THIS PAGE HAS BEEN ACTIVATED AS THE NEW STATESMAN BLOG IS NOW CLOSED FOR COMMENTS
At 10am this morning, the New Statesman finally closed the Mark Lynas thread on their website after 1715 comments had been added over a period of five months. I don’t know whether this constitutes any kind of a record, but gratitude is certainly due to the editor of of the New Statesman for hosting the discussion so patiently and also for publishing articles from Dr David Whitehouse and Mark Lynas that have created so much interest.
This page is now live, and anyone who would like to continue the discussion here is welcome to do so. I have copied the most recent contributions at the New Statesman as the first comment for the sake of convenience. If you want to refer back to either of the original threads, then you can find them here:
Dr David Whitehouse’s article can be found here with all 1289 comments.
Mark Lynas’ attempted refutation can be found here with 1715 comments.
Welcome to Harmless Sky, and happy blogging.
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10,000 Responses to “Continuation of the New Statesman Whitehouse/Lynas blogs.”
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Er, Max – it’s unimportant but I posted 3571. You asked who commissioned the report. This extract probably provides the answer:
i.e. the taxpayer is paying for it.
Robin #3571
We must read the same newspaper-I actually laughed when I read this report as at the time I was wearing a full set of thermals for the first time ever. This is something I dont do even when I go skiing in Switzerland!
The previous day I had read a report somewhere that British houses should be designed so they could be kept cooler to cope with rapidly increasing temperatures!
Postscript to everyone
I recently relayed the problems that the ghosts of Callendar Keeling Tyndall et al put in my way when I took my son to Cambridge University for an interview before Christmas.
I am pleased to say he has been offered a place to read Physics and Earth sciences.
TonyB
JZ: at post 3499 you quoted the saying that “Facts are stubborn things” and commented that the facts seem to be mounting against the AGW view. I agree. But I’m less sure that our political masters, especially here in the UK, are taking much notice of that. You may be interested to see the debate I am having with TonyN here – especially posts 3, 7 and 11.
But I particularly liked James P’s post 5. Here’s a great and sublimely relevant quote – “from the prescient pen of one L.Tolstoy:”
Re: 3570, Robin
I wonder how many people outside academia had heard of Profs. Battisti and Naylor before they published this groundbreaking piece of crystal-ball gazing?
It must be fun to work in a field where you can get worldwide news coverage so easily. Physicists, chemists and other mainstream scientists who invest decades in meticulous research and are still unknown might have doubts about whether they have followed the right career path.
Has it really gotten warmer?
The “globally averaged annual land and sea surface temperature anomaly” appears to be a “will o’ the wisp”, that bears little resemblance to what is actually going on in the real world. Many climate scientists doubt that this indicator has any real significance.
In addition, there are dozens of well-researched reports from all over the world, which show that this hypothetical indicator is seriously flawed, due to the urban heat island effect. These reports show that as much as 50% to 100% of the “measured” warming is actually an artifact of this upward distortion of the record.
Even despite this upward distortion in later years, this “average” indicator was lower in the USA in the 1990s than it was in the 1930s (as GISS was forced to correct its data on record hot years).
But let’s look at the real world.
The U.S. National Climatic Data Center publishes a list of record high and record low temperatures for each of the 50 states.
http://www.usatoday.com/weather/wheat7.htm
http://www.usatoday.com/weather/wcstates.htm
26 of the hottest days were recorded in the 1920s and 1930s (slightly over half of all).
Only 9 of the hottest days were recorded in the 26-year period 1980-2006.
11 of the coldest days were recorded in the 1920s and 1930s.
14 of the coldest days were recorded in the period 1980-2006.
So the US record clearly shows that the pre-AGW 1920s and 1930s were substantially warmer than the period since 1980, when we are supposed to be feeling the warming impact of AGW.
IPCC (SPM 2007) tells us (without any substantiation) that “warmer days and nights over most land areas” are “very likely” (>90% probability) to have occurred more frequently “in the late 20th century” than earlier, with a “likely (>66%) human contribution to the observed trend”.
The report also tells us that “cold days and nights over most land areas” are “very likely” (>90%) to have occurred less frequently “in the late 20th century” than earlier, with a “likely (>66%) human contribution to the observed trend”.
Based on these very dicey “observations”, IPCC goes on to predict that it is “virtually certain” (>99%!) that these trends (fewer cold days, more warm days) will continue “based on projections for the 21st century”.
High and low temperature records for the rest of the world are spotty, but a glance at the data that are published shows a similar story to that in the USA, i.e. no increase in record hot days in the late 20th century versus earlier periods, a higher incidence of record hot days in the 1930s than today and no reduction in record cold days in the late 20th century versus earlier periods.
So it appears that the IPCC claims and predictions are unfounded and that “global warming” may not really be happening at all, based on the actual temperatures out there in the real world.
Max
Re 3571 “whodunnit?”.
Sorry, Robin. Yes it was you.
BTW that was an amazingly stupid report, released at an astoundlingly poor time.
(And your taxes even helped pay for this rubbish! Can you get your “money back”?)
Regards,
Max
Max,
Re: # 3580
I’d brought this up previously pointing out that per state high/low temperatures recorded in The United States, 2/3rds were achieved pre 1950….before CO2 levels “skyrocketed, (I don’t remember the exact %, I’ll search through my previous posts. Record high temperatures were split 50% – 50% across the 20th Century.
Mr. Martin and I believe Mr. Benson argued that “Global Warming” was exactly that; a “global” phenomenon. I then posted the record highs and lows per continents and came up with the same results…..warmer before 1950, cooler post 1950.
They both replied with a sort of muddled response as to why this “didn’t matter” and wasn’t a true test of anything. I wasn’t convinced and I sort of felt as if I had “threatened the Queen”……but I let it go.
I’ll look further in my notes to resurrect the data.
I have posted this in various places so would be greatful if anyone can add to the growing volume of information
“The IPCC said; You can’t conclude anything about a global temperature from your own local experience”
I am collecting links to national and regional temperature records-the longer the better.
Whilst observations from one country on a single day are merely interesting, those from lots of different places over many years has considerable signficance. Links please
We already have;
Hadley CET to 1660
Armagh
Central Europe
Switzerland to 1860
44 stations in Germany
Finland
Russia
Holland
Denmark Faroe Greenland.
I will post these up as a general resource in due course.
This is in reaction to the oft quoted ‘global temperatures since 1850? which are continually changing in location/equipment/methodology and started off in 1850 with 100 stations, many of them described as ‘unreliable’ Callendar based his 1938 seminal co2 document on observations from 200 stations.
This composite ‘1850? data set is therefore best viewed as an interesting historical curio rather than a scientific data set on which the future of the worlds economy should be based.
I have lots of my own disjointed information on ‘1850? but if anyone has any links to a existing succinct explanation of the number of stations in each year, their location, changes etc etc I would be pleased to include it.
TonyB
Robin #3571: “A specially-commissioned Met Office report has found that the weather could become so hot in the coming years that the poor and elderly could need help paying bills to keep their homes air-conditioned.”
This is an extraordinary statement from the Met Office, really. Are they recommending that air-conditioning is installed in people’s homes, in the same way that loft insulation is currently being offered? How does that square with HM Government telling us all to be green, use less power, install energy-saving light bulbs, fret over our carbon footprints, etc.?
The other thing I’d comment on is that just as they are downplaying the current cold spell, they appear to be “bigging up” the 2006 heatwave. Yes. the summer of 2006 was hot and there were some water shortages, due to the lack of rain earlier in the year, but was it that terrible? I spent some time on the Norfolk coast during August 2006 and it was lovely – proper summer weather, and it would have been nice to have some of that last year. Could it be they are mentioning it to draw attention away from the fact that the heatwave of 2003 happened over five years (half a decade!) ago?
Further down the page in the Telegraph item, is a sentence that says it all: “Given the blow to its budget with cold weather payments, the Government is unlikely to commit itself to hot weather payments any time soon.”
TonyB and Peter Martin
Since your post 3575 was addressed to both Peter and me, we should probably both respond.
You wrote: “Alterations in planetary orbit might account for one or two of the years but it can’t be solar activity as I understand from the IPCC that this is relatively unimportant. So prior to our vandalism of the co2 thermostat what caused our climatic changes?”
I believe we have identified the source of the confusion.
It is, indeed, correct that IPCC have stated (SPM 2007) that the solar forcing of our climate has been “relatively unimportant” (less than 1/10th the forcing from anthropogenic sources. But on the same page IPCC concede that their “level of scientific understanding” of solar forcing is “low”, so we can discount their estimate.
Fortunately, there are many solar scientists, whose “level of scientific understanding” of solar forcing is significantly higher than that of the IPCC. Several of these have estimated that the sun was in a period of unusually high solar activity (highest in several thousand years) in the 20th century, and that this high level of activity contributed around 0.35°C (average value of the many studies) to the warming we have experienced.
If we truly believe in the validity of the record of “globally averaged annual land and sea surface temperature” as published by Hadley, we see that this showed a linear warming of 0.65°C over the entire record from 1850 to 2008.
We can therefore deduce that the anthropogenic warming is 0.65 – 0.35 = 0.3°C over this entire period.
This may be an oversimplified assumption, since we also know that increased El Nino activity in the late 20th century caused some years to have unusually high temperatures (thereby influencing the trend) but, as there are studies that indicate a possible link between solar activity and the ENSO (plus PDO, NAO, etc.), we can assume that this natural forcing is “included” in the solar impact.
The overall anthropogenic warming of 0.3°C would correspond to the theoretical anthropogenic warming from all sources, as calculated from the radiative forcing factors stated by IPCC (Myhre et al.) in its report, so (assuming the record itself is valid) this would give a reasonable check of the validity of the greenhouse hypothesis as postulated by IPCC, provided, of course, that the assumed atmospheric CO2 concentrations over the period are correct and representative of our entire atmosphere.
There is, however, a small fly in the ointment. Individual multi-decadal periods within the overall record do not show a robust correlation between temperature and Mauna Loa CO2 (see graph in 3541); there is rapid warming with essentially no increase in CO2, cooling with an accelerated increase in CO2 and finally the beginning of a cooling trend with all-time record increase in CO2.
In addition, the calculation is based on the somewhat uncertain assumption that IPCC is correct in stating that the urban heat island effect had a “negligible” impact on the temperature record (despite many studies from all over the world, which show that the UHI impact could well have been the cause for a spurious increase of 0.3°C over the entire period).
So your “whodunnit?” is only partially answered.
At least for the overall period 1850-2008 it appears we can account for the observed warming as follows:
0.35°C from increased solar activity over the period (several solar reports)
0.30°C from either AGW (as postulated by IPCC) or from UHI distortion of the record
0.65°C total observed warming over period
How this occurred over the various multi-decadal cycles is a bit less clear. Maybe Peter can give you an answer here.
Hope this helps.
Regards,
Max
Max
Thanks for your reply. Just to make it easier for others to reply I have simplified the question so people merely need to complete the sentence.
Co2 is said to be very closely related to fluctuating temperatures. In the past co2 was a constant 280ppm yet temperature fluctuated wildly because…..
TonyB
TonyB,
Does this help? I use this at work. If you bounce around on this site you can enter various locations around the world and enter specific time periods.
http://www.wunderground.com/history/airport/KDCA/2008/4/17/CustomHistory.html?dayend=16&monthend=5&yearend=2008&req_city=NA&req_state=NA&req_statename=NA
Tony b,
Try the “custom” button and the Historical Data button (top right of page).
These is global information, (I typed Moscow Russia and got information).
Brute
Thats great. Thanks Now all I need from you is a nice two page article complete with graphs on the back ground to the stations involved in ‘global warming since 1850’ and you can go to bed…
TonyB
TonyB
My simplified continuation of your simplified statement (3586):
“Co2 is said to be very closely related to fluctuating temperatures. In the past co2 was a constant 280ppm yet temperature fluctuated wildly because…”
… warming from increased atmospheric CO2 (as postulated by the greenhouse theory) is only one possible (but as yet unproven) piece of the puzzle; there are many natural factors, which cause our climate to change, some of which can be clearly identified with the mechanism involved and others, which are not yet fully understood.
To attempt to explain all past climate change as a result of changes in atmospheric CO2 would be an ignorant oversimplification.
To attempt to forecast long-term future climate change as a result of anticipated changes in atmospheric CO2 resulting from projected future human emissions would not only be ignorant, it would be arrogant.
Max
Max,
As a certified, official skeptic, I also question the validity of the temperature record (forget about the interference from urban heat islands, exhaust ducts, barbecue grills and air conditioning units). Maybe in a laboratory, under controlled conditions, measurements can be accurately recorded…….but this? I just can’t buy it. I don’t care if it’s UAH MSU, GISTEMP, RSS MSU or HadCRUT3.
I was wondering how you feel about…..let’s see…….how to put this…….
Look; we’re only talking about 10ths of degrees here over decades, spread out over 150 years, “averaged” over the entire surface of the globe.
I really have a problem with the accuracy of the instrumentation, data collection methods, human error, etc……coupled all together to make such outlandish statements and projections.
I simply cannot fathom why we, or anyone else, is making such a big deal over a few 10ths of degrees even if the numbers are rock solid, unimpeachably accurate……maybe I’m wrong…..
I simply don’t have enough faith in the process to believe that anyone could accurately measure the “average” temperature of the entire globe within a few 10ths (or 100ths or 1000ths) of degrees and seriously claim that it’s an accurate representation…..supercomputer or no supercomputer.
For example:
HadCRUT3 dataset
We have recently changed the way that the smoothed time series of data were calculated. Data for 2008 were being used in the smoothing process as if they represented an accurate estimate of the year as a whole. This is not the case and owing to the unusually cool global average temperature in January 2008, it looked as though smoothed global average temperatures had dropped markedly in recent years, which is misleading.
We’ve recently corrected a minor bug in the error ranges provided for HadCRUT3 (the best estimate data are unchanged). If you have downloaded HadCRUT3 before November 20th 2007 please see this page.
We’ve recently corrected a minor bug in the error ranges provided for HadCRUT3 (the best estimate data are unchanged). If you have downloaded HadCRUT3 before October 27th 2006 please see this page.
HadCRUT3 is a gridded dataset of global historical surface temperature anomalies. Data are available for each month since January 1850, on a 5 degree grid. The dataset is a collaborative product of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia.
The gridded data are a blend of the CRUTEM3 land-surface air temperature dataset and the HadSST2 sea-surface temperature dataset. As well as a best-estimate valuue for the surface temperature, a comprehensive set of uncertainty estimates are available. The image below shows near surface temperature anomalies for the most recent available month. A plus sign in any grid box indicates that the temperature anomaly in that grid box this month is the highest since the dataset starts in January 1850. Similarly a minus sign signals the lowest anomaly since 1850.
http://hadobs.metoffice.com/hadcrut3/
Hi Brute,
Your views on the validity of the “globally averaged annual land and sea surface temperature anomaly” mirror mine fairly closely.
When I see how this fictitious indicator gets manipulated and adjusted after the fact by individuals who have already expressed a strong opinion in favor of the disastrous AGW hypothesis, I doubt the scientific objectivity of this dubious indicator even more.
But when I see how many AGW-aficionados (like Peter, for example) “strongly believe” in the validity and absolute objectivity of this cooked-up number I tell myself, “let’s not fight the religious basis of those that hum the AGW mantra; instead, let’s see where the rest of their hypothesis is full of holes.”
This turns out to be fairly easy.
Solar scientists have told us that the increase in solar activity (to a several thousand year high in the late 20th century) has caused a temperature increase of around 0.35°C. This is the average of several independent studies.
I have no reason to doubt these estimates. Incidentally, IPCC does not accept this but relegates “solar forcing” to an insignificant fraction of “CO2 forcing, while at the same time conceding that its “level of scientific understanding” of solar forcing is “low”.
As a result of this low “level of scientific understanding” on tne part of IPCC, we can discount the IPCC estimate and stick with the estimate of experts in this field whose “level of scientific understanding” of solar forcing is not “low”.
So even if we accept the validity of the “globally averaged annual land and sea surface temperature anomaly” (whew!) we still see that human CO2 can only have caused a bit less than half of the theoretical warming recorded by this indicator, assuming (against the evidence of many reports from all over the globe) that the urban heat island effect is really negligible (as IPCC proclaims).
So now the “dedicated believers” (like Peter) have to admit that the IPCC’s own “climate forcing estimates” from CO2 (and other anthropogenic factors) agree with the observed record, i.e. the anthropogenic impact on the “globally averaged annual land and sea surface temperature anomaly” was around 0.3°C (over the period 1850 to 2008), as the IPCC anthropogenic “radiative forcing” estimates confirm, and the balance was from natural (solar) causes.
Let’s accept that this is the case (despite the fairly convincing evidence from many studies from all over the world that the rate of change of the “globally averaged annual land and sea surface temperature anomaly” is exaggerated by around 0.3°C (over the period 1850 to 2008) due to the urban heat island effect, which would essentially reduce the “anthropogenic warming” over the period to zero.
But rather than fighting this battle, let’s give Peter and his other AGW believers the benefit of the doubt on this.
This means (according to the greenhouse hypothesis) that the warming expected by year 2100 (with an atmospheric CO2 content 2x that in 1850) would be another 0.4°C above today’s values (and not 1.8 to 6.4°C, as projected by the inflated IPCC computer models).
This is obviously nothing to get very excited about.
For this reason, I prefer not to question the fundamental dogma of the AGW religion (i.e. the validity of the Holy Gospel of the “globally averaged annual land and sea surface temperature anomaly”), but rather to show how even this fictitious figure shows us that AGW is nothing for us to worry about in the future.
BTW I have exactly the same “problem with the accuracy of the instrumentation, data collection methods, human error, etc.” as you do, and, in addition, I am extremely suspicious of both the Hadley and GISS records due to the observed lack of scientific objectivity of the individuals doing the adjustments and corrections to the observed data.
But that’s another battle.
Regards,
Max
Agreed. Much of the equipment that I work with must be calibrated daily, (which prompted my earlier comment).
Secondly, all of the above mentioned organizations are bloated bureaucracies….adding layer upon layer of instances of error and manipulation. I’d be quite interested in the quality control measures employed and how stringently they’re applied.
Record Highest Temperatures by State
State Temp. °C Date
Alabama 44 Sept. 5, 1925
Alaska 38 June 27, 1915
Arizona 53 June 29, 1994
Arkansas 49 Aug. 10, 1936
California 57 July 10, 1913
Colorado 48 July 11, 1888
Connecticut 41 July 15, 1995
Delaware 43 July 21, 1930
D.C. 41 July 20, 1930
Florida 43 June 29, 1931
Georgia 44 Aug. 20, 1983
Hawaii 38 Apr. 27, 1931
Idaho 48 July 28, 1934
Illinois 47 July 14, 1954
Indiana 47 July 14, 1936
Iowa 48 July 20, 1934
Kansas 49 July 24, 1936
Kentucky 46 July 28, 1930
Louisiana 46 Aug. 10, 1936
Maine 41 July 10, 1911
Maryland 43 July 10, 1936
Massachusetts 42 Aug. 2, 1975
Michigan 44 July 13, 1936
Minnesota 46 July 6, 1936
Mississippi 46 July 29, 1930
Missouri 48 July 14, 1954
Montana 47 July 5, 1937
Nebraska 48 July 24, 1936
Nevada 52 June 29, 1994
New Hampshire 41 July 4, 1911
New Jersey 43 July 10, 1936
New Mexico 50 June 27, 1994
New York 42 July 22, 1926
North Carolina 43 Aug. 21, 1983
North Dakota 49 July 6, 1936
Ohio 45 July 21, 1934
Oklahoma 49 June 27, 1994
Oregon 48 Aug. 10, 1898
Pennsylvania 44 July 10, 1936
Rhode Island 40 Aug. 2, 1975
South Carolina 44 June 28, 1954
South Dakota 49 July 5, 1936
Tennessee 45 Aug. 9, 1930
Texas 49 June 28, 1994
Utah 47 July 5, 1895
Vermont 41 July 4, 1911
Virginia 43 July 15, 1954
Washington 48 Aug. 5, 1961
West Virginia 44 July 10, 1936
Wisconsin 46 July 13, 1936
Wyoming 46 Aug. 8, 1983
36 of 51 Record High Temperatures Recorded Before 1950-(70%)
Record Lowest Temperatures by State
State Temp.°C Date
Alabama –33 Jan. 30, 1966
Alaska –62 Jan. 23, 1971
Arizona –40 Jan. 7, 1971
Arkansas –34 Feb. 13, 1905
California –43 Jan. 20, 1937
Colorado –52 Feb. 1, 1985
Connecticut –36 Jan. 22, 1961
Delaware –27 Jan. 17, 1893
D.C. –26 Feb. 11, 1899
Florida –19 Feb. 13, 1899
Georgia –27 Jan. 27, 1940
Hawaii –11 May 17, 1979
Idaho –51 Jan. 18, 1943
Illinois –38 Jan. 5, 1999
Indiana –38 Jan. 19, 1994
Iowa –44 Feb. 3, 1996
Kansas –40 Feb. 13, 1905
Kentucky –38 Jan. 19, 1994
Louisiana –27 Feb. 13, 1899
Maine –44 Jan. 19, 1925
Maryland –40 Jan. 13, 1912
Massachusetts –37 Jan. 12, 1981
Michigan –46 Feb. 9, 1934
Minnesota –51 Feb. 2, 1996
Mississippi –28 Jan. 30, 1966
Missouri –40 Feb. 13, 1905
Montana –57 Jan. 20, 1954
Nebraska –44 Dec. 22, 1989
Nevada –46 Jan. 8, 1937
New Hampshire –44 Jan. 29, 1934
New Jersey –37 Jan. 5, 1904
New Mexico –46 Feb. 1, 1951
New York –47 Feb. 18, 1979
North Carolina –37 Jan. 21, 1985
North Dakota –51 Feb. 15, 1936
Ohio –39 Feb. 10, 1899
Oklahoma –33 Jan. 18, 1930
Oregon –48 Feb. 10, 1933
Pennsylvania –41 Jan. 5, 1904
Rhode Island –32 Feb. 5, 1996
South Carolina –28 Jan. 21, 1985
South Dakota –50 Feb. 17, 1936
Tennessee –36 Dec. 30, 1917
Texas –31 Feb. 8, 19331
Utah –56 Feb. 1, 1985
Vermont –46 Dec. 30, 1933
Virginia –34 Jan. 22, 1985
Washington –44 Dec. 30, 1968
West Virginia –38 Dec. 30, 1917
Wisconsin –48 Feb. 4, 1996
Wyoming –54 Feb. 9, 1933
24 of 51 Record Low Temperatures Recorded After 1950- (47%)
Max,
As I think I’ve pointed out to you before, the reason you get such a low figure for climate sensitivity is because you are ignoring two important factors in ocean heat uptake and the effect of aerosols.
I didn’t quite understand your comment that the IPCC had said that these could be ignored. That’s just not true. But, anyway since when have you uncoditionally accepted anything from the IPCC?
So why not produce a complete list off all factors resonsible for climate change together with actual numbers. I think you might get a slightly different result and closer to the scientific consensus of 3K for a doubling of CO2.
It might be worth just mentioning that the temperature difference between glacial and interglacial states, in recent ice ages has been around 5 degC. That has been enough to cause sea level changes of around 400 feet. That’s about 80 feet for every degree. Sea levels do not change at the same rate as the temperature rise of course, but they do happen over the course of time.
Brute and Max
You should both know my feelings by now on globally averaged temperatures, let alone ones that have the words ‘to 1850’ appended to them!
This is an absolute lynch pin of AGW yet it is so widely accepted. The whole concept is meaningless unless all the data points remain the same and the underlying methodology and equipment also remains constant-which is certainly not the case. National records tend to show a rather different picture to globally averaged ones, especially the longer data sets which indicate we have been this way before.
If any of you come across a properly researched piece on ‘temperatures to 1850’ please let me know as it will save me having to do one.
Peter
I am still hoping you will answer my question as to why the co2 thermostat didn’t appear to operate prior to 1900 or so, despite temperature fluctuations in the past being greater than now.
TonyB
Max and Brute
Just came across this site on temperatures . Scroll down to see graphs but in particular click on ‘this animation’ and watch it to the end-its very revealing!
http://icecap.us/images/uploads/MSU_Satellite_Temperatures_Continue_to_Diverge_from_Global_Data_Bases.pdf
TonyB
ALL: Here is a lamentable summary of how Pete, on just ONE TOPIC, refused long-term to be advised on how to do a running average on ‘time series data‘, persisted in repeatedly presenting graphs which were WRONG, and displayed that he has very little scientific understanding, or logical thought processes, and may even have a ‘spatial perception problem’
Re PAGE 20, by post number:
2870 Peter Martin says: November 22nd, 2008 at 7:56 am:
Published Hadley graph 1850-2000+ with obvious phasing error etc in 5-year smoothing.
2882 Peter Martin says: November 22nd, 2008 at 11:01 pm
I’m sure that teachers of all slow learning students feel that they are “flogging a dead horse” at times. I certainly do with you lot! However, let’s not give up. I’ve simplified the graph for you:
And, published another graph 1960-2000+ with the same errors as above
2887 Bob_FJ says: November 23rd, 2008 at 4:55 am
18 lines of text explaining the errors and considerations in Pete’s graphs to date. The following brief extract is of importance:
Any scientist worth his weight, will, after applying algorithms or whatever to data, and in presenting a graph, WILL THEN TEST such work for reasonableness both in absolute terms and with any other comparable work.
2890 Peter Martin says: November 24th, 2008 at 2:55 am
No alternative to my graph in posting #2882? The data is taken from Hadcrut and you can check it all for yourself if you feel I have misrepresented the data.
And 13 lines of waffle without addressing the issues I raised
2891 Bob_FJ says: November 24th, 2008 at 6:17 am
This was a substantial post, including:
Will you take notice of your errors that I identified in my 2887, or is it just that you don’t have the scientific comprehension to understand what I explained to you?
2900 Peter Martin says: November 25th, 2008 at 10:35 am
A substantial post to me and Max, which included:
NASA use the 5 year averaging technique too. Their graphs show exactly the same features. (but failing to notice/mention the difference in phasing)
2915 Bob_FJ says: November 26th, 2008 at 6:18 am
Another substantial tutorial for Pete, including the following image:
2916 Bob_FJ says: November 26th, 2008 at 6:41 am
Supplementing the above, comparing Petes’s graph 2882 (WRONG) with his Gistemp adaptation (RIGHT), with respect to Sync’ or phasing
2951 Bob_FJ says: December 1st, 2008 at 6:50 am
Remember, [Pete] per my earlier tuition, that if you generate any graph mathematically or by whatever means, it should always be checked for reasonableness, such as by eyeballing it.
VERY IMPORTANT!
PAGE 21
3003 Peter Martin says: December 3rd, 2008 at 8:32 am
In a lengthy post unrelated to the above, he includes a graph 1850-2007 containing the same obvious out of sync or phase error between raw data and 5-year smoothed data.
3032 Bob_FJ says: December 5th, 2008 at 8:10 am
The following graphic discusses various smoothing approaches, and again shows that Pete’s method is WRONG
3061 Bob_FJ says: December 6th, 2008 at 8:43 am
A modified version of my graphic in 3032.
3067 Bob_FJ says: December 7th, 2008 at 5:29 am
This is a lengthy post and here is an extract:
I guess the point when Hadley really started to get worried about cooling was about the time when they wrote this:
In March 2008, some diagrams were placed on [our] web site which showed smoothed annual series that included data for 2008. The annual value for 2008 was based on the only two months of data – January and February – that were available at the time. January and February 2008 were cooler than recent months, leading to a marked downturn towards the end of the smoothed series (Figure 2, orange line) that caused much discussion.
If no image OR, if you like, for a good laugh at the full Metoffice yarn, click:
http://hadobs.metoffice.com/hadcrut3/smoothing.html
I just love the: “that caused much discussion”….Oh to have been a fly on the wall!
[How Pete could not learn from this is a mystery]
3045 Peter Martin says: December 5th, 2008 at 1:40 pm
I’m sure that Max can vouch that I’ve done it all correctly. As he says himself, its all quite simple. If you have a problem with the way Excel calculates and plots either linear regressions or running five year averages maybe you’d like to take it up with Bill Gates?
3069 Bob_FJ says: December 7th, 2008 at 6:50 am responding to 3045:
Don’t be silly! Why do you continue to deny the blindingly obvious that your recent 5-year smoothing, howsoever you did it was WRONG.
3080 Peter Martin says: December 8th, 2008 at 1:41 am
This brief post included the statement:
…which I plotted out in Excel using the same averaging method NASA use.
This is a false statement.
3083 Bob_FJ says: December 8th, 2008 at 6:16 am
This is a diverse, complicated post, but it includes:
I’d also be interested to know the difference between your claimed NASA 5-year method, and your clearly different earlier 5-year method. (outcome)
3085 Peter Martin says: December 8th, 2008 at 7:08 am
I’m not sure why you have a problem with Excel’s running averages. Have a try for yourself. Just take any series and right click on it. Choose ‘add trend line’. Then choose a factor of 5, or whatever you like, for the running averages option. If you disagree with what Excel does , please let us all know!
He included another copy of one of his earlier graphs where the smoothed trend line was clearly out of phase, with the raw data
3088 Peter Martin says: December 8th, 2008 at 9:33 am
Showed a new graph where the smoothed trend line was clearly out of phase as before.
3096 Bob_FJ says: December 8th, 2008 at 9:24 pm
Pete, In your 3088, you present a TOTALLY NEW graph, on this thread, complete with the same 5-year smoothing error as before…
XXXX Peter Martin says: January 7th, 2009 at 10:22 pm
Repeats a graph with the obvious out of phase problem between smoothed and raw data
PAGE 24:
3543 Peter Martin says: January 8th, 2009 at 5:35 am
Max , I don’t mind you updating my graph but not when you make a b***s of it all. The black line in the five year running average. Here is the actual update. I’ve used your figure of 0.31 Is that correct for this year? I haven’t seen the official confirmation yet.
However his “updated” graph is wrong because of the obvious out of phase problem between smoothed and raw data
3544 Bob_FJ says: January 8th, 2009 at 6:30 am
This was a substantial post and briefly included:
The graph that you [Pete] keep posting is WRONG and misleading in several ways, and you should know that by now!. The most obvious problem is that your 5-year smoothing worm is out of phase with the raw-point data. This problem is more easily seen with the fuller version of YOUR graph in your 2780/20.
The following image elaborated on a comparative smoothing method:
Any comments Pete? For example, do you disagree with messiah Phil’s smoothing methods?
3545 Peter Martin says: January 8th, 2009 at 9:14 am
This is just waffle, but at last, Pete’s error is revealed, when he wrote in part:
…I’m not sure what you mean about the phase. To get the running five year average I just right click on the trace and choose “add trend line”. Excel does it automatically. The trend line is the average of the five previous values. But of course you can average over any number…
…I’m not sure of the smoothing methods used by Phil Jones. I prefer the NASA’s method of rolling five year averages… [both of which are different to Pete’s method] Golly Gosh!
3555 Bob_FJ says: January 8th, 2009 at 9:32 pm
This is a substantial post which explained yet again how to do a smoothing trend on a time series, and included the following graphic:
It also asked again: BTW, is there any good reason why you prefer Hansen et al to Phil Jones et al smoothing methods?
3560 Peter Martin says: January 9th, 2009 at 12:14 am
I think I suggested to [to you Bob] before that if you had a problem with the way Excel adds its 5 year running averaged trend lines that you should have a word with Bill Gates. I bet he told you what to do with your tiniest of quibbles didn’t he!
But maybe I’m wrong. Maybe Microsoft will organise a general recall of their product and millions of users will have to redo all their graphs :-)
3562 Bob_FJ says: January 9th, 2009 at 2:21 am
I responded to 3560 with:
[1] I don’t have an active (subscribed) version of Excel, have not checked it out, and do not have a problem with it. Thus I have not approached Bill Gates. It is you that has the problem, not me.
[2] Whatever it is that you have done, you have published various graphs that are WRONG. It is not trivial if your running average is only from previous values, and excludes the forward values! However, In this situation. you could sort-of correct the graph by having two different x axes, one for the raw data, and one for the smoothed data, but that would be confusing and very silly.
[3] If it is stated in Excel, that the moving average is of the previous ‘n’ years, then there is no need for a recall. It becomes a case of “user beware”. BTW, are you sure that there are no options? Certainly GISS and Hadley, (and others), do NOT use this method, because it is WRONG.
Will you comment on the various points I raised in my 3560?
You seem to be a very unwilling student, even evasive!
3566 Bob_FJ says: January 9th, 2009 at 6:02 am
Précis: I did some research and discovered what it was that Pete was doing wrong. He has been using what is known as ‘prior moving average’ (PMA) which does have an application in such things as weekly past performance in business. However, he should be using ‘central moving average’ (CMA) in analysing ‘time series data’ such as we have been discussing
For more info, including a nice CSIRO 11-year showing how a time-series running average should look. see my 3566/24
It will be interesting to see if he responds to all this, given that he has been proven to be WRONG.
Tony B,
There is a graph contained within the original Icecap article that I have always found to be quite interesting.
This particular graph exemplifies the number of stations that have been abandoned and removed from the data pool over the years. The important note is that most of these stations were located in remote areas of the former Soviet Union that could not be maintained due to budgetary constraints after the failure of the former Socialist/Collectivist economic system, (which is another historical lesson lost to the general public…..and off topic, sorry Tony N).
The last time I checked, many areas of the former Soviet Union encompassed Northern Hemisphere, rural, notoriously cold areas of the planet. Could the removal of these stations from the dataset cause the numbers to be skewed resulting in higher “average” temperatures?
I’ve always felt the timing of the station dropout was quite telling as it immediately preceded the “highest decadal temperature increase in recorded history”.