NASA GISS a temperature outlier again – this time for the southern hemisphere

Hansen, et al have absolutely no shame (nor credibility). How many times does Peter have to cry, “Wolf” before the people stop paying attention.

On a geological time frame, it’s thirty years of weather.

I would hazard a guess and say it’s Africa since just about the entire middle section of that continent is devoid of data.

I made the Animation in this video by making Anomaly maps from the GISS site. They are Jan-Dec, 1951-80 Normals but instead of using the 1200km “smooth” its set to the 250km option. Once you do that you see that the SH is really lacking in readings. Africa almost none, South America has a blank spot and if you do a polar view on the 250km scale Antarctica is very sparse in data.

Anthony, about when will the surfacestations summary come out?
Thouth I know you’ve been busy since the outbreak of Climategate and other stuffs, many folks probably await it.

Hey folks, just finished a post which I believe provides proof (or at least a clear way to prove) the AGW theories are mathematically invalid.
http://strata-sphere.com/blog/index.php/archives/12246
Comments welcomed!

I’d hate to see these people attempt to drive. Their reactions to the trees and rocks moving, let alone other vehicles, must be frightening. What happens when a bug hits the windshield???
http://www.flickr.com/photos/22364639@N07/3075281852/
http://www.flickr.com/photos/23094963@N08/2298533435/
http://image.motorcyclecruiser.com/f/8827875/WS-Lead-xl.jpg
http://image.motorcyclecruiser.com/f/8827933/WS-bug-tite-lg.jpg
Sorry it wasn’t a movie… 🙂
Ameteur vote: Darwin Station. (I read that great article last month, about how the hockey puck’s hockey stick was replicated, by a step-by-step process.)

Or as they have done move all of the thermometers, into cities which seems cheaper, and easier.

I wonder where the 0.1C added at start of 2007 came from? Before and after that date the trace appears to be constant.

Pursuing the fractional degree rises and falls a moment: I guess this is why a tipping point had to be introduced, else no one would have even listened.

Just a thought to get an ideal climate in less than 20 years you could build an impulse sprinkler into the base pole of the temp station, and plant fast growing trees in the circular drip line of the sweep, turn it on every day for 3 hours at mid day. What a wonderful world we could report on to the public, (can you say future immigration problem?)

ajstrata:
Nice graphical illustration of temperature variability on one day in a homogenous region smaller than the gridded areas used by GISS to record data. I was actually somewhat surprised by the range of high temperatures. Another nail in the IPCC coffin? Agree with j. pickens, though; some spell-checking and proof-reading is in order. The “there” on the second to last line is particularly jarring. ( I’m hoping meanwhile that I’ve avoided a grammar gremlin in this post – amazing how mistakes slip past one).

If GISS keeps up this parade of ‘outer limits’ reporting, there’s going to be a day of reckoning for wayward spenders of taxpayer monies. They are probably alread there or darned close to it.

BernieL: You asked, “Are we seeing the end of El Nino this southern summer?”
NINO3.4 SST anomalies have dropped the last few weeks.
http://i48.tinypic.com/5d2xzr.jpg
It’s the right time of the year for it to peak. Assuming it doesn’t turn into a multiyear El Nino, the next questions are how quickly will SST anomalies drop, and how significant will the La Nina be?

Neville
If we say the LIA ended in 1850 then the temp either goes up or we face a further reduction in temp
1850? I keep seeing that date crop up and am not certain why. The low that preceeded the current warming trend was 1830 on almost every reconstruction and even the cherry picked ones from the IPCC spaghetti graph of 9 reconstructions show it. Further, that low was after a very short cooling period which was preceeded by a low around 1600 or so which the IPCC graph also shows, regardless of how warm the reconstruction highs are compared to the current measured highs, the trend is obvious…. warming since 1600, the IPCC says so and I choose to believe them:
http://en.wikipedia.org/wiki/File:1000_Year_Temperature_Comparison.png

Can any data from these people be believed?
November 22, 1996: email 0848679780
“Remember all the fun we had last year over 1995 global temperatures, with the early release of information (via Australia), “inventing” the December monthly value, letters to Nature, etc., etc.?
I think we should have a cunning plan about what to do this year, simply to avoid a lot of wasted time.
We feed this selectively to Nick Nuttall (of the United Nations Environment Program) (who has had this in the past and seems now to expect special treatment) so that he can write an article for the silly season. We could also give this to Neville Nicholls (climate scientist at the Bureau of Meteorology Research Centre in Melbourne, Australia)?
I know it sound a bit cloak-and-dagger but it’s just meant to save time in the long run”.
Any data that has been anywhere within 1000miles of these crooks must be ditched in the bin. Yes they have been “inventing” data, torturing data and misrepresenting , misinterpreting data for years. They are useless for any meaningful scientific analysis.

Jimmy Haigh (20:18:06) :
ajstrata (19:47:43) :
Very interesting. I hope
I’m with you Jimmy. It is very logical and easy for laymen (like me) to understand.
i have always though that the data was too variable from place to place, that the margin of error even in reading the data over the years let alone recording was far too great for the AGW folk to arrive at such a certain conclusions for such a small annual increment to have any credibility.

If it’s too cold they hide the decline. If it’s not hot enough they fudge the ascent.
That reminds me. In a previous thread someone was saying something about clowns. Maybe GISS should adopt the following lyrics as their official climate change theme song:
Don’t you love a farce? My fault, I fear
I thought that you’d want what I want, sorry my dear
But where are the clowns? Send in the clowns
Don’t bother they’re here

January 6, 2005: email 1105019698
David Parker of the UK Met Office to Neil Plummer, Senior Climatologist at the National Climate Centre of the Bureau of Meteorology, Melbourne, Australia:
“There is a preference in the atmospheric observations chapter of the IPCC 4AR to stay with the 1961–1990 baseline. This is partly because a change of baseline confuses users, e.g. anomalies will seem less positive than before if we change to a newer baseline, so the impression of global warming will be muted”.
So the anomalies will SEEM LESS POSITIVE ha?
I was told by bloggers that changing baselines didn’t alter anomalies. Not so coming from the horses mouth. What baseline do we use and why?
REPLY: From GISTEMP “Temperature anomalies are computed relative to the base period 1951-1980.” which is part of the reason that GISS is an outlier, since they use a baseline that has some of the coldest weather in the 20th century. HadCRUT uses a 1961-1990 baseline. UAH by necessity uses a baseline starting in 1979, when data gathering first started. – Anthony

“Hadley Centre data is still not available for December, and they’ve been running late recently.”
Phil Jones still suspended? No records of how to manipulate his computer model? Bet the records show it’s cooler there these days!

Unless AGW believers are stupid enough to think that temperatures have remained completely flat up until the industrial age started, they have no case with a rise of only 0.6 C since then.

Terry Jackson (21:46:03) :
“Bolivia.”
Do you mean, as in Bolivia?

Good to hear some discussion of signal to noise in this thread. When you consider, hundreds of readings all subject to equipment and operator error, rounding errors, and to local changes such as urban heat effect, new buildings, airport runways etc. Then you consider that all these are “adjusted” as Anthony has demonstrated many times in the past, then they are averaged…
… and not an error bar in sight on any of these “average temperature” plots, no mention of what the standard deviations are, or the P values.. My PhD supervisor would have slapped me for producing a graph with no error bars. You would struggle to get a paper published in mt field (biological sciences) without a discussion of the P value i.e. what is the probability that this data was the result of chance?

Veronica (01:26:14) :
Good to hear some discussion of signal to noise in this thread. When you consider, hundreds of readings all subject to equipment and operator error, rounding errors, and to local changes such as urban heat effect, new buildings, airport runways etc. Then you consider that all these are “adjusted” as Anthony has demonstrated many times in the past, then they are averaged…
Agreed!
People are freaking out day to day about the shocking headlines they read in the papers. No one realizes that the actual data these headlines are based on is so far within the margin of error that its just as likely to be noise as it is to be a detected temp change .
We had one such headline from NIWA ‘warmest decade on record’ a few weeks back. It turned up on the front page of all the main media outlets…. None mentioned that NIWA was talking about less than ONE TENTH of a degree C.

brc: You wrote, “The southern hemisphere is sparsely populated (compared to the NH) and about 50% ocean.”
Oceans occupy about 70% of the global surface area and about 80% of the Southern Hemisphere.

RE: GISS/UAH SH ‘discrepancy’
Are you sure that the ENSO lag is not playing some part in this, i.e. satellite readings don’t respond as quickly to El Nino development.
The surface temperatures started to rise much earlier in the year. UAH readings for the 6 months since July have been at record levels – higher than the same period in 1998. The SH surface (GISS) temperatures seem to have moderated while it’s not clear that has happened with the satellite temperatures. I think we need to look at the Jan/Feb numbers before jumping to conclusions.
This issue came up some months ago (June??) when UAH was recording near zero anomalies while GISS and Hadcrut anomalies were rising. I reckon there’s a good chance that by May or June, UAH will have recorded it’s warmest ever 12 month period (SH and NH).

boballab: You wrote, “I would hazard a guess and say it’s Africa since just about the entire middle section of that continent is devoid of data.” And you included a link to your video:

I would tend to agree over the past 30 years. I compared GISS land surface temperature anomalies to UAH MSU TLT anomalies back in June:
http://bobtisdale.blogspot.com/2009/06/part-2-of-comparison-of-gistemp-and-uah.html
Of the areas I was able to check, Central and Southern Africa had the greatest difference between the GISTEMP and UAH MSU linear trends:
http://i40.tinypic.com/1hb5sm.png
But in that comparison I extended the data across the equator, so it’s not exclusively Southern Hemisphere.
PS: Thanks for the link to the video.

You can check out the animated global weather patterns for the past
ten says here:
http://www.ssec.wisc.edu/data/comp/cmoll/cmoll.html
Four frames = one 24 hour period.
This gives land & sea temperatures. Note how rapidly the day temperatures change as the sun warms the land. This is
especially obvious across Australia, the southern part of the
Indian subcontinent, Africa and South American.

Ajstrata, I’m afraid there are some serious flaws in your article. For example,
“…The standard deviation in percent temperature change was 38.5%!… ”
No ! to do this correctly you have to first convert to the Absolute temperature scale, on which zero is -273.15 degrees C. This would make your percent SD much smaller.
Also, I am not at all sure about your statistical reasoning. In principle, it is perfectly valid to use the average temp for a cell, as long as the same method is used to find the average for each cell.
This is what statistics is all about, picking out trends and patterns from noisy data. That’s it’s whole purpose in life.
It’s true that the noisier the data, the less the confidence level of the calculated trend. But nevertheless a trend line CAN be calculated, and a confidence band put on it.
It’s also true in these records, as you point out, the SD of an individual point is greater than the effect supposedly being measured. However, if there are a sufficient number of points (cells) the statistical calcs take this into account automatically. It can even weight points inversely relative to their uncertainty.

Oefinell (02:45:04) :
“That is why they do not measure the absolute temperature at all, they measure the temperature change or variance.”
“Provided the methodology is consistent from month to month then you can accurately see how temperatures have changed over time. You do not need to calculate an absolute temperature at all.”
A couple of questions:
(1) What were all of those mercury thermometers of yore measuring? How were they calibrated? Were they all calibrated regularly and consistently (especially those highly accurate bucket thermometers used by the scientifically-trained sailing crews upon which we base a large portion of the historical ocean surface temperature data)?
(2) Does the absolute temperature matter? Thermodynamically, of course, it does (e.g. in evaluating equations of state, thermophysical properties of gases and liquids, freezing/melt points, etc. etc.). But is climate science somehow exempt from this?
(3) Is the metric of a “world averaged temperature anomaly” thermodynamically meaningful? That is, does it accurately imply anything about the heat content of the air-ocean-land system?

I haven’t read through all the comments (in hurry this morning) so I apologize if this was already covered. A question to:
boballab (18:59:57) :
I would hazard a guess and say it’s Africa since just about the entire middle section of that continent is devoid of data.

Thanks for the work you did! It seems the middle Africa section dearth of data is for the recent years, with some decades prior coding in the yellow range which was about the same as large parts of the rest of the earth. What would cause the “dropout” of sensors for Africa in recent years??
Dan
New Jersey, USA

hunter: You wrote, “Hansen’s mental contortion to claim that we have just finished the hottest decade on record seems contrived, at best.”
Especially when you consider that the majority of the difference between the 1990s and the 2000s was caused by the aftereffects of the 1997/98 El Nino (and 1998/99/00/01 La Nina). Refer to:
http://bobtisdale.blogspot.com/2009/11/global-temperatures-this-decade-will-be.html
Regards

Bob Tisdale : Do the graphs that I’ve posted at
(05:12:10) and (05:40:28) accurately reflect the Global and Southern ice record? Are the a reasonable proxy for Global and Souther temperatures?

The ever-changing methods of adjustments and the dying of thermometers enable GISS to create a continuous bull market for global warming. Ultimately, imho, the point here is to create higher highs and an ongoing bull market. They understand that the PR is more important than the science in terms of accrual of power and money.
As boballab has clearly demonstrated, the center of Africa is butt naked. It is a huge continent with sparse coverage. In the 21st century no less.

Peter of Sydney–Thanks for emphasizing that the entire AGW debate is about 0.6 C. Much of the debate can be likened to early theologians arguing about how many angels can dance on the head of a pin. To believe that AGW is real, one would have to believe that the temperature measurements and the climate models are exceptionally precise. If you look at the purported science behind AGW, one would have to be BRAINDEAD not to be a skeptic. Please see my latest post at http://socratesparadox.com/?p=121#more-121 for further discussion.

Oefinell (02:45:04) :
ajstrata (19:47)
Interesting post but misguided. Your blog correctly states that it is not possible to get an accurate global surface temperature from current data. In fact that is well understood by Climate Scientists. That is why they do not measure the absolute temperature at all, they measure the temperature change or variance.
————–
So, what you’re saying is that when Alexei pulls on his parka and goes out to the airport stevensonsky screensky, he just looks at the top of the thermometer, not the whole thing?

Bob Tisdale (03:49:45) :
John Finn: You asked, “Are you sure that the ENSO lag is not playing some part in this, i.e. satellite readings don’t respond as quickly to El Nino development,” then clarified that satellite data meant TLT.
Note the difference between the GISTEMP and NCDC data.
Bob
Fair point about NCDC, but there’s an issue about the GISS 1998 anomaly. It’s always seemed, relatively speaking, much lower that the other datasets.

Bob,
The GISS divergence is no longer a mystery. Let me get things up to date a little. Since around 1998 GISS has been significantly diverging from HadCRUT and UAH and RSS. The reason that was given by Real Climate was that GISS did infill at the poles and the others did not represent the poles. Real Climate considered this to be a reason to consider the GISS data set as superior. Of course GISS is the only data set that shows warming since 1998. HadCRUT, UAH and RSS do not. I made the argument that it could not be the poles because it would take a huge amount of heating at the poles in order to produce such a large global divergence. Well, I was wrong. It was the poles. But I was not wrong about the huge amount of warming that it would take at the poles to cause the divergence. Four days ago Jim Hansen did a guest post on RC. What he had done was to take the GISS grided map and remove from it those areas that were not covered by HadCRUT. These were mostly polar of course. Then, when he did a global average on the map that resulted, the answer was very close to HadCRUT. So far so good. The divergence was in fact due to the poles. But the problem was that the infill that GISS is doing at the poles is completely irrational. For example, there were some polar cells that exist and show cooling in HadCRUT. These cells were converted to maximum hot by the GISS algorithms. The difference for some of these cells between the values that HadCRUT had for them and the value that GISS had for them was 6.7 C or greater. An outrageous difference. Then, if you look at the total anomaly that HadCRUT has for it’s most northern (a row with 30% coverage) row and compare it to the same row in GISS, the GISS anomaly was more than two times as large on a per cell basis. The GISS infill algorithms are pure nonesense. I have been pointing this out in the comments for Hansen’s latest post. And I have had no response from Hansen or Gavin. And there has been no meaningful response from the RC sycophants. Here are the Hansen charts that I am refering to:
http://www.realclimate.org/images/Hansen09_fig3.jpg
And here is one of the comments that I made on the Hansen thread.
“I’ve been talking about the qualitative problems that I noticed in the GISS charts in figure 3 above. So I thought that I would try to take a rough shot at quantizing the problem as well. I used the HadCRUT 2005 chart and the GISS 2005 chart to make comparisons. And I wanted to compare the HadCRUT gridcell row that was furthest north to the GISS gridcell row that occupied the same position. First I counted the number of gridcells in a row. There are 72. Then I counted the number of HadCRUT cells that have data in that row. There are 24. This means that the topmost HadCRUT row has 30% coverage. So I added up all of the covered gridcell anomaly values in the row. The total was 43.8. Dividing by 24 I got an average covered gridcell value for the HadCRUT row of 1.85 C. The GISS row obviously had 100% coverage using interpolation and extrapolation. When I added all of the gridcell anomaly values together for the GISS row I came up with 300. Dividing by 72 gave me an average anomaly value of 4.17 C. So the anomaly for the top row of GISS is 2.25 times as large as that of HadCRUT.
It seems to me that this reflect very badly on the GISS interpolation extrapolation algorithm. The other problem is that there are 6 cells in that top row that HadCRUT has negative values for. GISS turns them all to the maximum positive value. The difference is 6.7 C or greater per cell for those 6 cells.
I can only conclude from this that the GISS divergence from the HadCRUT data is an artifact of the GISS processing algorithms and not a reflection of actual temperature variance at the poles.”
As I point out, the GISS interpolation extrapolation algorithms are just nuts.

ajstrata (19:47:43) :
“Hey folks, just finished a post which I believe provides proof (or at least a clear way to prove) the AGW theories are mathematically invalid….”
Interesting analysis. I was always bothered by the claims such as “this year is 0.1 C hotter than last year” given the inaccuracy of the measurements, sparsity of the data and non-uniformity of temperature over distance.
So how many BILLIONS have we wasted on this boondoogle

j.pickens,
I have a day job, I am sure you can muddle through as is.

Ajstrata,
You have some serious problems with your work. First and most glaring is saying 2 degreesF or 2 degreesC is a larger percentage from a low temp day to a high temp day. False. Using your flawed theory your numbers would change just based on which scale the readings are being represented, as in C, F, absolute, K, etc.
Secondly if data is unadulterated by UHI, Station placement etc., a small number of land based stations could end up being accurate on average. Why? Because you have an equal chance of being high or low and an average gets rid of the noise in theory.
The problem of course in lies in the fact that many stations are not unadulterated in some form. Even lay of the land surrounding the station can make a large difference, such as higher or lower to surrounding land masses, open to the breezes the stir the temps and which direction the prevailing breezes are in comparison to temp influencing areas up or down wind from these influences.
But with all these influences obviously in play and they are not throwing out the high and low outliers, what it comes down to is, what is the LSD or noise in the model. I realize this is what you are trying to do but your method needs some major cleaning up……FWIW. Sincerely. John

C Osborne,
Actually they interpolate changes using guesstimates. You cannot measure .1% and claim you have a valid number for the globe (absolutes or variances). And in their effort to cover the globe they neglect to add in the natural error (+/- 2°F or greater) introduced in extrapolating distances of 100’s of kms – making their conclusion meaningless. I.e., we see a 0.8°C increase +/-10°???
If they worked for NASA launching and designing spacecraft they would be fired.

John Finn
“Fair point about NCDC, but there’s an issue about the GISS 1998 anomaly. It’s always seemed, relatively speaking, much lower that the other datasets.”
John, as I point out above, the polar infill algorithms that GISS uses are garbage. The fact that GISS is cooler than the other sources in 1998 is also a product of the GISS infill algorithms.

John:
a small number of land based stations could end up being accurate on average. Why? Because you have an equal chance of being high or low and an average gets rid of the noise in theory
Your comment on scale affecting variance is right on, these kinds of things should be done in degrees K only. But your comment on averages holds only if the distribution of errors is random and the direction of the errors also random. Since the preponderance of observation stations are located in proximity to human activity, the preponderance of errors from urban heating are all in the same direction. Except for all those Russian stations that were in urban centers that got subsidies in the days of Communism for heating fuel dependant on the winter temperatures and so reported false lows to get more fuel subsidy. The only way station data gets down to an error rate that is reasonable is if you comb through each and every station and adjust it for urban heating index across its entire data set and THEN analyze.

…and if you want to have a little fun with graphs and exageration and perception… take the CO2 graph from IPCC and extend it out to show CO2 steady at 280 ppm prior to 1920 and rising to meat the IPCC measurements starting in 1960. Then scale it so that the 38% rise in CO2 roughly equates to the 1 degree rise in temp over the same time period, then superimpose THAT on the IPCC temp graph starting in 1880 and it should be very simple to see where the impact of CO2 greenhouse effect kicks in. Too much work? OK, I will do it for you, but you will have to spot the place where CO2 kicks in yourself because I couldn’t:
http://knowledgedrift.files.wordpress.com/2010/01/temp-vs-c02-long-term1.png

Pascvaks (05:40:28) :
Once again from the simple answers department, for those interested in a proxy record of “Southern” temperature anomolies since 1979 up until a couple weeks ago.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/current.anom.south.jpg
And:
Pascvaks (07:22:11) :
Seemed that Sea Ice cover was a pretty effective way to tell if we were actually cooling or warming from a Macro point of view. Thanks again!
Assuming your interpretation of that graph of Southern sea ice is in an uptrend (more ice), it doesn’t seem to agree with GISStemp.

Ref – Tim Clark (09:54:10) :
“Assuming your interpretation of that graph of Southern sea ice is in an uptrend (more ice), it doesn’t seem to agree with GISStemp.”
________________
Right! While the Southern Ocean temps may be up ‘here and there’, the overall effect on the polar weather seems to say ~what? Seems a good gage of climate change (North or South or the Planet) is the amount of ice (or not). Just looked like a good proxy for climate change. If Gore&Co is right we’ll be sunbathing in Nome soon. If they aren’t, we might be skating in Tahiti soon, or not.

Oefinell (02:45:04) :
“…In fact that is well understood by Climate Scientists. That is why they do not measure the absolute temperature at all, they measure the temperature change or variance.
Provided the methodology is consistent from month to month then you can accurately see how temperatures have changed over time. You do not need to calculate an absolute temperature at all….”
The hypothesis is an increase in CO2 causes an increase in temperature and that CO2 is the primate driving force in the present day climate. So AJ’s, Anthony’s and Willis’ analysis of the temperature data are very important.
Anthony’s US surface station analysis showed changes in the methods used to collect temperature data and changes in the weather station siting and location that effect the temperature trend over time. Willis’ Darwin analysis [ http://wattsupwiththat.com/?s=darwin ] showed how a flat temperature trend was adjusted to show a rising trend. Now AJ shows how large the minimum error is in determining the temperature for a “grid” therefore negating the reasons for adjusting the Darwin data in the first place. On top of that add in the station drop out and the Russian’s complaint about the choice of data stations dropped and I do not care what type of “spin” you put on it, the data is crap and therefore ” the temperature change or variance” is also crap. “Climate scientists” are not comparing the change from the same thermometer at the same location with the same surrounding conditions but are looking at the variations in artificially “homogenized” and adjusted data.
If you have the time you can look at all of the local graphs of non-urban areas collected by John Daly. Some graphs show an increase in temperature, some a decrease but the thing I noticed was the sixty year sinusoid curve peaking in the thirties indicating the influence of the oceans on the weather. http://www.john-daly.com/stations/stations.htm
I do not see where diverting attention away from temperature to ” ..whether the climate sensitivites included in the IPCC models are correct.” gains us anything.
The argument reminds me of the Delphi technique used by the USDA to gain “Consensus” on animal ID, the technique didn’t work on the farmers either.

Tilo Reber (09:07:57) :

John, as I point out above, the polar infill algorithms that GISS uses are garbage. The fact that GISS is cooler than the other sources in 1998 is also a product of the GISS infill algorithms.
I’m not sure you can say they are garbage with any certainty. That is the easy response – which probably goes down well on WUWT. It’s clear that that ENSO fluctuations have a sharper impact on satellite troposphere readings. The UAH anomaly for 1998 was 0.54 deg. If we use the same base period as UAH (1979-1998) the GISS anomaly was 0.33deg, i.e. 0.2 deg lower. If we compare GISS to Hadley/CRU using the Hadley base period (1961-1990), the GISS anomaly is 0.50; Hadley is 0.54 deg – much closer.
Since ~1992 the trends of GISS, UAH, RSS and Hadcrut have been within about 4 hundredths of a degree of each other.
I’ve just checked the GISS 2009 SH anomaly relative to the satellite base period (1979-1998). It’s +0.366 deg . The UAH anomaly for the last 6 months of 2009 is +0.365 deg . As I wrote in an earlier post: give it a few more months.

Pascvaks (05:40:28) :
Once again from the simple answers department, for those interested in a proxy record of “Southern” temperature anomolies since 1979 up until a couple weeks ago.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/current.anom.south.jpg
Interesting. The problem, aside from those suggested by Bob Tisdale, is it only starts in 1979. This is after the cold of the seventies so it only shows the rise in temperature (recovery)
Too bad the satellite data record is not long enough yet to confirm or deny the sinusoidal curve seen in this graph from John Daly’s site of Jan Mayen Island. Not all of the records show the variation as clearly as this record does. But then it is a small mostly uninhabited island in the Arctic ocean (the Greenland Sea) so the ocean’s influence would be more clearly seen without influence by man.
http://www.john-daly.com/stations/janmayen.gif

A C Osborn (08:38:42) :
“Oefinell can you explain to me how they calculate the variance without using the Absolute Temperature?
What Temperature do they use in the variance calculation?
Or do they just make it up?”
They just make it up. That is why they “adjust” the early 20th century temp data down and the late 20th century data up, as they did to the Darwin record. Gives nice variance charts for the MSM to show the unwashed masses. That is why Mann just got rewarded with another million dollar plus grant. Honesty of course gets you a pink slip.

davidmhoffer (09:23:40) :
Gail,
“… which the IPCC graph also shows, regardless of how warm the reconstruction highs are compared to the current measured highs, the trend is obvious…. warming since 1600, the IPCC says so and I choose to believe them:
http://en.wikipedia.org/wiki/File:1000_Year_Temperature_Comparison.png
You forgot the [/sarcasm
“Actually I was mostly serious. Most of the reconstructions show a brief cooling period ending in 1830, but an over all warming trend since about 1600…”
Try this instead: http://www.c3headlines.com/temperature-charts-historical-proxies.html
I would not trust any of the IPCC data since reading the climategate e-mails.
“IPCC assessment reports, and particularly their Summaries for Policymakers (SPM), are noted for their selective use of information and their bias to support the political goal of control of fossil fuels in order to fight an alleged anthropogenic global warming (AGW).” http://www.powerlineblog.com/archives/2010/01/025294.php
Authors whose reports have been included have complained about the twisting of their reports. The Resignation Letter of Chris Landsea from IPCC details some of the problems. http://www.climatechangefacts.info/ClimateChangeDocuments/LandseaResignationLetterFromIPCC.htm

Ajstrata
I have one concern about you article and that is you used basic statistics which makes certain assumptions about observations ie that they are independent. This is not true of climatic data which shows “persistence” ie the temperature/rainfall will not be dramatically different 100m or even 10km away.
Whatever one may think about Jones of the CRU he does understand the need to use spatial statistical tools in analysing climate data. The wiki article on spatial statistics is very good, see especially spatial autocorrelation and spatial interpolation. For those who understand Time Series analysis, the problems of autocorrelation will be familar.

Phil. (12:34:45) :
“Now AJ shows how large the minimum error is in determining the temperature for a “grid” therefore negating the reasons for adjusting the Darwin data in the first place.
The reason for adjusting the Darwin data was inter alia to account for station moves (the first one was destroyed by bombing shortly after being moved because the original location had become unsuitable).”
The adjustments were minus one degree before 1940 and then stepwise up to over two degrees giving a total of close to a six degree per century adjustment to an otherwise flat temperature trend. (Gee makes it look just like Mann’s hockey stick) I can see a need for a one time half a degree adjustment up after the station was bombed and possibly another couple of tenths down after it was destroyed in a cyclone, IF the station was moved a significant distance and/or IF the calibration of the thermometers indicate the need for an adjustment because the thermometer is off. Otherwise you leave the data alone.
To be repeatedly adjusting the data without good solid evidence that an adjustment is absolutely necessary just adds MORE error to the data. Instead information about changes should be noted and if possible parallel readings taken. Since the original locations of the weather stations are often known that still could be done in many cases by going back to the original site and setting up a temporary station for up to a month so a more accurate and SCIENCE BASED adjustment can be calculated. The climate scientists were just too lazy to get off their duffs and do the work.
Reminds me of the “quality control” done on the USA surface station networks. Lazy @#$! government scientists are more interested in attending conferences and writing papers to get more grant money than doing real work aka Steve McIntyre’s “Starbucks Hypothesis” http://wattsupwiththat.com/2009/12/20/steve-mcintyre-on-fox-news-special-tonight-about-climategate/#more-14338

Try this instead: http://www.c3headlines.com/temperature-charts-historical-proxies.html
I would not trust any of the IPCC data since reading the climategate e-mails
Tx Gail! what a great link!
They mostly confirm what I have seen in other reconstructions… nasty cooling period about 1830ish stuck into a general warming trend since about 1600. Same pattern as the IPCC spaghetti, but showing that it was warmer in the mwp than it is now. Was interested to note though that while almost all of them showed the nasty cooling around 1830, a handfull did not show the same around 1600.

I am sorry for being a cracked record here, but, to me, the energy accounting approach is the only one which can begin to answer the “why is it warming” question.
I think you are 100% correct. All the temperature record accomplishes is to be a proxy for energy balance. When you try and correlate the models to energy balance there is invariably a hole in the models.
BTW, while you can store energy in the oceans, you can ALSO store “cold” in ice. The transition from ice to water consumes a huge amount of energy. At 1 watt/m2 (the current contribution from man made CO2) it would take about 12 years to warm the top 100 meters of the ocean 1 degree C. If I recall my physics correctly, assuming the ice was already at the melting point, the same would melt about 1.3 meters of ice.

Interesting to see that the surface stations project uncovered a cool bias to the temperature record. Great to see all the hard work of the volunteers come to fruition, though it is worrying that the rapid warming trend wasn’t simply an artifact.

Bob Tisdale (14:52:33) :
John Finn: You wrote, “…but there’s an issue about the GISS 1998 anomaly. It’s always seemed, relatively speaking, much lower that the other datasets.”
TLT anomalies can be more volatile:
http://i50.tinypic.com/208jqyq.png
I did acknowledge in my earlier post (John Finn (12:28:17) 🙂 that “It’s clear that that ENSO fluctuations have a sharper impact on satellite troposphere readings”. But, by the same argument, it’s possible that other factors amplify the surface temperatures (relative to the troposphere).
I’m not out to defend GISS, Hadley or the UK met office (certainly not them) but I do like to “play fair”. I’m not implying that you don’t. In fact every post I’ve seen from you suggests that you are as keen as I am to present the facts as accurately as possible.
I would just like to make this observation, though. If GISS are fudging the data to make it appear that it’s warming more than it actually is, they are not doing a very good job of it. Over the last 20 years the difference in trends between UAH and GISS is wafer thin.

Comparing the NZ and Giss 2009 sh T Anomaly ,there seems to be a divergence in the plots ie opposite sign.
With NZ we can see the effects of the ozone hole 9and breakdown of polar transport in AUG however Giss shows a downtrend it night be an interesting exercise to test other nid latitude sites in the SH
http://i255.photobucket.com/albums/hh133/mataraka/nzgisst2009.jpg

Connor (01:30:49) :
“Maybe if you look hard enough you people will find A YETI!!!! “
Well, we have been receiving reports of sightings…

OMG – should be “Why is the revision…” Guess one typo will void my post. At least the formatting was just fine.