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How the US Temperature Record is Adjusted

There has been criticism of the potential for official weather stations in the USA to record artificially high temperatures because of the changing environments in which they exist, for example, new asphalt, new building or new air conditioning outlets.   Meteorologist, Anthony Watts, has documented evidence of the problem and Canadian academic, Ross McKitrick, has attempted to calculate just how artificially elevated temperatures might be as a consequence.

A reader of this blog, Michael Hammer, recently studied the official data from the US official weather stations and in particular how it is adjusted after it has been collected.   Mr Hammer concludes that the temperature rise profile claimed by the US government is largely if not entirely an artefact of the adjustments applied after the raw data is collected from the weather stations.

Does the US Temperature Record Support Global Warming?
By Michael Hammer

IN the US, the National Oceanic and Atmospheric Administration (NOAA) collects, analyses and publishes temperature data for the United States.   As part of the analysis process, NOAA applies several adjustments to the raw data. 

If we consider, the above graph, which shows, their plot of the raw data  (dark pink) and the adjusted data (pale pink), it is obvious that the adjustments have little impact on data from early in the 20th century but adjust later temperature readings upwards by an increasing amount.  This means that the adjustments will create an apparent warming trend over the 20th century.  [Click on the above chart for a better larger view, this chart can also be viewed at http://cdiac.ornl.gov/epubs/ndp/ushcn/ndp019.html .]

NOAA state that they adjust the raw data for five factors.  The magnitude of the adjustments are shown in Figure 2. 

Figure 2.  Form of individual corrections applied by NOAA. The black line is the adjustment for time of observation.  The red line is for a change in maximum/minimum thermometers used.  The yellow line is for changes in station siting. The pale blue line is for filling in missing data from individual station records. The purple line is for UHI effects (this correction is now removed).  [Click on the chart for a better larger view or visit the same website as for Figure 1.]

It is obvious that the only adjustment which reduces the reported warming is UHI which is a linear correction of 0.1F or about 0.06C per century, Figure 2.  Note also that the latest indications are that even this minimal UHI adjustment has now been removed in the latest round of revisions to the historical record.  To put this in perspective, in my previous article on this site I presented bureau of meteorology data which shows that the UHI impact for Melbourne Australia was 1.5C over the last 40 years equivalent to 3.75C per century and highly non linear.

Compare the treatment of UHI with the adjustments made for measuring stations that have moved out of the city centre, typically to the airport.  These show lower temperatures at their new location and the later readings have been adjusted upwards so as to match the earlier readings.  The airport readings are lower because the station has moved away from the city UHI.  Raising the airport readings, while not adding downwards compensation for UHI, results in an overstatement of the amount of warming. This would seem to be clear evidence of bias.  It would be more accurate to lower the earlier city readings to match the airport readings rather than vice versa.

Note also the similarity between the shape of the time of observation adjustment and the claimed global warming record over the 20th century especially the steep rise since 1970.  This is even more pronounced if one looks at the total adjustment shown in Figure 3 (again from the same site as Figure 1).  As a comparison, a recent version of the claimed 20th century global temperature record downloaded from  www.giss.nasa.gov  is shown in Figure 4. 

Figure 3.  Magnitude of the total correction applied by NOAA

[Click on the charts for a larger/better view.]

 

Figure 4.  Temperature anomaly profile from NASA GISS

Since the total corrections for the US look so similar to the claimed temperature anomaly, it begs the questions as to what the raw data looks like without any corrections.  Does it show the claimed rapidly accelerating warming trend claimed by the AGW advocates?  To determine this I took the raw data from the USHCN graph shown in Figure 1 and plotted this using  a 5 year mean (blue trace), matching the smoothing in the NASA GISS profile shown in Figure 4.  The result is shown in Figure 5.  Please note that while the plot is one that I generated, the data comes directly from the raw data from Figure 1 published by NOAA. 

Figure 5  Plot of raw temperature data versus time (from fig 1) 5 point smoothing. Vertical axis degrees Fahrenheit.  Red line is a linear trend line. Green line is a 2nd order (parabolic) trend line. 

Clearly the shape of this graph bears no similarity at all to the graph shown in Figure 4.  The graph does not even remotely correlate to the shape of the CO2 versus time graph.  The warming was greatest in the 1930’s before CO2 started to rise rapidly.  The rate of rise in 1920, the early 1930’s and the early 1950’s is significantly greater than anything in the last 30 years.  Despite the rapid rise in CO2 since 1960, the 1970’s to early 1980’s was the time of the global cooling scare and looking at the graph in Figure 5 one can see why (almost 2F cooling over 50 years). 

A linear least squares trend line, created using the Excel trend line function (Red trace)  shows a small temperature rise of 0.09C per century which is far less than the rise claimed by AGW supporters and clearly of no concern.  However, the data shown in figure 5 bears little if any resemblance to a linear function.  One can always fit a linear trend line to any data but that does not mean the fitted line has any significance.  For example, if instead I fit a second order trend line (a parabolic) the result is extremely different.  That suggests a temperature peak around 1950 with an underlying cooling trend since.  Which trend line is the more significant one?  If there was really a strong underlying linear rise over the time period it should have shown up in the 2nd order trend line as well.  This suggests that it is questionable whether any relevant underlying trend can be determined from the data.

It would appear that the temperature rise profile claimed by the adjusted data is largely if not entirely an artefact arising from the adjustments applied (as shown in Figure 3), not from the experimental data record.  In fact, the raw data does not in any way support the AGW theory. 

Based on this data, the US temperature data does not correlate with carbon dioxide levels.  The warming over the last 3 decades is completely unremarkable and if present at all is significantly less than occurred in the 1930’s.  It is questionable whether any long term temperature rise over the 20th century can be inferred from the data but if there is any it is far less than claimed by the AGW proponents.

The corrected data from NOAA has been used as evidence of anthropogenic global warming yet it would appear that the rising trend over the 20th century is largely if not entirely an artefact arising from the “corrections” applied to the experimental data, at least in the US, and is not visible in the uncorrected experimental data record. 

This is an extremely serious issue.  It is completely unacceptable, and scientifically meaningless, to claim experimental confirmation of a theory when the confirmation arises from the “corrections” to the raw data rather than from the raw data itself.  This is even more the case if the organisation carrying out the corrections has published material indicating that it supports the theory under discussion.  In any other branch of science that would be treated with profound scepticism if not indeed rejected outright.  I believe the same standards should be applied in this case.

*********************

Notes and Links

Interestingly, there was an earlier version of the NASA GISS data shown in Figure 4 which was originally published at http://www.giss.nasa.gov/data/update/gistemp/graphs/FigD.txt  While this site has now been taken down the data was apparently archived by John Daly and available at his website http://www.john-daly.com/usatemps.006.  The data is presented in tabular form rather than graphical form but appears to be either identical or extremely similar to that shown in my Figure 5.

Other contributions from Michael Hammer can be read here: http://jennifermarohasy.com/blog/author/michael-hammer/
[scroll down, click on the title for the full article]

Ross McKitrick, Ph.D. – Quantifying the Influence of Anthropogenic Surface Processes on Gridded Global Climate Data
http://www.heartland.org/events/NewYork08/newyork2008-video.html

Anthony Watts – http://wattsupwiththat.com/

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94 Responses to “How the US Temperature Record is Adjusted”

Pages: « 1 [2] Show All

  1. Comment from: Luke


    Uh-huh. Yea good – we’ll call you if needed.

  2. Comment from: SJT


    ‘However to your more significant point that all the discussion on these blog sites is more or less armwaving. I have to say thats exactly the way I see the entire AGW issue. Sure CO2 is a green house gas and increasing its concentration must increase the retained heat to some degree. The serious questions is how much. So AGW is qualitatively supportable BUT the issue is whether or not it is significant and thats a quantitative issue. I strongly question whether AGW at a significant or dangerous level is quantitatively supportable.”

    I sometimes wonder if sites like this exist just to create the impression there is a huge debate. I really do wonder why Jennifer persists in putting up topics that push junk science such as G&T and Miskolczi, or political musings that are pointless, when the issue is about science.

    There is still much debate here about whether or not the greenhouse effect even exists, or if it breaks the second law of thermodyamics.

    I have said years ago, the only real debate is the extent to which CO2 will cause warming. It’s the claim at the basis of the whole schemozzle this has become, it surely can’t be too hard to focus on it and sort it out.

    sod you clearly did not understand what I wrote. I know a 3rd order polynomial is a cubic. You can see I said third order or cubic and I also said first order or linear, second order or parabolic. Your comment is so unreasonable given the other two references I am forced to the conclusion you are trying to make up reasons to criticise. Presumably that means you can find nothing of substance to criticise in what I wrote – thanks.

    I have seen other analysis of trends using polynomials, and the criticism is that they don’t handle endpoints well if there is a temporary excursion from the trend. It appears to me to be a valid criticism.

    Hardly an issue to destroy our economy over. The only way I could see that being wrong would be if there were long time constants so that we have not seen all the effects of the first half doubling as yet.

    There are positive feedback effects that are only just starting to appear, such as albedo change and methane released from permafrost. The heat content of oceans is clearly having a dramatic effect on the Arctic. The rate of change there is ahead of schedule. The air temperature in models will show periods where it drops. The scientific advice to Penny Wong http://www.environment.gov.au/minister/wong/2009/pubs/tr20090624c.pdf tells the story.

  3. Comment from: michael hammer


    How strange, I am accused of knowing nothing about statistics because I don’t know a 3rd order polynomial is a cubic. When I point out that I do and my words have been misread, then don’t know about statistics because of handling of endpoints. The really interesting point of course is that the issue is not statistics at all, it is curve fitting. Not quite the same thing.

    I must apologise to SJT – I missed out on mentioning the further positive feedback factors he mentions – albedo change, methane release. Any others I should know about? One question, do you acknowledge any negative feedback factors at all or do you seriously think there are none in Earth’s climate system? If so, how do you reconcile that with the fact that negative feedback plays an overwhelming role in natural systems? Do you understand how a system with multiple positive feedback loops and no negative feedabck loops is likely to behave?

    The talk about ocean heat content is interesting. You see a few years ago it was all about warming of the land – no mention of the oceans at all. Then when it became too obvious that the land and air was not warming the argument became ocean acidification and coral bleaching. When that did not serve, suddenly ocean warming is discovered to save the day.

    I have successfully worked in research now for more than 30 years and I have seen such situations before. Every time one line of evidence ceases to serve a new line of evidence is discovered and the earlier one dismissed as irrelevant. I need hardly say that the eventual outcome for the hypothesis was never good. If you put up a line of evidence and it ceases to support the hypothesis it is not valid to simply drop it and change to a different argument. This alone should be enough to raise major red flags. Apart from which, I am seeing reports that the oceans have started to cool. To me its like a rerun of about 2003. Any guesses on what the next argument will be?

    Please readers don’t you see that money can only be spent once. If we spend trillions on climate change and it is a false hypothesis thats trillions we don’t have to spend on real issues that need attention. Even worse, if in the process we destroy the economies of our countries we might never have the resources to find solutions to our real problems. There is no argument that mankind is outgrowing reliance on chemical energy but wind power and solar (at least on earth’s surface) cannot replace them. Why not spend the money to find a real alternative energy solution. Yes that will take time but we have time so long as we dont squander our resources on false crisies.

  4. Comment from: SJT


    “Any others I should know about? One question, do you acknowledge any negative feedback factors at all or do you seriously think there are none in Earth’s climate system?”

    Of course there are. That is why there is so much debate and research still going on. The new generation of models on the more powerful hardware now available will enable a better understanding of clouds.

  5. Comment from: SJT


    “The talk about ocean heat content is interesting. You see a few years ago it was all about warming of the land – no mention of the oceans at all. Then when it became too obvious that the land and air was not warming the argument became ocean acidification and coral bleaching. When that did not serve, suddenly ocean warming is discovered to save the day.”

    You are too cynical. The research has been extending on many fronts, including the oceans, land, models and several expensive space projects. The argos project is one such recent project that has been relatively new. You don’t get something like that going overnight. That’s the reason they can start to give informed information on the ocean heat content.

    Argo started deployments in 2000, it finished that phase in 2007. They must have been planning it for years before 2000.

    http://www.argo.ucsd.edu/

  6. Comment from: Luke


    “The talk about ocean heat content is interesting. You see a few years ago it was all about warming of the land – no mention of the oceans at all. Then when it became too obvious that the land and air was not warming the argument became ocean acidification and coral bleaching. When that did not serve, suddenly ocean warming is discovered to save the day.”

    Sigh – SJT – we’re just dealing with yet another conspiracy loving denialist. How utterly fanciful !

  7. Comment from: sod


    sod you clearly did not understand what I wrote. I know a 3rd order polynomial is a cubic. You can see I said third order or cubic and I also said first order or linear, second order or parabolic.

    you used a different term on the other ones. i think there is a difference to “second order or parabolic FIT”.(you moved the fit to the front. at best, that got me confused.
    but if you say you meant the right thing, i will of course accept it. it doesn t make sense to discuss the meaning of his words with the author..

    Your comment is so unreasonable given the other two references I am forced to the conclusion you are trying to make up reasons to criticise. Presumably that means you can find nothing of substance to criticise in what I wrote – thanks.

    pretty lame. the time of observation bias link i gave above is to John Daly, who is a denialist like you. he is using actual data to show the effect. time of observation bias is a fact.

    The really interesting point of course is that the issue is not statistics at all, it is curve fitting. Not quite the same thing.

    this is complete nonsense. you were not talking about splines. but about “trends”, “significant” and “linear least square”.
    words that i will of course find in my university statistics textbook (Ulrich Krengel “Einführung in die Wahrscheinlichkeitstheorie und Statistik”).

    the really interesting thing is, that you are discussing the curve fitting without looking at the statistics behind your claims!

    i did a simple test. as i didn t have your data, i just took 20 datapoints from your graph (eyeball..) and run the regressions in excel.
    both the linear and second order polynomial have extremely bad R² values. (0.004 and 0.02)

    things change pretty dramatically with the 3rd order polynomial. (R² 0.5) the problem with that cubic regression is, that it bends UPWARD at the end!
    higher polynomials again don t significantly increase the correlation and look very similar to the cubic one.

    i am curious, why don t you show us the graph with the cubic and R² values?

    A linear least squares trend line, created using the Excel trend line function (Red trace) shows a small temperature rise of 0.09C per century which is far less than the rise claimed by AGW supporters and clearly of no concern. However, the data shown in figure 5 bears little if any resemblance to a linear function. One can always fit a linear trend line to any data but that does not mean the fitted line has any significance. For example, if instead I fit a second order trend line (a parabolic) the result is extremely different. That suggests a temperature peak around 1950 with an underlying cooling trend since. Which trend line is the more significant one? If there was really a strong underlying linear rise over the time period it should have shown up in the 2nd order trend line as well. This suggests that it is questionable whether any relevant underlying trend can be determined from the data.

    you are making pretty strong claims about the trends. but you do NOT even use the most basic statistical tools to back up your claims.

    every person with any knowledge in statistics will tell you the same: stick to the linear regression. use others only, if you have a very strong reason to do it. (like everyone doing work on that subject is using it. or the graph looks like a perfect fit to a non-linear regression)

    but do NOT randomly chose a pretty bad non linear fit (your parabolic one) and ignore a much better one (the cubic one) just because one of them fits your ideas (the parabolic pointing downwards in recent times) while the other one does not (the cubic one pointing UP).

  8. Comment from: An Australian look at USHCN: 20th century trend is largely if not entirely an artefact arising from the “corrections” « Watts Up With That?


    [...] environmentalist Jennifer Marohasy’s blog in Australia, please pay her a visit here – [...]

  9. Comment from: Ian George


    ‘You are too cynical.’

    Of course we are cynical, SJT. It was ‘global warming’ until it began to cool – then it was ‘climate change’. When they couldn’t find the ‘hot spot’ in the atmosphere, they ‘discovered’ it in the oceans.
    They dismissed the MWP on the basis of one study in the N Hemisphere, disregarding all others taken in both hemispheres. They based pre-1950 CO2 levels on Callender’s cherry picking and disregarded all the measurements done by scientists from 1850. The Siple ice core sample shows CO2 levels were 330ppm around 1900 but the data was manipulated by moving the dates forward to match the Mauna Loa data.
    NASA dropped off lots of weather stations in 1990 and uses up to 1250km shading to cover the non-stationed areas. Yearly average temperatures prior to 1980 were ‘cooled’ whilst post 1980 were ‘warmed’ after NASA made ‘necessary adjustments’. Even our own BOM has began to use 1950 (a cooler time) as a start date for comparing temperature.
    They say this is ‘unprecedented warming’ and disregard 1910-1940 spike with less CO2 input. They totally disregarded the low ice extent in the early part of the 1900s and conclude the present situation is the worst.
    And you say we are too cynical.

  10. Comment from: Daniel L. Taylor


    Michael Hammer,

    Thank you for this. And thanks for hosting it Jennifer!

    I will be faxing copies to every U.S. senator ASAP. I suggest everyone living in the U.S. do the same before the Senate follows the House in voting for economic suicide.

    The only denialists in this debate are on the AGW side.

  11. Comment from: Nick Stokes


    Michael,
    I reiterate my complaint about armwaving. Karl et al carefully studied the real data about TOBS, and computed the effect of choice of climatological day. You are just speculating. You should read what he says.

    The cutoff does matter for min-max. Suppose the day runs from 9am to 9am. That would be common – the postmaster reads and resets the thermometer when opening the office, say. Suppose there is a big frost on Monday morning. The coldest temp is at 6am, and that counts as the Sunday minimum. But 9am is still cold, and that is the Monday minimum. The same frost is counted twice, which creates a cold bias. If the thermometer was read at 8am, Monday would have been counted as even colder.

    But if instead the day ended at 5pm, the frost would have affected only one day. Instead, you’d be counting hot afternoons twice. A warm bias.

  12. Comment from: sod


    Michael, you are slow to react to criticism. now the article has been reposted on wattsup, and you didn t adjust it.

    even among the WuWt crowd, a significant number of people will notice that you did not understand the time of observation bias.

    Dunning-Kruger-Effect, live performance.

  13. Comment from: Luke


    Hammer is just another died in the wool denialist masquerading as an objective scientist. I note he’s totally ducked a reasonable analysis of the centennial change warming signal. Fails on the literature review – as with all denialists a rampant cherry-picker as our little Melbourne episode demonstrated.

    Parker, D., C. Folland, A. Scaife, J. Knight, A. Colman, P. Baines, and B. Dong (2007), Decadal to multidecadal variability and the climate change background, J. Geophys. Res., 112, D18115, doi:10.1029/2007JD008411.

    As for Ian George – learn to think about what’s known first:

    Easterling, D. R., and M. F. Wehner (2009), Is the
    climate warming or cooling?, Geophys. Res. Lett., 36, L08706,
    doi:10.1029/2009GL037810.

  14. Comment from: cohenite


    Well, I’ve posted my first glaring error from the AGW camp with Karoly’s complete misinterpretation of DTR, something which impacts on this TOB issue which Nick is persisting with; now let me post another utterly damning error perpetuated by the AGW royalty; simple cherry picking to produce a false rising trend prediction;

    http://landshape.org/enm/another-copenhagen-synthesis-report-error/#more-2459

    Perhaps insufferable sod can give us another lecture, this time on smoothing? Now where to next; the long term with luke’s newest toy, EOF time-variable correlations, or the micro-climate effects at particular sites? Ah, AGW, the growing textbook of dissembling, artiface and the gobemouche.

  15. Comment from: spangled drongo


    And thermoadjustments.

    http://wattsupwiththat.com/2009/06/28/nasa-giss-adjustments-galore-rewriting-climate-history/#more-8991

  16. Comment from: Ian George


    ‘As for Ian George – learn to think about what’s known first’.

    Luke,

    Eh???? All those things I mentioned have made people rethink this debate. Which bits are wrong?

  17. Comment from: thefordprefect


    You need to sort your scales out before making these sort of wild claims:
    Since the total corrections for the US look so similar to the claimed temperature anomaly, it begs the questions as to what the raw data looks like without any corrections. Does it show the claimed rapidly accelerating warming trend claimed by the AGW advocates?

    Here is the visual overlay of adjustment and temperature. :
    http://img198.imageshack.us/img198/4931/uhcnadjust.jpg
    The only similarity is that both curves are flat in places And rise in others BUT not at the same time in both plots!!!!

    Have a read of the document bill illis links to, from the American Meteorological Society
    where removal of the UHI effect is explained. As are all the other adjustments with suitable references.
    http://ams.allenpress.com/archive/1520-0477/preprint/2009/pdf/10.1175_2008BAMS2613.1.pdf

  18. Comment from: sod


    now let me post another utterly damning error perpetuated by the AGW royalty; simple cherry picking to produce a false rising trend prediction;

    http://landshape.org/enm/another-copenhagen-synthesis-report-error/#more-2459

    Perhaps insufferable sod can give us another lecture, this time on smoothing?

    Stefan answered this on realclimate. M=15. just a minor caption error.

    http://www.realclimate.org/index.php/archives/2009/06/a-warning-from-copenhagen/langswitch_lang/wp#comment-127955

    don t worry about it.

  19. Comment from: sod


    from the replies on WuWt:

    Nick Stokes (19:57:22) :

    bill
    They are even less similar than your plot shows. The NOAA temps are in C but the adjustments you’ve plotted (as did the OP) are in F.

    it is not on the same scale (F vs °C) and not for the same place. (USA vs global), but it does look similar…

  20. Comment from: cohenite


    sod; you miss [ignore? I don't know how smart you are] the point; the actual data contradicts the trend produced by the smoothing; “just a minor caption error”?! The difference is between a false [that is contradicted by the data] trend which sustains alarmism and a declining trend which disproves the AGW bandwagon; wicked. And anyway how can you overlook a fundamental shift in the smoothing parameter from 11 to 15; Steffen is accumulating quite a body of form; his outrageous comments fresh from Copenhagen about AGW being worse than before when it was only going to destroy the world! Then his post-Fielding comment that atmospheric temperature was old hat, the important thing was ocean heat which had an increasing upward trend; this is just plain wrong and now another ‘oversight’ which allows alarmism to be cranked up again. Steffen has no shame and neither do you bozos for defending him.

  21. Comment from: sod


    Stefan explains the reason for his change:

    we chose M=15. In hindsight, the averaging period of 11 years that we used in the 2007 Science paper was too short to determine a robust climate trend. The 2-sigma error of an 11-year trend is about +/- 0.2 ºC, i.e. as large as the trend itself. Therefore, an 11-year trend is still strongly affected by interannual variability (i.e. weather). You can tell from the fact that adding just one cool year – 2008 – significantly changes the trend line, even though 2008 is entirely within the normal range of natural variability around the trend line and thus should not affect any statistically robust trend estimate. -stefan]

    but i guess, just like Miachael, you are not interested in that “statistics” stuff. you prefer your own little view of things and conspiracy theories.

  22. Comment from: Jan Pompe


    Jeremy, “you are not interested in that “statistics” stuff. ”

    You call what Stefan did statistics?

  23. Comment from: michael hammer


    Slightly off topic but hopefully Jennifer will indulge me. I have recently seen many comments to the effect that the last 10 years of cooling is not significant. Just random fluctuations and not abnormal. Yet the entire AGW hypothesis is based on the period from about 1973 to 1998 a 25 year period. This implies 10 years is just random fluctuations but 25 years is a definitive trend with an underlying cause. A bit odd that a 2.5:1 change in time scale makes such a huge differnec in outlook.

    However look at the raw data for the US. From around 1930 to about 1975-1980 there was a 45-50 year long distinct cooling trend. Well if 25 years is definitive then 45 years must be even more so. So what caused this cooling trend and how do we know the subsequent 25 years of warming was not say rebound because the cause of the cooling trend stopped.

  24. Comment from: cohenite


    sod; really, you have no idea; the post by David Stockwell shows that expanding the 11 point smoothing period to a 14 year period completely reverses the downward trend of the 11 period; what Steffen says is garbage because the 15 point smoothing he used to produce the non-linear ‘trend’ [remember your little exposition of the dangers of non-linear trends?] is actually worse than the 14 pointer supposed by Jean S; David Stockwell explains it here;

    http://landshape.org/enm/wp-content/uploads/2009/06/ee-20-4_7-stockwell.pdf

    michael; don’t you know the cooling period in the middle of the 20thC still had an underlying warming trend which was masked by either natural variation, EOF2 from luke’s Parker et al paper, or global dimming caused by aerosols :-) BTW, if you are interested in a new unpublished paper which looks at a different statistical approach to the temperature history of Australia and globally, with a specific rebuttal of the Easterling denigration of the post 1998 cooling, drop me a line and I’ll send you a copy.

  25. Comment from: cohenite


    My mistake for not differentiating Stefan Rahmstorf and Will Steffen; of course Stefan is the one with quaint ideas about preserving robust trends while Steffen is the one who is the expert in faux and phony reasons for alarmism; come to think about it there is no difference.

  26. Comment from: Faking global warming « Jim’s Blog


    [...] imitating the mock consensus style of the warmists, without giving a citation.  Here is the article that exposed the fakery for the US weather [...]

  27. Comment from: sod


    Here is the visual overlay of adjustment and temperature. :
    http://img198.imageshack.us/img198/4931/uhcnadjust.jpg
    The only similarity is that both curves are flat in places And rise in others BUT not at the same time in both plots!!!!

    brilliant graph. and things are even worse: the adjustments are in °F, while the global temperature data is in °C.

    the growth of the adjustment should be squeezed to about half of what it is in your picture.

    Michael, those graphs are extremely different!

  28. Comment from: Nick Stokes


    Coho,
    No, you are pinning your faith on a mirage here. David does,’t show a trend reversal – he shows a different endpoint behaviour. But in all these smoothing processes, endpoint behaviour is arbitrary. Smoothing implies taking account of past and future values, and near the end, future values have to be guessed, one way or another. That is why choosing 11 yr or 15 yr makes a marked difference near 2009, but not at earlier times. The 15yr plot just uses more of the guessed values. It will then depend on what the guess is, as DS shows when looking at MRC etc.

    If you could really find a magic way of reliably improving estimates of current trend, you could make a killing on the stock market.

  29. Comment from: Is Global Warming Real or a Correction Error? | The Neophyte


    [...] correction factor, not the trend in the measured data.  Michael Hammers’ report can be found here.  Here are three very interesting graphs from the [...]

  30. Comment from: SJT


    As Luke has pointed out before, the correlation between the satellite data and the surface data is good, just look up woodfortrees. The baseline is different, but wiggles up and down indicate both sources are measuring the same changes pretty closely.

  31. Comment from: SJT


    “No, you are pinning your faith on a mirage here. David does,’t show a trend reversal”

    Thank you, I wondered what graph Cohenite was looking at.

  32. Comment from: Ian George


    Luke says ‘the RCS is an investment in the future. We now have a quality reference network.’

    So I just checked the NSW weather stations used in ‘Australia’s Reference Climate Station Network’. These stations have been chosen on the basis of their ‘high quality, long-term climate monitoring, particularly with regard to climate change analysis.’ Preference was given to the following criteria:
    * high quality and long climate records, (the BOM gives a figure of 30 years only)
    * a location in an area away from large urban centres, and
    * a reasonable likelihood of continued, long-term operation.

    All the stations appear to be in open areas and would not be influenced by the UH effect. Of the 21 NSW stations they have selected I have noted the following.

    * Two stations appear to have been closed but are still listed (Nowra RAN Air in 2000 and Point Perpendicular in 2004).
    * Seven stations began recording data in the 1990s. (Richmond RAAF seems to have reverted to data from a previous station 0.4km away but their long-term average temps are not consistent).
    * Four stations go back to 1950, 3 go back to 1940 and 1 goes back to 1939.
    * Only 4 go back to 1910 and before (Yamba, Tibooburra, Bathurst and Moruya).

    So, of the 21 stations listed, 9 do not fit the criteria 1 to be a RCS (42%) and 8 fit the criteria but don’t have the past history to assure a ‘long-term climate monitoring, particularly with regard to climate change analysis’. Of the four that have a long, uninterrupted history, Yamba has temperature gaps in the past 11/14 months so I would question its ‘high quality’ data.

    As a matter of interest I ran the temp data for Tibooburra, Bathurst and Moruya using 1911-1940 and compared it with the 1971-2000 averages and found a mean average temperature rise of less than 0.2C over those periods.

    Maybe someone from the BOM can let us know if the above is correct (the source I use is at http://www.bom.gov.au/climate/change/reference.shtml#rcsmap) as these stations may have been updated.
    Also, do some of the above have neighbouring WS which go back some time and that data is used to calculate long-term averages?

  33. Comment from: Ryder


    OK, clearly the Time of Measurement correction is the kicker…

    What possibly could explain that sort of correction, where it seems that for half a century, the observations have been made earlier and earlier in the morning (or later and later in the evening)…

    The Time of Measurement correction should look like noise… randomly earlier or later in the day. It should not show a trend.

    What explanation could one offer? That those making the observations over the last 50 years are getting more and more lazy, and don’t get around to logging the time till later than they did in previous years?

    Perhaps the observers are all getting older… and walk more slowly out to the thermometers… slower and slower each year, delaying their arrival at the monitoring station?

    Is it possible that television commercials have been gradually shifting such that observers pry themselves away from the tv at a subtly different time?

    Maybe people are talking more on the phone, and as a result, get to their data collection when they are done yapping?

    For the life of me…. I just don’t get it.

    Well, I suppose there is one more. If it really is getting warmer, and observers prefer to stay out of the heat… they might take readings more in the mornings or evenings…. but really, I don’t think people can notice a 0.3 difference in temperatures.

    I don’t get it.

  34. Comment from: Ryder


    OK…. I just read where Time of Observation adjustments come from… I should have guessed. Software. It is empirically derived. “The TOB-adjustment software uses an empirical model to estimate and adjust the monthly temperature values so that they more closely resemble values based on the local midnight summary period.”

    Ah, this still seems very funky. how come this software sees fit to generate gradual 50 year upward trends?

    And since it is supposed to be correcting the data to look like the “midnight summary period”, which one might assume is a cold part of the daily temp cycle, and the observations probably made during warmer times of day… then the corrections should be *downward*.

  35. Comment from: sod


    Ah, this still seems very funky. how come this software sees fit to generate gradual 50 year upward trends?

    all this uneducated posts about TOB are simply stupid. please read something about the subject, before you comment on it!!!!

    http://ams.confex.com/ams/pdfpapers/141108.pdf

    The systematic time of observation bias would be of
    little concern with regard to temperature trends provided
    that the observation time at a given station did not
    change during its operational history. As shown in Fig.
    3, however, there has been a widespread conversion
    from afternoon to morning observation times in the
    HCN. Prior to the 1940s, for example, most observers
    recorded near sunset in accordance with U.S. Weather
    Bureau instructions. Consequently, the U.S. climate
    record as a whole contains a slight positive (warm) bias
    during the first half of the century. A switch to morning
    observation times has steadily occurred during the latter
    half of the century to support operational hydrological
    requirements. The result is a broad-scale reduction in
    mean temperatures that is simply caused by the
    conversion in the daily reading schedule of the
    Cooperative Observers. In other words, the gradual
    conversion to morning observation times in the United
    States during the past 50 years has artificially reduced
    the true temperature trend in the U.S. climate record
    (Karl et al. 1986; Vose et al. 2003; Hubbard and Lin
    2006; Pielke et al. 2007a).

    figure 3 clearly demonstrates the continuing change from afternoon to morning observation.

    if you don t understand or believe the articles, you can make a simple test in a excel or calc sheet. generate two random columns of numbers, low min in the first (0-5, for example) and high max in the second (20-25).
    a measurement at the “best” time of observation, those two numbers are the min and max value of the day. (generate a day average from them)
    to simulate a worst case scenario, simulate a n observation time close to the maximum, by calculating the day maximum as the as the higher number between this day max and thelast day max value.
    do the same for minums. the difference is massive!

    ————————

    if you on the other hand prefer to believe a denilaits, just check the Pielke article

    http://ccc.atmos.colostate.edu/pdfs/Pielke-etal_BAMS_Jun07.pdf

    you will find that even he comes to the conclusion:

    However, the
    evaluation of these TOB biases has indicated that the
    time-of-observation bias adjustments in USHCN
    appear to be robust (Vose et al. 2003).

  36. Comment from: cohenite


    Very ‘smooth’ Stokesy; so changing the “endpoint behaviour” is different from changing the trend; as always I defer to your greater wisdom on these crucial matters. Besides I’m still wondering why noone wants to talk about Karoly and DTR and why the adjustments are always upwards.

  37. Comment from: Ryder


    Hey, sod, *relax*. And learn to read while you are at it.

    I had JUST SAID that I had read something about it… (and I did).

    And then all I said was that it *seemed funky*, and asked a simple question, based on what I had already read.

    Read for yourself:

    “Ah, this still seems very funky. how come this software sees fit to generate gradual 50 year upward trends?”

    sod goes apoplectic:
    —————————
    all this uneducated posts about TOB are simply stupid. please read something about the subject, before you comment on it!!!!
    —————————

    BTW, your first link seems broken.

    I am finding it a little hard to believe that it is taking 50 years to get observers to change to morning readings. They must be stubborn old b*stards. 50 weeks maybe… but regardless:

    I checked the Peilke article…. and there is scant information about the TOB adjustment… just a cite of a paper that claimed it is robust.

    SO, the idea that as more and more stations added the same biases to their data…. the overall shift represents an accumulation of error for the entire dataset… now, in reference to what? Is the bias being normalized to the first year in the data? What year is considered to be a year where there is no bias?

  38. Comment from: LEAH


    we all know that global warming is a scam to get more tax dollars from already struggling americans. anyone with common sense can see that. but they will pass this ridiculous bill anyway, because ignorance is running this country right now. we will pay 250.00 extra a month on electric bills and have our hard earned money stolen from us for something fake. all of government is a scam. we need to get them all out of office and start new and fresh. i mean even the scientist who first raved about global warming had to retract their story, because it was misread. that was their words. we misread the data. that is something you didn’t see on cnn, and the AllBarackChannel. thank you for putting this out there for all who cares to know the truth to see. you are a patriot!

  39. Comment from: sod


    the link to the PDF does work for me. the title of the article is:

    THE UNITED STATES HISTORICAL CLIMATOLOGY NETWORK
    MONTHLY TEMPERATURE DATA – VERSION 2

    Figure 3 shows that since about 400 out f 1000 stations changed from pm to am observation time, and that it was a gradual change.

    fact. sorry.

  40. Comment from: Graeme Bird


    Notice that its not a case of blaming Goddard alone. The Goddard criminals are far more visible than the people who fake up the Hadcru figures and whoever that third group of frauds are (their name escapes me but who cares?). These other two groups keep a lower profile than Goddard members who are media queens. But they are all purveyors of lies just the same.

    The job that all three outfits had was quite simple. Apply quality control to the data, prior to going to work with it with the statistical techniques. Then they ought to have been using the satelite/balloon data to test their output.

    Neither of these three supposedly scientific outfits have reached so much as a Sesame Street level of ability in logical inference. If you look at all three of the ground data amalgamations, well they don’t agree with each-other perfectly. But they disagree far more with the satellite and the balloon data then they do with eachother.

    So we have the balloon data. We have the satellite data. Both of which agree with each-other. Convergent evidence. Good data. If the two sets of data were not good data they would not confirm each-other.

    Then we come to the ground data aggregations. And suddenly we find that “One of these things is not like the others. One of these things just doesn’t belong. Can you tell me which thing is not like the others………..”

    http://www.youtube.com/watch?v=0WhuikFY1Pg

    So we see that these people are not scientists of any sort but total failures. And an ideology has crept in that you just throw in all the data together, no quality control and then you go to work on it. Aggregate it all and don’t let anyone else check your work if you can help it.

    Well how about if the Soviet Union collapses and we aren’t getting their Siberian data all of a sudden? If they just throw everything in how is that going to affect things? Its going to make the 90′s warming look a lot higher than it ought to have looked. Siberia being cold right? If I’m not going too fast for the fraud side of the argument.

    What about if areas in Africa or other hotter-than-average regions are steadily coming on board over time? How is that going to rig the figures? Its going to produce a rising gradient of temperature on to of what ups and downs are already there. Thats what its going to do. And did revelations of the heat island effect and inappropriately placed measuring stations lead to a massive culling of historical data? I think we all know the answer to that don’t we?

    So all of them, and just Goddard, are failures. They had the balloon and satellite data that would have allowed them to see if they were on the right track. Then when they had nutted out their methodology and exercised enough quality control over the data they had, they could have worked backwards to the pre-Satellite error.

    Its no use getting any of this same crowd to try and reform their act. Each country ought to just sack them all. No need to replace them either. We know what needs to be done. Full steam ahead on governmental cost-cutting and clearing the road free of obstructions to synthetic diesel and nuclear power. Just release all the raw data onto the internet and let people argue it out. No conclusion anyone came up with could change the fact that we need to move quickly to make nuclear and synthetic diesel investor-friendly prospects. Billions of lives are counting on us doing just this.

    We have to understand that something has happened in the English-Speaking world with our public servants. There was a time where, for the most part, they were reasonably content with merely getting a free ride on their hosts. Now the parasite has turned nasty. And it wants to actively damage its host for no reason. Just out of spite and nihilism or so it seems. We see this tendency rearing its head at every turn.

  41. Comment from: Ryder


    sod,

    I had to copy/paste the link definition into my browser to get it to work (the first document link), but I got there…

    All that document says is that the reason for the gradual shift to morning readings is: “to support operational hydrological requirements”.

    So in the end… it’s not really helpful. What kind of “operational requirement” asserts itself gradually and evenly only over a 50 year period? It is still very much a puzzle.

    “fact. sorry.”

    Look, I am not searching for a particular answer… no apologies are needed… it is just a mystery that I have questions about. Whatever the real truth turns out to be.

  42. Comment from: Mike M.


    The overall magnitude of adjustment might actually be correct! … they just got the sign wrong.

    A .5 C reduction to data in 2000 would appear to line up with Anthony Watts’ surface station survey. http://surfacestations.org/

  43. Comment from: Jennifer Marohasy » Stop Averaging Global Temperatures (Part 1)


    [...] Michael Hammer after studying the official data from the US official weather stations, and in particular how it is adjusted after it has been collected, has concluded that the temperature rise profile claimed by the US government is largely if not entirely an artifact of the adjustments applied after the raw data is collected from the weather stations. http://jennifermarohasy.com/blog/2009/06/how-the-us-temperature-record-is-adjusted/ [...]

  44. Comment from: Jennifer Marohasy » Your Temperatures Diddled


    [...] 1. Hammer, M. June 27, 2009. Does the US Temperature Record Support Global Warming?
 http://jennifermarohasy.com/2009/06/how-the-us-temperature-record-is-adjusted/ [...]

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