrees East
Altitude: 46 meters
Model Type: AWS2B

History

1980 Dec: “…Station was half buried and RTG really frozen solid. Helo dropped us off and returned to McMurdo. Took us an hour digging out RTG and tower.”

1983 Jan: “Field calibrations were not done because the Argos test set was on the Glacier for the trip to Franklin Island. The beacon transmitter was installed. The station was in excellent condition and snow accumulation from 12/80 to 1/83 was 110 cm.”

1983 Dec: “AWS 8907 HAD CEASED OPERATING ON AUGUST 22 1983. INSPECTION SHOWED THAT WATER FROM MELTING SNOW HAD CORRODED ONE EDGE OF THE CPU BOARD. THE DAMAGE ACTUALLY BROKE ONE OF THE TRACES ON THE BOARD. THE BOARD WAS CLEANED AND REPAIRED. ALSO, THE AWS BOX WAS SECURED SO THAT SNOW COULD NOT AS EASILY GET INTO THE BOX.”

1985 Jan: “AWS 8907 HAD CEASED OPERATING IN OCTOBER, 1984. THE PROBLEM WAS TRACED TO A DEFECTIVE COMPONENT IN THE 10V POWER SUPPLY TO THE TX OSCILLATOR.”

1986 Jan: “The AWS unit was replaced with the same ID and the B format ROM on 16 January 1986.”

1987 Jan: “By 28 Jan 87 all sensors were operating.”

1991 ???: “No reception from July to mid-October.”

1992 ???: “Not received in August”

1993 Jan: “Repaired 13 January.”

1994 ???: “OK.”

1995 ???: “OK.”

1996 ???: “OK.”

1997 ???: “Aerovane operated intermittently July through September.

1998 ???: “Aerovane “frozen” occasionally May through August. Station stopped transmitting 25 August due to low battery voltage.”

1999 Jan: “Batteries were installed 21 January. Delta-T not functioning properly. Station stopped transmitting 14 March.”

2000 Jan: “New station installed 1 February. Erratic transmissions occurred by mid-February and the station stopped transmitting 11 March.”

2004 Nov: “Raised tower.”

2005 Feb: “Site visited. Acoustic depth gauge installed at 1.06 m above the surface.”

2006 Jan: “Site visited. Acoustic depth gauge raised to 1.08 m above the surface.”

2006 Oct: “Site visited. Acoustic depth gauge raised to 1.218 m above the surface.”

10. Mike Smith
Posted Feb 6, 2009 at 9:00 PM | Permalink

Also FWIW, note that in the Ferrell Site report of 1984, the laboratory calibration table has a delta of 0.75 C between AWS and MEASURED.

Ferrell Site Report 1984

11. Edward
Posted Feb 6, 2009 at 9:03 PM | Permalink

MArch #10
The manned station data for all 65 manned Antartica stations can be found at:

This was provided by Gavin at RC from Steig’s study. It was in post #30 at http://www.realclimate.org/index.php/archives/2009/02/antarctic-warming-is-robust/

I looked at the McMurdo manned station data and there did not seem to be much of a warming trend over the period of 1956 to Jan 2009.

Steve: We compiled READER data well before that and that’s what was used in analyzing Harry and other stations.

12. bender
Posted Feb 6, 2009 at 9:05 PM | Permalink

The adjustment dramtically shifts the geometric centre of the warm patch, from “west Antarctica” to just the peninsula. That is not a trivial change. It’s the difference between “continental-scale” warming and “local” warming.

Of course, either is consistent with GCM predictions … because nothing is inconsistent with them. They’re irrrrefutible.

• Jon
Posted Feb 6, 2009 at 10:12 PM | Permalink

Re: bender (#19),

snip

Stratospheric warming, rapid sustained warming on the order of several degrees C in years, monotonic warming, etc. are all inconsistent with the AR4 runs. There are enough legitimate issues with the models that one doesn’t need to invent them.

snip – enough bickering on both sides

• Jon
Posted Feb 7, 2009 at 3:07 AM | Permalink

Re: bender (#18),

I understand the snip, I guess [Psst- I don’t at all. You’re letting a comment stand that is the essence of what I described], but:

[Steve: foodfights bore me; if I miss something, email me or put a pointer rather then continue it. If I left some foodfight in, it’s not intentional.]

bender, if you’d like to get in touch with modelers to improve process,es I’m happy to help.

There is a big target to hit and you’re swinging at bystanders.

13. Gary A.
Posted Feb 6, 2009 at 9:14 PM | Permalink

Ferrell has had 3 Argo’s ID’s

8907 12/12/80 – 8/27/92
8934 1/13/93 – 12/31/96
8929 current

8907 was also Mt. Howe (1/26/93 – 11/11/93) and Cape Densison (1/1/95 – ?)
8934 was also Port Martin 1/26/91 – 1/9/92

14. Ryan O
Posted Feb 6, 2009 at 9:18 PM | Permalink

I’d be interested in your playing with the 1979-2003 period, too, Steve. I’m curious if it may be a case of cherry-picking endpoints to produce a neat looking graphic.

15. Edward
Posted Feb 6, 2009 at 9:49 PM | Permalink

The Ferrell AWS data can be found at

It shows Monthly data from Jan 1981 to August 1998. Between that period there are only about 12 months with missing data and those are all in the months Aug-Dec

There is no data between Sept 98 until Jan 2001. Full 2 years worth of data for 2001+2002 and then nothing since then.

• Hugo M
Posted Feb 8, 2009 at 3:06 PM | Permalink

Re: Edward (#21),
Edward observed on Ferrel AWS met reader data set:

[…] It shows Monthly data from Jan 1981 to August 1998. Between that period there are only about 12 months with missing data and those are all in the months Aug-Dec
There is no data between Sept 98 until Jan 2001. Full 2 years worth of data for 2001+2002 and then nothing since then.

At Feb 7, 2009, I started to archive the whole 10r directory from
amrc.ssec.wisc.edu/pub/aws/10min/rdr. Grepping through these files showed me, that in fact every month between 2003-2005 is almost completely covered by the Ferrel (ID 8929) data set. Cum grano salis, these 48 files provide 210480 entries, of which 174133 (or 78%) are valid (as of no 444 inband error marking). About the same relation holds for each month in that range. And each and every file header consistently contains “Station : 8929 Ferrell”. There is no hint in the various readme files, why these entries should be regarded erroneous.

When it comes to 1999 data set, there are 12 files for ID 8929. But, e.g. “1999/89290299.r” says:

Feb 99 Station : 8929 Willie Field
Lat : 77.87S Long : 167.02E Elev : 20 M

Again, no mention any transmitter was changed or something of that range. Assuming Willie Field is affected by the same type of transmitter specific personality disorder as Harry, then Ferrel would get 12 additional month worth of 52584 entries, 37724 of which valid.

E.g., “2003/089290103.r” is in line with the diagnosis:

Jan 03 Station : 8929 Ferrell
Lat : 77.88S Long : 170.82E Elev : 45 M

After Willi Field wandered a couple of miles, he decided to become Ferrel. Or was it the other was round? May be no. There are even more personalites involved. According to 2000/89200100.r:

Jan 00 Station : 8929 Uranus Glacier
Lat : 71.43S Long : 68.93W Elev : 780 M

360-68.93W is 291E, quite far away. But in Januar 2000, “2000/89290100.r” says:

Jan 00 Station : 8929 Willi Field
Lat 77.8S Long 167.02E Elev: 20 M

16. Posted Feb 6, 2009 at 10:21 PM | Permalink

Please correct the data before the West Antarctic Ice Sheet collapses! e! Science News provides a heads-up on a report published today in the respected journal Science:

If global warming some day causes the West Antarctic Ice Sheet to collapse, as many experts believe it could, the resulting sea level rise in much of the United States and other parts of the world would be significantly higher than is currently projected, a new study concludes. The catastrophic increase in sea level, already projected to average between 16 and 17 feet around the world, would be almost 21 feet in such places as Washington, D.C., scientists say, putting it largely underwater. Many coastal areas would be devastated. Much of Southern Florida would disappear.

The report will be published Friday in the journal Science, by researchers from Oregon State University and the University of Toronto. The research was funded by the National Science Foundation and other agencies from the U.S. and Canada.

“We aren’t suggesting that a collapse of the West Antarctic Ice Sheet is imminent,” said Peter Clark, a professor of geosciences at Oregon State University. “But these findings do suggest that if you are planning for sea level rise, you had better plan a little higher.”

I’ll feel alot more comfortable if the corrected data shows reports of warming in Antarctica are due to data errors, misinterpretation, or manipulations.

• tty
Posted Feb 7, 2009 at 2:27 AM | Permalink

Re: Ira (#23),

Don’t get too excited about that story. What they have done is just to refine the traditional figure for sea-level rise from a collapse of the WAIS (West Antarctic Ice-sheet) a bit by estimating geoid changes etc.
Incidentally the “traditional” figure of 16-17 feet sea-level raise is too high. It’s based on the BEDMAP data (Lythe et al. 2000) which uses an urealistically high figure (0.917) for the average density of glacier ice and also presumes that all ice in West Antarctica would melt. This of course won’t happen, a (geologically) rapid melt of the WAIS would be due to drawdown of the maritime part of the ice-cap and would leave residual icecaps on the land areas. The highest point in Antarctica (Vinson range, 5195 meters) is in West Antarctica. Anybody think that is likely to become ice-free?

17. George M
Posted Feb 6, 2009 at 10:44 PM | Permalink

So, the paper is based on statistical crunching of satellite temperature data, which is compared to the AWS and manned stations for confirmation of accuracy. A cursory reading of the maintenance logs of the AWS certainly does not provide any confidence of their accuracy, so what do we know about the manned stations? Isn’t an A. Watts survey of them needed to get a proper handle on that? From the few photos of the manned sites, and the one or two verbal descriptions of maintenance there, no really good vibes about them either, so far. Then there is the information from the satellite operators which says their data is only accurate during certain seasons?? How on earth can this combination produce the final accuracy which seems to be indicated by the paper? No wonder each new look at the “data” gives a different result, a red flag right there.

18. Edouard
Posted Feb 7, 2009 at 2:03 AM | Permalink

Since the real world gets colder than the best IPCC-guesses we need new headlines. This might be just as scientific as cherrypicking for any warming anywhere on earth. Am I the only one who is a little bit disappointed. I thought there was more real science behind global warming :-(((((

19. Laurens416
Posted Feb 7, 2009 at 2:30 AM | Permalink

Gavin Schmidt has another message for the hordes on this web site:

[Response: I see no evidence for that at all. I see a reluctance to have hordes of know nothings magnify every typo into federal case, but all the good scientists I know welcome constructive advice from any quarter. The key is the word ‘constructive’ – scientists are mostly driven by the desire to understand something about the world, and help in doing so is always appreciated. People whose only contribution is to malign or cast aspersions, whatever their background, are simply of no use in that endeavour. – gavin]

• Alan Wilkinson
Posted Feb 7, 2009 at 2:58 AM | Permalink

Re: Laurens416 (#27),

People whose only contribution is to malign or cast aspersions, whatever their background, are simply of no use in that endeavour. – gavin

Both sides have individuals demonstrably able to contribute both science and aspersions – most notably including the author of that comment.

Of course trends can be known a lot more accurately than individual measurements, just as means can be. In this case of course the confidence in the trend is vastly less precise.

• ClimateDoggle
Posted Feb 7, 2009 at 3:08 AM | Permalink

Re: Laurens416 (#27), And that comment contained:

Response: I see no evidence for that at all. I see a reluctance to have hordes of know nothings magnify every typo into federal case,

It annoys me greatly to see this common use of the word “typo” in the reference to any errors. The last lot certainly were not typos.

• nevket240
Posted Feb 7, 2009 at 4:07 AM | Permalink

Its reffered to as “blame shifting”. School bullies perfected it.

regards

• EW
Posted Feb 7, 2009 at 5:09 AM | Permalink

Re: Laurens416 (#27),

This has an eerie sound for me, the “constructive critics” connotation. I remember vividly. that under the Communist rule, the official point of view was that constructive critics was welcome, but no maligning or casting of aspersions and otherwise undermining of our way to progress would be tolerated. And, of course, what was or was not constructive was decided afterwards, regardless of the critic’s original intent…

20. Louis Hissink
Posted Feb 7, 2009 at 2:39 AM | Permalink

Steig”The mean trend for Antarctica changes by less than 0.004 degrees C/decade”

We have instrumentation to this resolution?

This is simply BS!.

21. VG
Posted Feb 7, 2009 at 2:44 AM | Permalink

It would be nice to know in simple terms (after all the #@**)does this “Harry” problem show that in fact there is significant Antarctica warming or not? Judging by the size of temp in Harry in pic 1 compared to pic 2 it certainly suggests no. In which case, The Nature paper should be withdrawn

22. Louis Hissink
Posted Feb 7, 2009 at 2:48 AM | Permalink

Just a totally, left field thought, but if the ice caps did melt, (only at the south pole), then isotatic requilibriation of the crust would probably mean a zero change in you know what.

This surreal ideas occur among geographers, occasionally when wandering into weather stations, to add meaning to their post modernist obfuscations. In other words they haven;t a freaking clue.

23. Jeff
Posted Feb 7, 2009 at 3:04 AM | Permalink

@#8: There’s a station named Doug that’s practically on top of Harry since ’94.

Well, what can you expect? All that isolation for years on end, no female company… 🙂

24. Posted Feb 7, 2009 at 6:47 AM | Permalink

Looking back to the 2004 NASA paper of Gavin Schmidt and Drew Shindell, the 2009 paper seems to be very much the result of a self-fulfilling prophecy stated in the earlier paper, a Global Climate Model showing Antarctica warming, alongside a standard map of Antarctica cooling. It seems as if Schmidt et al filed away the thought “the Antarctic data must be faulty somewhere” because they all believed in Global Warming. So when data surfaced that appeared to validate warming for Antarctica too, they were naturally keen to publish.

Now consider a more subtle picture, with several factors at work
(1) the planet has, at least from 1970-2000, been warming overall, and the resultant warmer ocean currents have poured in around the appropriately named Racer Rock and have warmed the largely maritime Peninsula
(2) volcanic activity, known in the area, may have contributed
(3) due to the slight lessening of cloud cover in this time frame, while the rest of the planet has been warming, ice-sheets have higher albedo than clouds and tend to cause cooling
(4) dry air helps the cold spikes of winter temperature when cloud cover abates
(5) these winter spikes could have been removed from the record as being too “anomalous”
(6) the majority of the planet has been warming, and some of this rubs off on Antarctica
(7) even with corrections, temperatures may have overall stayed pretty level – but – NO sign of the huge warming predicted by the models.

I follow the unearthing of data to confirm, or challenge, with interest. What seems to matter is the patterns, not just a single trend with the one-bullet headline “ANTARCTICA WARMING”. Perhaps Steig’s paper will eventually show that there has not been so much cooling as many skeptics have been wont to believe. But also, the expected drastic warming seems significant in its absence.

• Andrew Parker
Posted Feb 7, 2009 at 12:45 PM | Permalink

This brings to mind a statement by a climatologist who proposed, many years ago (and for this reason I cannot recall his name), that global warming might trigger a new age of glaciation, not to be confused with a new ice age. Would this relate to the statement that “all weather is local?”

25. wmanny
Posted Feb 7, 2009 at 8:11 AM | Permalink

[#27]

I tried, unsuccessfully, to post the following at RC. Gavin, who often does engage, has not done so this time, though perhaps he is not on duty at the moment.

“People whose only contribution is to malign or cast aspersions, whatever their background, are simply of no use in that endeavour.”

In context, it would seem you are referring to Steve McIntyre. Has he been of no use to the scientific endeavor in this case?

26. Hu McCulloch
Posted Feb 7, 2009 at 8:43 AM | Permalink

I’m suspicious of Steig Figure S3a (Fig 2 above), which is supposed to show reconstructed AWS temperature trends for 1957-2006. Here’s the graph I posted early Wed AM of Steig’s reconstructed AWS data for Racer Point, the leftmost point in the diagram, out at the end of the Peninsula. BAS revised the Racer Point data within 12 hours of my post.

Clearly if the 2004-06 are included, the trend is strongly negative, although if the series is truncated at 03, there is an uptrend. So I think S3a must have been tampered with to eliminate a “wrong” trend, at least in this case.

It would have helped if the Steig team had actually looked at their AWS Recon series before publishing trends based on them. If they had, this error (if not perhaps the several others that have been identified) would have been apparent immediately.

• Phil.
Posted Feb 7, 2009 at 8:55 AM | Permalink

Wouldn’t the elimination of points with greater than 10ºC deviation from climatology have fixed that?

• John M
Posted Feb 7, 2009 at 9:08 AM | Permalink

Re: Phil. (#40),

Wouldn’t the elimination of points with greater than 10ºC deviation from climatology have fixed that?

Why 10 degrees? Why not five or 20?

27. Cassandra King
Posted Feb 7, 2009 at 8:57 AM | Permalink

” hordes of know nothings”? How many know nothings does it take to make a horde I wonder? What is his definition of a ‘know nothing’?

I wonder why a scientist would refer to another person as a ‘know nothing’? The term puzzles me greatly and I find it worrying that a highly educated person would use such a term.

28. Posted Feb 7, 2009 at 9:02 AM | Permalink

#40, I assume that would only apply to sites that have independent climatology, which in this paper would be the manned stations.

29. Knut Witberg, Norway,
Posted Feb 7, 2009 at 9:14 AM | Permalink

snip – policy. sorry bout that

30. Fred
Posted Feb 7, 2009 at 9:27 AM | Permalink

Given the original and revised map graphs, the only thing that is “too small to be discernable” is the integrity of the opinion of the persons making that claim.

A five year old would be able to discern the differences in the two map grpahs.

31. Steve McIntyre
Posted Feb 7, 2009 at 9:28 AM | Permalink

#40. I think that the climatology test was a screen applied to AVHRR only.

32. Grant B
Posted Feb 7, 2009 at 9:51 AM | Permalink

#41 Cassandra King

I wonder why a scientist would refer to another person as a ‘know nothing’? The term puzzles me greatly and I find it worrying that a highly educated person would use such a term

Indeed. In Australia, as elsewhere, our government is talking about spending large amounts of our GDP for many years hence on “fighting climate change”. So it is important that we know the facts, how they are obtained, how they are analysed and how they are presented.

But I’m not a climate scientist. I merely have a PhD in Theoretical Physics (Statistical Mecahnics) obtained many years ago and long forgotten, so I clearly rank amongst Gavin’s “know nothings”. Nevertheless, this tawdry episode has been quite an eye-opener for me – it is quite appalling.

BTW has Steve ever invited a survey of the qualifications and disciplines of contibutors and lurkers of the “know nothings” to his blog? It might be interesting. Perhaps Naomi Oreskes could be contracted.

Steve: There are a LOT of PhDs that read and contribute to this site. For example, UC, Jean S, Roman M, Hu Mc are all statistics PhDs. It is not clear to me that many objective third parties would regard an isotope geochemist like Steig as being more qualified to carry out a statistical analysis of Antarctic time series than professional statisticians. If Steig was inspecting weather stations a la Anthony Watts, then the trips to Antarctica might be relevant, but it’s hard to see much in Steig et al that actually depends on site visits.

• David L. Hagen
Posted Feb 7, 2009 at 10:52 AM | Permalink

Re: Grant B (#47),
From RealClimate.org, Gavin Schmidt merely”:

. . .received a BA (Hons) in Mathematics from Oxford University, a PhD in Applied Mathematics from University College London and was a NOAA Postdoctoral Fellow in Climate and Global Change Research.

Amazing pronouncements for one who has no formal training in meteorology or climate science.

Steve: Puh-leeze. No one is contesting whether Gavin went to graduate school.

• mugwump
Posted Feb 8, 2009 at 5:17 AM | Permalink

Re: Grant B (#47),

BTW has Steve ever invited a survey of the qualifications and disciplines of contibutors and lurkers of the “know nothings” to his blog? It might be interesting.

I am more of a lurker here, but FWIW my PhD is mathematics, with a heavy dose of computer science and statistics.

Re: Hu McCulloch (#76), thanks for the pointer. Wiki has a good entry on stable distributions. For those who want the short summary: they arise from sums of independent random variables with fat tails, ie tails that obey a power law: $|x|^{ -( \alpha + 1)}$ for α > 0. These tails are “fat” because they decay much more slowly than the normal distribution tails which decay exponentially fast. What that means practically is events that are essentially impossible under a normal distribution are much more likely under a stable distribution.

If anyone doubts the importance of these seemingly arcane mathematical distinctions, I suspect the entire current financial crisis can ultimately be blamed on the use of normal distributions in place of stable (or similarly fat-tailed) distributions. There’s an article in the December Economist that quotes the Goldman Sachs CFO from 2007:

“We’ve seen 25 standard-deviation moves several days in a row”.

25 standard-deviation events just don’t happen. Ever. Their probability is essentially zero. If you see a 25 standard-deviation event, your model is wrong.

• Joel
Posted Feb 8, 2009 at 8:41 AM | Permalink

Re: mugwump (#83), Hello Mugwump,
I am a complete layman, but your quote of the financial analyst observing “25 standard deviation moves” might be misinterpreted in your comment. It looks to me like the fellow is describing several individual single standard deviation events over several days, whereas it looks like you are taking it to mean a single 25 standard deviation event. I would think that there is almost no way to claim that any event is 25 standard deviations from the mean. But I do agree with your general premise, that if you are experiencing too many single standard deviation events, your model is probably wrong.

• mugwump
Posted Feb 8, 2009 at 9:01 AM | Permalink

Re: Joel (#86), no, he meant 25-standard-deviations. My bad, I left out a critical hyphen:

“We’ve seen 25-standard-deviation moves several days in a row”.

I doubt he’d bother commenting on several single-standard-deviation events. That happens often enough.

33. Hu McCulloch
Posted Feb 7, 2009 at 10:16 AM | Permalink

Re # 39, 40, 46,
I think Steve is right, that the “climatology test” was supposed to be applied only to the satellite readings, which are known to have problems with cloud cover.

The Methods section at the end of the paper discusses both AWS and AVHRR data in its first paragraph. However, only the first 4 sentences pertain to AWS, and the remaining 7 to AVHRR. The last 2 sentences state, “We make use of the cloud masking in ref. 8 but impose an additional restriction that requires that daily anomalies be within a threshold of +/- 10 °C of climatology, a conservative technique that will tend to damp extreme values and, hence, minimize trends. Values that fall outside the threshold are removed.”

That indicates they are referring to AVHRR, not AWS.

The first section of the SI refers exclusively to AVHRR data. Its first paragraph discusses this threshold further, stating that 10°C from the climatological mean was used bececause it gave a better fit than 6°C. The following SI section on the AWS reconstructions makes no reference to truncating outliers in the AWS data or even in the AWS reconstructions.

This doesn’t mean that they didn’t truncate the surface data as well as they satellite data. In order to get Figure S3a, they must have. They just “fixed it”, as Phil puts it, without mentioning it in either the text or the SI.

34. Hu McCulloch
Posted Feb 7, 2009 at 10:21 AM | Permalink

RE 39, ummm, make that Racer Rock, not Racer Point. Penguin Point also has been changed, but it’s across the continent, on the coast of E. Ant.

35. Peter Hartley
Posted Feb 7, 2009 at 10:45 AM | Permalink

Re # 48

If one truncates the satellite data within a threshold of +/- 10 °C of climatology, it is not clear to me that would not bias the temperature trend calculations. In particular, why should the effects of clouds on the AVHRR data (which is the supposed motivation for truncation) be random? For example, if the clouds predominantly lead to colder readings, the truncation could remove the colder readings. Then a negative trend in cloud cover (fewer clouds over time) would be read as a positive trend in temperatures. More generally, trimming the data in this way might appear symmetric but the effect need not be neutral if the underlying data is skewed in some way and the skewness changes over time.

36. Posted Feb 7, 2009 at 11:06 AM | Permalink

Question for the knowledgeable – is Ferrell stationary? Is it on land or is it on Ross ice?

I’ve been comparing its monthly temperature properties with nearby Scott and McMurdo and am wondering if Ferrell is slowly moving northward.

Thanks

• Gary A.
Posted Feb 7, 2009 at 11:16 AM | Permalink

Re: David Smith (#52),
I believe Ferrell is on ice. There was a reference in one of the service logs that it would need to be relocated because of the possibility of the area breaking off into an iceberg. I think it was 10km from the sea.

37. DG
Posted Feb 7, 2009 at 11:43 AM | Permalink

Would the issues of the HO-83 hygrothermometer have any bearing on this subject?

38. Gary A.
Posted Feb 7, 2009 at 11:44 AM | Permalink

“Ferrell site was chosen due to its long climate record of thirty years. There is also
known accumulation to occur at this site from informal observations over the years by AWS
support personnel who have had to repeatedly raise the tower to keep it from being buried.”

“Nascent and Ferrell are located on the flat expanse
of the Ross Ice Shelf, affected by little topography.”

“Ferrell has a higher number of precipitation events
than any other site.” (in their study)

39. W F Lenihan
Posted Feb 7, 2009 at 11:46 AM | Permalink

snip – please don’t make this sort of comment here

40. Doc_Navy
Posted Feb 7, 2009 at 1:10 PM | Permalink

Steve,
Just wondering where my last post went?… Has anyone superimposed a map of active Antarctic volcanic locations over Yours and Roman’s temp trend reconstuctions? Watts has a map on his site that when dropped over the AWS data collection sites shows some interesting correlations.
Particularly:
AWS Site: Ferrel———-> Mt. Erebus
AWS Site: Racer Rock —-> Jun Jaegyu, Deception Island
AWS Site: Butler Island –> Nunatucks Group
Doc
PS. If I missed it somewhere, or the comment was moved to a different thread I apologize for restating something already addressed.

Steve: If you want to discuss volcanos, please do so at Anthony’s. Editorially, I don’t want to get involved in this, as I’ve mentioned from time to time. I sometimes edit when I’m tired and I may have pulled a trigger on your post, rather than saying the issue.

41. Doc_Navy
Posted Feb 7, 2009 at 1:59 PM | Permalink

Re: Steve (#58)
No Problem. I’ve just been doing some comparisons of map data across several sources, and since this site seems to have the most activity and most educated posters concerning the Stieg paper, I figured this would be a good place to bring it up. Sorry.
I’ll stick to statistics when posting here in the future.
Doc

42. Posted Feb 7, 2009 at 2:05 PM | Permalink

It appears that the Ross ice typically drifts away from the Pole towards open water at a rate of about 0.5 to 1.0 km per year, per a Wikipedia article. It seems reasonable to think that Ferrell has drifted perhaps 20km towards a warmer clime in its existence. The effect would be particularly noticeable if Ferrell is getting close to the ice edge and the (relative) warmth of open ocean.

If the above is correct and Ferrell has moved then it seems like a poor candidate for a climatology study.

• Posted Feb 7, 2009 at 3:52 PM | Permalink

It appears that the Ross ice typically drifts away from the Pole towards open water at a rate of about 0.5 to 1.0 km per year, per a Wikipedia article. It seems reasonable to think that Ferrell has drifted perhaps 20km towards a warmer clime in its existence. The effect would be particularly noticeable if Ferrell is getting close to the ice edge and the (relative) warmth of open ocean.
If the above is correct and Ferrell has moved then it seems like a poor candidate for a climatology study.

From the few people I have talked to that have been down there that is a normal drift rate. That would complicate the study but I don’t think make it a poor candidate. If you don’t allow for site migration it just gives SM another chance to raise a controversial point.

43. Knut Witberg, Norway,
Posted Feb 7, 2009 at 2:56 PM | Permalink

Unfortunately, the debate about subjectivity is not familiar to sciences like physics and mathematics, probably because it is seen inconceivable that subjectivity problems could occur in the “pure” sciences. We must, however, admit the problem of subjectivity is equally applicable to all sciences, not least the climate science.

Records show that every time data errors are found by the proponents of AGW, the corrected data supports the AGW.

This might very well be the result of manipulation, not consciously by a human or a group of humans, but manipulation by the system itself. Too many climate scientists confirm that an AGW skeptic has reduced chances to get the best jobs, grants etc. and that the subjects are selected in a partisan way. The big, international conferences have a certain resemblance with religious meetings.

An increasing number of people are seeing that this might be a big problem; below a link to an excellent article that points out that the corrections we have seen through the last few years in climate science may represent a biased selection of possible corrections.

http://online.wsj.com/article/SB120847988943824973.html?mod=opinion_main_commentaries

44. DJ
Posted Feb 7, 2009 at 3:46 PM | Permalink

After all of what I have seen on the Antarctic affair, I come to one question. Why don’t the Scientist’s know the “Mean Average” of the Snow Pack from over the years of being down there exploring and bring in data! It doesn’t make sense that they keep having to go back an keep raising the sensor group higher. Why don’t they put them above a distance that the snow has never reached? Any Ideas? Or snip this if its out of the Realm!

• D. Patterson
Posted Feb 7, 2009 at 4:00 PM | Permalink

Re: DJ (#63),

Standardization of the measurements limits the permissable range of heights for purposes of relative comparisons. There are substantial differences in temperature based upon height from the surface.

• tty
Posted Feb 7, 2009 at 4:19 PM | Permalink

Re: DJ (#63),

It seems you do not realize how an icecap like Antarctica works. There is no “mean average” because the snow just keeps on accumulating year by year and millenium by millenium. No matter how high a mast you use it will eventually be buried. The only exception is if it takes long enough for it to be buried for the ice to move down to the coast and calve into the Ocean first. And since metereological measurements by convention are done about 2 meters above ground level, relatively frequent lengthenings of the mast are unavoidable. In an ideal world this would always happen before the sensors are actually buried, but since in practice the snow accumulation is not exactly predictable, and site visits are only possible during the summer, occasional burials are more or less unavoidable.

• DJ
Posted Feb 7, 2009 at 4:52 PM | Permalink

Re: tty (#66), tty, Thanks for the indepth description! That would explain why the Snow doesn’t disappear if temperatures would not rise high enough in the Summer time to remove the snow. I thought it got at least into the upper 30’s for a few weeks then starts to go back down after Summer is done! Summer should be about done there now, Right? Appreciate your comment, tty and to D. Patterson, thanks!

• tty
Posted Feb 8, 2009 at 3:50 AM | Permalink

Re: DJ (#69),

The situation you describe with surface melting during the (short) summer season does apply for a large part of the Greenland Icecap and some coastal parts of Antarctica, particularily in the Antarctic peninsula, however for most of Antarctica and the higher northern part of Greenland, the temperature never rises above freezing, and melting is negligible.

As for your question in (70) the maximum recorded depth of ice, as far as I know, is about 4800 meters in the Aurora subglacial basin of East Antarctica, the ice in West Antarctica is thinner, with a maximum slightly over 3000 meters in the Byrd and Bentley basins. The mean thickness over the whole icecap is about 2000 meters.

Re 75

Crevasses occur regularily on the shelf where ice flow is disturbed, like for example in this area where the flow is deflected around Ross Island. Open water – no, the shelf ice is too thick (average about 400 meters).

• DJ
Posted Feb 8, 2009 at 12:06 PM | Permalink

Re: tty (#80), tty, Thank you for the response. Wow, that’s a lot of Ice! 4800 meters= 15,748.03 Feet = 2.98 Miles Deep.. Mind blowing to say the least. Today isn’t wasted for I have learned something more…

• Posted Feb 8, 2009 at 3:50 PM | Permalink

Re: DJ (#69), There are some areas in the Antarctic that are subject to spring thaw. A friend of mine did a stint down there in the late 50’s and told me of a lake (“Lake Nerney”) that suddenly appeared downhill from their base. It was, shall we say, brackish.

• tty
Posted Feb 8, 2009 at 4:10 PM | Permalink

Oh yes, there are a few lakes and even rivers in Antarctica. If you are interested in something really exotic in this line, I suggest you google “Lake Vanda” and “Onyx River”.

• DJ
Posted Feb 10, 2009 at 12:48 AM | Permalink

Re: jorgekafkazar (#96), Thanks for you reply,jorge! Do you know when in the Spring the Lake occured??

tty-Do these Lakes and Rivers occur “Every” Spring? Or is this Occasional??

• tty
Posted Feb 10, 2009 at 6:08 AM | Permalink

Re: DJ (#122),

The lakes are usually permanent (some of them are probably very old) and always ice-covered (except perhaps for a moat along the edges in summer). The streams are ephemeral and only run briefly in summer, and perhaps not even then, if the year is cold. As a matter of fact there are many more and much larger lakes under the icecap than in the unglaciated areas.

• Craig Loehle
Posted Feb 7, 2009 at 4:49 PM | Permalink

Re: DJ (#63), If they have to keep raising the instruments to keep them from being buried, doesn’t this rather rule against the continent melting away? Just asking.

• DJ
Posted Feb 7, 2009 at 4:58 PM | Permalink

Re: Craig Loehle (#68), Craig I was in belief that Summer Temps went beyond 32 degrees for a few weeks. If they don’t, then Antarctica becomes one Big Glacier and grows,advances and has its cycles over time! I wonder how deep it is at this present time?? At the Western Side of course!

• Phil.
Posted Feb 7, 2009 at 10:25 PM | Permalink

Craig Loehle:
February 7th, 2009 at 4:49 pm
Re: DJ (#63), If they have to keep raising the instruments to keep them from being buried, doesn’t this rather rule against the continent melting away? Just asking

They’re called snow drifts, you get a lot of those with winds up to 200mph, they move around like sand dunes. Where I grew up in the Welsh hills we’d get snowfalls of ~1′ but on the hills we’d have 15′ snow drifts in some places and bare ground elsewhere.

45. Posted Feb 7, 2009 at 4:31 PM | Permalink

Steve:

Maybe this explains some of the problems with Antarctic monitoring stations. 🙂 ..bruce..

46. Posted Feb 7, 2009 at 5:38 PM | Permalink

I did a plot of the sea ice trends on a pixel by pixel basis in the antarctic. I don’t think it matches well with large scale warming.

http://noconsensus.wordpress.com/2009/02/07/gridded-antarctic-sea-ice-trend/

47. Posted Feb 7, 2009 at 7:00 PM | Permalink

Re #64 Hello, Captain! I bet the Keys are fantastic this time of year.

As best as I can tell, Ferrill is about 60km from the nominal edge of the ice shelf. I say “nominal” because Ferrell seems to be near an iceberg calving region. If Ferrill was 80km away from ther coast and is now 60km away, and is approaching substantially warmer open ocean, then I think some amount of warming could be happening. Is it big, small or middle-sized? No idea.

48. bender
Posted Feb 7, 2009 at 8:39 PM | Permalink

Is Steig guilty of confirmation bias?

49. Posted Feb 7, 2009 at 8:51 PM | Permalink

Here’s a map of Ferrell and his neighbors –

Ferrell looks to be 40 to 70 km from the nominal edge of the ice sheet (ignore the brown dots for the moment).

And, here’s an interesting satellite image from 2000:

This shows the birth of iceberg C-19 in 2000. I marked the top map with brown dots which approximate (as best as I can) the place where the iceberg separated from the ice sheet. If the dotted line is correct then Ferrell went from about 60 km inland to 30 km inland in short order.

(Side note – Ferrell’s proximity to places named “crevasse” make me wonder if the region is fractured, with occasional exposed water interspersed with the very thick ice.)

50. Hu McCulloch
Posted Feb 7, 2009 at 9:29 PM | Permalink

Re Steve’s inline response to #47,

Steve: There are a LOT of PhDs that read and contribute to this site. For example, UC, Jean S, Roman M, Hu Mc are all statistics PhDs.

I can’t speak for the others, but although I have published a number of articles pertaining to the statistics of stable distributions, have other statistical research interests, and regularly teach OSU Economics department courses on probability (grad level) and econometrics (undergrad), my PhD is in Economics, not Statistics.

Incidentally, stable distributions, first propoposed by Benoit Mandelbrot back in 1960 as a model for financial and economic data, arise from the Generalized Central Limit as a limiting distribution for sums of random variables, yet have heavier tails than the Gaussian or normal distribution. They therefore are an appropriate and precise probabilistic model for the so-called “Black Swan” events noted by Nassim Tabeb and discussed last year on CA.

51. Alan Wilkinson
Posted Feb 8, 2009 at 2:45 AM | Permalink

I’ve had a look at raw Uranus, Limbert and Ferrell and the first two are short series and all three have a lot of missing data.

I did a simple-minded trend calculation by looking at each month compared with the median value for that month (so converting the data to monthly anomalies) and then plotting the average of those monthly anomalies for each year.

Two things stand out.

Uranus and Ferrell have large positive trends (0.22, 0.11 deg C/yr) but Limbert has a large negative trend (-0.17 deg C/yr). I’m puzzled that this can be converted into a positive trend by Seig. I think it could only be done by discarding the last 24 months of data (from Feb 2007).

Ferrell especially has a much greater standard deviation for winter month temperatures than summer. The others show a much less marked but somewhat similar pattern.

52. Alan Wilkinson
Posted Feb 8, 2009 at 2:53 AM | Permalink

One other point, Uranus has a much smaller temperature range from winter to summer. Comparing monthly mean temperatures (coldest month, warmest month):

Uranus -17.3 -3.4
Limbert -31.4 -5.3
Ferrell -36.0 -6.0

• tty
Posted Feb 8, 2009 at 4:09 AM | Permalink

The lesser temperature range at Uranus is to be expected, it is in a relatively maritime-influenced location on the western side of the Peninsula. Limbert and Ferrel are in relatively similar conditions near the northen edge of the Ross and Filchner shelf respectively, though I would have expected summer temperatures to be a bit higher at Ferrel since the Ross sea is regularily ice-free in summer, while the Weddell sea almost never is.

• Posted Feb 8, 2009 at 5:11 AM | Permalink

Re: Alan Wilkinson (#79), and re. #78,
I looked at NASA GISS graphs for Limbert and Ferrell but Uranus is missing. I found it revealing to compare to Jeff Id’s Sea Ice trends map. Uranus is maritime, on the peninsula, by the warm downwelling current, so its temperatures are both the highest and the least fluctuating. Limbert looks like it’s on sea ice, edging into the sea-ice-cooling hemisphere, so cooling would not be surprising. It looks dangerously close to the edge of the ice. Ferrell however looks fishy. It’s in the sea-ice-cooling area, much closer to the continental cold, so its greater range, and its greater SD for winter months, are what I’d expect. Yet it has two very high blips at the recent end of its record, that don’t seem to fit.

• tty
Posted Feb 8, 2009 at 10:36 AM | Permalink

Yesss… Ferrel does look a bit peculiar. There is no three-hour data för 2002-2006, though there is ten-minute data throughout. I would have thought that if you have measurements every 10 minutes, then you also automatically have measurements every 3 hours.
The monthly temperatures for the last three summers (there is gap in the monthly averages 2002-2006 too) are remarkably high. The December temperatures ranks 1,2,5 out of 19 and January 1,3,4 out of 25. Might well be because the site is now closer to the Ross sea which is open in summer.
As a matter of fact all sites on the Ross shelf should be moving slowly north unless they are shifted fairly frequently. The movement is about 1 km/yr on the unobstructed shelf east of Ross Island and about 0.5 km/yr in the the area where Ferrell is situated.

53. mugwump
Posted Feb 8, 2009 at 5:19 AM | Permalink

hmm, seems like the sup tag is broke.

“|x| – α – 1” in my comment above means “the inverse of |x| raised to the power (α + 1)”.

Steve
: did I fix it the way you want”?

54. anna v
Posted Feb 8, 2009 at 8:15 AM | Permalink

Ross McKitrick:
http://www.climateaudit.org/?p=5180#comment-326073
The thread “sweetness …” is frozen to comments, but I thought that it might interest you to know the answer to your request to Jack:

“I need to find if there is any place in the IPCC report where it was checked if models can reproduce the spatial pattern of temperature trends on a gridcell basis over the post-1980 interval. I don’t mean just 2 fuzzy maps put side-by-side, I mean an actual statistical test. From my reading no such test is in there, whether for model E or any other. But if you have any references to the IPCC text or other journal articles I’d be greatly obliged.”

From: 8.1.2.2 Metrics of Model Reliability
The AR4 report to be found in http://www.IPCC.ch
There is no possibility of a statistical test because the IPCC acknowledges that no likelihood function has been established for these models.

The above studies show promise
that quantitative metrics for the likelihood of model projections
may be developed, but because the development of robust
metrics is still at an early stage, the model evaluations presented
in this chapter are based primarily on experience and physical
reasoning, as has been the norm in the past.

An easy illustration is the albedo parameter. Using the toy model in http://junkscience.com/Greenhouse/Earth_temp.html
a 3% error on the albedo, a=.31% T=15C , a=.30% 16C, a=.32 T=14C. Think of the number of parameters entering. The spaghetti graphs would move all over the phase space if there were an attempt to calculate true errors .

55. tty
Posted Feb 8, 2009 at 11:45 AM | Permalink

I’ve been thinking a bit more and it seems almost certain that the break-off of C-19 in May 2002 must have caused a step change in summer temperatures at Ferrell.
Ferrell must have moved something like 15-25 km northwards since it was built in 1981, unless it has been shifted, which if so, is not mentioned in the station history (one wonders to what date the station coordinates refers, they must be changing constantly). This however would only have a very small effect on temperatures. However the abrupt decrease in the distance to the sea of about 32 km in May 2002 must have had an appreciable effect on summer temperatures. This might not have been noticeable in the 2002/2003 summer when B-19 was blocking the movement of the sea-ice, resulting in an unusually cold summer in the Ross Sea, but later summers should be significantly warmer (which they apparently are, see post 88). This effect should be even stronger for Laurie II which must be practically at the ice-front now. Unfortunately there are no monthly averages for Laurie II, only raw data.

56. Hu McCulloch
Posted Feb 8, 2009 at 12:32 PM | Permalink

Retraction Re #39:

I tried fitting a trend to the original Steig et al AWS recon for Racer Rock using all of 1957-2006, and to my surprise, the trend actually turns out to be positive, despite the spurious negative outliers in 2005-06:

(Click on graph for bigger view.)

The slope is .016°C/decade, and is actually significant: The OLS t-stat is 4.4, but the first order serial correlation of the residuals is 0.196, making the simple Quenouille-adjusted t-stat (multiplying by sqrt((1-rho)/(1+rho)) 3.6. My eyeball told me that those final negative values must have so much leverage that they would pull the trend well into the negative range, but I was clearly mistaken.

The trend for 1957-2003 is of course higher and more significant: 0.022°C/decade, OLS t = 7.5, rho = 0.347, adjusted t = 5.2.

Even though highly significant, these trends are very small: +1.6&degC/millenium and +2.2°C/millenium, respectively, so that neither could be contributing much to the Steig team’s conclusion of +.17°C/decade in W. Ant. in their Figure 2 (for TIR, and slightly higher for the average over AWS recons shown with their dotted line).

57. Hu McCulloch
Posted Feb 8, 2009 at 12:41 PM | Permalink

RE #92, the “retraction part” is where I rashly said back in #39,

Clearly if the 2004-06 are included, the trend is strongly negative, although if the series is truncated at 03, there is an uptrend. So I think S3a must have been tampered with to eliminate a “wrong” trend, at least in this case.

I was wrong to insist that the full-period trend is clearly strongly negative, and apologize to Eric Steig and his co-authors for insinuating that that must have “tampered” with their data to obtain their desired results.

58. Posted Feb 8, 2009 at 1:26 PM | Permalink

Re #89 tty, thanks for catching my dating error in #75. C-19 separated in 2002, not 2000.

Here is a map of the current (8 Feb) temperatures near Ross Island. I’ve marked the island with red splotches and the as-drawn ice shelf edge with green dots. Temperatures are degree F.

The warming as one approaches the ocean is apparent. This contrast is even greater in austral winter, I believe (it’s currently austral summer, of course).

59. Dishman
Posted Feb 8, 2009 at 2:56 PM | Permalink

I think the peer-review process is fundamentally unsound and overrated. It does not meet current standards for being a “Quality Process”.

Here’s the equivalent process in my own work:

I work in Aviation as an engineer. My role is equivalent to “author” in this context. The role of “reviewer” is played by Inspectors and DERs. Their signatures carry weight and consequences. Inspectors and DERs can face serious penalties (including loss of license and even jail time) for poor verification.

Now, what consequences do “peer reviewers” face? Who were the reviewers of this paper?

To meet the current standards, peer reviewers should affix their own signatures as having reviewed the paper. They need to be willing to take a stand and say, “Yes, I reviewed this, and it is good”, otherwise the review just a rubber stamp.

(cross posted with edits at Volokh.com in re the fraudulent Wakefield MMR paper)

60. tty
Posted Feb 8, 2009 at 3:59 PM | Permalink

Uranus Glacier is a simple scribal error, it should read:

Jan 00 Station: 8920 Uranus Glacier

As is also indicated by the file name. This isn’t exactly the first time in history that a sloppy “0” is transcribed as a “9”.

As to why the Ferrel data from 2002 to 2006 have not been used, I also wonder (se post 88).

61. Posted Feb 8, 2009 at 5:07 PM | Permalink

tty, or anyone else familiar with Antarctica, do you know the likely cause of the odd “hump” in Ross Island and Ferrell temperatures marked as “A” on this graph?

Average Monthly Temperature

My guess is that the winter temperature drop pauses until the open water north of Ross Island completely freezes, then proceeds to drop further.

This is just curiosity on my part and has no tie to the issue of Ferrell’s temperature history. Thanks.

62. tty
Posted Feb 8, 2009 at 5:33 PM | Permalink

Re 99:

That is very likely a correct explanation. There is usually a polynya off the western part of the Ross shelf for much of the winter.

63. Posted Feb 8, 2009 at 7:49 PM | Permalink

RE #91 above, I have been puzzling over why the numerical temperature trends I reported were much smaller than seemed consistent with the graph.

It turns out that I was treating the trend per month as if it were the trend per year, and so multiplying by 10 instead of 120 as I should have to get the trend per decade. This Climate Science is such hard stuff!

Where I wrote,

The slope is .016°C/decade, and is actually significant: The OLS t-stat is 4.4, but the first order serial correlation of the residuals is 0.196, making the simple Quenouille-adjusted t-stat (multiplying by sqrt((1-rho)/(1+rho)) 3.6. My eyeball told me that those final negative values must have so much leverage that they would pull the trend well into the negative range, but I was clearly mistaken.

The trend for 1957-2003 is of course higher and more significant: 0.022°C/decade, OLS t = 7.5, rho = 0.347, adjusted t = 5.2.

Even though highly significant, these trends are very small: +1.6&degC/millenium and +2.2°C/millenium, respectively, so that neither could be contributing much to the Steig team’s conclusion of +.17°C/decade in W. Ant. in their Figure 2 (for TIR, and slightly higher for the average over AWS recons shown with their dotted line).

I should have said,

The slope is 0.19°C/decade, and is actually significant: The OLS t-stat is 4.4, but the first order serial correlation of the residuals is 0.196, making the simple Quenouille-adjusted t-stat (multiplying by sqrt((1-rho)/(1+rho)) 3.6. My eyeball told me that those final negative values must have so much leverage that they would pull the trend well into the negative range, but I was clearly mistaken.

The trend for 1957-2003 is of course higher and more significant: 0.27°C/decade, OLS t = 7.5, rho = 0.347, adjusted t = 5.2.

With this correction, the Racer Rock reconstruction does appear to be contributing to Steig et al’s estimate of +.17°C/decade in W. Ant. in their Figure 2 (for TIR, and slightly higher for the average over AWS recons shown with their dotted line).

Since the se’s change in the same proportion as the slopes, the t-stats and rho are unaffected by this correction.

For just 1979-2003, as in Steig’s Figure S3 and Steve’s #4 in the post above, the trend is even higher: 0.33°C/decade, OLS t = 3.26, rho = 0.364, adjusted t = 2.23. It’s still significant, but not as strongly so, because of the shorter time period.

Here is the graph for this subperiod:

(Click on image for clearer view.)

Note that except for the brief periods 12/89-8/92 and 10/98-1/01, this series is almost entirely reconstruction (from the occupied stations?) rather than actual Racer Rock AWS data. Since these are in fact the noisiest periods, it is unlikely that there is any significant trend in the (now corrected) Racer Rock data itself.

Because the Racer Rock data errors only involved 3 months in 2005-06, they have no effect on trendlines ending in 2003. They may, however, have had a (very) slight effect on the average AWS reconstruction trend for 1957-2006, shown as the dotted line in Figure 2b.

Of course, we’re all still looking forward to seeing Steig’s own code that he used to call the Tapio Schneider RegEM routines linked on his webpage. (BTW, this is a different Schneider than the David P Schneider who is the second author of the Steig paper. There’s also a third, Stephen Schneider whom Steve has occasionally mentioned here.)

64. Willis Eschenbach
Posted Feb 8, 2009 at 11:49 PM | Permalink

Perhaps someone could explain why the READER data is so different from the GISS data? As a brief reality check, I just downloaded the “Amundsen-Scott” station records from both READER and GISS. The monthly difference between them has an RMS size of 0.25°C. The range of the monthly differences goes from +2.7°C to -1.7°C.

As an additional oddity, the differences are concentrated in January. This is important because when the monthly anomalies are removed, the January READER anomaly is 0.4°C larger than the GISS January anomaly. This means that when the anomalies are removed, there is an additional 0.4° difference between the two every January. Thus the removal of the anomalies, rather than reducing the error, actually increases it.

Next, from late 1993 to late 2002, the two datasets are exactly identical … why during that time and at no other time?

Does anyone have any insight into the differences between the GISS and READER records? I can’t find anything on the READER site that says they are doing any post-processing or adjusting …

w.

65. Steve McIntyre
Posted Feb 8, 2009 at 11:59 PM | Permalink

Willis, you’re getting back into the mysteries of the GISS algorithm for scribal variations (STEP 1)). If you go to dset0, the last series in the list looks like it’s READER. The others will be from GHCN and who knows. Then they get merged by GISS.

• Willis Eschenbach
Posted Feb 9, 2009 at 2:18 AM | Permalink

Re: Steve McIntyre (#103), So … does anyone know which one of them actually gets the data from say the Amundsen-Scott station and passes it to the other?

w.

66. Flanagan
Posted Feb 9, 2009 at 12:55 AM | Permalink

A bit OT (but just a bit).

Are you going to make some post about the state of polar ices (South and North) soon? We’re slowly getting to the seasonal extrema so maybe it could be great to follow the trends, state of the ice, etc.

Thanks

67. tty
Posted Feb 9, 2009 at 2:05 AM | Permalink

Re 101

That Racer Rock reconstruction seems to be a rather nice demonstration that RegEM decreases variance. You can actually pick out the parts that are real data by eye.

68. Willis Eschenbach
Posted Feb 9, 2009 at 2:20 AM | Permalink

As an aside, I’ve worked a good chunk of my life as a builder. If I build a house with shoddy materials, it would be ridiculous and dishonest were I to blame the supplier when the owner asks “Why is this plank cracked and warped”? Part of being a builder is to select your materials carefully, and inspect them for defects before adding them to the structure you are building.
.
The same holds true in science. If I am building support for the idea that antarctica is warming, it is incumbent on me to select my materials (datasets) carefully, and to inspect them for defects before I add them to the structure. There’s tons of data out there, good, bad, and ugly. I couldn’t just blame the supplier if my data were found to be bogus. I’d have to man up and say “Ooops, my quality control checks missed that. Thanks for finding it. I’ll re-run the analysis and tighten up on data integrity.” An honest builder blames neither his materials nor his tools.
.
Eric Steig takes the opposite view. He blames the BAS for the bad data for Harry, doesn’t bother checking his materials, washes his hands of it, takes no responsibility, not his job.
.
Say what?
.
When was it ever not a scientist’s job to check his data? I find that absolutely astonishing.
.
He even has a statement on his web site:

All of the data used in the temperature reconstructions are from publically available data sources. Any queries about the raw data, or access to it, should be directed to the appropriate data centers, listed below.

I have a query about the raw data for Dr. Steig, and I fear that the “appropriate data centers” can’t answer it …
.
For goodness sake, why on earth didn’t you check your materials carefully and thoroughly, in a workmanlike manner, as befits the gravity and prominence of the task? Or if the job is too big for one man, at least give it to a subset of your “co-authors” to check?
.
Here’s how I see it. In postmodern science, someone always, always will check and ground-truth and examine my data and my procedures. Maybe tomorrow, maybe six months from now, but it will happen. So I damn well better examine and check and double-check my data and my methods and my conclusions today, before I put them out there for the ravenous masses to tear apart. My rule of thumb is simple:

There’s a good chance that there’s still a flaw in my work somewhere, even after taking this rule into account.

This, of course, has the obvious corollary …

I’d better find it before someone else does.

Now to that I would add that nobody is being asked to bet a billion dollars based on my work. But Steig et al. and their adherents are asking the world to bet billions of dollars based on their work … and they won’t take responsibility for a warped, cracked plank in the construction? They want to blame the materials supplier?
.
Sorry, but that’s a bad builder in my book.
.
I would add to that one more comment. This is that the material supplier is also at fault. BAS seems to have an inadequate data integrity checking system as well.
.
w.

69. Posted Feb 9, 2009 at 2:38 AM | Permalink

Spot on Willis, as usual.

70. Posted Feb 9, 2009 at 7:37 AM | Permalink

Re #107 willis, wow! Your post nails the matter. Thank you for posting such a well-written analogy and contrast.

71. Robinedwards
Posted Feb 9, 2009 at 8:53 AM | Permalink

This is all very fascinating, but I have a couple of small technical queries. In #101 Hu McCulloch’s graph shows “Temp Anom”. In what respect are the temperatures anomalous, please? Or, what is the basic value on which they are based?

I ask this because in my analyses of climate time series I like to work with what I call “Monthly differences”, meaning the difference between a given month’s value and the average value for the month in question over the whole of the data set. In other words, I am using a simple “deseasonalised” value. This has the desirable effect of reducing the apparent and very loud noise due to typical seasonal differences and thus improving the precision of the analysis.

Willis (in #102) also uses the term “monthly difference”, but I think he’s referring to the month by month difference between the two sources of the Amundsen-Scott data, READER and GISS. “Monthly Anomalies” is also used in #102.

I just want to be sure about these things so that I can make a reasonable try at reproducing the analyses.

A further point – this time on analyses of time series – is about the Quenouille-adjusted t-statistic., given by Hu. Is this adjustment highly regarded by time series specialists, or is it looked upon as something of a “get-out” to avoid having to go through the more complex arithmetic necessary to identify the appropriate time series model and then use full-power specialised software requuired to run the computations? I don’t have such software as yet, so greatly favour the Quenouille adjustment!

Robin

72. Steve McIntyre
Posted Feb 9, 2009 at 9:20 AM | Permalink

#107. Another way of describing “engineering quality”. In an engineering report on a GCM, I would expect that the each parameterization would be described and QCed in a relevant way. Engineers aren’t permitted to rely on a daisy chain of refs in The PRL. There are standards for what they can rely (they don’t have to ground truth everything), but a journal ref somewhere in The PRL would not be enough.

73. Posted Feb 9, 2009 at 11:06 AM | Permalink

RE Robinedwards #110,

Good questions —

These “anomalies” are computed somehow by Steig et al relative to an average value for the site, for the individual month in question. If you’re only interested in a trend for a single site, the base period doesn’t matter. But if you’re comparing sites with very different coverage (as is the case), it’s important to do this consistently. We can’t know how Steig et al did this until they release the code they used to call the RegEM routines, so for now the world just has to take their numbers on Faith. (Either that or tentatively reject them as not yet Scientific.)

I’m currently playing with computing a trend for Racer Rock from its (corrected) raw data only. There are only 69 monthly observations, with only 4-6 observations per month, and lots of gaps in the data. It would make sense to regress temperature on 12 monthly intercepts, plus a common slope times time, plus a regression error. Each intercept would have a lot of uncertainty to it, because it is based on so few observations, but still they would be identified. However, their uncertainty would be an important factor in dermining the uncertainty of the slope. Most climate studies just pre-adjust their data for seasonality, and then ignore this easily quantifiable source of error.

My main problem here is just reading missing observations in Matlab. DLMREAD doesn’t recognize the – signs used by BAS to indicate missing data in their txt files. It still won’t read the file if I change these to . characters (the GAUSS missing code) or NA (the Excel missing code). Does anyone know a good trick for this?

Computing a composite trend across sites is tricker, since then the base period matters. However, a common base period can be imposed on the trend lines simply by subtracting the mean date of the base period from the time variable before running the regression.

Serial correlation is a big problem for which there is no standard easy solution. The Quenouille adjustment is quick and easy, and a lot better than nothing, so I used it. Here are some issues:

1. Even if the errors are AR(1), estimating rho from the residuals is different than estimating it from the unobserved errors themselves. Don Andrews (Econometrica 1993) had a way to obtain a “median-unbiased” estimate, that I have tried implementing and extending, but it’s really too cumbersome for everyday use.

2. The errors may be higher-order AR or ARMA, or even Fractionally Integrated (UC’s favorite). These are not insurmountable, but again cumbersome for everyday use.

3. Even if the errors are AR(1) and rho is known (instead of estimated with bias from the residuals), Quenouille’s adjustment (which dates back to 1950) is only a limiting value for a worst-case regressor (like a time trend). There is an exact formula involving matrices that is worth using, but Quenouille is still easier.

4. Another 1950s method is the Cochrane-Orcutt (CORC) adjustment. However, this re-estimates the coefficients under the assumption you know rho, which you don’t until you’ve estimated the coefficients. I now think that just adjusting the se’s of OLS coefficient estimates is the safest way to go. EViews and other programs generalize CORC to AR(p) adjustments, with the same drawback.

5. Econometricians often use the Newey-West HAC standard errors for OLS coefficients, and pretend the problem has gone away. However, this greatly undercompensates for serial correlation in most cases, so I dislike it.

6. Mainstream climatologists Santer, Nychka, et al (2008) just use Quenouille, creating a precedent for its use. Ironically, the same Nychka, with Santer and other others, in an unpublished 2000 working paper, suggested a solution to problems 1 and 2 above, but then went back to Quenouille in their recent paper. See threads 4106, 4127, 4163, 4216, and 4499 on CA last year for discussion (or use CA Google for Santer Nychka).

I hope this helps!

• Willis Eschenbach
Posted Feb 9, 2009 at 2:33 PM | Permalink

Re: Hu McCulloch (#113), thanks for your interesting comment. Inter alia you say:

These “anomalies” are computed somehow by Steig et al relative to an average value for the site, for the individual month in question. If you’re only interested in a trend for a single site, the base period doesn’t matter. But if you’re comparing sites with very different coverage (as is the case), it’s important to do this consistently. We can’t know how Steig et al did this until they release the code they used to call the RegEM routines, so for now the world just has to take their numbers on Faith. (Either that or tentatively reject them as not yet Scientific.)

I’m currently playing with computing a trend for Racer Rock from its (corrected) raw data only. There are only 69 monthly observations, with only 4-6 observations per month, and lots of gaps in the data. It would make sense to regress temperature on 12 monthly intercepts, plus a common slope times time, plus a regression error. Each intercept would have a lot of uncertainty to it, because it is based on so few observations, but still they would be identified. However, their uncertainty would be an important factor in dermining the uncertainty of the slope. Most climate studies just pre-adjust their data for seasonality, and then ignore this easily quantifiable source of error.

The error in the removal of the average monthly anomalies can be quite large. Let’s look at station ERIN, which is the red dot to the right of Harry, and slightly larger than Harry, in Figure 4. The size of the red dot shows that it is one of the fastest warming stations in the region.
.
Now, here’s the GISS data for ERIN:

Fastest warming in the region? It’s far too short to say anything firm, but the data clearly indicates that it is cooling.
.
I show the trendlines for the max, mean, and entire dataset. All of them are strongly negative. I suspect that part of the change in the data, from an actual trend of somewhere around -4°C/decade to some fictitious warming trend, occurs when the monthly anomalies are removed.
.
I say this because when I use the normal method to remove the monthly anomalies, the result has a trend which is only -1.5°C/decade, some 3°C greater. This occurs because, as is the case with many Antarctic records, the missing data is concentrated in one season of the year. For example, in the ERIN data, there are 7 records for February and March, but only two for August and September. This introduces large errors into the calculation of the monthly anomalies.
.
w.

• Hugo M
Posted Feb 9, 2009 at 3:04 PM | Permalink

since matlab is using libc, replacing ‘-‘ in BAS data by “nan” might do the trick? Alternatively, there is also the textread() function.

74. Robinedwards
Posted Feb 9, 2009 at 12:09 PM | Permalink

Thank you, Hu. Your post certainly does help, and I’m quite pleased to learn that Quenouille is “acceptable”. It looks like something I can implement readily in my own software.

I must find the Racer Rock data and have a go at it using my unconventional methods! Unfortunately I can’t handle masses of sites automatically, so have to be selective in my choice of sites. However I have no problem with missing value codes, which is quite important in climate studies I’ve learned.

Thanks again, Robin

75. Posted Feb 9, 2009 at 2:10 PM | Permalink

RE Robin, #114,

The raw Racer Rock data (as corrected Feb. 4) is at

Enjoy!

76. bernie
Posted Feb 9, 2009 at 4:13 PM | Permalink

Willis:
So how does Steig handle this issue? Apologies if this has already been nailed.

77. Mark T.
Posted Feb 9, 2009 at 4:17 PM | Permalink

Newer versions of MATLAB have replaced textread() and strread() with textscan(). You can also process the data using standard C functions such as fscanf().

Mark

78. Mark T.
Posted Feb 9, 2009 at 4:39 PM | Permalink

I think NaN, as Hugo mentioned, is probably the way to go, actually, because the MATLAB plotter will simply remove those points from the plot which is useful.

Mark

79. Posted Feb 9, 2009 at 10:24 PM | Permalink

Here’s another comparison of Ferrell’s temperature with those of several nearby stations.

Many of the monthly records, including Ferrell’s, have gaps. In this exercise I used only months when Ferrell and the other station both reported values. I took the difference between Ferrell and the other station in each of those months. I then averaged those calculated monthly differences over each calendar year, discarding any year with fewer than six useable months.

The resulting time series gives an impression of whether Ferrell is warming or cooling versus each nearby station. This method is not perfect but I think it is good-enough for this visualization purpose.

Here is a map of the selected stations. I’ll be glad to add other neighbors if someone has one with a reasonably long history.

Here are the comparisons. (Note: the y-axis is in degrees C (each y-axis line is two degrees C). Please ignore the numerical values shown as the plots were positioned closer together for ease of display.)

In each comparison Ferrell has warmed relative to the other station and at about the same rate. I don’t know a good physical explanation of how AGW could trigger such an apparently local effect.

• bernie
Posted Feb 10, 2009 at 3:08 PM | Permalink

Re: David Smith (#120), David:
How does Ferrell compare to proximate manned surface stations using the same approach?
Also I am not sure why the difference between Ferrell and Gill are smaller than the nearby Scott and McMurdo. Somehow I would have felt that Ferrel would have been on average warmer than Gill which appears closer to the SP. Am I reading the map and scale corrctly?

• Alan Wilkinson
Posted Feb 10, 2009 at 5:01 PM | Permalink

I thought we had clarified that Ferrell is on ice moving towards the open sea quite rapidly as you and tty mentioned previously – while Scott, McMurdo and Whitlock are fixed on islands and Gill is so far from the sea that it is unlikely to be greatly affected by its temperature?

80. Geoff Sherrington
Posted Feb 10, 2009 at 12:34 AM | Permalink

Out of synch?
Steig et al have a fig 2 in the Nature paper, p 460, caption “Reconstructed annual mean Antarctic temperature anomalies, January 1957 to December 2006. a. East Antarctica. b. West Antarctica.” (etc).

You might recall that I compare pairs of graphs by visual methods, by shaping, scaling, stretching one and overlying it on the other. This way one can get maximum visual correspondence of peaks and troughs and the eye is not a bad pattern detector.

I did this on the pair being West and East Antarctica temperature reconstructions. First step was to align the linear trend lines exactly. This needed a vertical stretch of the Y axis on the left side of fig b. Next was to move fig b left/right over fig a so that the max number of peaks and troughs aligned. (Correcting a lag). Quite good correspondence then.

A possible deduction is that the East data are out of synch with the West data by about 10 months. If this is supported by more formal statistics (and I am confident it can be), it raises a climate problem because of the rotational weather patterns of the region. I do not know the radial velocity of weather systems there, but I can think of no good reason why a peak in E Antarctic shows up 10 months later in West Antarctica, fairly reliably over a 40 year term.

A related question is why different vertical scaling is needed for correspondence. Is the W really cooler than the E except for a bump 1970-5? I thought the point of the paper was the opposite.

This is a bit hard to describe and post here. Interested parties are invited to email me at sherro1 at optusnet. com. au for the relevant data returned by email. There is about 1.5 Mb of it, with some probable questions from other figures too, so please don’t overload.

81. Bernie
Posted Feb 10, 2009 at 6:59 PM | Permalink

Alan:
Re: Alan Wilkinson (#125), If true, I still don’t understand the ordering of this graph. The relationships are almost opposite what I would have anticipated. What am I not seeing?

• Alan Wilkinson
Posted Feb 11, 2009 at 3:11 AM | Permalink

Re: Bernie (#126),

I was just looking at the relative slopes and ignoring the vertical positions.

I don’t understand what you don’t understand. Seems to me quite reasonable that Ferrell is warming relative to all the others given its movement towards the open sea and the considerable temperature differential between those near the sea and Gill – way south down McMurdo Sound.

And there’s a significant difference even between McMurdo and Scott though they are just at opposite ends of the same island I think.

82. Posted Feb 10, 2009 at 8:37 PM | Permalink

Re #124, #125 Bernie, both Scott and McMurdo are manned stations. Ferrel today runs about 2C cooler than Scott, 3C cooler than McMurdo and 6C warmer than Gill. I should have omitted the numerical values on the y-axis, to avoid confusion.
Alan, I believe the best guess is that Ferrell is moving at about 0.5km/yr. That is a drift but such small changes may be important due to proximity to water. As you note, McMurdo, Whitlock and Scott are land-based and Gill is far from the open sea. Those four stations, which partially surround Ferrell (at some distance), have temperature time series unlike Ferrell’s, which is a situation that is hard for me to explain. That’s the gist of what I was exploring. I wish there were useable sites closer to Ferrell, especially to the east, but the pickings are slim.

83. Posted Feb 10, 2009 at 8:49 PM | Permalink

bernie, see if this plot clarifies things. The color assignments are the same as in #120. The y-axis values on this one are true.

On the original I repositioned the lines to make their similarity more visually apparent and to separate Whitlock and McMurdo. As mentioned in #120, the numerical values on the y-axis in #120 should be ignored, due to the recentering. My apology for confusing things and I hope this explains it 🙂

• bernie
Posted Feb 12, 2009 at 6:35 AM | Permalink

Re: David Smith (#128), David:
Could you show a plot of the actual temps for the five stations. I am struck by the strong apparent relationship between Whitlock and Scott. Is Whitlock manned or an AWS? Are these stations manned all year round? Come to think about it, what are the actual equipment and procedural differences between a manned station and an AWS – besides wrt the manned stations, the location of the equipment close to places where people live?

84. Hu McCulloch
Posted Feb 10, 2009 at 9:12 PM | Permalink

RE #101, 112,
I have some new ideas concerning se’s with serially correlated errors. Stay tuned to this station…

Re Hugo M #116, Mark T 118, 199, thanks for the Matlab tips! I’ll give them a try.

85. Mark T
Posted Feb 11, 2009 at 2:16 AM | Permalink

Wish I could do more, Hu. Let me know if you need anything else offline or otherwise.

Mark

86. Robinedwards
Posted Feb 11, 2009 at 7:26 AM | Permalink

Trying my best to follow all this, but what I lack is a fully “detailed” map of Antarctica so that I can have the disposition of measurement sites readily to hand (actually, on screen) whenever I need it.

Can anyone recommend a really good map, please?

Thanks, Robin

87. David Smith
Posted Feb 11, 2009 at 2:58 PM | Permalink

Re #132 Robinedwards, try the “AWS Map (All Stations)” section, and links to smaller maps, at

AWS Homepage

88. thefordprefect
Posted Feb 11, 2009 at 10:22 PM | Permalink

Anyone looked at the manned Russian stations. 1957-2009 on a couple. Some missing data, some odd data but in general seemingly ok:

http://www.aari.aq/data/write_summary_data.asp?lang=0&mm=0

89. StuartR
Posted Feb 12, 2009 at 5:58 AM | Permalink

Quite amazingly Patrick Michaels has been given a page on the Guardian Comment Is Free to talk about this issue, the tenor of the responding comments is a sort of dazed confusion at seeing it there that is quite amusing.

http://www.guardian.co.uk/commentisfree/cifamerica/2009/feb/06/antarctic-warming-climate-change

• bender
Posted Feb 12, 2009 at 10:39 AM | Permalink

Re: StuartR (#135),
Maybe you want to say something there about all the ad hominem attacks on Michaels and point to his published paper, in the primary climatology literature, with co-author Ross McKitrick illustrating that up to half the precious AGW may be attributable to more localized effects of socioeconomics/land-use change that are negelcted by NASA? Maybe it’s less. Who knows. The precious GCMs don’t include such effects. Rather, what you have is the same group that builds the models tinkering with the data used to test the models, trying to estimate UHI “contamination” – but not trying all that hard.

As for Antarctica. Michaels is right about the Steig paper. Steig is another Juckes. Wanders in from far afield to save the planet, – snip

• Bill W
Posted Feb 13, 2009 at 1:46 PM | Permalink

Re: StuartR (#135),
Guardian Comment Is Free
Interestingly a Monbiot ad hominem attack against P Michaels was removed from the comments by a moderator.
BW

• StuartR
Posted Feb 14, 2009 at 9:49 AM | Permalink

Re: Bill W (#166),
Re: bender (#138),
I saw the first few comments all gobsmacked to a man when I posted the link here, and then later it turned into a wave of ad hominem maybe not coincidentally after Mr Monbiots prompting, I didnt revisit after that. It is interesting that his comment was struck, maybe the ad hominems were so boring and predictable that even the CiF moderators may have found it a bit embarassing.

• bender
Posted Feb 14, 2009 at 10:22 AM | Permalink

Re: StuartR (#175),
What percentage of those commenters actually examined the same evidence that Michaels was working from? Maybe less than 1%? The rush to judgement is a bad sign for everyone. It’s catching. Look at the way IPCC handled Michaels & McKitrick’s published papers. But you’re right, it’s not just ugly, it’s BORING. Endless sermonizing.

• StuartR
Posted Feb 14, 2009 at 10:57 AM | Permalink

Re: bender (#176),

“What percentage of those commenters actually examined the same evidence that Michaels was working from? Maybe less than 1%? ”
I agree less than 1%, but that is based on my very cheap and lazy survey of their responses. The only person who writes for the Guardian with a reasoned (if not glibly irreverant) scientific nature is Ben Goldacre, and he mainly sticks to medical matters. I think the fact that Patrick Michaels was given a chance to write a page is the most interesting thing. I wonder what went on in the editorial meetings that prompted it.

90. brendy
Posted Feb 12, 2009 at 10:30 AM | Permalink

Meanwhile …. up at the North Pole, Chrysophere Today’s satellite images of Artic sea ice show a rather remarkable jump in sea ice between Tuesday (Feb 10) and Wednesday (Feb 11)of this week in the Hudson Bay and the Newfoundland Sea between Greenland and Newfoundland that appears to be on the order of a few hundred thousand square kilometers. Take a look at

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=02&fd=10&fy=2009&sm=02&sd=11&sy=2009

Like the NSIDC, still using 20 year means, even though 30 years of data is available and somewhere in the fine print NSIDC acknowledges that satellite interpretations can be as much as a few hundred thousand square kilometers in error. Not in any press release, however.

91. Phil.
Posted Feb 12, 2009 at 11:33 AM | Permalink

brendy:
February 12th, 2009 at 10:30 am
Meanwhile …. up at the North Pole, Chrysophere Today’s satellite images of Artic sea ice show a rather remarkable jump in sea ice between Tuesday (Feb 10) and Wednesday (Feb 11)of this week in the Hudson Bay and the Newfoundland Sea between Greenland and Newfoundland that appears to be on the order of a few hundred thousand square kilometers. Take a look at
http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=02&fd=10&fy=2009&sm=02&sd=11&sy=2009

And a jump down on the 9th as well! The satellite images sometimes show a missing swath which the SSMI obviously did that day, note that it didn’t show on the ASMR-E which is what the daily image is from, also no corresponding drop/rise in the graphical data.

92. tty
Posted Feb 12, 2009 at 1:06 PM | Permalink

Re 140

The ice off southern Labrador, in the St Lawrence area and St James Bay has been popping into and out of existence repeatedly on Cryosphere the last several weeks. Either the satellites are missing preferentially in that area, which seems strange, or that old bugaboo, meltwater on the ice is the problem again.

93. bernie
Posted Feb 12, 2009 at 3:16 PM | Permalink

Interesting. Doesn’t the GISS Mirny data go back to 1956? And what happens if you drop 2007 because it only has 8 of 12 months data? (True 2007 is the warmest year on record but it also has the least monthly data!!) When I make these reasonable adjustments based on the available data, I get a warming trend that I bet is not significantly different from zero and in any case is half the rate you display for Mirny.

• thefordprefect
Posted Feb 12, 2009 at 4:19 PM | Permalink

Re: bernie (#143), Apologies, you’re right about the start point on Myrny and Novola.. new plots below
Myrny data for 2007 is complete so is not deleted
The averaging of data is for 12 months and this is set to zero if less than 9 months have data. Hence start and end of trace show as zero

The point is these 3 sites are in areas of decreasing (according to AWS) temperature. All 3 show signs of warming.
Mike

• bernie
Posted Feb 12, 2009 at 4:44 PM | Permalink

Re: thefordprefect (#145), Mirny GISS data indicates that there is no data for Feb, Mar, May and June for 2007. I know GISS infills for missing data and that may be OK for large scale multi-station analyses but I see no point in doing it when you are looking at station records one by one.

• thefordprefect
Posted Feb 12, 2009 at 9:59 PM | Permalink

Re: bernie (#147), the data is from the reference I gave in a previous post, the station data is here
http://www.aari.aq/data/data.asp?lang=0&station=3
There is no missing data noted for 2007 for Surface maximum air temperature and Surface minimum air temperature.
Re: bender (#151), No one in this thread has posted significance levels for their trends! Why should any climate parameters conform to quadratic/linear/other mathematical trends? I gave a linear trend as others on this thread had used this.

Re: RomanM (#149), Not sure what you are accusing me of. I suggested that ozone is a GHG (true?) Ozone levels over the antactic are constant (relatively) until 1980(approx). Up to this time temperature plots show a significant increase. After this time the “greenhouse effect” decreases as the concentration reduces by 6% over 10 years. This could reduce the ambient temp if it were not also being forced higher by other effects. The ozone levels having stabilised in 1993(approx) the temperature should again be rising. Mirny and Vostok may show this rise.

Why the animosity to me posting a graphical form of someone else’s data? I believed it added to knowledge of AWS stations showing them to be inconsistent with manual measurements. Please tell me where my simple plots are invalid!
Mike

• bernie
Posted Feb 12, 2009 at 10:17 PM | Permalink

Re: thefordprefect (#155), thefordperfect:
It looks like the GISS data differs from the data at the Russian site. Intriguing. I am going to have to look at this more closely.

Bender: The r2 on these trends appear to be very small. I doubt that the coefficients are in fact significant.

• bender
Posted Feb 13, 2009 at 12:58 AM | Permalink

Re: bernie (#156),

Bender: The r2 on these trends appear to be very small. I doubt that the coefficients are in fact significant.

ford: bernie’s on to you.

• bender
Posted Feb 13, 2009 at 12:55 AM | Permalink

Re: bender (#151), No one in this thread has posted significance levels for their trends! Why should any climate parameters conform to quadratic/linear/other mathematical trends? I gave a linear trend as others on this thread had used this.

1. Humor me. Step it up a notch and give me the stats.
2. Sounds like you are trying to dodge the issue of WHEN the warming occurred. Why?
3. Be a sport. Up the ante.

• thefordprefect
Posted Feb 13, 2009 at 7:05 AM | Permalink

Re: bender (#161), etc.
All I did was to draw some curves from someone elses data. I added some linear trend lines because everyone on this thread was adding them. I was simply showing that permanent station data was different from AWS data. I was not pushing any GW. I am not involved with antarctic environmental studies so I cannot explain the levelling out of increase in some data from 1980. I gave the ozone data as it seemed plausable (I am not the only one to think this). I would be willing to try to understand why ozone depletion is not the cause. I would be willing to listen to other theories as to why the temperature levelled for a bit.

I was not expecting the Spanish Inquisition!!!

Because internal climate variability is complex, nonlinear, stochastic, prone to flip-flopping? Or have you forgotten that there’s more to climate than linear deterministic forcing? No, that would be confirmation bias.

I was trying to point out that I cannot understand why anyone would try and mathematically fit a simple trend equation (linear, quad,exponential, etc.) to any temperature profile. Climate does not follow such simplifications. A moving average is better.

Warming was occuring around/before 1956. I have no problem with that

If you really want I will replot over the last 30 years. But I do not see the point and it seems very much like “cherry picking”.

• Thomas Gray
Posted Feb 13, 2009 at 2:11 PM | Permalink

I added some linear trend lines because everyone on this thread was adding them

This brings up a classic V&V question. What is the validity of the linear trend for this type of data? Does it have any physical meaning?

• bender
Posted Feb 13, 2009 at 7:10 PM | Permalink

Re: thefordprefect (#165),
snip – be polite to other posters
.
Same thing for San Quentin in the other thread. What’s happening in the Arctic is not UHI. What it is is a bona fide mystery. Or have you not been reading your Hansen papers? What’s happening there totally does not fit the GCMs. The experts are mystified by it. Again, something with the oceans. Rather fitting with Tennekes’ remark at Pielke’s blog, wouldn’t you say? Except that the folks at RC and NASA agree: the Arctic Ocean and the Artic Oscillation atmospheric circulation are still very mysterious to us.
.
Gavin, feel free to chime in and correct me.
.
San Quentin, feel free to educate us about the arctic. Mind you, there’s a few threads here at CA you’ll want to read where the pertinent literature is discussed.
.
Methinks the oceans are a tad more complex than you want them to be. Try reading Wunsch, also discussed at CA.

• thefordprefect
Posted Feb 14, 2009 at 5:25 AM | Permalink

Re: bender (#170), before the snip (I can take impolite, Steve!!)

[Steve- it doesn’t matter whether you can “take impolite” – I don’t want it]

I think you were talking about adding R2 etc to graphs.

An example of R2 “invalidness”

2 simple curves added (triangle amplitudex2) and 2 trend lines matched to resultant

1. Which represents the trend better in life, which gives the best R2
2. The linear trend is exactly the trend added to the triangular wave – why does the statistics not give this fact

Perhaps you can provide a better statistical correlation that shows this on this very simple example.

I’ll repeat my previous comment. Simple curve fitting a real life multi input data set is of little value.
Mike

• bender
Posted Feb 14, 2009 at 5:50 AM | Permalink

An example of R2 “invalidness”

“invalidness”? You’re certainly not quoting me on that one. I stop reading there.
.
I asked for real data, not toy examples. Another non-response. And a 6th ordern polynomial? That’s a bit overkill, don’t you think? Lastly, I didn’t just ask for “R2 etc”. I asked specifically for the s.e.s and p-values on the regression parameter estimates. How else you going to know if they’re significantly different from zero?
.
Answer those before I go on to read the rest of your comment where YOU ask ME questions.

• Mitchel44
Posted Feb 14, 2009 at 2:00 PM | Permalink

Your graph at 146 shows the trends starting in 1980, yet reductions in Ozone depleting substance production did not take place until 1989, in fact production actually increased up to 1988, then declined sharply after that.

http://www.afeas.org/overview.php

Don’t see that as a fit for the graph.

• thefordprefect
Posted Feb 14, 2009 at 3:58 PM | Permalink

Re: Mitchel44 (#178), Ozone is a ghg, hence ozone “hole” could cause cooling: the ozone “hole” began as shown in my previous graph in 1978 at about the point where antarctic warming “ceases”.

TES observations of tropospheric ozone as a greenhouse gas
Worden, H. M.; Bowman, K. W.; Worden, J. R.; Eldering, A.
American Geophysical Union, Fall Meeting 2007, abstract #A51D-0735
We present satellite observations of the downward radiative flux from tropospheric ozone, for cloud free ocean conditions…. We examine the sensitivity of the outgoing longwave radiation (OLR) in the 9.6 micron band to upper tropospheric ozone and water vapor by separating the data into hemispherical and sea-surface temperature (SST) ranges. For 2006 data, we estimate an annual average downward flux for upper tropospheric ozone of 0.48 ± 0.13 W/m2 with a standard deviation of 0.24 W/m2 for the latitude range between 45°S to 45°N. This estimate includes natural and anthropogenic ozone sources and is higher than the 2007 IPCC average for climate model estimates of anthropogenic tropospheric ozone radiative forcing of 0.35 W/m2. We also observe that water vapor dominates the clear-sky ocean variability of the outgoing IR radiation in the 9.6 micron ozone band for SSTs higher than 299 K, consistent with the “super greenhouse effect”. This underscores the importance of chemistry-climate coupling in forcing predictions for tropospheric ozone.

Re: bender (#174), the toy graph does not give sensible R2 values How can real world data. A linear curve fit can give only a general idea of rate of change of temp over the considered period.

If you are trying to get me to admit total ignorance of statistical methods, then I will freely admit it. In my working life I have never had to use statisics!! I cannot even find FREE information describing s.e.s whatever that is (unless you mean SEs Standard Errors?). As you have the tools then why not use them on the simple toy data and show me their worth (or perhaps show me how to calculate your required numbers)?
Mike

• bender
Posted Feb 12, 2009 at 7:06 PM | Permalink

Re: thefordprefect (#145),
1. Don’t bother posting trend lines unless you are going to report significance levels on regression parameters.
2. Try fitting a quadratic.
3. Nature newsflash: Antarctica warmed 50 years ago. Nothing since. Who knew?
4. Yawn.

94. thefordprefect
Posted Feb 12, 2009 at 4:44 PM | Permalink

Forgot to say where the ozone plot came from:
http://www.theozonehole.com/

95. Steve McIntyre
Posted Feb 12, 2009 at 7:21 PM | Permalink

careful with the GISS data. Please use the dset0 versions and specify the version, as, for what we’re doing here, version differences are worth keeping track of.

96. Paul Penrose
Posted Feb 12, 2009 at 8:27 PM | Permalink

Ford,
Since according to the experts over at RC climate is defined in terms of 30 year trends, why don’t we just look at the last 30 years?

• bender
Posted Feb 13, 2009 at 1:12 AM | Permalink

Ford, Since according to the experts over at RC climate is defined in terms of 30 year trends, why don’t we just look at the last 30 years?

I’m sure you’ll get an answer. Ford would never dodge.

Why should any climate parameters conform to quadratic/linear/other mathematical trends?

Because internal climate variability is complex, nonlinear, stochastic, prone to flip-flopping? Or have you forgotten that there’s more to climate than linear deterministic forcing? No, that would be confirmation bias.

97. Posted Feb 12, 2009 at 9:25 PM | Permalink

Re #136 bernie, here are the annual temperatures, using the . Ferrell is red, McMurdo pink, Scott dark blue, Whitlock green, and Gill plum.

Whitlock is an AWS station.

• bernie
Posted Feb 12, 2009 at 10:25 PM | Permalink

Re: David Smith (#154), McMurdo and Scott are apparently 2KM apart according to GISS. That is quite a difference in temperature over such a small distance.

98. Posted Feb 12, 2009 at 11:16 PM | Permalink

Re #157 bernie, here’s a quote from a New Zealand study

There is a significant difference between the mean annual air temperature at Scott and McMurdo,
only 2.5 km apart. It is believed that this difference is due to Hut
Point Peninsula acting as a dividing ridge, thereby directing air from
generally warmer sources onto McMurdo (Thompson and MacDonald 1961) .
The surface inversion (1.2) may also contribute to the difference, since
the recording thermometers at the two stations are located at different
heights above the ground (M. Sinclair, NZ Meteorological Service,
personal communication) and because McMurdo has a significantly higher
mean wind speed than Scott (section 4.5).

On a different note, I noticed a P.D. Jones 2001 study on longer-term Antarctic stations, which should be interesting to read and compare with current data.

99. Posted Feb 12, 2009 at 11:23 PM | Permalink

To find the Jones link, click on Amundsen-Scott penguin on the left side of this page , then click the button below this reference –

Jones, P.D. and P.A. Reid. 2001: A Data Bank of Antarctic Surface Temperature and Pressure Data. ORNL/CDIAC-27 NDP-032. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee

100. tty
Posted Feb 13, 2009 at 5:09 AM | Permalink

Re 154

What is the trend for Ferrell, pre-May 2002 when the C19 iceberg separated?
At a guess, not very different from Gill over the same period, which seems reasonable since they are both out on the open shelf-ice.

101. Ryan O
Posted Feb 13, 2009 at 2:21 PM | Permalink

In case anyone was trying to download the text files for the manned stations on READER, the text link for Mario Zucchelli’s info actually directs you to the text file for Terra Nova Bay. Email sent. 🙂

• conard
Posted Feb 13, 2009 at 9:28 PM | Permalink

Re: Ryan O (#168),

The problem is this:
89662,Terra_Nova_Bay,74.7S,164.1E,92m
89662,Mario_Zucchelli,74.7S,164.1E,92m

102. Paul Penrose
Posted Feb 13, 2009 at 4:09 PM | Permalink

Ford,
Using a 30 year window is not cherry picking, but using the currently accepted standard for the definition of “climate”. This is what we are after, correct, climate change? If you wish to do a little more work, then by all means, go ahead and slide a 30yr window across the entire range for each site looking at how the trend changes over time. That would be very instructive and much more informative than a simple linear trend over a basically arbitrary period.

103. conard
Posted Feb 13, 2009 at 9:58 PM | Permalink

Oh, and while I am thinking about it there is another little problem that must have been introduced earlier in the week.

If 00 were changed to All then it would be consistent with the other station files and not have broken my script 😉

104. Posted Feb 14, 2009 at 5:45 PM | Permalink

Amundsen (manned) and Clean Air (AWS) are located at the nominal South Pole. (I haven’t found just how many kilometers, or meters, apart they are but they are close. Also, since they are located on the “polar plateau”, I assume they are at about the same elevation.)

It’d be interesting to compare such nearby manned and AWS stations, just to see what if anything pops up. So, here’s a comparison of their reported monthly temperatures for 1986-2002, the period for which Clean Air data is available.

(It is shown as Admundsen (current GISS version) minus Clean Air (current READER version), with the y-axis in degrees C difference. Missing months are omitted.)

One of the features I find interesting is the annual cyclical behavior. I suspect that is due to the difference in averaging methods between manned and AWS stations. If true, then that hints that caution may be needed when working with combinations of manned and AWS data. If the cycling is unrelated to averaging methods and is “real”, then that’s quite an interesting microclimate effect.

Another feature is that the average difference seems to shift about 1994. That surprises me. I guess it is microclimate-related but that is a weak guess. It’s a sizeable change.

If, in Antarctica, nearby stations drift like that, or if subtle AWS/manned differences introduce such drift, then I wonder whether small changes over time in the scattered, gapped Antarctica data are meaningful.

• Bernie
Posted Feb 15, 2009 at 9:47 AM | Permalink

Re: David Smith (#180), David:
Are mannned stations manned continuously or are they unmanned during the depth of the Antarctic winter – JASO?

105. Hugo M
Posted Feb 14, 2009 at 7:40 PM | Permalink

Very interesting, as it documents a varying bias. According to station history:

Site: Clean Air
Operation: Established with ID 8919 on 29 January 1986. The unit is located at the tower in the clean air sector at the SouthPole.

ID 8919 is wrong. Clean Air’s station ID in 1986 ws 8918, according to 10min data. In 1994, Clean Air’s ID was changed to 8987 and the Station Field Report History of 1994 reads:

Site: Clean Air
Performance: Repaired and moved on 24 January, pressure jumps erratically. expecially during the colder months.

Why your plot ends 2002? In Feb 2003, Clean Air got a new station ID:
21356. According to the station history, the whole station was removed two years later, at Jan 24, 2005. But according to BAS READER data , Clean Air has the ID 89208, and no data for 2003-2005, whereas 10min data for 21356/Clean Air is again available:
2003: 43601 of 57050 entries are valid (76%)
2004: 42801 of 52738 valid entries (81%)

Since 1994, the raw data provides dT in the eight column.

• Hugo M
Posted Feb 14, 2009 at 8:34 PM | Permalink

In case you asked just how far Clean Air was eventually moved in 1994, another Field Report has this on Clean Air:

Clean Air site was moved from it’s previous location to one approximately 30 meters from the South Pole Meteorological tower on 24 January 1994. AWS 8918 was replaced with AWS 8987. A snow temperature profile was also added. The depth of the profile extends to 4 meters.

So, what I previously named a “dT” (sensor) is a “snow temperature profile”?

106. Posted Feb 15, 2009 at 1:00 AM | Permalink

Now that Harry’s values have been shaved it’s time to take a peek at Uranus (the Glacier, that is).

I’ve been looking at daily data for that site, which includes resultant (averaged) wind direction. Here’s a plot of this daily wind direction, expressed in degrees of compass, from startup in 1986 through late 2000:

It may take a few seconds for the chart to make sense. Think of 180 as a due-south wind, which for Uranus Glacier is an airflow from mainland Antarctica. A value of 90 is an east wind while 270 is a west wind. The values of 360 and 0 are the same compass direction, of course.
The plot shows a reduction in southerly wind and an increase in northerly wind, most pronounced around 1990.

Perhaps there has truly been a reduction in south wind from the cold mainland due to a shift in weather patterns. If so then the cold south wind has been largely replaced by milder maritime airflow from the north.

If that’s true, then is that shift in weather patterns due to AGW and predicted by the models, or is it just a natural shift which affects local temperature?

Or, maybe there is something local which is affecting Uranus, perhaps an indication of a station relocation or glacier movement circa 1990. Maybe the station is now experiencing funneled, possibly downslope winds due to something in the landscape. Perhaps the mast height and sensors have been somehow altered by the weather.

I dunno.

I’ll take a look at other Uranus Glacier daily data to see if it hints at explanations. One thing the other data does show is evidence of a snow-buried temperature sensor in 1988, when diurnal temperature variation dropped to near-zero. I’ll post that plot later.

107. Steve McIntyre
Posted Feb 15, 2009 at 8:11 AM | Permalink

#183. David, nice analysis.

108. Posted Feb 15, 2009 at 11:30 AM | Permalink

Re #185 Good question. I don’t know, bernie. My assumption is that most are manned year-round but that’s a guess.

Re #184

The 1990 station history for Uranus Glacier has this note:

Wind speed and direction were intermittent after 25 Apr. Site was removed on 5 Nov.

That makes me wonder if the site was relocated in 1990, which would explain the change in wind direction tendencies. I haven’t found a reference which confirms a 1990 move but there are at least three sets of coordinates given for Uranus Glacier over 1986-2002. If I use the set at the Wisconsin website then (per Google Earth) the station is now on a northward-facing slope of about 15 degrees. That could help explain the lack of southerly wind.

On #180, my averaging-method conjecture to explain the annual cycling doesn’t make sense for a site located at the South Pole, which sees the same angle of sunlight throughout 24 hours. So, scratch that thought. The conjecture does make some sense for sites where sun angle varies during the day. I now wonder if the two South Pole sensors are at different heights, as a sensor closer to the ice surface may run warmer in austral summer and colder in winter.

Back on Uranus Glacier, here is a plot of the diurnal temperature range from inception to the end of 2001. (It’s a 30-day average for ease of visualization. “Diurnal range” is defined as the difference between the highest and lowest three-hourly temperature readings.)

Of note are the drops to near-zero diurnal range, which I attribute to the sensor likely being covered/buried in snow.

There is also a hint (poorly displayed on this 30-day average) that, in the days immediately prior to burial, the range increases then drops sharply. I wonder if temperature right at the surface varies more than it does slightly above the surface. The question mark shows such a spike which then fell towards zero (not shown) immediately before the data ended.

There is also a hint of a downward shift in average about 1990. That adds to my sense that the station was relocated in 1990.

• Hugo M
Posted Feb 16, 2009 at 3:51 PM | Permalink

I now wonder if the two South Pole sensors are at different heights, as a sensor closer to the ice surface may run warmer in austral summer and colder in winter.

The diagram below was taken from an old book about Antarctica. It shows a vertical temperature profile taken at Molodjoshnaja/Antarctica at Oct 11, 1974 17:30 by Alfred Helbig, a metereologist and member of a geophysical research expedition mounted by the former GDR. In a short report describing his responsibilities he also states that (for another, but near point) the strongest gradient was found to be 7.1 [°K/m], at a height between 0.75 and one meter. Nightly gradients have been found biggest. Influential factors were also fall of ground and wind speed. The first column of the table located to the right provides values for the temperature gradient, which he probably regarded to be somewhat representative.

Image source: Lange, Gerd [ed.]: Bewährung in Antarktika,Antarktisforschung der DDR, VEB F.A. Brockhaus Verlag Leipzig, DDR, 1. Auflage 1982, p. 123

109. Robinedwards
Posted Feb 15, 2009 at 2:51 PM | Permalink

The Mirny data are unusual in that they run uninterruptedly for a long period, 1956 to the present, with no missing values. They thus present an opportunity for carrying out analyses that might be able to identify features that are perhaps hidden in the sparser data sets that are more typical of of polar regions.

I am therefore putting forward an alternative to the standard analyses which I submit for your comments.

First, I repeat my assertion, expressed in this blog in previous contributions, that fitting of a simple regression (trend line) to a data set that even to the most casual and least critical perusal looks extremely unlikely to be realistically approximated by a linear fit (y=ax+b) is an exercise of limited value. No-one could conceivably by persuaded that it has any useful basis, function or merit in the real world. It is I suppose possible that there is no intention to propose the simple model as a serious contender for explaining climate behaviour. However, this model and its associated or equivalent inferential statistical quantities – like R-Sq and correlation coefficient and sometimes confidence intervals – which are often cited or quoted seems to imply that it is regarded as satisfactory.

So, what is to be done? In the first place one must hypothesise a plausible underlying model that can allow for the existence of climate regimes that do not sit comfortably with the simple linear fit but which might be regarded by many as being “potentially realistic”. My suggestion is that an assembly of contiguous simple linear models (i.e. covering much smaller time periods than the whole 1956 to 2007 data span) might be suitable.

Choice of suitable segments of the data is clearly a problem, but one that can be addressed by making use of the venerable quality control technique of computing the cumulative sum of the data points over the time period of interest. Applying this to the individual monthly averages as reported by observing stations is readily done, but of course yields a sinusoidal plot due to seasonal effects. De-seasonalising by simply subtracting the overall average for each month from the appropriate observations is a simple and adequate method, and it yields a data set that I call a “monthly difference”. This difference has a mean of zero, by definition – and this is a simple check on the arithmetic involved. By forming the cumulative sum of these monthly differences one obtains a data set that sheds a remarkable amount of light onto the scene.

Without going into the interpretation of cusum plots – which requires a paragraph or so but which is in fact simple and logical, I’ll set out some conclusions on Mirny based on this method. The first and most important is that the data indicate /very clearly/ that there have been at least 5 regimes of varying lengths over the whole period. Most of these are marked by step changes (occurring over a period of 1 or 2 months) of magnitudes between 1 and 2 degrees C. A simple explanation or reason for such changes is difficult for me to advance, but a possibility is a change of instrumentation or siting. They could presumably also be real climate effects, but whatever the underlying explanation they are so obvious that I feel they cannot be ignored.

A further simple inference from the cusum plot which has the general shape of a W is that an overall rise in value over the whole time period seems likely. However, in view of the huge “noise” element in this type of data this slope may not be statistically “significant” – whatever that means – and this is borne out by the statistics of the simple trend line.

Due to my sad lack of computer literacy (and knowledge of Windows XP) unfortunately I do not know how to publish diagrams (GIFs) on this blog, so I have to use words and numbers instead.

As noted above, I have used cumulative sum technology to make tentative identifications of five major regimes that appear to have occurred at Mirny. I characterise them as follows:-

Initial stable period was Jan 1956 to June 1958.
Regimes are named 0,1,2,3,4

Classification of MonDif by Regime with 5 Classes and 636 Items in total

I cannot get the formatting right. Sorry! Will insert \ to indicate a new field.

Regime\ Mean\ Std Dev\ No.\ Percent\ Std error\ Period\ Probable step size\\
MonDif \ of total \\ at end of regime
Deg C

0 0.931175 1.6878 29 4.56 0.313416 to June 1958 -2.0

1 -0.542567 1.92737 134 21.069 0.16649 to Aug 1969 +1.2

2 0.16195 2.06277 272 42.767 0.1207 to Apr 1992 -1.9

3 -0.594584 2.01892 99 15.566 0.202909 to Jul 2000 +2.0

4 0.5605 1.78886 102 16.038 0.177124

Sorry about this formatting problem. Hope you can understand it all.
I could send the GIF illustrations to anyone via email – but everyone is anonymous :-((

Note that the step sizes do not correspond with the changes in mean level. This is because all the regimes have a slight upwards slope, so the beginnings and ends of the regimes are displaced from the regime means.

One way analysis of variance of the simple regime-less model yields a between regimes / within regimes F ratio of 2.51, probability 0.114. The slope of the trend line is 0.0083.

Using the Regime model the F ratio is 8.93, probability 5*E-7, showing that the hypothesised regimes are not randomly related to the data. Yes! I knew that because I chose them, but on very strong evidence.

Summarising, my tentative hypothesis is that Mirny data have presented a regime-like pattern, which is surely worthy of more exploration and explanation before firm conclusions on this coastal site’s climate history is put to bed.

I can provide more information if anyone wishes.

Robin

• thefordprefect
Posted Feb 15, 2009 at 4:37 PM | Permalink

Re: Robinedwards (#187), To upload an image
1. best to save as jpg. Scale to be approx 800 pixel wide or less
2. join an image hosting site eg, http://www.imageshack.us/
3. on first entry to the site you are given the oportunity to upload a picture by browsing to the image (easiest place to find it would be the desktop). click on [host it]
4.when uploaded I find it easiest to click [my images] in the long orange bar
5.click on the small [i] against the right hand edge of the image.
6. click once on the direct link and copy all the link (url).
7. return to the thread move the cursor to the place you want the picture in the edit box. Click on the [img] button. If a warning bar occurs at top of page warning abouit scripted windows – click on it and allow scripted windows. re-click the [img] button and a box should appear. delete its contents
8. paste the copied info from the image hosting site
9. ok the next box or 2 until the url appears in the text. press return and the image should appear below in the preview.
NEVER use the [greater than] [less than] angle brackes in a post it causes silly things to happen!
ALWAYS mark and copy your post (in the entry box) before submitting -when it goes wrong you can always paste back and repost
It is interesting that we use similar “Monthly differences” my plots are done over 1961-1990 periods not the whole record)

110. Posted Feb 15, 2009 at 3:05 PM | Permalink

Here’s a closeup of March, 1988 thru February, 1989 for Uranus Glacier. It shows the drop in diurnal range as well as the decline in temperature change from one day to the next. Those are consistent, I believe, with a sensor being buried in snow.

And here is a plot of the recorded temperatures for the same period, plus an overlay of the temperatures for the prior twelve months. There is no way to know what the austral winter of 1988 was actually like at Uranus Glacier but the overlay suggests it probably missed the cold spells.

To me, based on the last several posts, Uranus Glacier should probably be viewed as two time series, one from 1986-1990 (with the winter of 1988 missing) and the other from 1992 forward.

111. Robinedwards
Posted Feb 16, 2009 at 4:35 AM | Permalink

Thanks for those instructions in #189, FordPrefect! I shall have a go when I’ve mustered enough courage.

Robin

112. Posted Feb 16, 2009 at 10:43 PM | Permalink

Re #191 Hugo, thanks for the reference on the vertical change of T near the surface. I enjoy the older, well-written references. If there is an opposite effect in sunlight then we may have an explanation for the cycling, assuming the sensors are at somewhat different heights.

You also mentioned windspeed. I notice in the Ferrell data that higher winter windspeed tends to be associated with higher temperatures. When I detrend Ferrell’s winter temperature data and plot the anomalies against windspeed I get an r-squared of about 0.3, indicating that wind indeed affects polar winter temperature (probably due to the effect of wind on mixing). Makes sense and it makes me wonder if the apparent warming or cooling of some Antarctic places might be caused by changes in windspeed.

• Hugo M
Posted Feb 17, 2009 at 1:39 AM | Permalink

Re: David Smith (#192)
Dave, somewhere within one of those various sparsely written AWS field report (or – history) files I read that during summer, slow wind speed also affects temperature — because sunlight is directly heating up the sensor shields. Using raw data, if one could throw in the dT sensor information and windspeed readings, one could eventually come with a quality weighting? Something like this:

Winter && slow wind && dT -> const: sensor is near to be buried
Summer && slow wind && |dT| >> 0: sun heats up the upper sensor

Besides, there should be at least one type of AWS in use which is equipped with a snow hight sensor, termed Acoustic Depth Gauge Sensor, which could be used as an calibration example.

Another analytic approach could be using temperature data only if the wind speed is sufficiently high, say above 3 [m/s] and when a high daily variance indicates that the main temperatur sensor is probably not buried. Thus all considered values would represent mean air temperatures, which, as you said, should not so much depend on sensor height above ground.

113. Posted Feb 18, 2009 at 9:49 PM | Permalink

Here’s a plot of wind speed (30-day average) at Uranus Glacier:

(Note: the mauve trend lines should be viewed with caution, as the timing of the data gaps may affect those apparent trends.)

The appearance is of an apparent shift in mean wind speed circa 1990-1991. This is suggestive of a location change. A change in wind speed is also important because wind speed may affect winter temperature (higher wind speed tends to lead to higher near-surface temperature, due to greater mixing).

The two graphs (wind direction and diurnal range) shown earlier in this thread also suggest a shift of some kind in 1990-91.

Finally, here is a plot of temperature (30-day average):

(Note: as with the first plot, the mauve trend lines should be viewed with caution, as the data gaps as well as the different seasons in which the segments start and stop will affect the slope of the trendlines.

The visual suggestion is of a shift in the temperature mean, circa 1990-1991. My conjecture is that this was due to a sensor relocation. Perhaps the data could be used for trending purposes if separated into a 1986-1990 trend and a 1992-2002 trend, but not as a single series from 1986-2002.

114. curious
Posted Feb 19, 2009 at 8:02 AM | Permalink

re: David and Hugo above.
Thanks for these posts on windspeed and snow height issues.

I had wondered on the relationship between wind speed and temp. (posted on Roman’s recent thread) although I was wondering about the value of using still air readings to ensure temp. records were accurate to the location of the sensor rather than a block air temp. for a moving air mass arriving from across the continent. Having read your comments I wonder if there is any value in an upper and lower windspeed limit to be applied to find qualifying records? Also wonder about any value of a second larger radius concentric shield on the temp. sensor for better still air measures?

I’d also expect the snow height issue to be important and suggest minumum height to snow should also be a criteria for record selection and think all stations should have this measurement channel added either by PIR of other means. Also do/could the stations record incident solar and could this allied to TOD give a measure of cloud cover?

Apologies if this is off track or covered elsewhere, I’ve not been following word by word.

115. Posted Feb 20, 2009 at 6:10 AM | Permalink

Re #195 curious, my growing sense is that windspeed is an underappreciated factor in Western Antarctic temperature.

The winter wind seems to have increased somewhat in the western region in recent decades. This is important as the wind disturbs and mixes the very cold air near the ice surface with somewhat warmer air above the cold surface layer (see Hugo’s chart in #191).

The result is that the recorded temperature at the sensor reads a mix of cold surface air and warmer air from above, giving an indicated rise in temperature. It’s not a real rise in the sense as the atmosphere has not warmed, it’s just that the sensor is sampling a different portion of the atmosphere.

I’m still looking over data to see if this hypothesis holds and hope to have a few plots this weekend.

• Philip Mulholland
Posted Feb 24, 2009 at 7:09 AM | Permalink

David

If you want to find detailed temperature profile data have, you looked at the Dome A website?
Excellent examples here of temperature rise associated with mixing.
Note how on each day (e.g.15th Feb) the 1m sensor lags the temperature rise at the 4m level as the cold pool of air gets disturbed in a top down mixing process. When the wind stops on 16th Feb the cooling process re-establishes the temperature inversion and the 1m sensor plunges to the lowest value in the daily profile. The ice surface is continously acting as a massive radiator of heat to space.

• Geoff Sherrington
Posted Mar 1, 2009 at 3:12 AM | Permalink

David, further to the above, at Ferrell I have just looked at the latest wind speed 3-hourly readings for part of 2009. The least significant digit 7 is still completely absent, as you might expect of you summed 10-minute readings with the 7 absent (but not always if you averaged them). Fortunately, the numeral 3 is back with a vengeance, but now, poor old zero has dropped off the radar. There are 277 readings in this dataset so you’d expect each LSD to report 27 times, approx. Here are the actual occurrences:

0,0 times
1,42 times
2,20
3,94
4,17
5,24
6,35
7,0
8,41
9,4

If you combine defective wind speed data with defective temperature data as in post 216, I guess you get a defective graph. I’m no longer a practising statistician even by contamination, so that makes me just a defective detective.

• Hugo M
Posted Mar 4, 2009 at 8:35 PM | Permalink

Re: Geoff Sherrington (#218), Geoff, your jump to a thus far reaching conclusion is not compelling. Try this real world example:

#sample conversion function for Dragon Devices ECT sensors
raw_to_temp = function(d) {
t = log( (4095/d) – 1 );
t_c = 25.02 + t * (-22.84 + t * (1.532 + (-0.08372 * t)));
t_c;
}
T = round(raw_to_temp(500:800),1);
LSD = abs((T-trunc(T))*10);
hist(LSD);

• Geoff Sherrington
Posted Mar 4, 2009 at 10:39 PM | Permalink

Re: Hugo M (#219),

No, Hugo, I simply look at the numbers. You give some conversion code for temperature in a garden potting mix. I gave also an example for wind speed. Presumably it has a different but related algorithm; it has the same problem with missing numerals.

What I initially infer from the Ferrell data is that the temperature should be reported only in whole degrees, with no figures after the decimal. What would be the case for wind speed?

Do you consider that the combination of a large number of (rounded?) observations can overcome a lack of measurement resolution? I am sceptical of how temperature change of 0.1 degrees a decade for the Antarctic can be derived from such coarse data, but I am open to education.

Do you know how many bits cover the designed instrument temperature range in the Antarctic AWS sensors?

116. Posted Feb 20, 2009 at 11:16 PM | Permalink

Sometimes data wiggles in curious ways.

Several days ago an odd wiggle in the Ferrell temperature data was mentioned at CA. This was a wiggle in which the winter temperature decline paused for several months despite the lack of sunshine. See “A” on this plot:

There was speculation that perhaps this was somehow tied to the freezing of Ross Sea ice but that conjecture never gained legs.

Then, Hugo M posted an
interesting graphic
on the near-surface temperature inversion found in Antarctic regions. That raised the question of whether increases in winter windspeed might affect the temperature measured at a sensor, as higher windspeed might turbulently mix the cold near-surface air with somewhat warmer air from above, exposing the sensor to a mix of “warm” and cold air.

To explore this, here is the chart with Ferrell’s monthly windspeed added:

Hmmm….the windspeed at Ferrell wiggles at the same time of year that the temperature wiggles. Do the (katabatic) winds noticeably increase at that time of year, perhaps due an increasing temperature contrast between ice shelf and sea, and the stronger wind then affects the reported temperature due to vertical mixing of air? Looks plausible to me. Has Ferrell’s slow move closer the sea increased its exposure to katabatic wind effects? That, too, seems plausible.

Of greater interest is a question which is raised by this apparent wind/temperature relationship. The question is, could the reported warming in West Antarctica be due, in part, to a natural decadal increase in windspeed rather than to the global increase in CO2?

To initially explore that, here’s the relationship between Ferrell’s windspeed anomalies (1981-2008) and its temperature anomalies. These are monthly anomalies from READER:

An r-squared of 0.67 hints at a relationship, I believe.

(I also plotted the relationship for all twelve months ( here ) and got an r-squared of 0.43 . Note that using all twelve months captures both inversion and non-inversion months, so the weaker relationship looks explainable.)

Might AGW drive the windspeed which in turn drives the surface temperature, thus meaning that AGW is behind the warming after all? Could be, though if I was Occam I’d begin to sharpen my razor over that reasoning.
Of course, this effect may be confined to Ferrell or the ice sheet and be untrue elsewhere on the continent. The only way to find out is to look at data for other sites. But, at a minimum, it raises questions about the suitability of using Ferrell, or any site with decadal changes in winter windspeed, in estimating regional temperature trends.

• John F. Pittman
Posted Feb 24, 2009 at 6:44 AM | Permalink

Re: David Smith (#197), Nice post David.

• bernie
Posted Feb 24, 2009 at 7:43 AM | Permalink

Re: David Smith (#197), Nice piece of investigation and very interesting. It raises the spectre of micro-climate effects for otherwise small changes in height, placing of buildings, etc. Of course, the micro-climate changes are of indeterminate impact (cooling or warming).

117. bender
Posted Feb 21, 2009 at 12:25 AM | Permalink

Hmm, neat.

118. Posted Feb 24, 2009 at 8:21 PM | Permalink

Thanks for the link, Philip. The differences in temperature near the surface and the effects of wind mixing are remarkable. I’ve added it to my Antarctica links page.

Here’s a final plot on Ferrell. It shows the monthly wind anomalies (anomalies from the mean monthly values for 1981-2008) and, in a light mauve, the temperature anomalies:

It’s a homely plot but I hope it illustrates –

* the fractured nature of the Ferrell data (and most AWS data for that matter)
* the rise in windspeed over the period
* that windspeed and temperature move similarly
* a hint that windspeed may have taken a step up after the birth of iceberg C-19 in 2002

119. bender
Posted Feb 25, 2009 at 8:03 AM | Permalink

Interesting. Would be nice to see some other station data.

120. Posted Feb 25, 2009 at 10:37 PM | Permalink

bender, here is an indication of the relationship between winter temperature and windspeed for various long-term Antarctic stations. (The background map, borrowed from here (see 3’rd penguin from the top), has better resolution for reading the station names.)

I’ll create a smaller map for Western Antarctica if I can find some long-term wind records (most AWS data is too brief)

It’s an interesting distribution of values. I’ll take a shot at interpretation tomorrow.

• bender
Posted Feb 27, 2009 at 12:45 AM | Permalink

Re: David Smith (#204),
Those are r-squared, not r? They’re huge!
.
Windspeed can make the difference between life and death. Any LSU Tiger knows that. Guess the team is still figuring out the basic facts of life. Nature newsflash.

121. Posted Feb 26, 2009 at 5:47 AM | Permalink

Re #204 Correction – That’s “austral”, not “astral” 🙂

The values shown are for linear relationships. The two locations marked “N/A” lack sufficent wind data. The data is from READER.

122. curious
Posted Feb 26, 2009 at 12:00 PM | Permalink

Re: David at 204. Thanks David – as a novice I was thinking of tackling this!

I’d also hoped to include the wind direction. I had a look at the Ferrell data and if I’d got my head round it properly it was pretty much continuously offshore within a 30deg splay. I’d be interested how other stations compare. I did a quick check and there do seem to be references about on antarctic wind patterns but haven’t had time to follow up. I’m wondering about what the overall airflow pattern across the continent is – no doubt it is known and understood already but I’m wondering how it relates to AWS data from up to approx 3m height. Thought I’d mention it FWIW – sorry if it is a dead end.

I’d also like to see any realtime or short time step series data from these AWS stations so if anyone knows a source please shout.

123. Posted Feb 26, 2009 at 8:54 PM | Permalink

Re #206 curious, try these for Ferrell 10-minute or daily data:

http://uwamrc.ssec.wisc.edu/aws/archive/Ferrellarchive.html

ftp://aws.ssec.wisc.edu/pub/aws/climate/

Ferrell is known as 8907 and, later, 8929.

Current readings can be found at the links here:

http://uwamrc.ssec.wisc.edu/aws/ferrellmain.html

124. curious
Posted Feb 27, 2009 at 2:57 AM | Permalink

Re: David at 207 – Thanks will follow up. C

125. David Smith
Posted Feb 27, 2009 at 12:32 PM | Permalink

Re #208 bender, those are r-squared, not r, and indeed some are of a respectable size. I plan to look at Ferrell and several other sites to see how well their their decadal temperature increases corespond to their wintertime windspeed increases.

• bender
Posted Feb 27, 2009 at 1:01 PM | Permalink

Re: David Smith (#210),
gavin? mike? You watching this?

I know, I know. It doesn’t matter that your methods are wrong; you still have the right answer.

126. curious
Posted Feb 27, 2009 at 4:19 PM | Permalink

Re: David at 207 – I’ve had a look around at those links but I haven’t been able to find a format statement for the time step record. Does anyone have any pointers? I think the AWS data has been discussed on other threads but looking back I can’t see the info. I’m after:

Looking at this link: http://amrc.ssec.wisc.edu/~amrc/8929.txt

at 20:15GMT today I got 443 records with several apparent duplicate entries. The first 10 records were:

ARGOS ID Date Time T(C) P(MB) SPD(MPS) DIR RH(%) LAT/LON
—- —- —- —– ——– — —– ——-
8929 2009057 4254 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4251 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4254 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4251 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4254 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4251 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4254 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4251 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4254 -23.2 972.7 5.6 203 71.2 -77.86 -170.819
8929 2009057 4251 -23.2 972.7 5.6 203 71.2 -77.86 -170.819

I’m not sure what the time column is – I think it is mins to 2dp. So there are some duplicates and in mixed order. Using Excel I’ve sorted and cleaned the duplicates which reduces the number of records to 146 (approx 1/3). The duplication and mixing did not follow an obvious pattern. Some time values had 8 records, others had one.

On this test sample I did simple column averages of the full 443 record set:

T(C) P(MB) SPD(MPS) DIR RH(%)
-18.24604966 975.4316027 9.441760722 220.4085779 91.12370203

and on the reduced 146 record set:

T(C) P(MB) SPD(MPS) DIR RH(%)
-18.15547945 975.509589 9.562328767 221.8493151 91.42054795

So the results are different (sorry re: tabulation and no. of dp).

I am curious to know how the timestep series is arrived at – I think I saw somewhere the stations use buffering and send blocks when they get the “chance”? If so is the timestamp the time of the reading or of the sending and what is the significance of the duplicates? As far as calculating averages is concerned if the duplication is random it seems to me it will mean calculated averages are not representative?

I’d welcome views and explanations and links/pointers to any further info. Apologies if I’m repeating info. covered on other threads or if this is very basic – I tried a Google on CA but didn’t find what I’m after. Thanks

• Hugo M
Posted Feb 27, 2009 at 5:16 PM | Permalink

Re: curious (#212),
you are looking at non-qc’d AWS data, with some noise due to multiple transmissions (sat uplink is one-way). Date and time format is obviously “year day-of-year” “hhmmss”, leading zeros implied.

• Geoff Sherrington
Posted Mar 1, 2009 at 1:39 AM | Permalink

Re: curious (#212),

There is a strange impediment with the Ferrell temperature data, reported to one place after the decimal Celsius.

Taking the month of December 08 at random, one can look for systematics in the figures. First, the “444” figures for missing data can be arbitrarily replaced by the number adjacent to them, to make counting easier. Not many corrections are needed in the 464 observations. Then the dataset can be examined for the frequency of reporting of each numeral 0 … 9 as the least significant digit.
David Stockwell offers this service on his Wikipedia chapter of Niche Modeling. Thank you David.

The strange matter about the Dec 08 data with the minor correction noted is that numerals 3 and 7 do not appear at all in the LSD data. Each would be expected to appear 446 times on a probability basis (give or take a little, if you wish to argue distribution effects).

The frequencies of the LSDs in these 10-minute readings are
0,731
1,333
2,609
3,0
4,646
5,573
6,543
7,0
8,484
9,548

One suspects the hand on man, or perhaps a corruption of the logic on the circuit board gathering the information. Who knows? It might even be Mrs Millamant seeking a husband.

It would take a brave person to invest significant research or statistical time on these data, which are obviously distorted, for that month at least. If I as a non-expert can find this huge error on my first examination of the data, where stands quality control?

• Geoff Sherrington
Posted Mar 1, 2009 at 2:02 AM | Permalink

Typo, there are 4464 data points in 10 minute intervals, for the month, not 464 observations as I wrote above.

127. curious
Posted Feb 27, 2009 at 6:32 PM | Permalink

Thanks Hugo – ahem: red face over the seconds! 😦

As far as QC goes does everyone apply their own view on this? Or is there a standard weighting method for getting an hourly, daily, monthly average value? Presumably there has to be an integrating step wrt time? It seems the 3 hourly values published have had “bad points” removed but it does not mention the averaging process in this FAQ:

Is this 3hr data taken as the “starting point” before RegEMs etc are applied? If there is a good source please just point me to it. Thanks.

128. Posted Feb 28, 2009 at 8:32 AM | Permalink

curious, I’ve looked at the archived 10-minute data available here , with the first column being the sequential day of the year and the second column being the sequential (10-minute) reading of the day. I’m pretty sure that data has undergone cleanup. The three-hour data is on the same page, at the bottom.

You might spot-check some examples to see just how the three-hour data is calculated (spot reading every 180 minutes, or average of 10-minute readings or something else).